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Chapter 9. Reviewing the Literature

What is a “literature review”.

No researcher ever comes up with a research question that is wholly novel. Someone, somewhere, has asked the same thing. Academic research is part of a larger community of researchers, and it is your responsibility, as a member of this community, to acknowledge others who have asked similar questions and to put your particular research into this greater context. It is not simply a convention or custom to begin your study with a review of previous literature (the “ lit review ”) but an important responsibility you owe the scholarly community.


Too often, new researchers pursue a topic to study and then write something like, “No one has ever studied this before” or “This area is underresearched.” It may be that no one has studied this particular group or setting, but it is highly unlikely no one has studied the foundational phenomenon of interest. And that comment about an area being underresearched? Be careful. The statement may simply signal to others that you haven’t done your homework. Rubin ( 2021 ) refers to this as “free soloing,” and it is not appreciated in academic work:

The truth of the matter is, academics don’t really like when people free solo. It’s really bad form to omit talking about the other people who are doing or have done research in your area. Partly, I mean we need to cite their work, but I also mean we need to respond to it—agree or disagree, clarify for extend. It’s also really bad form to talk about your research in a way that does not make it understandable to other academics.…You have to explain to your readers what your story is really about in terms they care about . This means using certain terminology, referencing debates in the literature, and citing relevant works—that is, in connecting your work to something else. ( 51–52 )

A literature review is a comprehensive summary of previous research on a topic. It includes both articles and books—and in some cases reports—relevant to a particular area of research. Ideally, one’s research question follows from the reading of what has already been produced. For example, you are interested in studying sports injuries related to female gymnasts. You read everything you can find on sports injuries related to female gymnasts, and you begin to get a sense of what questions remain open. You find that there is a lot of research on how coaches manage sports injuries and much about cultures of silence around treating injuries, but you don’t know what the gymnasts themselves are thinking about these issues. You look specifically for studies about this and find several, which then pushes you to narrow the question further. Your literature review then provides the road map of how you came to your very specific question, and it puts your study in the context of studies of sports injuries. What you eventually find can “speak to” all the related questions as well as your particular one.

In practice, the process is often a bit messier. Many researchers, and not simply those starting out, begin with a particular question and have a clear idea of who they want to study and where they want to conduct their study but don’t really know much about other studies at all. Although backward, we need to recognize this is pretty common. Telling students to “find literature” after the fact can seem like a purposeless task or just another hurdle for completing a thesis or dissertation. It is not! Even if you were not motivated by the literature in the first place, acknowledging similar studies and connecting your own research to those studies are important parts of building knowledge. Acknowledgment of past research is a responsibility you owe the discipline to which you belong.

Literature reviews can also signal theoretical approaches and particular concepts that you will incorporate into your own study. For example, let us say you are doing a study of how people find their first jobs after college, and you want to use the concept of social capital . There are competing definitions of social capital out there (e.g., Bourdieu vs. Burt vs. Putnam). Bourdieu’s notion is of one form of capital, or durable asset, of a “network of more or less institutionalized relationships of mutual acquaintance or recognition” ( 1984:248 ). Burt emphasizes the “brokerage opportunities” in a social network as social capital ( 1997:355 ). Putnam’s social capital is all about “facilitating coordination and cooperation for mutual benefit” ( 2001:67 ). Your literature review can adjudicate among these three approaches, or it can simply refer to the one that is animating your own research. If you include Bourdieu in your literature review, readers will know “what kind” of social capital you are talking about as well as what kind of social scientist you yourself are. They will likely understand that you are interested more in how some people are advantaged by their social capital relative to others rather than being interested in the mechanics of how social networks operate.

The literature review thus does two important things for you: firstly, it allows you to acknowledge previous research in your area of interest, thereby situating you within a discipline or body of scholars, and, secondly, it demonstrates that you know what you are talking about. If you present the findings of your research study without including a literature review, it can be like singing into the wind. It sounds nice, but no one really hears it, or if they do catch snippets, they don’t know where it is coming from.

Examples of Literature Reviews

To help you get a grasp of what a good literature review looks like and how it can advance your study, let’s take a look at a few examples.

Reader-Friendly Example: The Power of Peers

The first is by Janice McCabe ( 2016 ) and is from an article on peer networks in the journal Contexts . Contexts presents articles in a relatively reader-friendly format, with the goal of reaching a large audience for interesting sociological research. Read this example carefully and note how easily McCabe is able to convey the relevance of her own work by situating it in the context of previous studies:

Scholars who study education have long acknowledged the importance of peers for students’ well-being and academic achievement. For example, in 1961, James Coleman argued that peer culture within high schools shapes students’ social and academic aspirations and successes. More recently, Judith Rich Harris has drawn on research in a range of areas—from sociological studies of preschool children to primatologists’ studies of chimpanzees and criminologists’ studies of neighborhoods—to argue that peers matter much more than parents in how children “turn out.” Researchers have explored students’ social lives in rich detail, as in Murray Milner’s book about high school students, Freaks, Geeks, and Cool Kids , and Elizabeth Armstrong and Laura Hamilton’s look at college students, Paying for the Party . These works consistently show that peers play a very important role in most students’ lives. They tend, however, to prioritize social over academic influence and to use a fuzzy conception of peers rather than focusing directly on friends—the relationships that should matter most for student success. Social scientists have also studied the power of peers through network analysis, which is based on uncovering the web of connections between people. Network analysis involves visually mapping networks and mathematically comparing their structures (such as the density of ties) and the positions of individuals within them (such as how central a given person is within the network). As Nicholas Christakis and James Fowler point out in their book Connected , network structure influences a range of outcomes, including health, happiness, wealth, weight, and emotions. Given that sociologists have long considered network explanations for social phenomena, it’s surprising that we know little about how college students’ friends impact their experiences. In line with this network tradition, I focus on the structure of friendship networks, constructing network maps so that the differences we see across participants are due to the underlying structure, including each participant’s centrality in their friendship group and the density of ties among their friends. ( 23 )

What did you notice? In her very second sentence, McCabe uses “for example” to introduce a study by Coleman, thereby indicating that she is not going to tell you every single study in this area but is going to tell you that (1) there is a lot of research in this area, (2) it has been going on since at least 1961, and (3) it is still relevant (i.e., recent studies are still being done now). She ends her first paragraph by summarizing the body of literature in this area (after giving you a few examples) and then telling you what may have been (so far) left out of this research. In the second paragraph, she shifts to a separate interesting focus that is related to the first but is also quite distinct. Lit reviews very often include two (or three) distinct strands of literature, the combination of which nicely backgrounds this particular study . In the case of our female gymnast study (above), those two strands might be (1) cultures of silence around sports injuries and (2) the importance of coaches. McCabe concludes her short and sweet literature review with one sentence explaining how she is drawing from both strands of the literature she has succinctly presented for her particular study. This example should show you that literature reviews can be readable, helpful, and powerful additions to your final presentation.

Authoritative Academic Journal Example: Working Class Students’ College Expectations

The second example is more typical of academic journal writing. It is an article published in the British Journal of Sociology of Education by Wolfgang Lehmann ( 2009 ):

Although this increase in post-secondary enrolment and the push for university is evident across gender, race, ethnicity, and social class categories, access to university in Canada continues to be significantly constrained for those from lower socio-economic backgrounds (Finnie, Lascelles, and Sweetman 2005). Rising tuition fees coupled with an overestimation of the cost and an underestimation of the benefits of higher education has put university out of reach for many young people from low-income families (Usher 2005). Financial constraints aside, empirical studies in Canada have shown that the most important predictor of university access is parental educational attainment. Having at least one parent with a university degree significantly increases the likelihood of a young person to attend academic-track courses in high school, have high educational and career aspirations, and ultimately attend university (Andres et al. 1999, 2000; Lehmann 2007a). Drawing on Bourdieu’s various writing on habitus and class-based dispositions (see, for example, Bourdieu 1977, 1990), Hodkinson and Sparkes (1997) explain career decisions as neither determined nor completely rational. Instead, they are based on personal experiences (e.g., through employment or other exposure to occupations) and advice from others. Furthermore, they argue that we have to understand these decisions as pragmatic, rather than rational. They are pragmatic in that they are based on incomplete and filtered information, because of the social context in which the information is obtained and processed. New experiences and information can, however, also be allowed into one’s world, where they gradually or radically transform habitus, which in turn creates the possibility for the formation of new and different dispositions. Encountering a supportive teacher in elementary or secondary school, having ambitious friends, or chance encounters can spark such transformations. Transformations can be confirming or contradictory, they can be evolutionary or dislocating. Working-class students who enter university most certainly encounter such potentially transformative situations. Granfield (1991) has shown how initially dislocating feelings of inadequacy and inferiority of working-class students at an elite US law school were eventually replaced by an evolutionary transformation, in which the students came to dress, speak and act more like their middle-class and upper-class peers. In contrast, Lehmann (2007b) showed how persistent habitus dislocation led working-class university students to drop out of university. Foskett and Hemsley-Brown (1999) argue that young people’s perceptions of careers are a complex mix of their own experiences, images conveyed through adults, and derived images conveyed by the media. Media images of careers, perhaps, are even more important for working-class youth with high ambitions as they offer (generally distorted) windows into a world of professional employment to which they have few other sources of access. It has also been argued that working-class youth who do continue to university still face unique, class-specific challenges, evident in higher levels of uncertainty (Baxter and Britton 2001; Lehmann 2004, 2007a; Quinn 2004), their higher education choices (Ball et al. 2002; Brooks 2003; Reay et al. 2001) and fears of inadequacy because of their cultural outsider status (Aries and Seider 2005; Granfield 1991). Although the number of working-class university students in Canada has slowly increased, that of middle-class students at university has risen far more steeply (Knighton and Mizra 2002). These different enrolment trajectories have actually widened the participation gap, which in tum explains our continued concerns with the potential outsider status Indeed, in a study comparing first-generation working-class and traditional students who left university without graduating, Lehmann (2007b) found that first-generation working-class students were more likely to leave university very early in some cases within the first two months of enrollment. They were also more likely to leave university despite solid academic performance. Not “fitting in,” not “feeling university,” and not being able to “relate to these people” were key reasons for eventually withdrawing from university. From the preceding review of the literature, a number of key research questions arise: How do working-class university students frame their decision to attend university? How do they defy the considerable odds documented in the literature to attend university? What are the sources of information and various images that create dispositions to study at university? What role does their social-class background- or habitus play in their transition dispositions and how does this translate into expectations for university? ( 139 )

What did you notice here? How is this different from (and similar to) the first example? Note that rather than provide you with one or two illustrative examples of similar types of research, Lehmann provides abundant source citations throughout. He includes theory and concepts too. Like McCabe, Lehmann is weaving through multiple literature strands: the class gap in higher education participation in Canada, class-based dispositions, and obstacles facing working-class college students. Note how he concludes the literature review by placing his research questions in context.

Find other articles of interest and read their literature reviews carefully. I’ve included two more for you at the end of this chapter . As you learned how to diagram a sentence in elementary school (hopefully!), try diagramming the literature reviews. What are the “different strands” of research being discussed? How does the author connect these strands to their own research questions? Where is theory in the lit review, and how is it incorporated (e.g., Is it a separate strand of its own or is it inextricably linked with previous research in this area)?

One model of how to structure your literature review can be found in table 9.1. More tips, hints, and practices will be discussed later in the chapter.

Table 9.1. Model of Literature Review, Adopted from Calarco (2020:166)

Embracing Theory

A good research study will, in some form or another, use theory. Depending on your particular study (and possibly the preferences of the members of your committee), theory may be built into your literature review. Or it may form its own section in your research proposal/design (e.g., “literature review” followed by “theoretical framework”). In my own experience, I see a lot of graduate students grappling with the requirement to “include theory” in their research proposals. Things get a little squiggly here because there are different ways of incorporating theory into a study (Are you testing a theory? Are you generating a theory?), and based on these differences, your literature review proper may include works that describe, explain, and otherwise set forth theories, concepts, or frameworks you are interested in, or it may not do this at all. Sometimes a literature review sets forth what we know about a particular group or culture totally independent of what kinds of theoretical framework or particular concepts you want to explore. Indeed, the big point of your study might be to bring together a body of work with a theory that has never been applied to it previously. All this is to say that there is no one correct way to approach the use of theory and the writing about theory in your research proposal.

Students are often scared of embracing theory because they do not exactly understand what it is. Sometimes, it seems like an arbitrary requirement. You’re interested in a topic; maybe you’ve even done some research in the area and you have findings you want to report. And then a committee member reads over what you have and asks, “So what?” This question is a good clue that you are missing theory, the part that connects what you have done to what other researchers have done and are doing. You might stumble upon this rather accidentally and not know you are embracing theory, as in a case where you seek to replicate a prior study under new circumstances and end up finding that a particular correlation between behaviors only happens when mediated by something else. There’s theory in there, if you can pull it out and articulate it. Or it might be that you are motivated to do more research on racial microaggressions because you want to document their frequency in a particular setting, taking for granted the kind of critical race theoretical framework that has done the hard work of defining and conceptualizing “microaggressions” in the first place. In that case, your literature review could be a review of Critical Race Theory, specifically related to this one important concept. That’s the way to bring your study into a broader conversation while also acknowledging (and honoring) the hard work that has preceded you.

Rubin ( 2021 ) classifies ways of incorporating theory into case study research into four categories, each of which might be discussed somewhat differently in a literature review or theoretical framework section. The first, the least theoretical, is where you set out to study a “configurative idiographic case” ( 70 ) This is where you set out to describe a particular case, leaving yourself pretty much open to whatever you find. You are not expecting anything based on previous literature. This is actually pretty weak as far as research design goes, but it is probably the default for novice researchers. Your committee members should probably help you situate this in previous literature in some way or another. If they cannot, and it really does appear you are looking at something fairly new that no one else has bothered to research before, and you really are completely open to discovery, you might try using a Grounded Theory approach, which is a methodological approach that foregrounds the generation of theory. In that case, your “theory” section can be a discussion of “Grounded Theory” methodology (confusing, yes, but if you take some time to ponder, you will see how this works). You will still need a literature review, though. Ideally one that describes other studies that have ever looked at anything remotely like what you are looking at—parallel cases that have been researched.

The second approach is the “disciplined configurative case,” in which theory is applied to explain a particular case or topic. You are not trying to test the theory but rather assuming the theory is correct, as in the case of exploring microaggressions in a particular setting. In this case, you really do need to have a separate theory section in addition to the literature review, one in which you clearly define the theoretical framework, including any of its important concepts. You can use this section to discuss how other researchers have used the concepts and note any discrepancies in definitions or operationalization of those concepts. This way you will be sure to design your study so that it speaks to and with other researchers. If everyone who is writing about microaggressions has a different definition of them, it is hard for others to compare findings or make any judgments about their prevalence (or any number of other important characteristics). Your literature review section may then stand alone and describe previous research in the particular area or setting, irrespective of the kinds of theory underlying those studies.

The third approach is “heuristic,” one in which you seek to identify new variables, hypotheses, mechanisms, or paths not yet explained by a theory or theoretical framework. In a way, you are generating new theory, but it is probably more accurate to say that you are extending or deepening preexisting theory. In this case, having a single literature review that is focused on the theory and the ways the theory has been applied and understood (with all its various mechanisms and pathways) is probably your best option. The focus of the literature reviewed is less on the case and more on the theory you are seeking to extend.

The final approach is “theory testing,” which is much rarer in qualitative studies than in quantitative, where this is the default approach. Theory-testing cases are those where a particular case is used to see if an existing theory is accurate or accurate under particular circumstances. As with the heuristic approach, your literature review will probably draw heavily on previous uses of the theory, but you may end up having a special section specifically about cases very close to your own . In other words, the more your study approaches theory testing, the more likely there is to be a set of similar studies to draw on or even one important key study that you are setting your own study up in parallel to in order to find out if the theory generated there operates here.

If we wanted to get very technical, it might be useful to distinguish theoretical frameworks properly from conceptual frameworks. The latter are a bit looser and, given the nature of qualitative research, often fit exploratory studies. Theoretical frameworks rely on specific theories and are essential for theory-testing studies. Conceptual frameworks can pull in specific concepts or ideas that may or may not be linked to particular theories. Think about it this way: A theory is a story of how the world works. Concepts don’t presume to explain the whole world but instead are ways to approach phenomena to help make sense of them. Microaggressions are concepts that are linked to Critical Race Theory. One could contextualize one’s study within Critical Race Theory and then draw various concepts, such as that of microaggressions from the overall theoretical framework. Or one could bracket out the master theory or framework and employ the concept of microaggression more opportunistically as a phenomenon of interest. If you are unsure of what theory you are using, you might want to frame a more practical conceptual framework in your review of the literature.

Helpful Tips

How to maintain good notes for what your read.

Over the years, I have developed various ways of organizing notes on what I read. At first, I used a single sheet of full-size paper with a preprinted list of questions and points clearly addressed on the front side, leaving the second side for more reflective comments and free-form musings about what I read, why it mattered, and how it might be useful for my research. Later, I developed a system in which I use a single 4″ × 6″ note card for each book I read. I try only to use the front side (and write very small), leaving the back for comments that are about not just this reading but things to do or examine or consider based on the reading. These notes often mean nothing to anyone else picking up the card, but they make sense to me. I encourage you to find an organizing system that works for you. Then when you set out to compose a literature review, instead of staring at five to ten books or a dozen articles, you will have ten neatly printed pages or notecards or files that have distilled what is important to know about your reading.

It is also a good idea to store this data digitally, perhaps through a reference manager. I use RefWorks, but I also recommend EndNote or any other system that allows you to search institutional databases. Your campus library will probably provide access to one of these or another system. Most systems will allow you to export references from another manager if and when you decide to move to another system. Reference managers allow you to sort through all your literature by descriptor, author, year, and so on. Even so, I personally like to have the ability to manually sort through my index cards, recategorizing things I have read as I go. I use RefWorks to keep a record of what I have read, with proper citations, so I can create bibliographies more easily, and I do add in a few “notes” there, but the bulk of my notes are kept in longhand.

What kinds of information should you include from your reading? Here are some bulleted suggestions from Calarco ( 2020:113–114 ), with my own emendations:

  • Citation . If you are using a reference manager, you can import the citation and then, when you are ready to create a bibliography, you can use a provided menu of citation styles, which saves a lot of time. If you’ve originally formatted in Chicago Style but the journal you are writing for wants APA style, you can change your entire bibliography in less than a minute. When using a notecard for a book, I include author, title, date as well as the library call number (since most of what I read I pull from the library). This is something RefWorks is not able to do, and it helps when I categorize.

I begin each notecard with an “intro” section, where I record the aims, goals, and general point of the book/article as explained in the introductory sections (which might be the preface, the acknowledgments, or the first two chapters). I then draw a bold line underneath this part of the notecard. Everything after that should be chapter specific. Included in this intro section are things such as the following, recommended by Calarco ( 2020 ):

  • Key background . “Two to three short bullet points identifying the theory/prior research on which the authors are building and defining key terms.”
  • Data/methods . “One or two short bullet points with information about the source of the data and the method of analysis, with a note if this is a novel or particularly effective example of that method.” I use [M] to signal methodology on my notecard, which might read, “[M] Int[erview]s (n-35), B[lack]/W[hite] voters” (I need shorthand to fit on my notecard!).
  • Research question . “Stated as briefly as possible.” I always provide page numbers so I can go back and see exactly how this was stated (sometimes, in qualitative research, there are multiple research questions, and they cannot be stated simply).
  • Argument/contributions . “Two to three short bullet points briefly describing the authors’ answer to the central research question and its implication for research, theory, and practice.” I use [ARG] for argument to signify the argument, and I make sure this is prominently visible on my notecard. I also provide page numbers here.

For me, all of this fits in the “intro” section, which, if this is a theoretically rich, methodologically sound book, might take up a third or even half of the front page of my notecard. Beneath the bold underline, I report specific findings or particulars of the book as they emerge chapter by chapter. Calarco’s ( 2020 ) next step is the following:

  • Key findings . “Three to four short bullet points identifying key patterns in the data that support the authors’ argument.”

All that remains is writing down thoughts that occur upon finishing the article/book. I use the back of the notecard for these kinds of notes. Often, they reach out to other things I have read (e.g., “Robinson reminds me of Crusoe here in that both are looking at the effects of social isolation, but I think Robinson makes a stronger argument”). Calarco ( 2020 ) concludes similarly with the following:

  • Unanswered questions . “Two to three short bullet points that identify key limitations of the research and/or questions the research did not answer that could be answered in future research.”

As I mentioned, when I first began taking notes like this, I preprinted pages with prompts for “research question,” “argument,” and so on. This was a great way to remind myself to look for these things in particular. You can do the same, adding whatever preprinted sections make sense to you, given what you are studying and the important aspects of your discipline. The other nice thing about the preprinted forms is that it keeps your writing to a minimum—you cannot write more than the allotted space, even if you might want to, preventing your notes from spiraling out of control. This can be helpful when we are new to a subject and everything seems worth recording!

After years of discipline, I have finally settled on my notecard approach. I have thousands of notecards, organized in several index card filing boxes stacked in my office. On the top right of each card is a note of the month/day I finished reading the item. I can remind myself what I read in the summer of 2010 if the need or desire ever arose to do so…those invaluable notecards are like a memento of what my brain has been up to!

Where to Start Looking for Literature

Your university library should provide access to one of several searchable databases for academic books and articles. My own preference is JSTOR, a service of ITHAKA, a not-for-profit organization that works to advance and preserve knowledge and to improve teaching and learning through the use of digital technologies. JSTOR allows you to search by several keywords and to narrow your search by type of material (articles or books). For many disciplines, the “literature” of the literature review is expected to be peer-reviewed “articles,” but some disciplines will also value books and book chapters. JSTOR is particularly useful for article searching. You can submit several keywords and see what is returned, and you can also narrow your search by a particular journal or discipline. If your discipline has one or two key journals (e.g., the American Journal of Sociology and the American Sociological Review are key for sociology), you might want to go directly to those journals’ websites and search for your topic area. There is an art to when to cast your net widely and when to refine your search, and you may have to tack back and forth to ensure that you are getting all that is relevant but not getting bogged down in all studies that might have some marginal relevance.

Some articles will carry more weight than others, and you can use applications like Google Scholar to see which articles have made and are continuing to make larger impacts on your discipline. Find these articles and read them carefully; use their literature review and the sources cited in those articles to make sure you are capturing what is relevant. This is actually a really good way of finding relevant books—only the most impactful will make it into the citations of journals. Over time, you will notice that a handful of articles (or books) are cited so often that when you see, say, Armstrong and Hamilton ( 2015 ), you know exactly what book this is without looking at the full cite. This is when you know you are in the conversation.

You might also approach a professor whose work is broadly in the area of your interest and ask them to recommend one or two “important” foundational articles or books. You can then use the references cited in those recommendations to build up your literature. Just be careful: some older professors’ knowledge of the literature (and I reluctantly add myself here) may be a bit outdated! It is best that the article or book whose references and sources you use to build your body of literature be relatively current.

Keep a List of Your Keywords

When using searchable databases, it is a good idea to keep a list of all the keywords you use as you go along so that (1) you do not needlessly duplicate your efforts and (2) you can more easily adjust your search as you get a better sense of what you are looking for. I suggest you keep a separate file or even a small notebook for this and you date your search efforts.

Here’s an example:

Table 9.2. Keep a List of Your Keywords

Think Laterally

How to find the various strands of literature to combine? Don’t get stuck on finding the exact same research topic you think you are interested in. In the female gymnast example, I recommended that my student consider looking for studies of ballerinas, who also suffer sports injuries and around whom there is a similar culture of silence. It turned out that there was in fact research about my student’s particular questions, just not about the subjects she was interested in. You might do something similar. Don’t get stuck looking for too direct literature but think about the broader phenomenon of interest or analogous cases.

Read Outside the Canon

Some scholars’ work gets cited by everyone all the time. To some extent, this is a very good thing, as it helps establish the discipline. For example, there are a lot of “Bourdieu scholars” out there (myself included) who draw ideas, concepts, and quoted passages from Bourdieu. This makes us recognizable to one another and is a way of sharing a common language (e.g., where “cultural capital” has a particular meaning to those versed in Bourdieusian theory). There are empirical studies that get cited over and over again because they are excellent studies but also because there is an “echo chamber effect” going on, where knowing to cite this study marks you as part of the club, in the know, and so on. But here’s the problem with this: there are hundreds if not thousands of excellent studies out there that fail to get appreciated because they are crowded out by the canon. Sometimes this happens because they are published in “lower-ranked” journals and are never read by a lot of scholars who don’t have time to read anything other than the “big three” in their field. Other times this happens because the author falls outside of the dominant social networks in the field and thus is unmentored and fails to get noticed by those who publish a lot in those highly ranked and visible spaces. Scholars who fall outside the dominant social networks and who publish outside of the top-ranked journals are in no way less insightful than their peers, and their studies may be just as rigorous and relevant to your work, so it is important for you to take some time to read outside the canon. Due to how a person’s race, gender, and class operate in the academy, there is also a matter of social justice and ethical responsibility involved here: “When you focus on the most-cited research, you’re more likely to miss relevant research by women and especially women of color, whose research tends to be under-cited in most fields. You’re also more likely to miss new research, research by junior scholars, and research in other disciplines that could inform your work. Essentially, it is important to read and cite responsibly, which means checking that you’re not just reading and citing the same white men and the same old studies that everyone has cited before you” ( Calarco 2020:112 ).

Consider Multiple Uses for Literature

Throughout this chapter, I’ve referred to the literature of interest in a rather abstract way, as what is relevant to your study. But there are many different ways previous research can be relevant to your study. The most basic use of the literature is the “findings”—for example, “So-and-so found that Canadian working-class students were concerned about ‘fitting in’ to the culture of college, and I am going to look at a similar question here in the US.” But the literature may be of interest not for its findings but theoretically—for example, employing concepts that you want to employ in your own study. Bourdieu’s definition of social capital may have emerged in a study of French professors, but it can still be relevant in a study of, say, how parents make choices about what preschools to send their kids to (also a good example of lateral thinking!).

If you are engaged in some novel methodological form of data collection or analysis, you might look for previous literature that has attempted that. I would not recommend this for undergraduate research projects, but for graduate students who are considering “breaking the mold,” find out if anyone has been there before you. Even if their study has absolutely nothing else in common with yours, it is important to acknowledge that previous work.

Describing Gaps in the Literature

First, be careful! Although it is common to explain how your research adds to, builds upon, and fills in gaps in the previous research (see all four literature review examples in this chapter for this), there is a fine line between describing the gaps and misrepresenting previous literature by failing to conduct a thorough review of the literature. A little humility can make a big difference in your presentation. Instead of “This is the first study that has looked at how firefighters juggle childcare during forest fire season,” say, “I use the previous literature on how working parents juggling childcare and the previous ethnographic studies of firefighters to explore how firefighters juggle childcare during forest fire season.” You can even add, “To my knowledge, no one has conducted an ethnographic study in this specific area, although what we have learned from X about childcare and from Y about firefighters would lead us to expect Z here.” Read more literature review sections to see how others have described the “gaps” they are filling.

Use Concept Mapping

Concept mapping is a helpful tool for getting your thoughts in order and is particularly helpful when thinking about the “literature” foundational to your particular study. Concept maps are also known as mind maps, which is a delightful way to think about them. Your brain is probably abuzz with competing ideas in the early stages of your research design. Write/draw them on paper, and then try to categorize and move the pieces around into “clusters” that make sense to you. Going back to the gymnasts example, my student might have begun by jotting down random words of interest: gymnasts * sports * coaches * female gymnasts * stress * injury * don’t complain * women in sports * bad coaching * anxiety/stress * careers in sports * pain. She could then have begun clustering these into relational categories (bad coaching, don’t complain culture) and simple “event” categories (injury, stress). This might have led her to think about reviewing literature in these two separate aspects and then literature that put them together. There is no correct way to draw a concept map, as they are wonderfully specific to your mind. There are many examples you can find online.

Ask Yourself, “How Is This Sociology (or Political Science or Public Policy, Etc.)?”

Rubin ( 2021:82 ) offers this suggestion instead of asking yourself the “So what?” question to get you thinking about what bridges there are between your study and the body of research in your particular discipline. This is particularly helpful for thinking about theory. Rubin further suggests that if you are really stumped, ask yourself, “What is the really big question that all [fill in your discipline here] care about?” For sociology, it might be “inequality,” which would then help you think about theories of inequality that might be helpful in framing your study on whatever it is you are studying—OnlyFans? Childcare during COVID? Aging in America? I can think of some interesting ways to frame questions about inequality for any of those topics. You can further narrow it by focusing on particular aspects of inequality (Gender oppression? Racial exclusion? Heteronormativity?). If your discipline is public policy, the big questions there might be, How does policy get enacted, and what makes a policy effective? You can then take whatever your particular policy interest is—tax reform, student debt relief, cap-and-trade regulations—and apply those big questions. Doing so would give you a handle on what is otherwise an intolerably vague subject (e.g., What about student debt relief?).

Sometimes finding you are in new territory means you’ve hit the jackpot, and sometimes it means you’ve traveled out of bounds for your discipline. The jackpot scenario is wonderful. You are doing truly innovative research that is combining multiple literatures or is addressing a new or under-examined phenomenon of interest, and your research has the potential to be groundbreaking. Congrats! But that’s really hard to do, and it might be more likely that you’ve traveled out of bounds, by which I mean, you are no longer in your discipline . It might be that no one has written about this thing—at least within your field— because no one in your field actually cares about this topic . ( Rubin 2021:83 ; emphases added)

Don’t Treat This as a Chore

Don’t treat the literature review as a chore that has to be completed, but see it for what it really is—you are building connections to other researchers out there. You want to represent your discipline or area of study fairly and adequately. Demonstrate humility and your knowledge of previous research. Be part of the conversation.

Supplement: Two More Literature Review Examples

Elites by harvey ( 2011 ).

In the last two decades, there has been a small but growing literature on elites. In part, this has been a result of the resurgence of ethnographic research such as interviews, focus groups, case studies, and participant observation but also because scholars have become increasingly interested in understanding the perspectives and behaviors of leaders in business, politics, and society as a whole. Yet until recently, our understanding of some of the methodological challenges of researching elites has lagged behind our rush to interview them.

There is no clear-cut definition of the term elite, and given its broad understanding across the social sciences, scholars have tended to adopt different approaches. Zuckerman (1972) uses the term ultraelites to describe individuals who hold a significant amount of power within a group that is already considered elite. She argues, for example, that US senators constitute part of the country’s political elite but that among them are the ultraelites: a “subset of particularly powerful or prestigious influentials” (160). She suggests that there is a hierarchy of status within elite groups. McDowell (1998) analyses a broader group of “professional elites” who are employees working at different levels for merchant and investment banks in London. She classifies this group as elite because they are “highly skilled, professionally competent, and class-specific” (2135). Parry (1998:2148) uses the term hybrid elites in the context of the international trade of genetic material because she argues that critical knowledge exists not in traditional institutions “but rather as increasingly informal, hybridised, spatially fragmented, and hence largely ‘invisible,’ networks of elite actors.” Given the undertheorization of the term elite, Smith (2006) recognizes why scholars have shaped their definitions to match their respondents . However, she is rightly critical of the underlying assumption that those who hold professional positions necessarily exert as much influence as initially perceived. Indeed, job titles can entirely misrepresent the role of workers and therefore are by no means an indicator of elite status (Harvey 2010).

Many scholars have used the term elite in a relational sense, defining them either in terms of their social position compared to the researcher or compared to the average person in society (Stephens 2007). The problem with this definition is there is no guarantee that an elite subject will necessarily translate this power and authority in an interview setting. Indeed, Smith (2006) found that on the few occasions she experienced respondents wanting to exert their authority over her, it was not from elites but from relatively less senior workers. Furthermore, although business and political elites often receive extensive media training, they are often scrutinized by television and radio journalists and therefore can also feel threatened in an interview, particularly in contexts that are less straightforward to prepare for such as academic interviews. On several occasions, for instance, I have been asked by elite respondents or their personal assistants what they need to prepare for before the interview, which suggests that they consider the interview as some form of challenge or justification for what they do.

In many cases, it is not necessarily the figureheads or leaders of organizations and institutions who have the greatest claim to elite status but those who hold important social networks, social capital, and strategic positions within social structures because they are better able to exert influence (Burt 1992; Parry 1998; Smith 2005; Woods 1998). An elite status can also change, with people both gaining and losing theirs over time. In addition, it is geographically specific, with people holding elite status in some but not all locations. In short, it is clear that the term elite can mean many things in different contexts, which explains the range of definitions. The purpose here is not to critique these other definitions but rather to highlight the variety of perspectives.

When referring to my research, I define elites as those who occupy senior-management- and board-level positions within organizations. This is a similar scope of definition to Zuckerman’s (1972) but focuses on a level immediately below her ultraelite subjects. My definition is narrower than McDowell’s (1998) because it is clear in the context of my research that these people have significant decision-making influence within and outside of the firm and therefore present a unique challenge to interview. I deliberately use the term elite more broadly when drawing on examples from the theoretical literature in order to compare my experiences with those who have researched similar groups.

”Changing Dispositions among the Upwardly Mobile” by Curl, Lareau, and Wu ( 2018 )

There is growing interest in the role of cultural practices in undergirding the social stratification system. For example, Lamont et al. (2014) critically assess the preoccupation with economic dimensions of social stratification and call for more developed cultural models of the transmission of inequality. The importance of cultural factors in the maintenance of social inequality has also received empirical attention from some younger scholars, including Calarco (2011, 2014) and Streib (2015). Yet questions remain regarding the degree to which economic position is tied to cultural sensibilities and the ways in which these cultural sensibilities are imprinted on the self or are subject to change. Although habitus is a core concept in Bourdieu’s theory of social reproduction, there is limited empirical attention to the precise areas of the habitus that can be subject to change during upward mobility as well as the ramifications of these changes for family life.

In Bourdieu’s (1984) highly influential work on the importance of class-based cultural dispositions, habitus is defined as a “durable system of dispositions” created in childhood. The habitus provides a “matrix of perceptions” that seems natural while also structuring future actions and pathways. In many of his writings, Bourdieu emphasized the durability of cultural tastes and dispositions and did not consider empirically whether these dispositions might be changed or altered throughout one’s life (Swartz 1997). His theoretical work does permit the possibility of upward mobility and transformation, however, through the ability of the habitus to “improvise” or “change” due to “new experiences” (Friedman 2016:131). Researchers have differed in opinion on the durability of the habitus and its ability to change (King 2000). Based on marital conflict in cross-class marriages, for instance, Streib (2015) argues that cultural dispositions of individuals raised in working-class families are deeply embedded and largely unchanging. In a somewhat different vein, Horvat and Davis (2011:152) argue that young adults enrolled in an alternative educational program undergo important shifts in their self-perception, such as “self-esteem” and their “ability to accomplish something of value.” Others argue there is variability in the degree to which habitus changes dependent on life experience and personality (Christodoulou and Spyridakis 2016). Recently, additional studies have investigated the habitus as it intersects with lifestyle through the lens of meaning making (Ambrasat et al. 2016). There is, therefore, ample discussion of class-based cultural practices in self-perception (Horvat and Davis 2011), lifestyle (Ambrasat et al. 2016), and other forms of taste (Andrews 2012; Bourdieu 1984), yet researchers have not sufficiently delineated which aspects of the habitus might change through upward mobility or which specific dimensions of life prompt moments of class-based conflict.

Bourdieu (1999:511; 2004) acknowledged simmering tensions between the durable aspects of habitus and those aspects that have been transformed—that is, a “fractured” or “cleft” habitus. Others have explored these tensions as a “divided” or “fragmented” habitus (Baxter and Britton 2001; Lee and Kramer 2013). Each of these conceptions of the habitus implies that changes in cultural dispositions are possible but come with costs. Exploration of the specific aspects of one’s habitus that can change and generate conflict contributes to this literature.

Scholars have also studied the costs associated with academic success for working-class undergraduates (Hurst 2010; Lee and Kramer 2013; London 1989; Reay 2017; Rondini 2016; Stuber 2011), but we know little about the lasting effects on adults. For instance, Lee and Kramer (2013) point to cross-class tensions as family and friends criticize upwardly mobile individuals for their newly acquired cultural dispositions. Documenting the tension many working-class students experience with their friends and families of origin, they find that the source of their pain or struggle is “shaped not only by their interactions with non-mobile family and friends but also within their own minds, by their own assessments of their social positions, and by how those positions are interpreted by others” (Lee and Kramer 2013:29). Hurst (2010) also explores the experiences of undergraduates who have been academically successful and the costs associated with that success. She finds that decisions about “class allegiance and identity” are required aspects of what it means to “becom[e] educated” (4) and that working-class students deal with these cultural changes differently. Jack (2014, 2016) also argues that there is diversity among lower-income students, which yields varied college experiences. Naming two groups, the “doubly disadvantaged” and the “privileged poor,” he argues that previous experience with “elite environments” (2014:456) prior to college informs students’ ability to take on dominant cultural practices, particularly around engagement, such as help seeking or meeting with professors (2016). These studies shed light on the role college might play as a “lever for mobility” (2016:15) and discuss the pain and difficulty associated with upward mobility among undergraduates, but the studies do not illuminate how these tensions unfold in adulthood. Neither have they sufficiently addressed potential enduring tensions with extended family members as well as the specific nature of the difficulties.

Some scholars point to the positive outcomes upwardly mobile youth (Lehmann 2009) and adults (Stuber 2005) experience when they maintain a different habitus than their newly acquired class position, although, as Jack (2014, 2016) shows, those experiences may vary depending on one’s experience with elite environments in their youth. Researchers have not sufficiently explored the specific aspects of the habitus that upwardly mobile adults change or the conflicts that emerge with family and childhood friends as they reach adulthood and experience colliding social worlds. We contribute to this scholarship with clear examples of self-reported changes to one’s cultural dispositions in three specific areas: “horizons,” food and health, and communication. We link these changes to enduring tension with family members, friends, and colleagues and explore varied responses to this tension based on race.

Further Readings

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation: A Road Map from Beginning to End . 2nd ed. Thousand Oaks, CA: SAGE. In keeping with its general approach to qualitative research, includes a “road map” for conducting a literature review.

Hart, Chris. 1998. Doing a Literature Review: Releasing the Social Science Research Imagination . London: SAGE. A how-to book dedicated entirely to conducting a literature review from a British perspective. Useful for both undergraduate and graduate students.

Machi, Lawrence A., and Brenda T. McEvoy. 2022. The Literature Review: Six Steps to Success . 4th ed. Newbury Park, CA: Corwin. A well-organized guidebook complete with reflection sections to prompt successful thinking about your literature review.

Ridley, Diana. 2008. The Literature Review: A Step-by-Step Guide for Students . London: SAGE. A highly recommended companion to conducting a literature review for doctoral-level students.

The process of systematically searching through pre-existing studies (“literature”) on the subject of research; also, the section of a presentation in which the pre-existing literature is discussed.

Follow-up questions used in a semi-structured interview  to elicit further elaboration.  Suggested prompts can be included in the interview guide  to be used/deployed depending on how the initial question was answered or if the topic of the prompt does not emerge spontaneously.

A tool for identifying relationships among ideas by visually representing them on paper.  Most concept maps depict ideas as boxes or circles (also called nodes), which are structured hierarchically and connected with lines or arrows (also called arcs). These lines are labeled with linking words and phrases to help explain the connections between concepts.  Also known as mind mapping.

The people who are the subjects of an interview-based qualitative study. In general, they are also known as the participants, and for purposes of IRBs they are often referred to as the human subjects of the research.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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Qualitative research: literature review .

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Exploring the literature review 

Literature review model: 6 steps.

literature review process

Adapted from The Literature Review , Machi & McEvoy (2009, p. 13).

Your Literature Review

Step 2: search, boolean search strategies, search limiters, ★ ebsco & google drive.

Right arrow

1. Select a Topic

"All research begins with curiosity" (Machi & McEvoy, 2009, p. 14)

Selection of a topic, and fully defined research interest and question, is supervised (and approved) by your professor. Tips for crafting your topic include:

  • Be specific. Take time to define your interest.
  • Topic Focus. Fully describe and sufficiently narrow the focus for research.
  • Academic Discipline. Learn more about your area of research & refine the scope.
  • Avoid Bias. Be aware of bias that you (as a researcher) may have.
  • Document your research. Use Google Docs to track your research process.
  • Research apps. Consider using Evernote or Zotero to track your research.

Consider Purpose

What will your topic and research address?

In The Literature Review: A Step-by-Step Guide for Students , Ridley presents that literature reviews serve several purposes (2008, p. 16-17).  Included are the following points:

  • Historical background for the research;
  • Overview of current field provided by "contemporary debates, issues, and questions;"
  • Theories and concepts related to your research;
  • Introduce "relevant terminology" - or academic language - being used it the field;
  • Connect to existing research - does your work "extend or challenge [this] or address a gap;" 
  • Provide "supporting evidence for a practical problem or issue" that your research addresses.

★ Schedule a research appointment

At this point in your literature review, take time to meet with a librarian. Why? Understanding the subject terminology used in databases can be challenging. Archer Librarians can help you structure a search, preparing you for step two. How? Contact a librarian directly or use the online form to schedule an appointment. Details are provided in the adjacent Schedule an Appointment box.

2. Search the Literature

Collect & Select Data: Preview, select, and organize

AU Library is your go-to resource for this step in your literature review process. The literature search will include books and ebooks, scholarly and practitioner journals, theses and dissertations, and indexes. You may also choose to include web sites, blogs, open access resources, and newspapers. This library guide provides access to resources needed to complete a literature review.

Books & eBooks: Archer Library & OhioLINK

Databases: scholarly & practitioner journals.

Review the Library Databases tab on this library guide, it provides links to recommended databases for Education & Psychology, Business, and General & Social Sciences.

Expand your journal search; a complete listing of available AU Library and OhioLINK databases is available on the Databases  A to Z list . Search the database by subject, type, name, or do use the search box for a general title search. The A to Z list also includes open access resources and select internet sites.

Databases: Theses & Dissertations

Review the Library Databases tab on this guide, it includes Theses & Dissertation resources. AU library also has AU student authored theses and dissertations available in print, search the library catalog for these titles.

Did you know? If you are looking for particular chapters within a dissertation that is not fully available online, it is possible to submit an ILL article request . Do this instead of requesting the entire dissertation.

Newspapers:  Databases & Internet

Consider current literature in your academic field. AU Library's database collection includes The Chronicle of Higher Education and The Wall Street Journal .  The Internet Resources tab in this guide provides links to newspapers and online journals such as Inside Higher Ed , COABE Journal , and Education Week .


Search Strategies & Boolean Operators

There are three basic boolean operators:  AND, OR, and NOT.

Used with your search terms, boolean operators will either expand or limit results. What purpose do they serve? They help to define the relationship between your search terms. For example, using the operator AND will combine the terms expanding the search. When searching some databases, and Google, the operator AND may be implied.

Overview of boolean terms

About the example: Boolean searches were conducted on November 4, 2019; result numbers may vary at a later date. No additional database limiters were set to further narrow search returns.

Database Search Limiters

Database strategies for targeted search results.

Most databases include limiters, or additional parameters, you may use to strategically focus search results.  EBSCO databases, such as Education Research Complete & Academic Search Complete provide options to:

  • Limit results to full text;
  • Limit results to scholarly journals, and reference available;
  • Select results source type to journals, magazines, conference papers, reviews, and newspapers
  • Publication date

Keep in mind that these tools are defined as limiters for a reason; adding them to a search will limit the number of results returned.  This can be a double-edged sword.  How? 

  • If limiting results to full-text only, you may miss an important piece of research that could change the direction of your research. Interlibrary loan is available to students, free of charge. Request articles that are not available in full-text; they will be sent to you via email.
  • If narrowing publication date, you may eliminate significant historical - or recent - research conducted on your topic.
  • Limiting resource type to a specific type of material may cause bias in the research results.

Use limiters with care. When starting a search, consider opting out of limiters until the initial literature screening is complete. The second or third time through your research may be the ideal time to focus on specific time periods or material (scholarly vs newspaper).

★ Truncating Search Terms

Expanding your search term at the root.

Truncating is often referred to as 'wildcard' searching. Databases may have their own specific wildcard elements however, the most commonly used are the asterisk (*) or question mark (?).  When used within your search. they will expand returned results.

Asterisk (*) Wildcard

Using the asterisk wildcard will return varied spellings of the truncated word. In the following example, the search term education was truncated after the letter "t."

Explore these database help pages for additional information on crafting search terms.

  • EBSCO Connect: Searching with Wildcards and Truncation Symbols
  • EBSCO Connect: Searching with Boolean Operators
  • EBSCO Connect: EBSCOhost Search Tips
  • EBSCO Connect: Basic Searching with EBSCO
  • ProQuest Help: Search Tips
  • ERIC: How does ERIC search work?

★ EBSCO Databases & Google Drive

Tips for saving research directly to Google drive.

Researching in an EBSCO database?

It is possible to save articles (PDF and HTML) and abstracts in EBSCOhost databases directly to Google drive. Select the Google Drive icon, authenticate using a Google account, and an EBSCO folder will be created in your account. This is a great option for managing your research. If documenting your research in a Google Doc, consider linking the information to actual articles saved in drive.

EBSCO Databases & Google Drive

EBSCOHost Databases & Google Drive: Managing your Research

This video features an overview of how to use Google Drive with EBSCO databases to help manage your research. It presents information for connecting an active Google account to EBSCO and steps needed to provide permission for EBSCO to manage a folder in Drive.

About the Video:  Closed captioning is available, select CC from the video menu.  If you need to review a specific area on the video, view on YouTube and expand the video description for access to topic time stamps.  A video transcript is provided below.

  • EBSCOhost Databases & Google Scholar

Defining Literature Review

What is a literature review.

A definition from the Online Dictionary for Library and Information Sciences .

A literature review is "a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works" (Reitz, 2014). 

A systemic review is "a literature review focused on a specific research question, which uses explicit methods to minimize bias in the identification, appraisal, selection, and synthesis of all the high-quality evidence pertinent to the question" (Reitz, 2014).

Recommended Reading

Cover Art

About this page

EBSCO Connect [Discovery and Search]. (2022). Searching with boolean operators. Retrieved May, 3, 2022 from https://connect.ebsco.com/s/?language=en_US

EBSCO Connect [Discover and Search]. (2022). Searching with wildcards and truncation symbols. Retrieved May 3, 2022; https://connect.ebsco.com/s/?language=en_US

Machi, L.A. & McEvoy, B.T. (2009). The literature review . Thousand Oaks, CA: Corwin Press: 

Reitz, J.M. (2014). Online dictionary for library and information science. ABC-CLIO, Libraries Unlimited . Retrieved from https://www.abc-clio.com/ODLIS/odlis_A.aspx

Ridley, D. (2008). The literature review: A step-by-step guide for students . Thousand Oaks, CA: Sage Publications, Inc.

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:


Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.


We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.


Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.


is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Libraries | Research Guides

Literature reviews, what is a literature review, learning more about how to do a literature review.

  • Planning the Review
  • The Research Question
  • Choosing Where to Search
  • Organizing the Review
  • Writing the Review

A literature review is a review and synthesis of existing research on a topic or research question. A literature review is meant to analyze the scholarly literature, make connections across writings and identify strengths, weaknesses, trends, and missing conversations. A literature review should address different aspects of a topic as it relates to your research question. A literature review goes beyond a description or summary of the literature you have read. 

  • Sage Research Methods Core Collection This link opens in a new window SAGE Research Methods supports research at all levels by providing material to guide users through every step of the research process. SAGE Research Methods is the ultimate methods library with more than 1000 books, reference works, journal articles, and instructional videos by world-leading academics from across the social sciences, including the largest collection of qualitative methods books available online from any scholarly publisher. – Publisher

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importance of literature review in qualitative research

3 Literature Review

Charitianne Williams

By the end of this chapter, you will be able to do the following:

  • Understand the purpose and function of a literature review.
  • Structure a literature review according to basic genre expectations.
  • Synthesize ideas from multiple sources using a synthesis matrix.
  • Choose between narrative or parenthetical citation and direct quoting, or paraphrase with intent and purpose.

I. Introduction

The purpose of a literature review is just that—it reviews. This means that literature reviews examine a text after it was produced, with all the benefits that hindsight allows a reader. In popular culture, we commonly review movies, restaurants, vacation spots, products, etc. In those reviews, you look back at the single thing you are reviewing and your experience with it. You focus on the strengths and weaknesses of your experience and judge the experience as positive or negative while recommending or not recommending the place or product and explaining why.

An academic literature review does something different, although some of the skills and strategies you use remain the same. The job of a literature review is to examine a collection of research or scholarship (not a single thing or text) on a given topic and show how that scholarship fits together. Literature reviews summarize, describe, evaluate, and synthesize the work of other authors and researchers while looking for common trends/patterns, themes, inconsistencies, and gaps in this previous research. The main strategy writers of a literature review use is synthesis.

SYNTHESIS: the combination of ideas and elements to form a complete system or theory.

A good metaphor for synthesis is cooking! Imagine the ingredients for a loaf of bread laid out on a kitchen cabinet. Each ingredient—eggs, milk, flour, sugar, salt, yeast—have their own purpose and can be combined in different ways to form food other than bread. Knowing all of those individual attributes that make an egg an egg, or the difference between yeast and flour, is what makes you a chef. When you combine all these ingredients according to the recipe, you get something different than all the ingredients on their own: and most of us would rather eat a slice of bread than a spoonful of flour. The product of synthesis is like bread. Synthesis takes a list of ingredients and makes them into something more than the ingredients alone.

The images show ingredients, followed by a recipe, and then all put together for bread. These images are meant to compare the baking process to synthesis in writing.

Usually, the writers of a literature review will start with a question that they want to answer through informed and research-based evidence gathered while reading others’ work on related topics. The “thesis” or controlling idea of a literature review may be that same question ( “This review seeks to answer…” ) or it may be a statement describing the reviewed research. The thesis reflects the purpose of the literature review as a genre and is different from the thesis you will write for the research paper that argues a claim or asserts a new idea.

Example 3.1: Look at this thesis statement taken from the introduction of a literature review in environmental psychology on the relationship between “nature sounds” and restorative environments:

From this example, we can learn many things about literature reviews:

  • They are explicit and focused on their topic. The opening states an observable truth about the current research ( emphasizes nature ), is followed by a general condition ( positive psychological experiences) within that research, and then finally focuses on describing how a particular outcome is achieved (listening to nature sounds is restorative).
  • They seek to pre vent or eliminate misunderstanding. Note the use of specialized key terms, exacting transitional phrases, and meaningful verbs in the thesis such as “ restorative environments,” “in particular,” and “ generate .”
  • They seek to forward understanding. In other words, literature reviews examine and link together evidence described and validated in the research of others so a reader can learn how a field is developing. ( Research seems to agree that nature sounds can relieve stress and fatigue–this review will examine that conclusion so readers can understand/ build on how and why.)

Moving from the beginning to the very end of the literature review, we can also learn many things about literature reviews from the sources used. Think of each text listed in the References section of a literature review as contributing pieces to a gigantic puzzle.

Example 3.2: Look at the first three articles listed in the References for the article excerpted above:

Abbott, L. C., Taff, D., Newman, P., Benfield, J. A., and Mowen, A. J. (2016). The influence of natural sounds on attention restoration. J. Park Recreation Adm. 34, 5–15. doi: 10.18666/JPRA-2016-V34-I3-6893

Aletta, F., and Kang, J. (2019). Promoting healthy and supportive acoustic environments: going beyond the quietness. Int. J. Environ. Res. Public Health 16:4988. doi: 10.3390/ijerph16244988

Aletta, F., Oberman, T., and Kang, J. (2018). Associations between positive health-related effects and soundscapes perceptual constructs: a systematic review. Int. J. Environ. Res. Public Health 15:2392. doi: 10.3390/ijerph15112392

None of these sources are exactly the same. One focuses on sound and attention, the next two on sound and health, and none of them are quite the same as sound and restoration —but they are all pieces of the puzzle that give a full understanding of how sound and restorative environments relate.

As the author of the literature review, it is your job to join the pieces together, giving your reader a complete picture of what researchers know about your topic.

Literature reviews are an indispensable tool for researchers. Instead of having to read dozens of articles on a topic, a researcher could instead read a literature review that synthesizes what is known and puts each piece of scholarship into conversation with the others. This could be not only quicker, but also more valuable.

Have you heard the saying that the whole is more than the sum of its parts? The knowledge constructed by a well-written literature review often outweighs the knowledge constructed by simply reading each article in the References section on its own because the author of a literature review processes and analyzes the information for the reader.

Literature reviews occur in two general forms—as a background section in a scholarly work or as a stand-alone genre in and of itself. In both situations, the basic purpose and structure of the literature review is similar: it is the length and the scope that varies. For example, consider the previous chapter, the Proposal. In most proposals, you will want to convince your audience that you are informed on the background of your topic—a literature review is how you would do that. Since a proposal is commonly a short text, you do not have the space to summarize every piece of research. You must select an important set and synthesize that information into a small section signaling your expertise.

On the other hand, consider a professional journal intended to keep its readers up to date on new technologies and findings in a specific field or career. New ideas and discoveries are emerging every day, and it can be difficult to stay on top of all of these new findings, understand how they fit together, and also keep track of your own career responsibilities! A magazine might hire an author to read all the new research on a specific topic and synthesize it into a single article, a state-of-the-art review, so that practitioners in a field can read a single 25-page article instead of 100 25-page articles.

More Resources 3.1: Literature Reviews

II. Rhetorical Considerations: Voice

Using the scholarship of other writers and researchers is one of the things that differentiates academic writing from other types of writing. Using others’ scholarship in a meaningful way that creates new knowledge without mischaracterizing the original findings takes effort, attention, and usually several rounds of revision and rewriting. One of the issues is voice , which refers to the attitude and tone of a text—think of it as what the text “sounds like” in your head as you read it. Voice is an important element of cohesion , or what some people think of as “flow.” Creating a consistent voice in the mind of your reader helps them fit all the information in a text together in the way the author intends. Check out this advice from APAstyle.org about academic style and voice.

Think back to your annotated bibliography and how you created your summaries. You probably used key terms from the original authors’ texts, but because you had to take whole articles and restate the meaning in a short paragraph, there wasn’t room to just repeat the words of the original author. So you had to write the summaries in your voice . If you used those key terms correctly and in ways similar to original authors, those key terms probably did not interfere with cohesiveness and voice. However, in the literature review, you have many more voices to synthesize than you did to summarize in the annotated bibliography. Maintaining a consistent and cohesive voice will be challenging. An important way to maintain voice is through paraphrasing, discussed later in this chapter.

More Resources 3.2: Transitions

Another important way to maintain cohesion is through the use of metadiscourse (see Chapter 2) and transitional phrases. See this link for the use and meaning of transitional phrases, sometimes called signposts .

III. The Literature Review Across the Disciplines

Example 3.3: Academic and Professional Examples

Structure of Literature Reviews

While the details vary across disciplines, all literature reviews tend to have similar basic structure. The introduction of a literature review informs the reader on the topic by defining key terms, citing key researchers or research periods in the field, and introducing the main focus of the review in a descriptive thesis statement. The introduction also explains the organization of the review. In a literature review, you organize your discussion of the research by topic or theme— not article or author. This is in direct contrast to the annotated bibliography, which is often the first step in the writing process for a literature review.

In the annotated bibliography, you organize your entries in alphabetical order by authors’ last names. Each annotation is directly connected to a single text. A literature review is connected to a collection of texts, and therefore must be organized in a way that reflects this.

Example 3.4: Let’s examine the full paragraph that the thesis statement we analyzed earlier came from:

A systematic review by Aletta et al. (2018) has identified links between positive urban soundscapes (which may also include nature sounds) and health and well-being, including stress recovery. Given the emphasis on nature w ithin restorative environments (see Hartig et al., 2014 ), the present narrative literature review focuses on evidence for positive psychological experiences of nature sounds and soundscapes specifically, and in particular how listening to these can generate perceptions and outcomes of restoration from stress and fatigue. This review has five key objectives, summarized in Figure 1 [in the article] . First, it explores literature regarding the impact of nature sounds on perceptions and experiences of wider natural environments. Second, it examines evidence regarding cognitive and affective appraisals of nature sounds and their contributions to overall perceptions of restorative environments. Third, literature regarding restorative outcomes in response to nature sounds is assessed. Fourth, the relevance of key restoration theories to this top ic is examined and areas where these theories are limited are identified. Fifth, a possible new theoretical area of interest—semantic associations with nature—is discussed and exemplified by recent acoustics research (Ratcliffe, 2021, emphasis added).

Notice how the thesis statement (in bold ) is followed by an explicit description of the five key objectives—which correspond to the titles (usually called headings ) of the five major sections of the body of the literature review. The introduction basically outlines the body of the literature review to make it easier for a researcher to find the specific information they are looking for. What follows each of these headings is an analysis and synthesis of the topic described in the heading—which is what we mean when we say a literature review is organized by topic.

Example 3.5: See how the body sections of a literature review synthesize research and evidence in relation to a focused topic. Read this example taken from a literature review in another discipline, nursing.

The introduction states that the review’s purpose is to understand the issues facing nurses in situations such as the COVID-19 pandemic. The researchers found several themes in the research that all contributed to nurses’ experiences. This paragraph describes one of those themes which the authors label “Professional collegiality”:

3.2.2. Professional collegiality

Professional camaraderie amongst nursing colleagues working during a pandemic was high (Ives et al., 2009, Kim, 2018, Liu a nd Liehr , 2009). Nurses acknowledged the importance of caring for their co-workers and in sharing the load. Some nurses associated the experience with working on a battlefield, whereby they worked together as a team protecting one another (Chung et al., 20 05, Kang et al., 2018, Liu and Liehr , 2009). Appreciation of their nursing colleagues was demonstrated through sharing their experiences, willingness to work together and encouraging a team spirit (Shih et al., 2007, Chung et al., 2005, Chiang et al., 2007 ). (Ratcliffe, 2021, p.4)

In this single paragraph, there are seven different research articles cited, and some of them are cited twice. There is no way to write a coherent paragraph summarizing seven different research articles at once—instead, the authors of this paragraph reviewed what the researchers said about collegiality, found where their findings pointed in the same direction, and put those connections into their own words. This is the importance of the review’s body section: it is here where you really dig into the content, meaning, and implications of the scholarship you are discussing.

The end of a literature review looks different from the one- or two-paragraph conclusion we are used to in other texts. The end is often made up of multiple sections, each with a slightly different purpose, although all are probably recognizable to you. A “Discussion” section is almost always present, where the author summarizes the most important findings of each section. In most cases, the “Discussion” section does not contain new information, but ties the different body sections together in ways that provide a deeper analysis.

The end of a literature review may also contain an “Implications for Future Research” or “Resolution” after the Discussion—sometimes this final section is even called “Conclusion.” What this last section looks like is often dependent upon the type of review you are writing, and whether the review is standing alone as a complete text or part of a larger project.

In any situation, across all disciplines, it is important to understand how your literature review is meant to inform the reader and what kind of review is appropriate for the context, in order to decide how you should structure the beginning and end of your review.

Types of Literature Reviews

There are different types of literature reviews, although in undergraduate study the Traditional or Narrative Review is most common. Narrative reviews are somewhat exploratory in their content—in a narrative review you are synthesizing the results of specific texts selected for their connection to your topic. Narrative reviews almost always end with a section describing areas for future research if they are a stand-alone text, or a section describing why the author’s research is so needed if part of a larger research article. The chart below outlines the key differences between three major literature review types. Notice that each type has a slightly different purpose. You might think about which type best fits your project as you read.

Table 3.1: Types of Literature Reviews

More Resources 3.3: Literature Review Structures

IV. Research Strategies: Developing a Methodology

Systematic and scoping reviews should always contain a Research Methodology that explains to your reader exactly how you found the research you are reviewing. Often Narrative Reviews will also contain a research methodology, although it will be slightly different since they are not comprehensive reviews, meaning, they do not attempt to find all the research on a topic—by design, they cover only a specific portion. Even if you are not required to write up your methodology, you need clear research strategies to find the appropriate scholarship for your literature review.

Example 3.6: Check out this excerpt from the methods sections from a psychology literature review. Note how the authors clearly describe what types of sources they’ll be using as well as their steps throughout the research process.

Drawing on individual case studies, archival reports, correlational studies, and laboratory and field experiments, this monograph scrutinizes a sequence of events during which confessions may be obtained from criminal suspects and used as evidence. First, we examine the pre-interrogation interview, a process by which police …( Kassin and Gudjonsson , 2004, p.33)

Example 3.7: Here is another example from the field of education. In it the authors describe two separate searches they performed to gather the literature—the first search used key terms they decided upon before reading any scholarship, and the second search used the terms that they found were common to that first set of texts (see more about key terms here and in the Annotated Bibliography chapter).

We conducted two rounds of literature searches, utilizing the following databases: World CAT (general search), EB SCO Academic Search Complete, EBSCO Education Source, and Linguistics and Language Behavior Abstracts (ProQuest). In the first round, we searched using every possible combination of the following terms: ‘race,’ ‘language teaching,’ ‘ethnicity,’ ‘language p edagogy,’ ‘Whiteness,’ ‘racialized,’ ‘antiracism,’ and ‘ nativeness .’ For the second round of our literature search, we searched using terms that we saw emerging from the literature such as ‘racial identities of language learners,’ ‘racial identities of lan guage teachers,’ ‘language varieties and language teaching,’ ‘race and language teacher education,’ ‘race and educational policy,’ ‘race and language programs,’ and ‘race and language curriculum’ and also repeated our earlier searches in order to keep the literature updated. (Von Esch et al., 2020, p. 392)

No matter the type of research (see a description of qualitative vs. quantitative research ), the specific genres (see descriptions of academic research genres ), or the time frame (see a discussion on the importance of publication date ) you use for your review, it is important to think through the options, make a decision, and incorporate all your research knowledge—use of key terms, use of subject filters, use of specialized databases, etc.—into a coherent and meaningful process that results in the best scholarship for your inquiry and review.

Here’s a video to help you get started on using databases for research:

Library Referral: Connecting the Conversation with Scholarly Sources and Beyond​

(by Annie R. Armstrong)

Research involves drawing from numerous voices from a range of source types. The sources you choose to include in your conversation are context-specific and might vary depending on your topic or the parameters of your assignment. Review your assignment description and talk to your instructor about guidelines. While most research papers emphasize scholarly sources, expertise isn’t always equated with scholarliness and you might want to branch out. For example, a research paper focusing on exploitation of Native American land and communities by the mining industry should make some attempt to include sources generated by the communities under discussion, especially if their point of view is not represented in the peer-reviewed, scholarly sources you’ve found. Think about who the stakeholders are as related to various aspects of your topic and how you can tap into their voices through available resources. You may want to consult a librarian about this.

The chart below summarizes the breadth of source types available through library websites versus the open web:

Table 3.2: Scholarly Sources and Beyond

V. Reading Strategies: Intertextuality and Graphic Organizers

Typically we think of reading as something we do to learn the content of a text—and this is absolutely true! But true understanding means knowing the relationships between and impact of separate but related topics, which might mean understanding how different texts—generally focused on one topic—overlap or differ.

Intertextuality refers to the connections that exist between texts. Intertextuality as a reading strategy means looking for the connections between the text you are reading and others you have already read; anticipating connections with other texts that you have not yet read, but plan to; as well as connections to whole disciplines, fields, and social phenomena. Reading for intertextuality means looking for opportunities to connect texts with each other, and keeping track of those connections in a productive way.

This means note-taking is essential to intertextual reading. Once you have thought carefully about why you are reading a text, what types of information to look for, and what you will do with that information, you can better decide how to keep track of that information. In regards to literature reviews, one type of graphic organizer dominates: the Synthesis Matrix.

The synthesis matrix is a way to keep track of the themes, concepts, and patterns that are emerging from your reading—NOT all the individual content of each article. This is important, yes, and you will need the citations, but literature reviews move one step further into the topic than simply identifying the pieces. You will need to synthesize.

If you have an annotated bibliography of sources already, it is the perfect way to start your synthesis matrix. An annotated bibliography is often the first step in preparing for a literature review, and is quite similar to an ingredient list, if we are using the metaphor from the introduction. (For a detailed description of how to write an annotated bibliography, see Chapter 1 ).

In your annotations, you will have selected the most important information that text supplies in relation to your topic. For an example, let’s take the Conference on College Composition and Communication’s statement “ Students’ Right to Their Own Language ,” which contains two annotated bibliographies. The second uses more recent sources and looks most like the annotated bibliographies you will write as a student, so let’s start there.

Example 3.8: Here are three annotations from that bibliography. As you read, take notice of the different highlighted colors. Phrases italicized and highlighted green identify ideas related to linguistic identity , phrases bolded and highlighted in blue identify concepts related to grammar analysis , and phrases underlined and highlighted orange identify groups and ideas related to educational objectives :

Fought, Carmen. Chicano English in Context. New York: Palgrave Macmillan, 2003.

Based primarily on data collected from adolescent and young adult native speakers in Los Angeles , this book is a comprehensive sociolinguistic study of language and language change in Latino/a communities. It provides the basics of Chicano English (CE) structure (phonology, syntax, and semantics) and its connection to the social and cultural identity of its speakers, along with detailed analyses of particular sociolinguistic variables. Emphasis is given to the historical, social, and linguistic contexts of CE. In addition, the differences between native and non-native CE speakers are covered. A final chapter discusses the future of research on CE.

Lippi-Green, Rosina. English with an Accent: Language, Ideology, and Discrimination in the United States . London and New York: Routledge, 1997.

The author examines linguistic facts about the structure and function of language , explores commonly held myths about language, and develops a model of “the language subordination process.” Then, using a case-study approach, she applies the model to specific institutional practices (e.g., in education, news media, business) to show how false assumptions about language lead to language subordination. The author analyzes specific groups and individuals (speakers of African American English, Southern U.S. English, and the foreign-language accent of Latinos and Asian Americans) and discusses why and how some embrace linguistic assimilation while others resist it.

Nero, Shondel J. Englishes in Contact: Anglophone Caribbean Students in an Urban College. Cresskill, NJ: Hampton Press, 2001.

This qualitative study of four anglophone Caribbean students at a New York City college offers an in-depth examination of the students’ written and spoken language and the challenges faced by both students and teachers as such students acquire academic literacy. Case studies of the four participants include excerpts from tape-recorded interviews, which reflect their linguistic self-perception, and sociolinguistic and educational experiences in their home countries and in New York City. Samples of their college writing over four semesters are represented and analyzed on morphosyntactic and discourse levels to determine the patterns that emerge when Creole English speakers attempt to write Standard Written English. Related issues such as language and identity , language attitudes, and educational responses to ethnolinguistic diversity are also discussed.

Once you have identified a concept like “language and identity” for your literature review, you can start getting “intertextual”! Review your other annotated sources and your new sources for their discussion of language and identity, as well as parallel concepts—what else do researchers address when they discuss language and identity? What do they discuss instead? Go back to the methods you used to come up with key terms for your literature search—the same strategies now apply to your reading. Also look for “umbrella” concepts, patterns in methodologies—anything that emerges while you read intertextually, focusing on the text in front of you while also remembering all the others you read before. Look for the themes in your annotated bibliography and keep track of the page numbers where these themes appear—plan to go back to those pages several times as you write your literature review.

This is a different type of reading than you did for the annotated bibliography, and might mean you go back and reread your sources several times in this new way—don’t think of this as just repeating labor you have already performed. This is new work, designed to uncover new things in the research. Re-reading articles multiple times is something all serious writers do, and something you should do, too. It isn’t redundant, it is recur sive .

Table 3.3: Synthesis Matrix for Individuals’ Choices in Linguistic Identity

Put your sources into conversations around your themes, as shown in the table above. Notice that the top row names the themes covered in that column, put into original wording similar, but not identical, to the wording in the annotated bibliographies. Not every source will address every topic—not every article is the same. The last row starts to describe what is happening in each column across the whole collection of texts. In this way, your synthesis matrix takes the ingredient list provided by the annotated bibliography and makes it into a recipe for your final product—the literature review.

More Resources 3.4: Synthesis Matrix

VI. Writing Strategies: Citation, Quotation, and Paraphrase

Citation is when you use the work of other authors in your writing and mark that portion of your writing so your reader understands what idea is being “borrowed.” Citation also tells your reader where they could find that original idea in the original text, and how your text fits together with the web of other texts related to your topic: in other words, citations help create intertextuality. A citation placed in your sentences should refer directly to the full bibliographic information in your Works Cited or References page.

As you read in Chapter 1, there are different styles of citation including AMA, APA, CMS, and MLA. You can refer back to that chapter for a more detailed explanation of each. In this section, we’ll cover the basics that are common to citation practices. Most academic styles use the original author’s last name as the central part of the in-text citation, since References pages usually list cited works alphabetically by last name, but some use footnotes or endnotes instead, listing works in the order they were cited. It is important to know which academic style you are using for your literature review so that you can make the right choice.

In-text citation takes one of two forms: parenthetical or narrative. In a narrative citation the author of the original work is mentioned in the sentence.

Example 3.9: Here’s an example taken from the introduction of the same literature review discussed in the Research Strategies: Developing a Methodology section of this chapter.

Several pieces offered a comprehensive review of the historical literature on the formation of Black English as a construct in the context of slavery and Jim Crow, and the historical teaching of Black English within the U .S. context, including Wheeler ( 2016 ) and Alim and Baugh (2007). Wheeler (2016) equated Standard English with ‘White’ English and challenged its hegemony in dialectically diverse classrooms. She named the “racism inherent in [fostering] bidialectalism [th rough teaching]” (p. 380), arguing that we are acknowledging that the only way for African-Americans to be upwardly mobile was to learn how to speak ‘White’ English. Alim (2010) , explained, “By uncritically presenting language varieties as ‘equal’ but diff ering in levels of ‘appropriateness,’ language and Dialect Awareness programs run the risk of silently legitimizing ‘Standard English’” (p. 215)…. Current work addressing AAVE studies has been shifting focus to translingualism and to promoting such pedag ogies as code-meshing (Young, Barrett, Young Rivera and Lovejoy, 2014) and translanguaging (García & Wei, García and Wei, 2014) , embedded in a critical analysis of the racial logics underpinning the denigration of some languages. This work, combined with e xtensive examinations of the connections between race, language, teaching, and identity ( e.g. Flores & Rosa, 2015; Alim et al., 2016 ), has laid a foundation for a raciolinguistics approach to teaching, which we return to later in this article. (Von Esch et al., 2020, p. 399, emphasis added .)

In the first sentence, we see two narrative citations just before the period. These citations state the authors’ names as a part of the sentence, and put the publication date of the articles in parenthesis. It makes sense to use a narrative citation in the topic sentence, since most of the paragraph is a synthesis of Wheeler and Alim’s research. The second sentence starts with Wheeler’s name in the subject position, and the fourth sentence starts with Alim’s name in the subject position—both are narrative citations, a form chosen by the author to emphasize the importance and similarities in the two articles.

In the last two sentences, we see parenthetical citations. The citation information is in parenthesis within the sentences, which focuses the reader on the ideas, not the research itself. Imagine you were reading this article out loud—you would most certainly say the narrative citations “Wheeler” and “Alim”; you might choose not to say “Young, Barrett, Young-Rivera, & Lovejoy, 2014,” though, and no one listening to you would notice the omission. This is the most important difference between narrative and parenthetical citation—narrative draws attention to the researchers, while parenthetical allows a focus on ideas. In academic writing, you often have reason to use both, but it is important to note that using parenthetical citation is less disruptive to your voice—it keeps a reader focused on the ideas you are explaining.

Usually you are citing a type of quotation in your text (although different disciplines have other situations that they cite). Direct quotation and paraphrase are usually what we talk about when we talk about using resources in your writing, although summary is cited as well.

Direct quotation is when you take the original words of one author and place them in your own text. When you quote in your own writing, you mark the copied text—usually with quotation marks “” around the text and a citation afterwards. Quoting is useful when the original author is an important authority on a topic or if you want to define/describe another’s point of view in a way that leaves no room for misinterpretation.

In a literature review, a direct quote will almost always be accompanied by a narrative citation. But direct quoting can cause some issues in your own text, such as a sudden shift in voice and a loss of cohesion; the potential for misunderstanding and misrepresentation, since the quote has been separated from its original context; and wordiness —quotes can take up too much space both in terms of the quote itself, and of the explanation and context you must provide for the introduced idea. For these reasons, literature reviews do not contain much direct quoting.

Paraphrasing is a way to accomplish similar goals to direct quoting without causing the same problems. Paraphrasing is when you use only the original author’s key terms and ideas, but your own words. Paraphrasing still contains a citation afterwards that directs the reader to the full bibliographic information in your Works Cited, but does not require quotation marks since the language is yours. Paraphrase may be longer or shorter than the original author’s text, and uses both narrative and parenthetical citation. Paraphrase also allows you to cite more than one piece of research containing the same idea in a single sentence, such as the last sentence in the example paragraph above. This kind of citation string is important to literature reviews because it clearly identifies patterns and trends in research findings.

Key Takeaways

  • Literature reviews are a synthesis of what other researchers have discovered on your topic. Think of reviews as “the big picture.”
  • Taking so much information from other sources can get confusing–use section headings to keep your review organized and clear.
  • Diverse citation, quotation, and paraphrasing techniques are necessary to help your reader understand where the ideas are coming from, AND to help make the ideas “stick together.”
  • Keeping all the new knowledge you are learning from your sources organized is hard! Take notes using citations and use a graphic organizer to keep yourself on track.

Fernandez, Lord, H., Halcomb, E., Moxham, L., Middleton, R., Alananzeh, I., & Ellwood, L. (2020). Implications for COVID-19: A systematic review of nurses’ experiences of working in acute care hospital settings during a respiratory pandemic. International Journal of Nursing Studies , 111. https://doi.org/10.1016/j.ijnurstu.2020.103637

Kassin, S. M., & Gudjonsson, G. H. (2004). The psychology of confessions. Psychological Science in the Public Interest , 5 (2), 33–67. https://doi.org/10.1111/j.1529-1006.2004.00016.x

National Council of Teachers of English. (2018, June 16). Students’ right to their own language (with bibliography) . Conference on College Composition and Communication. Retrieved July 24, 2022, from https://cccc.ncte.org/cccc/resources/positions/srtolsummary

NEIU Libraries. (2020). “How should I search in a database?”  YouTube . https://www.youtube.com/watch?v=8fgBF0EuH_o

Ratcliffe, E. (2021). Summary Flowchart [Image]. Frontiers in Psychology. https://www.frontiersin.org/articles/10.3389/fpsyg.2021.570563/full#B3

Ratcliffe, E. (2021). Sound and soundscape in restorative natural environments: A narrative literature review. Frontiers in Psychology , 12 . https://doi.org/10.3389/fpsyg.2021.570563

Sasaki. K. (2022). Synthesis and Recipes [Image].

Von Esch, K., Motha, S., & Kubota, R. (2020). Race and language teaching. Language Teaching, 53 (4), 391-421. doi:10.1017/S0261444820000269

Writing for Inquiry and Research Copyright © 2023 by Charitianne Williams is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Qualitative researchers TEND to:

Researchers using qualitative methods tend to:

  • t hink that social sciences cannot be well-studied with the same methods as natural or physical sciences
  • feel that human behavior is context-specific; therefore, behavior must be studied holistically, in situ, rather than being manipulated
  • employ an 'insider's' perspective; research tends to be personal and thereby more subjective.
  • do interviews, focus groups, field research, case studies, and conversational or content analysis.

reasons to make a qualitative study; From https://www.editage.com/insights/qualitative-quantitative-or-mixed-methods-a-quick-guide-to-choose-the-right-design-for-your-research?refer-type=infographics

Image from https://www.editage.com/insights/qualitative-quantitative-or-mixed-methods-a-quick-guide-to-choose-the-right-design-for-your-research?refer-type=infographics

Qualitative Research (an operational definition)

Qualitative Research: an operational description

Purpose : explain; gain insight and understanding of phenomena through intensive collection and study of narrative data

Approach: inductive; value-laden/subjective; holistic, process-oriented

Hypotheses: tentative, evolving; based on the particular study

Lit. Review: limited; may not be exhaustive

Setting: naturalistic, when and as much as possible

Sampling : for the purpose; not necessarily representative; for in-depth understanding

Measurement: narrative; ongoing

Design and Method: flexible, specified only generally; based on non-intervention, minimal disturbance, such as historical, ethnographic, or case studies

Data Collection: document collection, participant observation, informal interviews, field notes

Data Analysis: raw data is words/ ongoing; involves synthesis

Data Interpretation: tentative, reviewed on ongoing basis, speculative

  • Qualitative research with more structure and less subjectivity
  • Increased application of both strategies to the same study ("mixed methods")
  • Evidence-based practice emphasized in more fields (nursing, social work, education, and others).

Some Other Guidelines

  • Guide for formatting Graphs and Tables
  • Critical Appraisal Checklist for an Article On Qualitative Research

Quantitative researchers TEND to:

Researchers using quantitative methods tend to:

  • think that both natural and social sciences strive to explain phenomena with confirmable theories derived from testable assumptions
  • attempt to reduce social reality to variables, in the same way as with physical reality
  • try to tightly control the variable(s) in question to see how the others are influenced.
  • Do experiments, have control groups, use blind or double-blind studies; use measures or instruments.

reasons to do a quantitative study. From https://www.editage.com/insights/qualitative-quantitative-or-mixed-methods-a-quick-guide-to-choose-the-right-design-for-your-research?refer-type=infographics

Quantitative Research (an operational definition)

Quantitative research: an operational description

Purpose: explain, predict or control phenomena through focused collection and analysis of numberical data

Approach: deductive; tries to be value-free/has objectives/ is outcome-oriented

Hypotheses : Specific, testable, and stated prior to study

Lit. Review: extensive; may significantly influence a particular study

Setting: controlled to the degree possible

Sampling: uses largest manageable random/randomized sample, to allow generalization of results to larger populations

Measurement: standardized, numberical; "at the end"

Design and Method: Strongly structured, specified in detail in advance; involves intervention, manipulation and control groups; descriptive, correlational, experimental

Data Collection: via instruments, surveys, experiments, semi-structured formal interviews, tests or questionnaires

Data Analysis: raw data is numbers; at end of study, usually statistical

Data Interpretation: formulated at end of study; stated as a degree of certainty

This page on qualitative and quantitative research has been adapted and expanded from a handout by Suzy Westenkirchner. Used with permission.

Images from https://www.editage.com/insights/qualitative-quantitative-or-mixed-methods-a-quick-guide-to-choose-the-right-design-for-your-research?refer-type=infographics.

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Qualitative Research

Literature Review

Literature review is important because it:

  • Provides ideas about what should be studied;
  • Helps us conduct inquires that have not already been done
  • Connects our research to existing studies

But…doing a literature review is not simply summarizing (or copying) what you think is related and useful to your work. BEING CRITICAL AND CAREFUL IS A MUST !

In reviewing existing literature, you may try to look for gaps in the field and rework your study in a different setting or with different people. Nonetheless, literature review is a continuous sense-making process -- you need to review the literature continuously in order to organize your thoughts and refine your analysis.

A good literature review should be able to:  

  • Connect to your research questions
  • Connect to your choice of methods and research design
  • Support your data analysis
  • Help you draw conclusions and make claims about your research.

Selecting your literature with a purpose

It is impossible to read everything, so when selecting literature  for reviewing, consider these:

  • Is it relevant to your topic/field of study?
  • Is it a primary source from the researcher(s) or secondary source (e.g. a summary you read in a book about someone’s research)?
  • Is it updated?

Nature of literatures:

Your literature review can be of different dimensions. Each has its foci and purposes

importance of literature review in qualitative research

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Conducting a Literature Review

Benefits of conducting a literature review.

  • Steps in Conducting a Literature Review
  • Summary of the Process
  • Additional Resources
  • Literature Review Tutorial by American University Library
  • The Literature Review: A Few Tips On Conducting It by University of Toronto
  • Write a Literature Review by UC Santa Cruz University Library

While there might be many reasons for conducting a literature review, following are four key outcomes of doing the review.

Assessment of the current state of research on a topic . This is probably the most obvious value of the literature review. Once a researcher has determined an area to work with for a research project, a search of relevant information sources will help determine what is already known about the topic and how extensively the topic has already been researched.

Identification of the experts on a particular topic . One of the additional benefits derived from doing the literature review is that it will quickly reveal which researchers have written the most on a particular topic and are, therefore, probably the experts on the topic. Someone who has written twenty articles on a topic or on related topics is more than likely more knowledgeable than someone who has written a single article. This same writer will likely turn up as a reference in most of the other articles written on the same topic. From the number of articles written by the author and the number of times the writer has been cited by other authors, a researcher will be able to assume that the particular author is an expert in the area and, thus, a key resource for consultation in the current research to be undertaken.

Identification of key questions about a topic that need further research . In many cases a researcher may discover new angles that need further exploration by reviewing what has already been written on a topic. For example, research may suggest that listening to music while studying might lead to better retention of ideas, but the research might not have assessed whether a particular style of music is more beneficial than another. A researcher who is interested in pursuing this topic would then do well to follow up existing studies with a new study, based on previous research, that tries to identify which styles of music are most beneficial to retention.

Determination of methodologies used in past studies of the same or similar topics.  It is often useful to review the types of studies that previous researchers have launched as a means of determining what approaches might be of most benefit in further developing a topic. By the same token, a review of previously conducted studies might lend itself to researchers determining a new angle for approaching research.

Upon completion of the literature review, a researcher should have a solid foundation of knowledge in the area and a good feel for the direction any new research should take. Should any additional questions arise during the course of the research, the researcher will know which experts to consult in order to quickly clear up those questions.

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  • Calvin Moorley 1 ,
  • Xabi Cathala 2
  • 1 Nursing Research and Diversity in Care, School of Health and Social Care , London South Bank University , London , UK
  • 2 Institute of Vocational Learning , School of Health and Social Care, London South Bank University , London , UK
  • Correspondence to Dr Calvin Moorley, Nursing Research and Diversity in Care, School of Health and Social Care, London South Bank University, London SE1 0AA, UK; Moorleyc{at}lsbu.ac.uk


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In order to make a decision about implementing evidence into practice, nurses need to be able to critically appraise research. Nurses also have a professional responsibility to maintain up-to-date practice. 1 This paper provides a guide on how to critically appraise a qualitative research paper.

What is qualitative research?

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Useful terms

Some of the qualitative approaches used in nursing research include grounded theory, phenomenology, ethnography, case study (can lend itself to mixed methods) and narrative analysis. The data collection methods used in qualitative research include in depth interviews, focus groups, observations and stories in the form of diaries or other documents. 3


Title, keywords, authors and abstract.

In a previous paper, we discussed how the title, keywords, authors’ positions and affiliations and abstract can influence the authenticity and readability of quantitative research papers, 4 the same applies to qualitative research. However, other areas such as the purpose of the study and the research question, theoretical and conceptual frameworks, sampling and methodology also need consideration when appraising a qualitative paper.

Purpose and question

The topic under investigation in the study should be guided by a clear research question or a statement of the problem or purpose. An example of a statement can be seen in table 2 . Unlike most quantitative studies, qualitative research does not seek to test a hypothesis. The research statement should be specific to the problem and should be reflected in the design. This will inform the reader of what will be studied and justify the purpose of the study. 5

Example of research question and problem statement

An appropriate literature review should have been conducted and summarised in the paper. It should be linked to the subject, using peer-reviewed primary research which is up to date. We suggest papers with a age limit of 5–8 years excluding original work. The literature review should give the reader a balanced view on what has been written on the subject. It is worth noting that for some qualitative approaches some literature reviews are conducted after the data collection to minimise bias, for example, in grounded theory studies. In phenomenological studies, the review sometimes occurs after the data analysis. If this is the case, the author(s) should make this clear.

Theoretical and conceptual frameworks

Most authors use the terms theoretical and conceptual frameworks interchangeably. Usually, a theoretical framework is used when research is underpinned by one theory that aims to help predict, explain and understand the topic investigated. A theoretical framework is the blueprint that can hold or scaffold a study’s theory. Conceptual frameworks are based on concepts from various theories and findings which help to guide the research. 6 It is the researcher’s understanding of how different variables are connected in the study, for example, the literature review and research question. Theoretical and conceptual frameworks connect the researcher to existing knowledge and these are used in a study to help to explain and understand what is being investigated. A framework is the design or map for a study. When you are appraising a qualitative paper, you should be able to see how the framework helped with (1) providing a rationale and (2) the development of research questions or statements. 7 You should be able to identify how the framework, research question, purpose and literature review all complement each other.

There remains an ongoing debate in relation to what an appropriate sample size should be for a qualitative study. We hold the view that qualitative research does not seek to power and a sample size can be as small as one (eg, a single case study) or any number above one (a grounded theory study) providing that it is appropriate and answers the research problem. Shorten and Moorley 8 explain that three main types of sampling exist in qualitative research: (1) convenience (2) judgement or (3) theoretical. In the paper , the sample size should be stated and a rationale for how it was decided should be clear.


Qualitative research encompasses a variety of methods and designs. Based on the chosen method or design, the findings may be reported in a variety of different formats. Table 3 provides the main qualitative approaches used in nursing with a short description.

Different qualitative approaches

The authors should make it clear why they are using a qualitative methodology and the chosen theoretical approach or framework. The paper should provide details of participant inclusion and exclusion criteria as well as recruitment sites where the sample was drawn from, for example, urban, rural, hospital inpatient or community. Methods of data collection should be identified and be appropriate for the research statement/question.

Data collection

Overall there should be a clear trail of data collection. The paper should explain when and how the study was advertised, participants were recruited and consented. it should also state when and where the data collection took place. Data collection methods include interviews, this can be structured or unstructured and in depth one to one or group. 9 Group interviews are often referred to as focus group interviews these are often voice recorded and transcribed verbatim. It should be clear if these were conducted face to face, telephone or any other type of media used. Table 3 includes some data collection methods. Other collection methods not included in table 3 examples are observation, diaries, video recording, photographs, documents or objects (artefacts). The schedule of questions for interview or the protocol for non-interview data collection should be provided, available or discussed in the paper. Some authors may use the term ‘recruitment ended once data saturation was reached’. This simply mean that the researchers were not gaining any new information at subsequent interviews, so they stopped data collection.

The data collection section should include details of the ethical approval gained to carry out the study. For example, the strategies used to gain participants’ consent to take part in the study. The authors should make clear if any ethical issues arose and how these were resolved or managed.

The approach to data analysis (see ref  10 ) needs to be clearly articulated, for example, was there more than one person responsible for analysing the data? How were any discrepancies in findings resolved? An audit trail of how the data were analysed including its management should be documented. If member checking was used this should also be reported. This level of transparency contributes to the trustworthiness and credibility of qualitative research. Some researchers provide a diagram of how they approached data analysis to demonstrate the rigour applied ( figure 1 ).

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Example of data analysis diagram.

Validity and rigour

The study’s validity is reliant on the statement of the question/problem, theoretical/conceptual framework, design, method, sample and data analysis. When critiquing qualitative research, these elements will help you to determine the study’s reliability. Noble and Smith 11 explain that validity is the integrity of data methods applied and that findings should accurately reflect the data. Rigour should acknowledge the researcher’s role and involvement as well as any biases. Essentially it should focus on truth value, consistency and neutrality and applicability. 11 The authors should discuss if they used triangulation (see table 2 ) to develop the best possible understanding of the phenomena.

Themes and interpretations and implications for practice

In qualitative research no hypothesis is tested, therefore, there is no specific result. Instead, qualitative findings are often reported in themes based on the data analysed. The findings should be clearly linked to, and reflect, the data. This contributes to the soundness of the research. 11 The researchers should make it clear how they arrived at the interpretations of the findings. The theoretical or conceptual framework used should be discussed aiding the rigour of the study. The implications of the findings need to be made clear and where appropriate their applicability or transferability should be identified. 12

Discussions, recommendations and conclusions

The discussion should relate to the research findings as the authors seek to make connections with the literature reviewed earlier in the paper to contextualise their work. A strong discussion will connect the research aims and objectives to the findings and will be supported with literature if possible. A paper that seeks to influence nursing practice will have a recommendations section for clinical practice and research. A good conclusion will focus on the findings and discussion of the phenomena investigated.

Qualitative research has much to offer nursing and healthcare, in terms of understanding patients’ experience of illness, treatment and recovery, it can also help to understand better areas of healthcare practice. However, it must be done with rigour and this paper provides some guidance for appraising such research. To help you critique a qualitative research paper some guidance is provided in table 4 .

Some guidance for critiquing qualitative research

  • ↵ Nursing and Midwifery Council . The code: Standard of conduct, performance and ethics for nurses and midwives . 2015 https://www.nmc.org.uk/globalassets/sitedocuments/nmc-publications/nmc-code.pdf ( accessed 21 Aug 18 ).
  • Barrett D ,
  • Cathala X ,
  • Shorten A ,

Patient consent for publication Not required.

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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  • http://orcid.org/0000-0001-5660-8224 Veronika Williams ,
  • Anne-Marie Boylan ,
  • http://orcid.org/0000-0003-4597-1276 David Nunan
  • Nuffield Department of Primary Care Health Sciences , University of Oxford, Radcliffe Observatory Quarter , Oxford , UK
  • Correspondence to Dr Veronika Williams, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK; veronika.williams{at}phc.ox.ac.uk


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  • qualitative research


Qualitative evidence allows researchers to analyse human experience and provides useful exploratory insights into experiential matters and meaning, often explaining the ‘how’ and ‘why’. As we have argued previously 1 , qualitative research has an important place within evidence-based healthcare, contributing to among other things policy on patient safety, 2 prescribing, 3 4 and understanding chronic illness. 5 Equally, it offers additional insight into quantitative studies, explaining contextual factors surrounding a successful intervention or why an intervention might have ‘failed’ or ‘succeeded’ where effect sizes cannot. It is for these reasons that the MRC strongly recommends including qualitative evaluations when developing and evaluating complex interventions. 6

Critical appraisal of qualitative research

Is it necessary.

Although the importance of qualitative research to improve health services and care is now increasingly widely supported (discussed in paper 1), the role of appraising the quality of qualitative health research is still debated. 8 10 Despite a large body of literature focusing on appraisal and rigour, 9 11–15 often referred to as ‘trustworthiness’ 16 in qualitative research, there remains debate about how to —and even whether to—critically appraise qualitative research. 8–10 17–19 However, if we are to make a case for qualitative research as integral to evidence-based healthcare, then any argument to omit a crucial element of evidence-based practice is difficult to justify. That being said, simply applying the standards of rigour used to appraise studies based on the positivist paradigm (Positivism depends on quantifiable observations to test hypotheses and assumes that the researcher is independent of the study. Research situated within a positivist paradigm isbased purely on facts and consider the world to be external and objective and is concerned with validity, reliability and generalisability as measures of rigour.) would be misplaced given the different epistemological underpinnings of the two types of data.

Given its scope and its place within health research, the robust and systematic appraisal of qualitative research to assess its trustworthiness is as paramount to its implementation in clinical practice as any other type of research. It is important to appraise different qualitative studies in relation to the specific methodology used because the methodological approach is linked to the ‘outcome’ of the research (eg, theory development, phenomenological understandings and credibility of findings). Moreover, appraisal needs to go beyond merely describing the specific details of the methods used (eg, how data were collected and analysed), with additional focus needed on the overarching research design and its appropriateness in accordance with the study remit and objectives.

Poorly conducted qualitative research has been described as ‘worthless, becomes fiction and loses its utility’. 20 However, without a deep understanding of concepts of quality in qualitative research or at least an appropriate means to assess its quality, good qualitative research also risks being dismissed, particularly in the context of evidence-based healthcare where end users may not be well versed in this paradigm.

How is appraisal currently performed?

Appraising the quality of qualitative research is not a new concept—there are a number of published appraisal tools, frameworks and checklists in existence. 21–23  An important and often overlooked point is the confusion between tools designed for appraising methodological quality and reporting guidelines designed to assess the quality of methods reporting. An example is the Consolidate Criteria for Reporting Qualitative Research (COREQ) 24 checklist, which was designed to provide standards for authors when reporting qualitative research but is often mistaken for a methods appraisal tool. 10

Broadly speaking there are two types of critical appraisal approaches for qualitative research: checklists and frameworks. Checklists have often been criticised for confusing quality in qualitative research with ‘technical fixes’ 21 25 , resulting in the erroneous prioritisation of particular aspects of methodological processes over others (eg, multiple coding and triangulation). It could be argued that a checklist approach adopts the positivist paradigm, where the focus is on objectively assessing ‘quality’ where the assumptions is that the researcher is independent of the research conducted. This may result in the application of quantitative understandings of bias in order to judge aspects of recruitment, sampling, data collection and analysis in qualitative research papers. One of the most widely used appraisal tools is the Critical Appraisal Skills Programme (CASP) 26 and along with the JBI QARI (Joanna Briggs Institute Qualitative Assessment and Assessment Instrument) 27 presents examples which tend to mimic the quantitative approach to appraisal. The CASP qualitative tool follows that of other CASP appraisal tools for quantitative research designs developed in the 1990s. The similarities are therefore unsurprising given the status of qualitative research at that time.

Frameworks focus on the overarching concepts of quality in qualitative research, including transparency, reflexivity, dependability and transferability (see box 1 ). 11–13 15 16 20 28 However, unless the reader is familiar with these concepts—their meaning and impact, and how to interpret them—they will have difficulty applying them when critically appraising a paper.

The main issue concerning currently available checklist and framework appraisal methods is that they take a broad brush approach to ‘qualitative’ research as whole, with few, if any, sufficiently differentiating between the different methodological approaches (eg, Grounded Theory, Interpretative Phenomenology, Discourse Analysis) nor different methods of data collection (interviewing, focus groups and observations). In this sense, it is akin to taking the entire field of ‘quantitative’ study designs and applying a single method or tool for their quality appraisal. In the case of qualitative research, checklists, therefore, offer only a blunt and arguably ineffective tool and potentially promote an incomplete understanding of good ‘quality’ in qualitative research. Likewise, current framework methods do not take into account how concepts differ in their application across the variety of qualitative approaches and, like checklists, they also do not differentiate between different qualitative methodologies.

On the need for specific appraisal tools

Current approaches to the appraisal of the methodological rigour of the differing types of qualitative research converge towards checklists or frameworks. More importantly, the current tools do not explicitly acknowledge the prejudices that may be present in the different types of qualitative research.

Concepts of rigour or trustworthiness within qualitative research 31

Transferability: the extent to which the presented study allows readers to make connections between the study’s data and wider community settings, ie, transfer conceptual findings to other contexts.

Credibility: extent to which a research account is believable and appropriate, particularly in relation to the stories told by participants and the interpretations made by the researcher.

Reflexivity: refers to the researchers’ engagement of continuous examination and explanation of how they have influenced a research project from choosing a research question to sampling, data collection, analysis and interpretation of data.

Transparency: making explicit the whole research process from sampling strategies, data collection to analysis. The rationale for decisions made is as important as the decisions themselves.

However, we often talk about these concepts in general terms, and it might be helpful to give some explicit examples of how the ‘technical processes’ affect these, for example, partialities related to:

Selection: recruiting participants via gatekeepers, such as healthcare professionals or clinicians, who may select them based on whether they believe them to be ‘good’ participants for interviews/focus groups.

Data collection: poor interview guide with closed questions which encourage yes/no answers and/leading questions.

Reflexivity and transparency: where researchers may focus their analysis on preconceived ideas rather than ground their analysis in the data and do not reflect on the impact of this in a transparent way.

The lack of tailored, method-specific appraisal tools has potentially contributed to the poor uptake and use of qualitative research for informing evidence-based decision making. To improve this situation, we propose the need for more robust quality appraisal tools that explicitly encompass both the core design aspects of all qualitative research (sampling/data collection/analysis) but also considered the specific partialities that can be presented with different methodological approaches. Such tools might draw on the strengths of current frameworks and checklists while providing users with sufficient understanding of concepts of rigour in relation to the different types of qualitative methods. We provide an outline of such tools in the third and final paper in this series.

As qualitative research becomes ever more embedded in health science research, and in order for that research to have better impact on healthcare decisions, we need to rethink critical appraisal and develop tools that allow differentiated evaluations of the myriad of qualitative methodological approaches rather than continuing to treat qualitative research as a single unified approach.

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Contributors VW and DN: conceived the idea for this article. VW: wrote the first draft. AMB and DN: contributed to the final draft. All authors approve the submitted article.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Correction notice This article has been updated since its original publication to include a new reference (reference 1.)

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  • Systematic Review
  • Open access
  • Published: 30 May 2024

Patient experiences: a qualitative systematic review of chemotherapy adherence

  • Amineh Rashidi 1 ,
  • Susma Thapa 1 ,
  • Wasana Sandamali Kahawaththa Palliya Guruge 1 &
  • Shubhpreet Kaur 1  

BMC Cancer volume  24 , Article number:  658 ( 2024 ) Cite this article

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Adherence to chemotherapy treatment is recognized as a crucial health concern, especially in managing cancer patients. Chemotherapy presents challenges for patients, as it can lead to potential side effects that may adversely affect their mobility and overall function. Patients may sometimes neglect to communicate these side effects to health professionals, which can impact treatment management and leave their unresolved needs unaddressed. However, there is limited understanding of how patients’ experiences contribute to improving adherence to chemotherapy treatment and the provision of appropriate support. Therefore, gaining insights into patients’ experiences is crucial for enhancing the accompaniment and support provided during chemotherapy.

This review synthesizes qualitative literature on chemotherapy adherence within the context of patients’ experiences. Data were collected from Medline, Web of Science, CINAHL, PsychINFO, Embase, Scopus, and the Cochrane Library, systematically searched from 2006 to 2023. Keywords and MeSH terms were utilized to identify relevant research published in English. Thirteen articles were included in this review. Five key themes were synthesized from the findings, including positive outlook, receiving support, side effects, concerns about efficacy, and unmet information needs. The review underscores the importance for healthcare providers, particularly nurses, to focus on providing comprehensive information about chemotherapy treatment to patients. Adopting recommended strategies may assist patients in clinical practice settings in enhancing adherence to chemotherapy treatment and improving health outcomes for individuals living with cancer.

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Cancer can affect anyone and is recognized as a chronic disease characterized by abnormal cell multiplication in the body [ 1 ]. While cancer is prevalent worldwide, approximately 70% of cancer-related deaths occur in low- to middle-income nations [ 1 ]. Disparities in cancer outcomes are primarily attributed to variations in the accessibility of comprehensive diagnosis and treatment among countries [ 1 , 2 ]. Cancer treatment comes in various forms; however, chemotherapy is the most widely used approach [ 3 ]. Patients undergoing chemotherapy experience both disease-related and treatment-related adverse effects, significantly impacting their quality of life [ 4 ]. Despite these challenges, many cancer patients adhere to treatment in the hope of survival [ 5 ]. However, some studies have shown that concerns about treatment efficacy may hinder treatment adherence [ 6 ]. Adherence is defined as “the extent to which a person’s behaviour aligns with the recommendations of healthcare providers“ [ 7 ]. Additionally, treatment adherence is influenced by the information provided by healthcare professionals following a cancer diagnosis [ 8 ]. Patient experiences suggest that the decision to adhere to treatment is often influenced by personal factors, with family support playing a crucial role [ 8 ]. Furthermore, providing adequate information about chemotherapy, including its benefits and consequences, can help individuals living with cancer gain a better understanding of the advantages associated with adhering to chemotherapy treatment [ 9 ].

Recognizing the importance of adhering to chemotherapy treatment and understanding the impact of individual experiences of chemotherapy adherence would aid in identifying determinants of adherence and non-adherence that are modifiable through effective interventions [ 10 ]. Recently, systematic reviews have focused on experiences and adherence in breast cancer [ 11 ], self-management of chemotherapy in cancer patients [ 12 ], and the influence of medication side effects on adherence [ 13 ]. However, these reviews were narrow in scope, and to date, no review has integrated the findings of qualitative studies designed to explore both positive and negative experiences regarding chemotherapy treatment adherence. This review aims to synthesize the qualitative literature on chemotherapy adherence within the context of patients’ experiences.

This review was conducted in accordance with the Joanna Briggs Institute [ 14 ] guidelines for systemic review involving meta-aggregation. This review was registered in PROSPERO (CRD42021270459).

Search methods

The searches for peer reviewed publications in English from January 2006-September 2023 were conducted by using keywords, medical subject headings (MeSH) terms and Boolean operators ‘AND’ and ‘OR’, which are presented in the table in Appendix 1 . The searches were performed in a systematic manner in core databases such including Embase, Medline, PsycINFO, CINAHL, Web of Science, Cochrane Library, Scopus and the Joanna Briggs Institute (JBI). The search strategy was developed from keywords and medical subject headings (MeSH) terms. Librarian’s support and advice were sought in forming of the search strategies.

Study selection and inclusion criteria

The systematic search was conducted on each database and all articles were exported to Endnote and duplicates records were removed. Then, title and abstract of the full text was screened by two independent reviewers against the inclusion criteria. For this review, populations were patients aged 18 and over with cancer, the phenomenon of interest was experiences on chemotherapy adherence and context was considered as hospitals, communities, rehabilitation centres, outpatient clinics, and residential aged care. All peer-reviewed qualitative study design were also considered for inclusion. Studies included in this review were classified as primary research, published in English since 2006, some intervention implemented to improve adherence to treatment. This review excluded any studies that related to with cancer and mental health condition, animal studies and grey literature.

Quality appraisal and data extraction

The JBI Qualitative Assessment and Review Instrument for qualitative studies was used to assess the methodological quality of the included studies, which was conducted by the primary and second reviewers independently. There was no disagreement between the reviews. The qualitative data on objectives, study population, context, study methods, and the phenomena of interest and findings form the included studies were extracted.

Data synthesis

The meta-aggregation approach was used to combine the results with similar meaning. The primary and secondary reviewers created categories based on the meanings and concept. These categories were supported by direct quotations from participants. The findings were assess based on three levels of evidence, including unequivocal, credible, and unsupported [ 15 , 16 ]. Findings with no quotation were not considered for synthesis in this review. The categories and findings were also discussed by the third and fourth reviewers until a consensus was reached. The review was approved by the Edith Cowan University Human Research Ethics Committee (2021–02896).

Study inclusion

A total of 4145 records were identified through a systematic search. Duplicates ( n  = 647) were excluded. Two independent reviewers conducted screening process. The remaining articles ( n  = 3498) were examined for title and abstract screening. Then, the full text screening conducted, yielded 13 articles to be included in the final synthesis see Appendix 2 .

Methodological quality of included studies

All included qualitative studies scored between 7 and 9, which is displayed in Appendix 3 . The congruity between the research methodology and the research question or objectives, followed by applying appropriate data collection and data analysis were observed in all included studies. Only one study [ 17 ] indicated the researcher’s statement regarding cultural or theoretical perspectives. Three studies [ 18 , 19 , 20 ] identified the influence of the researcher on the research and vice-versa.

Characteristics of included studies

Most of studies conducted semi-structured and in-depth interviews, one study used narrative stories [ 19 ], one study used focus group discussion [ 21 ], and one study combined focus group and interview [ 22 ] to collect data. All studies conducted outpatient’s clinic, community, or hospital settings [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. The study characteristics presented in Appendix 4 .

Review findings

Eighteen findings were extracted and synthesised into five categories: positive outlook, support, side effects, concern about efficacy and unmet information needs.

Positive outlook

Five studies discussed the link between positivity and hope and chemotherapy adherence [ 19 , 20 , 23 , 27 , 28 ]. Five studies commented that feeling positive and avoid the negativity and worry could encourage people to adhere in their mindset chemotherapy: “ I think the main thing for me was just keeping a positive attitude and not worrying, not letting myself worry about it ” [ 20 ]. Participants also considered the positive thoughts as a coping mechanism, that would help them to adhere and complete chemotherapy: “ I’m just real positive on how everything is going. I’m confident in the chemo, and I’m hoping to get out of her soon ” [ 23 ]. Viewing chemotherapy as part of their treatment regimen and having awareness of negative consequences of non-adherence to chemotherapy encouraged them to adhere chemotherapy: “ If I do not take medicine, I do not think I will be able to live ” [ 28 ]. Adhering chemotherapy was described as a survivor tool which helped people to control cancer-related symptoms: “ it is what is going to restore me. If it wasn’t this treatment, maybe I wasn’t here talking to you. So, I have to focus in what he is going to give me, life !” [ 27 ]. Similarly, people accepted the medical facts and prevent their life from worsening; “ without the treatment, it goes the wrong way. It is hard, but I have accepted it from the beginning, yes. This is how it is. I cannot do anything about it. Just have to accept it ” [ 19 ].

Finding from six studies contributed to this category [ 20 , 21 , 23 , 24 , 25 , 29 ]. Providing support from families and friends most important to the people. Receiving support from family members enhanced a sense responsibility towards their families, as they believed to survive for their family even if suffered: “ yes, I just thought that if something comes back again and I say no, then I have to look my family and friends in the eye and say I could have prevented it, perhaps. Now, if something comes back again, I can say I did everything I could. Cancer is bad enough without someone saying: It’s your own fault!!” [ 29 ]. Also, emotional support from family was described as important in helping and meeting their needs, and through facilitation helped people to adhere chemotherapy: “ people who genuinely mean the support that they’re giving […] just the pure joy on my daughter’s face for helping me. she was there day and night for me if I needed it, and that I think is the main thing not to have someone begrudgingly looking after you ” [ 20 ]. Another study discussed the role family, friends and social media as the best source of support during their treatment to adhere and continue “ I have tons of friends on Facebook, believe it or not, and it’s amazing how many people are supportive in that way, you know, just sending get-well wishes. I can’t imagine going through this like 10 years ago whenever stuff like that wasn’t around ” [ 23 ]. Receiving support from social workers was particularly helpful during chemotherapy in encouraging adherence to the chemotherapy: “ the social worker told me that love is courage. That was a huge encouragement, and I began to encourage myself ” [ 25 ].

Side effects

Findings from five studies informed this category [ 17 , 21 , 22 , 25 , 26 ]. Physical side effects were described by some as the most unpleasure experience: “ the side effects were very uncomfortable. I felt pain, fatigue, nausea, and dizziness that limited my daily activities. Sometimes, I was thinking about not keeping to my chemotherapy schedule due to those side effect ” [ 17 ]. The impact of side effects affected peoples’ ability to maintain their independence and self-care: “ I couldn’t walk because I didn’t have the energy, but I wouldn’t have dared to go out because the diarrhoea was so bad. Sometimes I couldn’t even get to the toilet; that’s very embarrassing because you feel like you’re a baby ” [ 26 ]. Some perceived that this resulted in being unable to perform independently: “ I was incredibly weak and then you still have to do things and you can’t manage it ” [ 22 ]. These side effect also decreased their quality of life “ I felt nauseated whenever I smelled food. I simply had no appetite when food was placed in front of me. I lost my sense of taste. Food had no taste anymore ” [ 25 ]. Although, the side effects impacted on patients´ leisure and free-time activities, they continued to undertake treatment: “ I had to give up doing the things I liked the most, such as going for walks or going to the beach. Routines, daily life in general were affected ” [ 21 ].

Concern about efficacy

Findings form four studies informed this category [ 17 , 18 , 24 , 28 ]. Although being concerned about the efficacy of the chemotherapy and whether or not chemotherapy treatment would be successful, one participant who undertook treatment described: “the efficacy is not so great. It is said to expect about 10% improvement, but I assume that it declines over time ” [ 28 ]. People were worried that such treatment could not cure their cancer and that their body suffered more due to the disease: “ I was really worried about my treatment effectiveness, and I will die shortly ” [ 17 ]. There were doubts expressed about remaining the cancer in the body after chemotherapy: “ there’s always sort of hidden worries in there that whilst they’re not actually taking the tumour away, then you’re wondering whether it’s getting bigger or what’s happening to it, whether it’s spreading or whatever, you know ” [ 24 ]. Uncertainty around the outcome of such treatment, or whether recovering from cancer or not was described as: “it makes you feel confused. You don’t know whether you are going to get better or else whether the illness is going to drag along further” [ 18 ].

Unmet information needs

Five studies contributed to this category [ 17 , 21 , 22 , 23 , 26 ]. The need for adequate information to assimilate information and provide more clarity when discussing complex information were described. Providing information from clinicians was described as minimal: “they explain everything to you and show you the statistics, then you’re supposed to take it all on-board. You could probably go a little bit slower with the different kinds of chemo and grappling with these statistics” [ 26 ]. People also used the internet search to gain information about their cancer or treatments, “I’ve done it (consult google), but I stopped right away because there’s so much information and you don’t know whether it’s true or not ” [ 21 ]. The need to receive from their clinicians to obtain clearer information was described as” I look a lot of stuff up online because it is not explained to me by the team here at the hospital ” [ 23 ]. Feeling overwhelmed with the volume of information could inhibit people to gain a better understanding of chemotherapy treatment and its relevant information: “ you don’t absorb everything that’s being said and an awful lot of information is given to you ” [ 22 ]. People stated that the need to know more information about their cancer, as they were never dared to ask from their clinicians: “ I am a low educated person and come from a rural area; I just follow the doctor’s advice for my health, and I do not dare to ask anything” [ 17 ].

The purpose of this review was to explore patient’s experiences about the chemotherapy adherence. After finalizing the searches, thirteen papers were included in this review that met the inclusion criteria.

The findings of the present review suggest that social support is a crucial element in people’s positive experiences of adhering to chemotherapy. Such support can lead to positive outcomes by providing consistent and timely assistance from family members or healthcare professionals, who play vital roles in maintaining chemotherapy adherence [ 30 ]. Consistent with our study, previous research has highlighted the significant role of family members in offering emotional and physical support, which helps individuals cope better with chemotherapy treatment [ 31 , 32 ]. However, while receiving support from family members reinforces individuals’ sense of responsibility in managing their treatment and their family, it also instils a desire to survive cancer and undergo chemotherapy. One study found that assuming self-responsibility empowers patients undergoing chemotherapy, as they feel a sense of control over their therapy and are less dependent on family members or healthcare professionals [ 33 ]. A qualitative systematic review reported that support from family members enables patients to become more proactive and effective in adhering to their treatment plan [ 34 ]. This review highlights the importance of maintaining a positive outlook and rational beliefs as essential components of chemotherapy adherence. Positive thinking helps individuals recognize their role in chemotherapy treatment and cope more effectively with their illness by accepting it as part of their treatment regimen and viewing it as a tool for survival. This finding is supported by previous studies indicating that positivity and positive affirmations play critical roles in helping individuals adapt to their reality and construct attitudes conducive to chemotherapy adherence [ 35 , 36 ]. Similarly, maintaining a positive mindset can foster more favourable thoughts regarding chemotherapy adherence, ultimately enhancing adherence and overall well-being [ 37 ].

This review identified side effects as a significant negative aspect of the chemotherapy experience, with individuals expressing concerns about how these side effects affected their ability to perform personal self-care tasks and maintain independent living in their daily lives. Previous studies have shown that participants with a history of chemotherapy drug side effects were less likely to adhere to their treatment regimen due to worsening symptoms, which increased the burden of medication side effects [ 38 , 39 ]. For instance, cancer patients who experienced minimal side effects from chemotherapy were at least 3.5 times more likely to adhere to their treatment plan compared to those who experienced side effects [ 40 ]. Despite experiencing side effects, patients were generally willing to accept and adhere to their treatment program, although one study in this review indicated that side effects made some patients unable to maintain treatment adherence. Side effects also decreased quality of life and imposed restrictions on lifestyle, as seen in another study where adverse effects limited individuals in fulfilling daily commitments and returning to normal levels of functioning [ 41 ]. Additionally, unmet needs regarding information on patients’ needs and expectations were common. Healthcare professionals were considered the most important source of information, followed by consultation with the internet. Providing information from healthcare professionals, particularly nurses, can support patients effectively and reinforce treatment adherence [ 42 , 43 ]. Chemotherapy patients often preferred to base their decisions on the recommendations of their care providers and required adequate information retention. Related studies have highlighted that unmet needs among cancer patients are known factors associated with chemotherapy adherence, emphasizing the importance of providing precise information and delivering it by healthcare professionals to improve adherence [ 44 , 45 ]. Doubts about the efficacy of chemotherapy treatment, as the disease may remain latent, were considered negative experiences. Despite these doubts, patients continued their treatment, echoing findings from a study where doubts regarding efficacy were identified as a main concern for chemotherapy adherence. Further research is needed to understand how doubts about treatment efficacy can still encourage patients to adhere to chemotherapy treatment.

Strengths and limitation

The strength of this review lies in its comprehensive search strategy across databases to select appropriate articles. Additionally, the use of JBI guidelines provided a comprehensive and rigorous methodological approach in conducting this review. However, the exclusion of non-English studies, quantitative studies, and studies involving adolescents and children may limit the generalizability of the findings. Furthermore, this review focuses solely on chemotherapy treatment and does not encompass other types of cancer treatment.

Conclusion and practical implications

Based on the discussion of the findings, it is evident that maintaining a positive mentality and receiving social support can enhance chemotherapy adherence. Conversely, experiencing treatment side effects, concerns about efficacy, and unmet information needs may lead to lower adherence. These findings present an opportunity for healthcare professionals, particularly nurses, to develop standardized approaches aimed at facilitating chemotherapy treatment adherence, with a focus on providing comprehensive information. By assessing patients’ needs, healthcare professionals can tailor approaches to promote chemotherapy adherence and improve the survival rates of people living with cancer. Raising awareness and providing education about cancer and chemotherapy treatment can enhance patients’ understanding of the disease and its treatment options. Utilizing videos and reading materials in outpatient clinics and pharmacy settings can broaden the reach of educational efforts. Policy makers and healthcare providers can collaborate to develop sustainable patient education models to optimize patient outcomes in the context of cancer care. A deeper understanding of individual processes related to chemotherapy adherence is necessary to plan the implementation of interventions effectively. Further research examining the experiences of both adherent and non-adherent patients is essential to gain a comprehensive understanding of this topic.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. on our submission system as well.

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First author (AR) and second author (ST) conceived the review and the second author oversight for all stages of the review provided by the second author. All authors (AR), (ST), (WG) and (SK) undertook the literature search. Data extraction, screening the included papers and quality appraisal were undertaken by all authors (AR), (ST), (WG) and (SK). First and second authors (AR) and (ST) analysed the data and wrote the first draft of the manuscript and revised the manuscript and all authors (AR), (ST), (WG) and (SK) approved the final version of the manuscript.

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Correspondence to Amineh Rashidi .

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The review was approved by the Edith Cowan University Human Research Ethics Committee (2021–02896). A proposal for the systematic review was assessed by the Edith Cowan University Human Research Ethics Committee and deemed not appropriate for full ethical review. However, a Data Management Plan (2021-02896-RASHIDI) was approved and monitored as part of this procedure. Raw data was extracted from the published manuscripts and authors could not identify individual participants during or after this process.

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Classroom communications post pandemic: a case study

  • Marwa Abdelmonem 1 &
  • Sherin Karawia 1  

Humanities and Social Sciences Communications volume  11 , Article number:  728 ( 2024 ) Cite this article

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This cross-sectional case study ( n  = 20) took place in Qatar over a 3-month period spanning from September until the end of November in 2021. It examined the impacts of a post-COVID classroom arrangement that incorporated preventive measures like social distancing and the use of face coverings. Using the case study methodology, we employed two qualitative research methods, namely non-participant observation and semi-structured interviews, to gather primary data. We also conducted an extensive literature review to identify the key themes for investigation in the field. The primary focus of our study was on proxemics (personal space and crowding), technology (Zoom), non-verbal communication, and ergonomics (lighting and acoustics). Our study uncovered new areas for future research, particularly in how proxemics change in socially distanced classrooms, affecting personal space and perceptions of crowding. Additionally, it highlighted themes in post-pandemic classroom design, emphasizing the impact of factors like seating arrangements and available amenities (e.g., pinup walls) on student engagement, especially in design-studio classrooms. The study also revealed unexpected challenges, such as issues with microphone usage due to users’ lack of familiarity with their operation. In summary, the research underscores the ongoing importance of adaptable learning methods and communication strategies, particularly in response to preventive measures like social distancing and face-covering, which have reshaped our concept of personal space and emphasized the crucial role of telecommunication in crisis resilience for communities and organizations.

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The COVID-19 pandemic, caused by the novel coronavirus (SARS-CoV-2), was declared a global pandemic by the World Health Organization (WHO) due to its rapid spread to multiple countries ( WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19 - 11 March 2020 , 2020 ). It is important to note that COVID-19 is not an isolated event in history, as previous pandemics like the 1918 American Polio epidemic, the 1918 Spanish flu, the 1957 Asian flu, the 1981 AIDS pandemic, the 2009 H1N1 Swine flu, the 2014 West African Ebola, and the 2014 Zika Virus epidemic have occurred (Cennimo, 2020 ; Jarus, 2023 ). COVID-19 can have severe health consequences, particularly for the elderly and those with pre-existing health conditions (World Health Organization, n.d. ) .

Preventing the transmission of COVID-19 involves a combination of physical and medical interventions. The WHO recommends physical measures such as handwashing, social distancing, and wearing face coverings (Centers for Disease Control and Prevention, n.d. ). Medical interventions include vaccines, although their long-term effectiveness is still being studied (Frequently Asked Questions about COVID-19 Vaccination, 2023 ). Vaccines have proven effective in reducing hospitalization rates by 92–96% (Robson, 2021 ), but ongoing research is examining their long-term impacts.

The COVID-19 pandemic led to significant changes in the operations of various institutions, including educational establishments. Measures like remote work and restricted access to buildings were implemented, and as vaccines were developed, some restrictions were lifted. In Qatar, strict COVID-19 measures included travel bans and public place closures, and the use of the Ehteraz app for exposure alerts (Al Khal et al., 2020 ). Mandatory face masks, protective equipment distribution, and clear public communication highlighted preventive measures, linking access to public facilities with a healthy Ehteraz status during the lockdown (Al Khal et al., 2020 ). The gradual reopening and removal of restrictions occurred in four phases, commencing on May 21, 2021 (Government Communications Office, 2020 ). Our study coincided with the second phase, marked by the partial lifting of restrictions, enabling a return to campus within designated daily hours and specific building capacities that varied across different structures.

The transition back to in-person learning has brought challenges in ensuring safety in alignment with WHO guidelines, including social distancing measures within classrooms. Given the mixed sentiments surrounding the reopening, communication within the classroom under setups adhering to WHO guidelines was unforeseen and unfamiliar to everyone. With varied opinions on the reopening, communication within classrooms following WHO guidelines was unexpected. Hence, our research study aimed to explore classroom communication post-online learning during the pandemic, as there is limited existing research on the effects of preventive measures on this aspect.

Student engagement is related to academic performance, and a conducive learning environment plays a crucial role in fostering effective communication and learning (Shernoff et al., 2016 , as cited in Kelly, 2008; Kopec, 2012 ). Therefore, this study aims to investigate the effects of preventive measures like face-covering and social distancing on classroom communication in a post-pandemic, socially-distanced classroom setting. In essence, our study seeks to answer the research question: “What impact do preventive measures have on classroom communication within a post-pandemic classroom environment?” This study was conducted on two interconnected classrooms, which were intentionally furnished to comply with social distancing requirements and create a cohesive socially distanced learning environment, prompting further exploration of this phenomenon.

Literature review

To investigate how preventive measures might impact classroom communication dynamics, our study conducted a review of the literature to identify and extract certain themes from this body of work. These predetermined themes were integral to addressing the aforementioned research question. Out of more than 50 studies examined, only 29 were selected to form the basis of the literature review for this study. Additional sources were incorporated for specific definitions and concepts. The literature selection criteria included original works in environmental design pertaining to proxemics, exploration of blended learning and technology use, considerations in classroom design, and aspects of verbal and non-verbal communication in classrooms.

Personal space

Due to the physical nature of the social distancing measure, literature on personal space was reviewed to better understand the impact of the changing proxemics. The first scholar to introduce the concept of personal space was Edward Hall in 1959 (Beaulieu, 2004 , p. 794). Hall defined personal space as “an invisible three-dimensional zone surrounding a person, which allows that person to regulate his interactions with the outside world” (Beaulieu, 2004 , p. 294). Research shows that “the idea of personal space is actually an interpersonal phenomenon” (Kopec, 2012 ). In other words, it requires the existence of others in order to occur. This was the definition pertaining to the psychological nature of this entity. However, it is also defined based on its physical characteristics as the variable and subjective distance at which one person feels comfortable talking to another ( Dictionary.com | Meanings & Definitions of English Words , 2021 ).

According to Hall ( 1990 ), the hidden boundaries of personal space are not fixed and can vary from one culture to another, as culture plays an important role in defining personal space. Nevertheless, in a socially distanced classroom, personal space that was long referred to as an invisible bubble has become well-identified with its visible physical boundaries after the COVID-19 pandemic. Spacing mechanisms used in design, in general, and in a socially distanced classroom, in particular, serve to maintain one’s perception of their personal space (Kopec, 2012 ).

The importance of the concept of personal space lies in regulating communication and human interaction. Research shows that “the concept of personal space is viewed as variable and permeable in different settings” (Beaulieu, 2004 , p. 297). According to Hall ( 1990 ), interpersonal distance zones, which govern our interactions, can be categorized into four zones. The first category is the intimate, which ranges from 0 to 18”, typically reserved for individuals with close relationships, such as family members or individuals in deeply connected interpersonal bonds (Kopec, 2012 ). The second interpersonal zone is the personal which can range from 18” up to 4’ (Kopec, 2012 , p. 78). This zone is usually used in casual interactions between friends and acquaintances (Kopec, 2012 ). The third level is social , which is usually maintained in business relations between coworkers (Beaulieu, 2004 ) and ranges from 4’ to 12’ (Kopec, 2012 , p. 78). Lastly, the public zone which is usually used by people in public places where they find themselves surrounded by a number of strangers (Kopec, 2012 ). This zone varies from 12’ to 25’ (Kopec, 2012 . p. 78). In a recent study, Mehta ( 2020 ) investigated Hall’s proxemics in urban settings, focusing on changes in street and public space dynamics in residential areas during COVID-19. The research highlighted how residents in mid- to low-density areas repurpose spaces, fostering sociability despite social distancing measures.

In our study, we chose to explore the personal space perceived by participants in an attempt to analyze the various elements that define this concept within the new classroom setup. Our study was mostly exploratory and was not focused on a certain type of interpersonal distance.

Crowding concept

We also explored another concept in environmental psychology that is closely related to personal space, which is Crowding. In normal situations, the occupant load, which is “the number of people that a building code assumes will occupy a given building or a portion of a building”, is based on the building classification (Ballast, 2013 ). The number, placement, and capacity of exits are based on more than just occupant load. The type of occupancy and use, travel distance and remoteness or separation of exits are examples of other factors typically considered when designing a building.

As Kopec ( 2012 , p. 77) indicated, “spacing mechanisms used in design serve to help maintain an individual’s sense of personal space”. To put it differently, the use of physical boundaries such as partitions, furniture and layout allows the individual to identify their own personal space. Crowding, on the other hand, is defined as the “psychological tension produced in environments of high population density, especially when individuals feel that the amount of space available to them is insufficient for their needs” (American Psychological Association, n.d. ). In that sense, it can be argued that implementing social distancing in a classroom can potentially eliminate any sensation of crowding. However, our study examines this concept further, as the perception of crowding can be subjective in nature.

Some researchers such as Evans and Wener ( 2007 ) analyzed the concept of personal space and crowding in trains. According to their review of the literature, incursions into personal space by unfamiliar individuals lead to greater stress compared to those committed by individuals with positive interpersonal relationships. Evans and Wener ( 2007 ) suggested that crowding occurs when the regulation of social interaction fails, leading to a higher level of social interaction than desired. Worchel and Teddie ( 1976 ) also asserted that a feeling of overcrowding is associated with violations of personal space. Crowding can have negative impacts on mental health, causing decreased performance on complex tasks, stress aftermaths, and increased physiological stress (American Psychological Association, n.d. ). The lack of control over social interaction (i.e. privacy) and the decline of socially supportive relationships are considered to be two key mechanisms that contribute to crowding (American Psychological Association, n.d. ).

Upon reviewing the existing literature, specific inquiries emerge concerning the concept of crowding. Our principal emphasis lies in examining how the notion of crowding, closely intertwined with the concept of personal space, has evolved within a socially distanced classroom environment.


According to Wahyuni ( 2018 ), teachers are required to excel in specific nonverbal communication skills, which encompass body language, the utilization of eye contact, maintaining appropriate distance from students, and the use of touch. Wahyuni ( 2018 ), who further cited Darn (Darn, n.d. ), noted that nearly 75% of classroom management relies on nonverbal communication. In this research, our objective was to investigate the alterations in both verbal and nonverbal communication within the new setup. This change was prompted by the introduction of social distancing measures through the rearrangement of furniture and the adoption of Zoom as an auxiliary tool to facilitate communication between two interconnected classrooms.

Non-verbal communication

It is evident that nonverbal communication plays an important role in classroom interaction (Hall et al., 1977 ). French ( 1977 ) described the non-verbal experience as a multi-dimensional, multi-sensory experience. In his study, French ( 1977 ) emphasized the need for incorporating the non-verbal experience into curriculum development. “The non-verbal experience focused both on self and others”, which requires “an active engagement rather than a passive one” (French, 1977 , p. 176). French’s ( 1977 ) findings resonate well with Astin’s ( 1984 ) regarding the degree of student involvement. Astin ( 1984 ) defines student involvement as the extent of physical and psychological energy invested in the college experience, including academic absorption, extracurricular participation, and interaction with faculty. Education literature distinguishes between student engagement and involvement. Engagement , according to Campus Intelligence (Gay, 2019 ), entails dedicating time and effort to educationally purposeful activities, surpassing mere involvement. Engaged students actively pursue endeavors that contribute to their educational goals, going beyond classroom actions like note-taking and questioning. In their recent research, Walker and Koralesky ( 2021 ) employed the definition of student engagement found in various scholarly reviews, indicating that student engagement is a multi-dimensional construct with three interconnected dimensions: affective, behavioral, and cognitive engagement (Walker and Koralesky, 2021 ; as cited in Chapman, 2002; Fredricks et al., 2004 ; Mandernach, 2015 ; Trowler, 2010 ). Our comprehension of the distinction between these two terms aided us in pinpointing the themes of observation. This is because engagement, in this context, is not the behavior we are focusing on; instead, we are interested in examining classroom dynamics and communication.

Hall et al. ( 1977 ) indicated that non-verbal communication involves a sender and a recipient. Hall et al. ( 1977 ) highlighted that there are some variables that make this sending-receiving type of interaction more effective. Among those variables that Hall et al. ( 1977 ) listed is the “climate”, which refers to how friendly the teacher is in interacting with students. Students are encouraged to actively participate in class discussions if they receive these cues about friendliness and positivity through the sender’s facial expressions and voice tone (Hall et al., 1977 ). This coincides with Zeki’s ( 2009 ) findings that the teacher’s non-verbal communication creates a comfortable and relaxing climate, which consequently enables the students to effectively and confidently engage in class discussions.

In the literature, we discovered another element that affects the student’s engagement in class, which is the locus of control (Astin, 1984 ; Richmond and McCroskey, 2012 , p. 13). According to Astin ( 1984 ), “students’ degree of involvement in learning tasks can be influenced by whether they believe that their behavior is controlled by internal or by external factors.” This is related to belief systems, which are often rooted in one’s locus of control (Kopec, 2012 ). Those who have “a strong external locus of control believe that they are controlled by external forces” (Kopec, 2012 , p. 98). On the other hand, people who have an “internal locus of control believe that their actions, choices, and pursuits control their destiny” (Kopec, 2012 , p. 98). This can be an indicative measure of the student’s level of motivation (Zeki, 2009 ). A number of studies (Zeki, 2009 ; Kopec, 2012 ; Hall, 1959 ) stated that the components of non-verbal communication include, but are not limited to; facial expressions (i.e. mimics), eye contact, angulation, and gestures (i.e. body language). The amount of information one receives from their surroundings comes from all senses but mainly from the eyes and ears (Zeki, 2009 ). This highlights the importance of visual and auditory environmental cues in a classroom.

Verbal communication

Additionally, we sought to comprehend the influence of the new environment on verbal communication. Consequently, we delved into the literature pertaining to physical ergonomics, such as classroom layout, acoustics, and lighting within the field of environmental design.

Classroom layout

Through an examination of early literature centered on the physical ergonomics of classroom configurations, we came across a notable study conducted by Sommer ( 1977 ) that underscored the significance of classroom layout as a means of non-verbal communication. Sommer emphasized that a classroom should not be viewed as a single homogeneous space but rather as a collection of interconnected micro-environments. Elements such as windows, lighting, heating vents, blackboards, and display equipment were identified as factors influencing interactions within the classroom. Additionally, the arrangement of classroom furniture was found to impact body angulation, which in turn affects nonverbal communication (Kopec, 2012 ).

In the realm of classroom design, the establishment of structures known as “affordances” gives rise to opportunities for engagement or limitations in that regard (Metzger and Langley, 2020 ). Affordances pertain to both the perceived and tangible characteristics of objects or surroundings, influencing how they can be employed (Metzger and Langley, 2020 , as cited in Gibson, 1979). In other words, these affordances represent resources within an environment for those who perceive and interact with them. In the context of our study, affordances are represented by movable chairs, movable tables, Zoom technology, and microphones. These affordances are meant to enhance communication while also imposing limitations on social proximity.

Verbal communication in a classroom involves the teacher conveying speech to students through a combination of direct and reflected sound (Berg et al., 1996 ). Effective acoustics are achieved when the reflected sound enhances the quality of the direct sound (Berg et al., 1996 ). Sound within the classroom space exhibits three behaviors: reflection off obstacles, diffraction around obstacles, and transmission into obstacles or new media (Timeline: Sound Wave, n.d. ). Reflected sound can lead to two issues: echoes or reverberation (Timeline: Sound Wave, n.d. ). An echo occurs when a reflected sound wave reaches the ear more than 0.1 s after the original sound wave was heard (Timeline: Sound Wave, n.d. ). On the other hand, reverberation is the prolongation of sound as it repeatedly bounces off hard surfaces (Ballast, 2013 ). Reverberation is generally preferred in classroom acoustics as it enhances speech intelligibility in the interior environment (Ballast, 2013 ). To achieve good acoustics in a classroom, a well-designed space includes an appropriate combination of absorbent, reflective, and diffusive materials (Berg et al., 1996 ).

Classroom acoustics can be affected by sound transmission through barriers, such as HVAC systems and external noise from corridors or streets (Ballast, 2013 ). Research efforts have been directed towards exploring issues such as listening problems among special students, student disengagement, the teacher’s voice, and teacher fatigue (Berg et al., 1996 ). This information is relevant to our study as it pertains to the investigation of a socially distanced classroom setup. We also aimed to investigate acoustics because of its significant impact on both verbal and nonverbal communication, especially when considering the use of face coverings.

Daytime light exposure, particularly from sunlight, full-spectrum LEDs, and digital screens, is significant for learning as it affects both vision and a non-visual system tied to sleep-wake cycles and cognitive performance. Blue light has the most powerful impact on alertness and reduced sleepiness compared to other wavelengths, influencing hormonal secretion in the non-visual system (Uncapher, 2016 ).

In their case study, Tureková et al. ( 2018 ) aimed to show how the school environment significantly affects students’ academic performance. They found that factors like accurate lighting influence visual comfort and fatigue during visual tasks. Assessing the daylight factor in a university classroom revealed insufficient values, prompting the design of a potential software-based alternative to improve visual comfort. They also highlighted that natural light’s impact goes beyond academics, influencing physiological, psychological, and behavioral aspects of both students and workers (Tureková et al., 2018 ).

Al-Sallal ( 2010 ) studied daylighting in UAE classrooms, analyzing visual performance and quality. His research involved data collection from architectural drawings, compliance documents, site visits, and photography. Crucial design issues affecting visual quality, such as space size, depth-to-height ratio, window orientation, lighting direction, and desk position, were investigated through simulation. The study revealed design issues impacting daylighting and visual quality, including depth, glazing area, orientation, and daylighting direction. Visual discomfort was found due to contrasting luminance, high window brightness, and uneven daylight distribution. Mitigation strategies discussed focused on solar shading, glare protection, and daylight redirection, considering UAE climate design requirements. This study holds great relevance to our research because Qatar and the UAE share a similar climate. Our objective was to investigate whether there are any unexpected issues related to lighting in the new setup.

Joia and Lorenzo ( 2021 ) investigated the effectiveness of using Zoom, a popular choice for virtual communication during the pandemic (Joia and Lorenzo, 2021 ). The study’s findings emphasize the importance of a teacher’s digital proficiency on the platform and the availability of metacognitive support within the digital environment as key factors in achieving successful pedagogical objectives. Additionally, the research highlights that disciplines involving hard skills are more prone to not meeting their educational goals when transitioning to technology-mediated environments compared to soft skill disciplines undergoing a similar transition (Joia and Lorenzo, 2021 ).

Another study highlighted the benefits of video communication platforms, including expanding educational reach and enabling multimedia-based pedagogy (Earon, n.d. ). Online learning via Zoom showed satisfactory student levels in a study conducted in Pakistan (Minhas et al., 2021 ), but some students reported dissatisfaction due to technical issues (Kim, 2020 ). While online learning cannot replace face-to-face instruction (Ramadani and Xhaferi, 2020 ; Alawamleh et al., 2020 ), instructors’ digital competence and metacognitive support on Zoom can enhance the online experience (Joia and Lorenzo, 2021 ). The potential of using Zoom in a socially distanced classroom requires further exploration, given the COVID-19 pandemic’s impact and new social distancing measures. In our study, we aim to explore the use of Zoom as a supplementary communication medium in socially distanced classrooms.

To bridge the research gap on socially distanced classrooms that are specific to the context of Qatar, we embraced the philosophy of Epistemic Contextualism, asserting that knowledge attribution varies based on context (Rysiew, 2021 ). Following Morgan et al.’s ( 2016 ) recommendation, we adopted the case study methodology, drawing inspiration from the Case Study Observational Research (CSOR) approach. This approach entails conducting observations before interviews to delve deeper into aspects within the contextual framework. Our choice of a case study methodology aligns with qualitative research principles, suitable for exploring new fields or theorizing important issues (Jamshed, 2014 ). Consequently, we employed two data collection methods: observations followed by semi-structured interviews. Semi-structured interviews, rooted in the belief in socially constructed reality, offer flexibility for cross-verification within and between interviews (Azungah, 2018 ). The main objective was to investigate the impact of socially distanced classrooms on student engagement and classroom communication. This cross-sectional study was conducted within a three-month timeframe. Data were analyzed using thematic analysis (Lawless and Chen, 2018 ) for both the observation and interviews. The study was conducted in a unique setting. Prior to the COVID-19 pandemic, the classroom was designed as a studio for a single group, separated into two interconnected classrooms, illustrated in Fig. 1 as Classroom A and Classroom B. Additionally, two vestibules were designated as break areas for students. Classroom A had a dual function, serving as both a studio space and a location where students assembled their tables in the center for lectures. However, in response to the COVID-19 pandemic, social distancing measures were implemented, mandating that each student remain in their assigned seat even during lectures. In other words, students were assigned to design-studio classrooms A and B. The instructor’s workstation, which contained all the necessary equipment, was located in classroom A. As a result, Classroom A was equipped with a TV screen for presentations, while Classroom B was equipped with a projector. Both the screen and the projector were connected to the audio/speakers’ area that was located next to the instructor’s workstation in Classroom A (see Fig. 2 ).

figure 1

This figure demonstrates Pre- and Post-COVID layouts showcasing a floor plan of the two design-studio classrooms (A and B) interconnected by two vestibules, forming a unified socially distanced classroom. It also illustrates the locations of screens and instructor’s workstation in both classrooms.

figure 2

A floor plan depicting the layout of design-studio classrooms A and B , along with four perspectives from both classrooms viewed from various camera angles (angles A , B , C , and D ).

Non-participant observations

Observational documentation spanned three months, from September to November, commencing at the start of the semester before obtaining Institutional Review Board (IRB) approval for interviews, as no direct participant contact was required. Field notes encompassed written observations, hand sketches, and circulation maps, providing visual representations of classroom communications. The observer, the second researcher, attended the bi-weekly class sessions for approximately 60 min, ensuring comprehensive consideration of any potential confounding variables. The observation method was guided by findings from the literature review, shaping the framework for the study.

The observations involved observing students without actively participating, providing an overview of the setting and narrowing focus to specific elements of interest (Non-participant Observation, n.d. ). Students were closely monitored in their natural environments, with observations aligned with several themes derived from the literature review mentioned earlier. Field notes were recorded, specifically focusing on non-verbal communication aspects like angulation, body language, and gestures. Additionally, the observer examined any unanticipated data that had not been emphasized in the literature review. The aim of this method was to examine our predetermined themes extracted from the literature review and explore the emerging themes resulting from the new setup. Data were collected through field notes, sketches, and movement mapping over a period of three months.

Access to the classrooms was granted by both the Interim Chair of the Department and the Research Department. The first author served as the instructor for a lecture-based course during the research period, while the second author conducted the non-participant observations and subsequent semi-structured interviews. To maintain confidentiality, only data that had been de-identified and coded were provided to the first author for the purpose of data analysis.

It’s important to mention that we initially piloted a participant-observation method at the start of the semester, involving observations from both researchers. However, this proved impractical as the first researcher was also the course instructor, heavily engaged in fulfilling teaching obligations. Consequently, we opted for a non-participant observation approach, allowing one researcher to fully immerse in observing and documenting the identified variables from the literature review. Generally, “observational data can be integrated as auxiliary or confirmatory research” (Jamshed, 2014 , p. 88). Essentially, the use of observational data is intended to confirm the applicability of the predetermined themes identified in our literature review and to identify any unforeseen themes.

Semi-structured interviews

The second method utilized involved the conducting of face-to-face semi-structured interviews with college students who were pursuing a major in interior design. This was carried out following the approval granted by a national Institutional Review Board. Data was collected from a group of students ( n  = 20) aged between 18 and 20 years old. Ultimately, a total of 17 interviews were conducted, with three participants choosing to withdraw due to scheduling conflicts that arose during the final weeks of the semester. The inclusion and exclusion criteria can be found below in Table 1 .

Interviews were recorded and transcribed verbatim, with each session lasting approximately 30 min (Jamshed, 2014 ). The interview questions, derived from the literature review and observations, were intentionally designed as semi-structured to provide participants with the opportunity to elaborate on their responses. The inquiries primarily consisted of open-ended questions, aiming to delve into participants’ authentic feelings and attitudes regarding the new setup. However, close-ended questions were also incorporated to ensure clarity and consistency in responses.

The interviewing process employed a funnel approach, focusing on building trust and rapport and presenting questions in an unbiased manner to minimize biases from both the interviewer and interviewee (Azungah, 2018 ).

Data analysis

We adopted the inductive/deductive hybrid thematic analysis approach. According to Proudfoot ( 2022 ), thematic analysis that combines elements of both inductive and deductive approaches presents promising prospects for researchers. We initiated the coding process with a deductive approach, employing pre-established themes crafted before engaging with the collected data. These themes were formulated based on the literature review findings, detailed in Tables 2 and 3 . As we analyzed the interview data, we identified new themes that emerged from the study. Consequently, we adopted an inductive coding approach to highlight these additional insights.


During a 3-month period, the various movements of communication behaviors were captured with sketches. Video or audio recordings were not viable options due to cultural considerations. The outcomes of the non-participant observations align with the previously identified findings from literature review as shown below in Table 2 .

Based on our field observations, the instructor’s position within the room has a significant impact on student engagement. When the instructor is physically present in the room, it positively influences student-instructor interaction. Some students actively participate in class discussions and take notes only when the instructor is within their line of sight. However, there are other students who seem eager to participate regardless of the instructor’s location. While this observation might seem apparent, it proved valuable as it allowed us to connect it to the concept of locus of control. We were particularly interested in exploring whether student engagement stemmed from an internal or external source. Although this observation didn’t offer in-depth information, it provided an insight into how some students might possess an internal locus of control, motivating them to participate actively in class discussions regardless of classroom conditions or arrangements.

Additionally, our observations highlight that establishing eye contact plays a significant role in enhancing verbal communication and increasing student engagement. It is quite normal to see students eagerly joining classroom discussions by raising their hands, especially when they are in a position where the instructor can easily see them. In instances where students cannot recall technical terms for architectural concepts (e.g., forms, shapes, etc.), they resort to using hand gestures to convey their ideas. However, this might pose a challenge for those participating in the class discussion through Zoom from the adjacent room (classroom A or B), as they may not be able to see or interpret these hand gestures effectively. Body language encompasses a broad spectrum of non-verbal cues involving different parts of the body. Emphasizing the significance of hands in particular, they play a pivotal role in enhancing the effectiveness of verbal communication. Our observations also reveal that students commonly adjust their body position, specifically their angulation, to enhance their ability to actively engage in classroom discussions. This adjustment often involves orienting themselves towards key focal points within the classroom, which typically include the instructor’s position or the screen/display, particularly in lecture-style classes. This angulation adjustment may have potential musculoskeletal consequences, which is an aspect we aimed to explore further during the interviews.

This setup is relatively novel and has yet to receive attention in the existing literature. Our field observations underscore the significance of technology utilization in a socially distanced classroom setting. It notably reduces the time spent on communication between two separate rooms. Without the aid of microphones and speakers, instructors are required to repeat discussions for both rooms, effectively duplicating their verbal communication efforts. This duplication of effort can lead to fatigue, occasionally diminishing the instructor’s overall productivity in a socially distanced classroom. Conversely, the positioning of the microphone held significant importance for student engagement. Students seated in closer proximity to the microphone or those with unobstructed access to it demonstrated higher levels of participation in class activities and discussions as illustrated in the mapping diagram (Fig. 3 ).

figure 3

A mapping diagram that layers the instructor’s movement and students’ movement in the classrooms. In this diagram, the instructor’s movement frequency is highlighted with purple hexagons, while student movements are depicted with green hexagons.The dark microphone symbol denotes the primary location of the microphone, while the gray microphone symbol indicates changes in its position based on student movement.

Personal space and crowding

We also aimed to investigate the concept of crowding concerning personal space within the socially distanced setup. Most responses indicated that this feeling was barely experienced within the new arrangement. It appears that some students confused the psychological meaning of crowding with the physical aspects of overcrowding, and a follow-up question might have been helpful to clarify the investigation’s focus. Nonetheless, we suggest that the absence of the feeling of crowding could be attributed to individual personality traits, particularly whether one is a screener or non-screener (Kopec, 2012 ). Screeners are skilled at filtering out irrelevant stimuli and are less easily distracted or upset (“The Oxford Dictionary of Sports Science & Medicine,” 2006 ), while non-screeners have difficulty shifting attention and tend to experience higher levels of anxiety and empathy ( Nonscreener , n.d. ). Participant 4 exhibited a generally calm demeanor and a resilience to the influence of environmental factors. This disposition may shed light on the coping strategy that was observed, which includes either texting or stepping outside the classroom as a response to feeling overwhelmed. This coping strategy was also highlighted by participant 17.

Participant 17: “I actually try to take a break and try to go to the toilet or get a coffee, just a five-minute break, try to look to my phone to distract myself” .

Regarding the concept of personal space, the majority of participants perceived it positively in the socially distanced classroom. They appreciated the spaciousness of the setup and the generous size of their workspace, aligning with existing literature findings related to the concept of personal space as indicated below in Table 3 .

Furniture arrangement was generally perceived positively by 11 out of 20 participants, who appreciated the spacious personal space it provided in studio classes. However, some participants found the layout inconvenient, especially during lecture classes. The availability of a personal pin-up wall was appreciated by some students, but those sitting in the middle of the classroom, such as participant 13, felt disadvantaged due to the lack of this feature. Socially distanced classrooms were better tolerated in studio classes than in lecture classes, with students enjoying the increased personal space regardless of their location in the classroom.

Participant 13: “It is good, but at the same time I feel I don’t like it. I need a corner to sit in, in my area I sit in the middle, so I don’t have a pin up wall. Like in the Junior studio, I feel it is better because they have more corners, their tables are arranged in a U-shape, so most of them have corners and the area in the middle is empty. Having our tables in the middle, ok it is good for me to concentrate during the lecture classes, but in the studio classes it is uncomfortable” .

One drawback of this layout was the limited number of electrical outlets, which could become crowded when students needed to charge their laptops simultaneously. Another concern raised was the L-shaped table setup, which provided more space but required students to frequently turn their bodies and necks to view the screen during lectures, leading to potential musculoskeletal problems as emphasized by participant 14.

Participant 14: “The L-shape table setup is nice, because it gives us more space. However, the layout is not good, because we are not facing the screen, so we have to turn our bodies and neck in order to see the screen, which is very tiring. To open the laptop, take notes, following the lectures on the big screen with a layout that is not comfortable makes me lose focus” .

Instructors moving between the two rooms during class meetings to ensure equal engagement posed a distraction for some participants. They described maintaining two classrooms simultaneously as overwhelming for the instructor. Furthermore, some students found communication with instructors more convenient through Zoom compared to the socially distanced setup.

Nonverbal communication

Body language significantly influences a student’s attentiveness, as highlighted by 16 participants who emphasized that they are more focused when the instructor is physically present in the same classroom. Participant 14 expressed that seeing the instructor’s body language and personality creates a more engaging experience compared to feeling like they are listening to a machine, which helps them concentrate better. The term “focus” was used by those 16 participants to describe their level of engagement in class. Regardless of whether the interactions are one-way or two-way conversations, most students indicated that body language plays a vital role in keeping them attentive during class. However, it is essential to note that in-class participation does not always imply complete engagement with the class content. Rather, it is a term we used to assess the effectiveness of communication within this setting.

Participant 14: “Because focusing makes me understand the class materials, for example, if he or she (referring to the instructor) is here, I will be able to focus and understand, however, if they are in the other room, I try to listen to them but I cannot focus much “ .

Participant 13 emphasized the significance of body language, especially eye contact, in enhancing vocal communication. She mentioned that being able to see the instructor in front of her helps her understand the class materials better compared to when the instructor is in another room, and she struggles to maintain focus. This aligns with the observation that students tend to be more engaged when the instructor is within their line of sight.

Non-verbal communication or body language encompasses various aspects such as eye contact, gestures, voice, facial expressions, touch, space, and body movement/posture (Segal et al., 2023 ). Among these elements, the eyes and ears are the most utilized in any form of vocal communication, whether in one-way or two-way conversations. Hall’s ( 1966 ) findings indicate that the unaided ear’s effective coverage is limited, making visual cues crucial for effective communication.

Participant 14 mentioned relying more on visual cues than auditory ones, suggesting that visual learners may find it challenging to adapt to socially distanced classroom environments, especially when they cannot consistently see the speaker. This lack of human connection, as described by Participant 16, can hinder effective communication between the speaker and the audience.

Participant 10 emphasized the significance of visual access provided by Zoom in a socially distanced classroom. She expressed that when the instructor makes eye contact with the camera, it creates a sense of direct connection and engagement. To her, establishing eye contact is essential for comprehending lessons and establishing a connection with the instructor. She also noted that recalling the instructor’s body language while reviewing PowerPoint slides after class enhances information retention compared to audio-only classes, where relying on notes is necessary.

Additionally, Participant 10 highlighted the importance of eye contact, even in virtual settings, through the Zoom camera. When the instructor looks directly at the camera, it gives the remote audience the impression of maintained eye contact. This effort allows visually inaccessible students to stay involved and potentially engaged with the class content. Furthermore, the participant mentioned that body language helps in mentally noting information for better retention.

Participant 10: “somehow it does work, especially if the instructor is making eye contact with the camera or something. It makes me feel she is directed towards the students and she is looking at us. And for me eye contact is very important in communication, especially when it comes to understanding a lesson. Also, it is like having a relationship with the instructor, it is not just audio, but it is visual as well. Sometimes, when I go over the PowerPoint slides again after class to study, I sort of remember the instructor’s body language and it is like remembering the information that was said during the class. I feel I retain the information better, however, if it was only audio, I feel I will need to go back to my notes to remember and to refresh my memories.”

Participant 1 mentioned the advantage of immediate interaction in studio or graphics classes, where movement and questions are encouraged. However, there was confusion between audience etiquette and lack of participation, as remaining silent during a lecture is expected to avoid distractions. Questions were facilitated through raised hands, achieved by sharing screens via Zoom to connect both rooms. The perception of student engagement may have been skewed because of the room’s dual function (serving as both a studio and a lecture room), potentially causing some misinterpretation.

Three participants mentioned that the socially distanced setup facilitated effective communication with their classmates within the same classroom more than with those in other classrooms. Participant 6 expressed developing stronger relationships and feeling comfortable talking to nearby classmates, whereas communication with students in the other room was less frequent. This sentiment was shared by other participants, highlighting that student-to-student communication was confined within microenvironments, typically within a 1-m radius.

The type of course, whether studio-based or lecture-based, played a significant role in defining student-to-student communication. Studio classes held in those classrooms allowed for more walking around and talking, leading to increased interactions among students. On the other hand, lecture courses tended to limit communication to those sitting nearby or using microphones for questions.

Participant 10 acknowledged the ease of communication within their class but found it challenging to interact with students in the other room. However, efforts were made to maintain personal connections and engage in group discussions, even with students in the adjacent room. Similar experiences were shared by other participants, who expressed greater communication with those sitting closer to them, particularly in lecture classes.

Student location

The quality of a student’s learning experience is correlated with their location in the classroom, as indicated by several responses. Participants mentioned that being closer to the instructor’s position resulted in a better learning experience, allowing for comfortable, conversational distance and improved concentration.

Apart from proximity to the instructor, students also considered other factors when choosing their seats, such as adequate daylighting. Some preferred corner spots for privacy, storage space, and access to pinup walls, while middle spots were perceived as lacking privacy due to the absence of vertical partitions. However, certain desk locations led to musculoskeletal issues for students as they tried to adjust their positions to see the screen or instructor clearly. Participants 5 and 17 pointed out that poor ergonomics could result in disengagement from class activities.

Participant 17: “As a social distance I have no issues. But after the midterms I changed my location because I got neck issues. My table was facing the wall, so I had to twist my whole body to follow the lecture on the screen and that was very tiring”. She added, “…. and after the midterms, I did not like my grades, they were average but I did not like them. So, I felt I had to change, I had to be more comfortable, so I can focus more. Then I found another available place” .

Participant 6 indicated that the instructors’ movement between classrooms was influenced by the layout, with the primary workstation attracting them to stay longer in that room. This affected student engagement and communication with the instructor during class.

Participant 6 said, “Now that I think about it, I mainly talk with people sitting closer to me. However, my location is near the junior partition, which is annoying because I can hear everything through a little crack in the partition—their lectures, jokes, fights, everything.” The external noise from adjacent rooms with similar setups poses additional distractions, especially for students sitting on the wall-side. Despite having absorptive materials (fabric) on the pinup walls, the doors in between the classrooms require further treatment to address noise issues, considering the use of microphones and speakers as part of the socially distanced setup. Acoustics are significantly impacted by the flooring in the classroom, and footsteps and flooring noises can also contribute to distractions.


Some participants described the circulation as tight, with Participant 1 stating, “I think the circulation is a bit tight, but overall it is good.” This perception may be attributed to the limited pathways intentionally designed to restrict each student’s space and minimize potential areas of congregation. On the other hand, other participants found the circulation to be convenient for their work and overall smooth. Participant 5 expressed appreciation for the circulation, particularly the provision of two desks for each student, which was beneficial for their work and required ample space. They also found the circulation easy to navigate, with no challenges in moving around the classroom.

Upon analyzing the layout and comparing the seating positions of Participant 1 and Participant 5, we observed that both locations were unobstructed and conveniently accessible from the classroom entrance. Both participants were equidistant from the instructor’s position and the TV screen. However, it is worth mentioning that while Participant 5 was seated near a window, Participant 1 occupied a seat in the middle of classroom A. Despite this difference, they were still relatively close to each other. This variation in seating may have influenced their perceptions of the room’s overall circulation, with the window-side location potentially contributing to a greater sense of spaciousness.

Participant 1 expressed a preference for dimmer environments during lecture courses, stating, “Sometimes when I see it is dark there, I wish I was in the other room. My side has too much light.” This suggests that there is a variation in lighting preferences among students in a classroom setting. The proximity to windows is considered a privilege by some students, providing them with a view and the ability to control daylight, as described by Participant 1. Participant 14, on the other hand, mentioned being situated far from the window and lacking direct sunlight. Additionally, she found the artificial lighting in her class to be either excessively bright or too dim. As someone who enjoys natural light, she expressed a desire for more sunlight in her space. The quality of light, whether natural or artificial, significantly impacts students’ perceptions of the environment. For instance, Participant 14 attributed feelings of lethargy and tiredness during afternoon classes to the absence of sunlight. She believed that more windows would increase her energy and alertness. Participant 5 indicated that having her desk somehow close to the window and receiving sunlight in the morning helps awaken her, suggesting a positive association between productivity and good daylighting. However, Participant 12 pointed out that sitting near windows could be overwhelming in hot weather, expressing a preference for blinds to regulate natural light and maintain a comfortable temperature. Surprisingly, glare was not as problematic as initially thought, as students found ways to adjust their seating to avoid it, utilizing the spacious workspaces provided. In fact, several participants, including Participant 1, stated they had no glare issues due to the L-shaped tables, which allowed them to adjust their laptops accordingly.

While many participants appreciated the adequate amount of daylight in their classroom, they felt that the artificial lighting was inadequate and, to some extent, contributed to feelings of drowsiness. For instance, Participant 16 mentioned that the artificial light in her class (referring to classroom B) was low and dull. Furthermore, Participant 6, who occupies a seat in classroom B, found screen light during presentations or lectures to be bothersome for her eyes despite not receiving direct sunlight due to her window being closed. The room’s darkness and strong light from the screen caused discomfort and eye irritation for her.

The placement of microphones and their limited number discouraged several students from actively participating in class discussions during lecture-based courses. Participant 14 expressed frustration, describing walking to the fixed microphone location as a “nightmare.” A significant issue, pointed out by 12 participants, is the challenging distance between their desks and the microphone, which hinders their ability to engage in class discussions effectively. Participants used terms like “time-consuming” and “waste of time” to describe the inconvenience of walking to the microphone, which can impact the overall communication in the class.

Some students prefer to participate in discussions while remaining seated, especially if the microphone’s location is prominently visible in the room. Shyness was identified as a reason for some students’ hesitance to use the fixed microphone. It is speculated that shyness may stem from cultural factors or personality traits, but further investigation is required to understand the underlying reasons behind this sentiment.

Another theme that emerged from the interviews is that students intentionally refrain from participating due to spatial and technical challenges. For example, participant 4 explained that she holds back from answering questions because she believes others in the second room will reach the microphone faster or the instructor will notice them first. As a result, she remains silent and stays in her place. Participant 10 echoed a similar sentiment, stating that sometimes it takes the instructor time to realize that they want to ask or answer a question, leading to a reluctance to disturb the class or interrupt the instructor. The time required to walk to the microphone makes them hesitant, as by the time they reach there, the instructor might have moved on to the next topic. This situation can be embarrassing for students, as they do not want to interrupt the lecture inadvertently.

Participant 6 shared a similar experience, stating that she refrained from participating altogether during lecture classes due to the effort and stress involved. The process of walking to the microphone, ensuring it works, and repeating herself to those in the other room feels overwhelming. Participant 12 also acknowledged this challenge, indicating that she often weighs whether her question or comment is worth the time and potential disruption to the class.

Participant 3 expressed that she avoids participation due to the lengthy process involved in a socially distanced classroom. She feels that someone else will answer, so she does not need to speak up. Similarly, Participant 4 chooses not to participate in certain situations, believing that others will answer before her.

We propose that this pattern of hesitating to participate may be linked to a concept known as “learned helplessness.” This phenomenon occurs when individuals are repeatedly exposed to uncontrollable stressors, leading them to develop a belief that they lack control over their environment. Thus, this diminished sense of control can reduce their motivation to take action or attempt to change the situation ( APA Dictionary of Psychology , n.d.)

Microphone manners

One emerging sub-theme from the study is the intimidation some users, especially students, experience when using microphones. Instructors are also not effectively trained in microphone usage. Participants reported instances where they could not hear the instructor clearly due to audio volume fluctuations. This was attributed to instructors holding the microphone too far away or pointing it at their chin instead of their mouth, causing acoustic issues for students in the other classroom. Consequently, students tended to zone out when unable to hear clearly, impacting their engagement in class discussions.

Participant 5 mentioned that although instructors were generally audible, there were instances of sound cut-offs or distractions when the microphone was too close to the professor’s mouth, picking up unwanted sounds like breathing. Participant 7 also noted that some students had soft voices even when using the microphone, affecting clarity.

Zoom was deliberately chosen to visually connect people in both rooms for this study, as the transition from full online learning for two years made it a suitable platform. However, interview results revealed two main perspectives on using Zoom in a socially distanced classroom. Some participants found Zoom distracting, perceiving it as a reminder of online classes, while others appreciated its usefulness, especially visual learners who could easily view lecture slides through the sharing feature.

Distraction emerged as a recurring concern among several participants, particularly related to visual and auditory stimuli. These distractions encompassed factors such as noise originating from neighboring classrooms, the movements of the instructor, and technical issues. Notably, some students, like Participant 14, disclosed that they had Attention Deficit Hyperactivity Disorder (ADHD) and experienced heightened sensitivity to various forms of movement, which made both virtual and in-person classes equally challenging in terms of maintaining focus. Conversely, some participants held a positive perspective regarding Zoom’s role in enhancing communication between the two interconnected classrooms. For example, participant 10 expressed gratitude for the opportunity to observe the lecturer’s body language, which contributed to a sense of human interaction, even within a semi-virtual learning environment.

Technical issues occasionally led to student disengagement, but Zoom proved helpful for those in the no-instructor classroom. Students utilized Zoom’s sharing feature to follow lecture slides and virtually raise their hands for participation. However, overall, students preferred face-to-face interaction over Zoom communication, finding the latter tiring and distracting. Observations during the study supported this preference for face-to-face interaction.

Locus of control

Four participants indicated that they had little control over their classroom location and settled for what was available. However, some, like Participant 5, displayed an internal locus of control, stating she could teach herself and adapt to any situation. Participant 5 emphasized that the physical presence of the instructor was not crucial for her learning, indicating a strong internal strength and adaptability.

Conversely, Participant 17 exhibited a blend of external and internal locus of control. Initially, her seat choice was influenced by the location of her friends, reflecting an external factor. However, she later opted to change her seat with the goal of “improving her grades,” indicating a degree of internal control in her decision-making process.

Participant 17: “At the beginning I was just walking with my friends, and they sat so I sat. So, we sat and we were chatting, then I realized oh ok this is my place. But then I felt I cannot continue, and after the midterms, I did not like my grades, they were average but I did not like them. So, I felt I had to change, I had to be more comfortable, so I can focus more. Then I found another available place” .

Participant 15, on the other hand, favored keeping her laptop active during lectures, utilizing Zoom’s sharing feature to manage slides and search for answers when necessary. In doing so, she demonstrated an external locus of control, relying on available resources such as Zoom to address technical and acoustic challenges.

To our knowledge, this study is the first exploration of post-pandemic classroom design and its effects on classroom communication and student engagement under preventive measures such as face covering and social distancing. To investigate the research question in this case study, a thorough examination of both old and recent literature was methodically undertaken. This approach serves as both a limitation and a strength. The absence of pertinent studies prior to the research in 2021 posed a significant challenge. Nevertheless, delving into well-established older literature proved instrumental in overcoming this hurdle and establishing the groundwork for this exploratory research.

With the implementation of social distancing and the redefined proxemics, our study aimed to investigate the variations in the concept of personal space in this context. Hall’s work provided the foundation for our research in this specific area. While reviewing several studies referencing proxemics theory, none closely resembled ours. Thus, we utilized the original work as a starting point for exploration. This approach mirrors Mehta’s study ( 2020 ), which explored the impact of COVID-19 measures in urban settings, noting the transformation of spaces in response to social distancing. Mehta’s findings on sociable spaces resonated with our results regarding furniture arrangement and classroom layout. Our findings on the redefined proxemics in the new setup reveal that the post-pandemic classroom was widely praised for its redefined personal space. A majority of 11 out of 17 participants expressed positive sentiments about the spaciousness and convenience of the newly defined personal space (Table 3 ). Crowding, a psychological concept associated with personal space, was seldom experienced in the new setup. Some participants mentioned that crowding was only felt when there was limited access to charging outlets for their laptops. Additionally, individuals who experienced any form of stress in class identified checking their phones or taking short breaks as coping strategies.

Our findings also show that the furniture arrangement of the post-pandemic classroom is key in facilitating class communication. While being in close proximity to the instructor in the front or middle of the classroom is deemed conducive to student engagement, as it enables close and direct communication that helps students stay on task (Berg et al., 1996 ; as cited by Gullup, 1986), our study reveals that these middle seats do not cater to the spatial requirements of design students in studio classes, mainly due to the absence of pin-up walls. The findings indicate insufficient attention to the needs of students situated in the middle, exposing them to more visibility and diminished privacy compared to their counterparts along the perimeter. This situation is akin to the airplane aisle and window seats’ dilemma. While middle-seat students benefit from being close to the lecturer as a source of information, wall-side students enjoy privacy, access to a pin-up wall, and window advantages. A socio-petal (Mehta, 2020 ) furniture arrangement is recommended as it can provide equal opportunities and amenities for art and design students while facilitating communication in a socially distanced classroom.

The results of interviews and observations highlight the substantial influence of the instructor’s positioning in the classroom on communication with students, encompassing both verbal and non-verbal aspects. The students are more inclined to engage in class discussion if the instructor’s location in the classroom, as well as their body language are visually accessible. This highlights Kopec’s insights about the benefits of a rectangular classroom layout and how it supports the instructor’s capacity to establish eye contact with students since they fall within “the instructor’s primary visual field” (Kopec, 2012 , p. 224). Moreover, our research shows that 80% of the interview responses highlight the positive impact of body language on students’ attentiveness and engagement. This finding is consistent with the established literature, specifically Zeki’s ( 2009 ), emphasizing the significance of body language in non-verbal communication within the classroom. Put differently, the arrangement of the classroom is pivotal for both verbal and non-verbal communication, both in a general classroom setting and specifically in the post-pandemic classroom. Our study contributes to the existing knowledge by examining the utilization of Zoom to enhance body language, including eye contact, in a scenario involving the coordination of two or more classrooms simultaneously, necessitated by insufficient space in the facility. Fifteen percent of our sample expressed positive perceptions of using Zoom as an alternative to face-to-face communication to address spatial challenges in this context (Table 3 ). Based on these findings, we propose that new hidden dimensions arise, shaping communication and interactions within socially distanced classrooms. The noted expansion of personal, social, and public spheres, with the public sphere arguably encompassing the use of Zoom, prompts further exploration in these settings. The distances between students and instructors have the potential to redefine proxemics in post-pandemic classroom arrangements.

Our investigation explored lighting aspects, revealing that they had the least impact on the socially distanced classroom setup. Students’ main concerns revolved around having more control over lighting levels in their designated spaces. Responses showed diverse preferences for lighting conditions, with some favoring dim lighting and others opting for brighter classrooms. The L-shaped workspace effectively addressed glare issues, allowing students to adjust their positions for control if the problem arose. In a prior UAE study (Al-Sallal, 2010 ), it was observed that simulation runs revealed three key issues causing visual discomfort: sharp contrasts in luminance between the task surface (e.g., whiteboard) and nearby surfaces, excessive brightness from windows and uneven distribution of daylight in the space. In his study, the student’s sitting location was identified as a crucial factor influencing visual quality. The most problematic location was reported to be “the rear, opposite side of the windows” (Al-Sallal, 2010 , p. 208) in terms of acceptable luminance. While our study primarily addressed lighting preferences and emerging behaviors impacting post-pandemic classroom communications, certain findings resonate with Al-Sallal’s ( 2010 ), especially those related to student location. Six out of 17 students favored daylighting and found glare issues insignificant, attributing this to their ability to adjust positions within the spacious workspace. Additionally, four out of 17 participants expressed a preference for more control and the ability to adjust lighting levels according to their individual needs to enhance attention and focus (Table 3 ). Some participants positively associated proximity to windows with productivity, as highlighted in the lighting results subsection. To prioritize confidentiality, our study analyzed responses without linking them to specific student locations, resulting in a lack of specificity in our results. This limitation is acknowledged, but the decision was made to safeguard confidentiality, especially since one researcher served as the course instructor, creating a potential challenge in handling information related to student locations. This aspect is worth exploring in future research to understand the correlation between lighting and student location in post-pandemic classrooms.

In addition, we investigated acoustics in this distinctive setup utilizing technology to facilitate the operation of two classrooms simultaneously, aiming to improve verbal communication. Our research focused on exploring the consequences of preventive measures on classroom communication in a post-pandemic setting. Considering earlier research in the field, notably Berg et al.’s ( 1996 ) review article, which synthesized results from diverse studies, emphasizing the influence of noisy classrooms on students’ effective listening, impacting task engagement, discipline, and cooperation. They highlighted that teachers adjust their vocal approach, exhibiting variations in strength (Berg et al., 1996 ; as cited in Gallup, 1986; Ray, 1990). While some effectively project their voices, individuals with weaker voices may encounter stress when elevating their vocal levels (Berg et al., 1996 ; as cited in Berg, 1993). These findings proved valuable as we sought to comprehend the challenges faced by instructors in both general and specific settings. Our findings show that the adoption of microphones eliminated the need for vocal exertion by instructors. One of the acoustic concerns pointed out by some participants was noise. In this setup, noise primarily originated from adjacent classrooms and internal sources, such as speakers’ echoing sound and unwanted noise resulting from improper microphone use (e.g., instructor breathing). Seven out of 17 interviewees expressed more concern about noise related to technical issues, while three out of 17 interviewees identified external noise as more distracting (Table 3 ). For instance, participant 6 mentioned that her location is mainly distracting due to external noise from the neighboring classroom. These findings emphasize emerging challenges in temporary arrangements for socially distanced classrooms, suggesting areas for further exploration, such as the impact of using speakers in acoustically unprepared lecture spaces during emergencies.

This research uncovered novel findings not present in existing literature. One such discovery is the concept of microphone etiquette, an aspect not previously addressed in the specific context of our study. This introduces a new avenue for exploration by researchers and designers. The intentional inclusion of microphones in this setting aimed to improve verbal communication between two interconnected classrooms. Further investigation into blended learning or hybrid approaches utilizing microphones could be valuable, potentially mitigating challenges during local or global outbreaks.

An aspect warranting future exploration in research is students’ perceptions of microphone usage. Approximately 70.6% of participants indicated that microphone location affected their level of engagement in class. Three out of 17 participants explicitly reported abstaining from engagement due to recurrent technical issues, leading to delayed verbal communication. Students refrained from participating due to shyness, as they had to walk to the microphone location and their apprehension that technical problems might arise (Table 3 ). Arguably, this behavior can be attributed to learned helplessness, which is defined as “occurring when an individual continuously faces a negative, uncontrollable situation and stops trying to change their circumstances, even when they have the ability to do so” (Psychology Today, n.d. ). This finding resonates with Polat’s study ( 2022 , p. 95), which suggests that the students’ “individual uncertainties” can lead to learned helplessness, diminishing motivation and resulting in decreased academic performance and passive behaviors. However, given the sample’s size and homogeneity, it remains challenging to definitively associate learned helplessness with the socially-distanced setup or other variables in this case study. Additional data is needed to establish this as a dependent variable specific to this context. The locus of control was also identified within the responses, as outlined in the results section. A more comprehensive understanding of the data regarding locus of control could have been achieved with a larger sample and the incorporation of additional qualitative methods, such as surveys. The four responses collected in this aspect may be influenced by unanticipated variables specific to this context beyond the locus of control.

It is essential to recognize that the findings derived from this case study are highly contextual. If a similar setup is implemented in a different context or country, the results, especially concerning student attitudes toward microphone usage and privacy concerns, may vary. The transferability of our findings may be constrained both geographically and across disciplines. Since the study exclusively targeted interior design students, its relevance to other fields in the hard sciences may be restricted due to the unique nature of their work. It is noteworthy that cultural aspects were not explicitly addressed within the scope of this research.

It is worth mentioning that the non-participant observation method proved valuable in aligning predetermined themes from the literature review with the research question. Given this unprecedented environmental context, we opted for deductive coding to stay within the scope of this research study on classroom communication post-pandemic. However, the semi-structured interviews revealed unexpected themes, providing opportunities for further research, as mentioned earlier. Hence, we utilized a hybrid approach, incorporating both deductive and inductive coding, to identify patterns in the interview responses. This method facilitated the emergence of new themes, including the consideration of microphone etiquette.

In addressing potential biases arising from observations, we took measures to clearly delineate the role of each researcher (Glesne, 2011 ) to ensure transparency and maintain participant data confidentiality. Throughout the study, we consistently practiced reflexivity ( Reflexivity , n.d. ), allowing us to continually scrutinize our own biases and perspectives during data collection and analysis. The decision to employ a single observer was influenced by regulations limiting classroom capacity and other restrictions related to external visitors. Additionally, we incorporated the Devil’s Advocate approach (Trochim, 2020 ) during data analysis, actively challenging our interpretations of the findings.

This research holds relevance for administrators as they strategize for campus emergencies. Future studies could delve into the optimization of furniture arrangement, considering aspects like privacy and body language, particularly in emergency scenarios necessitating preventive measures like face covering and social distancing. The insights gleaned from our findings might aid administrators in effectively organizing designated spaces for concurrent use or incorporating hybrid modes to ensure instructional continuity during emergencies. A deeper understanding of enhancing hybrid learning environments post-pandemic could contribute to user satisfaction and reduce reliance on lockdown measures.


The pandemic has instilled in us the importance of carefully designing successful learning experiences and programs for our students. It forced us to reevaluate our priorities and life choices, leading to significant changes in communication due to preventive measures like face coverings and social distancing. In times of hardship and uncertainty, telecommunication has become indispensable for businesses, governments, and communities to sustain themselves. As a result, interior environments should be adaptable to accommodate such emergencies.

Our study investigated communication dynamics within a classroom environment adapted to mitigate the spread of the coronavirus while ensuring instructional continuity. We conclude that the impact of preventive measures on classroom communication in a post-pandemic setting is multifaceted and context-dependent. While we have delved into specific aspects we believe are linked to communication, there may be more to consider. Among these aspects, we have explored proxemics, which have evolved beyond its cultural definition to incorporate new physical dimensions to accommodate social distancing. Our findings indicated that psychological concepts like crowding in this socially distanced setting require reassessment. The increased spaciousness in classrooms resulting from the setup with social distancing has reduced crowding. Interestingly, the use of cell phones during class, not resulting in disciplinary action, has served as a positive distraction for students experiencing crowding or stress.

Furthermore, post-COVID spacing mechanisms, including occupant load and furniture arrangement with social distancing in mind, have reshaped our perception of personal space. People became less concerned with non-verbal cues that differ across cultures and define their personal space. Instead, the COVID-preventative measures have introduced new hidden dimensions to our understanding of personal space. These new hidden dimensions encompass factors such as proximity to microphones, the instructor’s desk, the pinup walls, and/or windows, all of which regulate communication within a socially distanced classroom. For instance, adopting a socio-petal layout in the classroom could significantly enhance these new hidden dimensions, thereby facilitating communication in a socially distanced setting. Our findings indicate that crowding, often associated with personal space and spatial density, is less prevalent in the post-COVID setup, as each student benefits from a more spacious personal area dictated by COVID protocols. This reduction in crowding contributes to improved performance as individuals regain control over their social interactions.

In times of emergency, like the pandemic, technology becomes essential to facilitate both verbal and non-verbal communication. This exploratory case study highlights the significance of technology in socially distanced setups in design-studio classrooms, particularly in addressing the communication challenges identified. However, further research is needed to investigate the potential for tailored technology usage and its effectiveness within these distinctive educational environments.

Data availability

The data supporting the findings of this study are accessible upon request from the corresponding author (MA). The data cannot be publicly released as they may contain information that could compromise the privacy or consent of research participants.

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We thank all the students who participated in this study for sharing their time and valuable insights. We also appreciate the support and funding provided by Virginia Commonwealth School of the Arts in Qatar for this research.

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importance of literature review in qualitative research

importance of literature review in qualitative research

What Is a Research Design? | Definition, Types & Guide

importance of literature review in qualitative research


Parts of a research design, types of research methodology in qualitative research, narrative research designs, phenomenological research designs, grounded theory research designs.

  • Ethnographic research designs

Case study research design

Important reminders when designing a research study.

A research design in qualitative research is a critical framework that guides the methodological approach to studying complex social phenomena. Qualitative research designs determine how data is collected, analyzed, and interpreted, ensuring that the research captures participants' nuanced and subjective perspectives. Research designs also recognize ethical considerations and involve informed consent, ensuring confidentiality, and handling sensitive topics with the utmost respect and care. These considerations are crucial in qualitative research and other contexts where participants may share personal or sensitive information. A research design should convey coherence as it is essential for producing high-quality qualitative research, often following a recursive and evolving process.

importance of literature review in qualitative research

Theoretical concepts and research question

The first step in creating a research design is identifying the main theoretical concepts. To identify these concepts, a researcher should ask which theoretical keywords are implicit in the investigation. The next step is to develop a research question using these theoretical concepts. This can be done by identifying the relationship of interest among the concepts that catch the focus of the investigation. The question should address aspects of the topic that need more knowledge, shed light on new information, and specify which aspects should be prioritized before others. This step is essential in identifying which participants to include or which data collection methods to use. Research questions also put into practice the conceptual framework and make the initial theoretical concepts more explicit. Once the research question has been established, the main objectives of the research can be specified. For example, these objectives may involve identifying shared experiences around a phenomenon or evaluating perceptions of a new treatment.


After identifying the theoretical concepts, research question, and objectives, the next step is to determine the methodology that will be implemented. This is the lifeline of a research design and should be coherent with the objectives and questions of the study. The methodology will determine how data is collected, analyzed, and presented. Popular qualitative research methodologies include case studies, ethnography , grounded theory , phenomenology, and narrative research . Each methodology is tailored to specific research questions and facilitates the collection of rich, detailed data. For example, a narrative approach may focus on only one individual and their story, while phenomenology seeks to understand participants' lived common experiences. Qualitative research designs differ significantly from quantitative research, which often involves experimental research, correlational designs, or variance analysis to test hypotheses about relationships between two variables, a dependent variable and an independent variable while controlling for confounding variables.

importance of literature review in qualitative research

Literature review

After the methodology is identified, conducting a thorough literature review is integral to the research design. This review identifies gaps in knowledge, positioning the new study within the larger academic dialogue and underlining its contribution and relevance. Meta-analysis, a form of secondary research, can be particularly useful in synthesizing findings from multiple studies to provide a clear picture of the research landscape.

Data collection

The sampling method in qualitative research is designed to delve deeply into specific phenomena rather than to generalize findings across a broader population. The data collection methods—whether interviews, focus groups, observations, or document analysis—should align with the chosen methodology, ethical considerations, and other factors such as sample size. In some cases, repeated measures may be collected to observe changes over time.

Data analysis

Analysis in qualitative research typically involves methods such as coding and thematic analysis to distill patterns from the collected data. This process delineates how the research results will be systematically derived from the data. It is recommended that the researcher ensures that the final interpretations are coherent with the observations and analyses, making clear connections between the data and the conclusions drawn. Reporting should be narrative-rich, offering a comprehensive view of the context and findings.

Overall, a coherent qualitative research design that incorporates these elements facilitates a study that not only adds theoretical and practical value to the field but also adheres to high quality. This methodological thoroughness is essential for achieving significant, insightful findings. Examples of well-executed research designs can be valuable references for other researchers conducting qualitative or quantitative investigations. An effective research design is critical for producing robust and impactful research outcomes.

Each qualitative research design is unique, diverse, and meticulously tailored to answer specific research questions, meet distinct objectives, and explore the unique nature of the phenomenon under investigation. The methodology is the wider framework that a research design follows. Each methodology in a research design consists of methods, tools, or techniques that compile data and analyze it following a specific approach.

The methods enable researchers to collect data effectively across individuals, different groups, or observations, ensuring they are aligned with the research design. The following list includes the most commonly used methodologies employed in qualitative research designs, highlighting how they serve different purposes and utilize distinct methods to gather and analyze data.

importance of literature review in qualitative research

The narrative approach in research focuses on the collection and detailed examination of life stories, personal experiences, or narratives to gain insights into individuals' lives as told from their perspectives. It involves constructing a cohesive story out of the diverse experiences shared by participants, often using chronological accounts. It seeks to understand human experience and social phenomena through the form and content of the stories. These can include spontaneous narrations such as memoirs or diaries from participants or diaries solicited by the researcher. Narration helps construct the identity of an individual or a group and can rationalize, persuade, argue, entertain, confront, or make sense of an event or tragedy. To conduct a narrative investigation, it is recommended that researchers follow these steps:

Identify if the research question fits the narrative approach. Its methods are best employed when a researcher wants to learn about the lifestyle and life experience of a single participant or a small number of individuals.

Select the best-suited participants for the research design and spend time compiling their stories using different methods such as observations, diaries, interviewing their family members, or compiling related secondary sources.

Compile the information related to the stories. Narrative researchers collect data based on participants' stories concerning their personal experiences, for example about their workplace or homes, their racial or ethnic culture, and the historical context in which the stories occur.

Analyze the participant stories and "restore" them within a coherent framework. This involves collecting the stories, analyzing them based on key elements such as time, place, plot, and scene, and then rewriting them in a chronological sequence (Ollerenshaw & Creswell, 2000). The framework may also include elements such as a predicament, conflict, or struggle; a protagonist; and a sequence with implicit causality, where the predicament is somehow resolved (Carter, 1993).

Collaborate with participants by actively involving them in the research. Both the researcher and the participant negotiate the meaning of their stories, adding a credibility check to the analysis (Creswell & Miller, 2000).

A narrative investigation includes collecting a large amount of data from the participants and the researcher needs to understand the context of the individual's life. A keen eye is needed to collect particular stories that capture the individual experiences. Active collaboration with the participant is necessary, and researchers need to discuss and reflect on their own beliefs and backgrounds. Multiple questions could arise in the collection, analysis, and storytelling of individual stories that need to be addressed, such as: Whose story is it? Who can tell it? Who can change it? Which version is compelling? What happens when narratives compete? In a community, what do the stories do among them? (Pinnegar & Daynes, 2006).

importance of literature review in qualitative research

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A research design based on phenomenology aims to understand the essence of the lived experiences of a group of people regarding a particular concept or phenomenon. Researchers gather deep insights from individuals who have experienced the phenomenon, striving to describe "what" they experienced and "how" they experienced it. This approach to a research design typically involves detailed interviews and aims to reach a deep existential understanding. The purpose is to reduce individual experiences to a description of the universal essence or understanding the phenomenon's nature (van Manen, 1990). In phenomenology, the following steps are usually followed:

Identify a phenomenon of interest . For example, the phenomenon might be anger, professionalism in the workplace, or what it means to be a fighter.

Recognize and specify the philosophical assumptions of phenomenology , for example, one could reflect on the nature of objective reality and individual experiences.

Collect data from individuals who have experienced the phenomenon . This typically involves conducting in-depth interviews, including multiple sessions with each participant. Additionally, other forms of data may be collected using several methods, such as observations, diaries, art, poetry, music, recorded conversations, written responses, or other secondary sources.

Ask participants two general questions that encompass the phenomenon and how the participant experienced it (Moustakas, 1994). For example, what have you experienced in this phenomenon? And what contexts or situations have typically influenced your experiences within the phenomenon? Other open-ended questions may also be asked, but these two questions particularly focus on collecting research data that will lead to a textural description and a structural description of the experiences, and ultimately provide an understanding of the common experiences of the participants.

Review data from the questions posed to participants . It is recommended that researchers review the answers and highlight "significant statements," phrases, or quotes that explain how participants experienced the phenomenon. The researcher can then develop meaningful clusters from these significant statements into patterns or key elements shared across participants.

Write a textual description of what the participants experienced based on the answers and themes of the two main questions. The answers are also used to write about the characteristics and describe the context that influenced the way the participants experienced the phenomenon, called imaginative variation or structural description. Researchers should also write about their own experiences and context or situations that influenced them.

Write a composite description from the structural and textural description that presents the "essence" of the phenomenon, called the essential and invariant structure.

A phenomenological approach to a research design includes the strict and careful selection of participants in the study where bracketing personal experiences can be difficult to implement. The researcher decides how and in which way their knowledge will be introduced. It also involves some understanding and identification of the broader philosophical assumptions.

importance of literature review in qualitative research

Grounded theory is used in a research design when the goal is to inductively develop a theory "grounded" in data that has been systematically gathered and analyzed. Starting from the data collection, researchers identify characteristics, patterns, themes, and relationships, gradually forming a theoretical framework that explains relevant processes, actions, or interactions grounded in the observed reality. A grounded theory study goes beyond descriptions and its objective is to generate a theory, an abstract analytical scheme of a process. Developing a theory doesn't come "out of nothing" but it is constructed and based on clear data collection. We suggest the following steps to follow a grounded theory approach in a research design:

Determine if grounded theory is the best for your research problem . Grounded theory is a good design when a theory is not already available to explain a process.

Develop questions that aim to understand how individuals experienced or enacted the process (e.g., What was the process? How did it unfold?). Data collection and analysis occur in tandem, so that researchers can ask more detailed questions that shape further analysis, such as: What was the focal point of the process (central phenomenon)? What influenced or caused this phenomenon to occur (causal conditions)? What strategies were employed during the process? What effect did it have (consequences)?

Gather relevant data about the topic in question . Data gathering involves questions that are usually asked in interviews, although other forms of data can also be collected, such as observations, documents, and audio-visual materials from different groups.

Carry out the analysis in stages . Grounded theory analysis begins with open coding, where the researcher forms codes that inductively emerge from the data (rather than preconceived categories). Researchers can thus identify specific properties and dimensions relevant to their research question.

Assemble the data in new ways and proceed to axial coding . Axial coding involves using a coding paradigm or logic diagram, such as a visual model, to systematically analyze the data. Begin by identifying a central phenomenon, which is the main category or focus of the research problem. Next, explore the causal conditions, which are the categories of factors that influence the phenomenon. Specify the strategies, which are the actions or interactions associated with the phenomenon. Then, identify the context and intervening conditions—both narrow and broad factors that affect the strategies. Finally, delineate the consequences, which are the outcomes or results of employing the strategies.

Use selective coding to construct a "storyline" that links the categories together. Alternatively, the researcher may formulate propositions or theory-driven questions that specify predicted relationships among these categories.

Develop and visually present a matrix that clarifies the social, historical, and economic conditions influencing the central phenomenon. This optional step encourages viewing the model from the narrowest to the broadest perspective.

Write a substantive-level theory that is closely related to a specific problem or population. This step is optional but provides a focused theoretical framework that can later be tested with quantitative data to explore its generalizability to a broader sample.

Allow theory to emerge through the memo-writing process, where ideas about the theory evolve continuously throughout the stages of open, axial, and selective coding.

The researcher should initially set aside any preconceived theoretical ideas to allow for the emergence of analytical and substantive theories. This is a systematic research approach, particularly when following the methodological steps outlined by Strauss and Corbin (1990). For those seeking more flexibility in their research process, the approach suggested by Charmaz (2006) might be preferable.

One of the challenges when using this method in a research design is determining when categories are sufficiently saturated and when the theory is detailed enough. To achieve saturation, discriminant sampling may be employed, where additional information is gathered from individuals similar to those initially interviewed to verify the applicability of the theory to these new participants. Ultimately, its goal is to develop a theory that comprehensively describes the central phenomenon, causal conditions, strategies, context, and consequences.

importance of literature review in qualitative research

Ethnographic research design

An ethnographic approach in research design involves the extended observation and data collection of a group or community. The researcher immerses themselves in the setting, often living within the community for long periods. During this time, they collect data by observing and recording behaviours, conversations, and rituals to understand the group's social dynamics and cultural norms. We suggest following these steps for ethnographic methods in a research design:

Assess whether ethnography is the best approach for the research design and questions. It's suitable if the goal is to describe how a cultural group functions and to delve into their beliefs, language, behaviours, and issues like power, resistance, and domination, particularly if there is limited literature due to the group’s marginal status or unfamiliarity to mainstream society.

Identify and select a cultural group for your research design. Choose one that has a long history together, forming distinct languages, behaviours, and attitudes. This group often might be marginalized within society.

Choose cultural themes or issues to examine within the group. Analyze interactions in everyday settings to identify pervasive patterns such as life cycles, events, and overarching cultural themes. Culture is inferred from the group members' words, actions, and the tension between their actual and expected behaviours, as well as the artifacts they use.

Conduct fieldwork to gather detailed information about the group’s living and working environments. Visit the site, respect the daily lives of the members, and collect a diverse range of materials, considering ethical aspects such as respect and reciprocity.

Compile and analyze cultural data to develop a set of descriptive and thematic insights. Begin with a detailed description of the group based on observations of specific events or activities over time. Then, conduct a thematic analysis to identify patterns or themes that illustrate how the group functions and lives. The final output should be a comprehensive cultural portrait that integrates both the participants (emic) and the researcher’s (etic) perspectives, potentially advocating for the group’s needs or suggesting societal changes to better accommodate them.

Researchers engaging in ethnography need a solid understanding of cultural anthropology and the dynamics of sociocultural systems, which are commonly explored in ethnographic research. The data collection phase is notably extensive, requiring prolonged periods in the field. Ethnographers often employ a literary, quasi-narrative style in their narratives, which can pose challenges for those accustomed to more conventional social science writing methods.

Another potential issue is the risk of researchers "going native," where they become overly assimilated into the community under study, potentially jeopardizing the objectivity and completion of their research. It's crucial for researchers to be aware of their impact on the communities and environments they are studying.

The case study approach in a research design focuses on a detailed examination of a single case or a small number of cases. Cases can be individuals, groups, organizations, or events. Case studies are particularly useful for research designs that aim to understand complex issues in real-life contexts. The aim is to provide a thorough description and contextual analysis of the cases under investigation. We suggest following these steps in a case study design:

Assess if a case study approach suits your research questions . This approach works well when you have distinct cases with defined boundaries and aim to deeply understand these cases or compare multiple cases.

Choose your case or cases. These could involve individuals, groups, programs, events, or activities. Decide whether an individual or collective, multi-site or single-site case study is most appropriate, focusing on specific cases or themes (Stake, 1995; Yin, 2003).

Gather data extensively from diverse sources . Collect information through archival records, interviews, direct and participant observations, and physical artifacts (Yin, 2003).

Analyze the data holistically or in focused segments . Provide a comprehensive overview of the entire case or concentrate on specific aspects. Start with a detailed description including the history of the case and its chronological events then narrow down to key themes. The aim is to delve into the case's complexity rather than generalize findings.

Interpret and report the significance of the case in the final phase . Explain what insights were gained, whether about the subject of the case in an instrumental study or an unusual situation in an intrinsic study (Lincoln & Guba, 1985).

The investigator must carefully select the case or cases to study, recognizing that multiple potential cases could illustrate a chosen topic or issue. This selection process involves deciding whether to focus on a single case for deeper analysis or multiple cases, which may provide broader insights but less depth per case. Each choice requires a well-justified rationale for the selected cases. Researchers face the challenge of defining the boundaries of a case, such as its temporal scope and the events and processes involved. This decision in a research design is crucial as it affects the depth and value of the information presented in the study, and therefore should be planned to ensure a comprehensive portrayal of the case.

importance of literature review in qualitative research

Qualitative and quantitative research designs are distinct in their approach to data collection and data analysis. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research prioritizes understanding the depth and richness of human experiences, behaviours, and interactions.

Qualitative methods in a research design have to have internal coherence, meaning that all elements of the research project—research question, data collection, data analysis, findings, and theory—are well-aligned and consistent with each other. This coherence in the research study is especially crucial in inductive qualitative research, where the research process often follows a recursive and evolving path. Ensuring that each component of the research design fits seamlessly with the others enhances the clarity and impact of the study, making the research findings more robust and compelling. Whether it is a descriptive research design, explanatory research design, diagnostic research design, or correlational research design coherence is an important element in both qualitative and quantitative research.

Finally, a good research design ensures that the research is conducted ethically and considers the well-being and rights of participants when managing collected data. The research design guides researchers in providing a clear rationale for their methodologies, which is crucial for justifying the research objectives to the scientific community. A thorough research design also contributes to the body of knowledge, enabling researchers to build upon past research studies and explore new dimensions within their fields. At the core of the design, there is a clear articulation of the research objectives. These objectives should be aligned with the underlying concepts being investigated, offering a concise method to answer the research questions and guiding the direction of the study with proper qualitative methods.

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importance of literature review in qualitative research

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importance of literature review in qualitative research

  • Open access
  • Published: 03 June 2024

Patients’ expectations surrounding revision total hip arthroplasty: a literature review

  • Omar Mohammad   ORCID: orcid.org/0000-0002-3054-2578 1 ,
  • Shahril Shaarani 2 ,
  • Adnan Mohammad 3 &
  • Sujith Konan 2  

Arthroplasty volume  6 , Article number:  28 ( 2024 ) Cite this article

44 Accesses

Metrics details

Revision total hip arthroplasties (RTHA) are associated with a higher complication rate than primary total hip arthroplasties (THA), and therefore it is important for patients to have realistic expectations regarding outcomes. The aim of this literature review was to gather and summarize the available evidence on patients’ expectations following RTHA.

A literature search was conducted in PubMed, PsycINFO, Cochrane, Google Scholar, Web of Science and Embase from inception to November 2023. Articles assessing patient expectations for RTHA were included. Methodological quality was assessed by two independent reviewers using the National Heart, Lung and Blood Institute (NIH) study quality assessment tool for observational cohort and cross-sectional studies. A qualitative analysis was performed involving the summarization of study characteristics and outcomes.

The search strategy generated 7,450 references, of which 5 articles met the inclusion criteria. Methodological quality scores ranged from 7–10. Patients had high expectations concerning future walking ability, pain and implant longevity relative to actual postoperative outcomes. A significant positive correlation was found between fulfilled expectations of pain and walking ability and patient satisfaction ( r  = 0.46–0.47). Only two studies assessed the fulfillment of patient expectations. Great variability was seen in the measurement of expectations.

Patients undergoing RTHA appeared to have high expectations for pain and functionality compared to postoperative outcomes. However, there was a paucity of high-quality data in this area, limiting the accuracy of the conclusion. Further research is needed, that emphasizes developing a sound theoretical framework for expectations, allowing for the consistent implementation of valid measurement tools for patient expectations.


Total hip arthroplasty (THA) is a cost-effective procedure for improving a patient’s quality of life (QOL), pain, and function when conservative therapies have failed [ 1 , 2 , 3 ]. Despite the widely recognized success of THA, there is a certain level of risk that may necessitate a revision procedure. The incidence of revisions is on the rise and is projected to increase by 31% by 2030 in England & Wales, UK [ 4 ].

When compared to primary THA, revision THA (RTHA) is associated with higher rates of short- and long-term complications, elevated mortality rates, lower satisfaction, and smaller improvements in functional outcomes [ 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. Whether patients undergo either primary or RTHA, they largely expect a reduction in pain and an improvement in both function and quality of life [ 12 , 13 , 14 , 15 ]. In the preoperative period, it is important to assess these expectations, to ensure that patients have a realistic perspective of the outcomes of the operation and are not dissatisfied. Aside from technical factors and the quality of existing bone, patient factors may also partially explain the less favourable outcomes of RTHA relative to primary THA [ 8 ].

There is a growing body of literature across a variety of medical specialties linking clinical outcomes with patients’ expectations and satisfaction. Patient satisfaction has been shown to lead to higher compliance and attendance for monitoring and follow-up care [ 16 ], which are integral factors in optimizing prosthesis longevity. Furthermore, patients’ expectations are strongly correlated with satisfaction, with satisfied patients having their expectations fulfilled [ 17 ] and unrealistic expectations being correlated with dissatisfaction [ 18 ]. This has led to increasing emphasis on measures of quality of life and patients’ feelings of satisfaction [ 19 , 20 ]. Therefore, as a reflection of this shift in emphasis, it has become essential to gain a better understanding of patients’ expectations.

Although patient expectations have been widely discussed in current primary THA research [ 17 , 18 , 21 ], there is an apparent sparsity in the RTHA literature. This literature review therefore aimed to comprehensively assess all relevant studies evaluating the expectations of patients undergoing RTHA, and how this in turn relates to post-operative outcomes where possible.

Materials and methods

Search strategy.

A comprehensive electronic literature search was performed in the following databases: PubMed, The Cochrane Library, Google Scholar, PsychINFO, Web of Science and Embase to identify eligible studies published until the 7th November 2023. Search terms were derived from MeSh terms in PubMed and free text terms relating to (1) hip arthroplasty, (2) revision and (3) expectations/expectancies (Table  1 ). Although Haanstra et al. offered distinct definitions for expectations and expectancies as being “cognitions regarding probable future events” and “the act or state of expecting” [ 22 ], the current literature uses the two terms interchangeably to show that an individual is “expecting something to occur in the future”. Therefore, whilst they are different concepts, no distinction was acknowledged between the two.

Inclusion criteria

The individual search results from each database were combined barring duplicates, and the remaining titles and abstracts were then screened against the inclusion criteria found below.

The studies had to meet the following inclusion criteria to be eligible:

The study included revision THA patients;

Patients’ expectations were assessed;

The study had to be written in English;

The patients were adults > 18 years of age.

If an article assessed both primary and RTHA groups but failed to report the data separately for each group, the study was excluded, as we would not be able to extract the relevant data.

Two reviewers (OM and SRS) independently assessed the full text articles, based on the title and abstract, against the inclusion criteria. If there was any uncertainty regarding the eligibility of a study the full text was examined. The results of the search are shown in Table  2 .

Data extraction and methodological quality assessment

The same two reviewers extracted relevant data from the included studies using a standardized data extraction form (Table  3 ). The form included information on study design, study population, follow-up period, measurement of expectations and outcome measurements. Moreover, data on the strength of the relationship between expectations and outcomes was extracted where possible (e.g., P -values and correlation coefficients).

Furthermore, the methodological quality of the selected studies was assessed using the National Heart, Lung and Blood Institute (NIH) study quality assessment tool for observational cohort and cross-sectional studies [ 26 ]. Each study was judged on key concepts for internal validity, such as sample size, exposure/outcome measurement and compatibility of the groups. There were fourteen questions in total, for which studies could score a maximum of 14 points in sum. If there was any disagreement between the two reviewers, it was agreed that a discussion would be held to reach a point of consensus. This did not occur.

Data analysis

Due to the heterogeneity of the measurement of patients’ expectations in the studies identified, it was not possible to statistically pool the data in a meta-analysis. Instead, a qualitative analysis was performed involving the summarization of study characteristics and outcomes, as well as a methodological assessment using the NIH quality assessment tool. Studies were noted as poor quality if they scored 0–4, fair if they scored 5–10 and good if they scored 11–14 out of 14 questions [ 27 ].

Study selection process

The literature search retrieved a total of 7,450 records. After removal of duplicates ( n  = 162), records not in English ( n  = 382), non-human studies ( n  = 251) and studies not on adults aged > 18 ( n  = 1,876), a total of 4,779 papers remained. After screening of the titles and abstracts, 4,742 studies were excluded, as they either did not assess patient expectations, did not include revision THA or were review articles. This left a total of 37 studies for further investigation. After full-text assessment, a further 32 articles were excluded, leaving 5 articles that met all the inclusion criteria [ 12 , 14 , 23 , 24 , 25 ] and were subsequently included in this review (Fig.  1 ).

figure 1

Flowchart of literature search and selection process

Study characteristics

Five cohort studies were included in this review. The sample size ranged from 60 to 320 participants. Four studies only included RTHA [ 12 , 14 , 23 , 25 ] and one included both primary and RTHA [ 24 ]. In the assessment of expectations, two studies utilized a single item measurement which utilized either a three-point Likert-scale [ 23 ] or a six-point Likert-scale [ 25 ], two studies implemented a two-item instrument utilizing either a 4-point Likert scale [ 12 ] or a close-ended multiple-choice format [ 24 ]. One study modified the pre-existing Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC scale—a validated instrument) to assess patients’ expectations of pain, stiffness and physical function in 6 months after the revision operation [ 14 ]. Overall, no validated instruments were used in the assessment of patients’ expectations in revision THA across all studies.

Methodological quality

The average quality score was 9 out of 14 (range 7–9) (Table  2 ). As expected, the lowest scoring items were:

“Were the outcome assessors blinded to the exposure status of the participants?” —due to all studies having utilized a self-reported questionnaire;

“For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome”;

“Was the exposure(s) assessed more than once over time?”—as the exposure was a single revision THA.

Other notable methodological shortcomings were the common lack of sample size justification and often absent statistical analyses of confounding variables.


The measurement of patient expectations varied across the studies included in this review. Two studies focused on revision longevity expectations [ 23 , 24 ]. Barrack et al. implemented a single postoperative question concerning implant longevity and scaled responses using a 3-point Likert scale. Hellman et al. also measured implant longevity expectations using a single retrospective question and graded responses with close-ended multiple-choice questions.

One study prospectively measured the expectations of future pain and walking ability utilizing two questions scaled via a 4-point Likert scale [ 12 ]. One study assessed patients’ expectations of pain, stiffness and physical function utilizing the modified WOMAC scale [ 14 ]. These were measured prospectively and used a 5-point Likert scale. Two studies examined fulfillment of patients’ expectations after surgery [ 12 , 25 ]. Eisler et al. postoperatively assessed fulfillment of expectations with two questions and utilized a 4-point Likert scale. Zhang et al. used one postoperative question with a 6-point Likert scale. Only one study measured how this in turn correlated with patient satisfaction [ 12 ].

Patients’ expectations of pain were measured in two studies. Eisler et al. found that 92% of patients expected to have no pain or to have much less pain, and only 8% expected a slight reduction in pain. Haddad et al. reported an average score of 7.4/25 (CI 6.2–8.6) for pain, with a lower score conferring a low expectation of pain.

Function was assessed in two studies [ 12 , 14 ]. Eisler et al. noted that 82% of patients expected the same walking ability as after the first THA or markedly improved walking ability, 15%, slightly improved and 3%, no difference in walking ability. Haddad et al. reported an average expectation of 28.1/85 (CI 24.0–32.2) for physical activity, with a lower score indicating a higher expectation of function. Additionally, only Haddad et al. assessed expectations on stiffness, with an average expectation of 3.5/10 (CI 3.0–4.0) for stiffness, with a lower score indicating a lower expectation for stiffness.

Fulfilled expectations

Eisler et al. found that 55 and 69% of patients had fulfilled expectations regarding walking ability and pain. Furthermore, fulfilled expectations about pain and walking ability demonstrated a modest positive correlation with satisfaction ( r  = 0.46–0.47). The absence of complications was the only predictor of fulfilled pain expectations during the postoperative hospital period (odds ratio (OR) 4.8; 95% confidence interval (CI) 1.1–20.8). Zhang et al. found that at 6 months postoperatively, distressed patients had significantly lower rates of fulfilled expectations compared to non-distressed patients (64.5% vs. 94.1%, P  = 0.027). At 2 years postoperatively, this was no longer significantly different (63.6% vs. 79.3%, P  = 0.342).

Implant longevity

Two studies assessed patients’ expectations concerning the longevity of their revision THA [ 23 , 24 ]. Barrack et al. found that most patients, regardless of original implant longevity, expected their revision to last longer. In patients in whom the primary THA lasted < 5 years: 77% expected revision to last longer and in those where the primary lasted 5–10 years: 76% expected revision to last longer. If the primary lasted 10–15 years: 69% expected the revision to last longer and in those where the primary THA lasted > 15 years: 62% expected the revision to last longer. Hellman et al. found that 35% of patients expected the revision to last for the rest of their lives.

This review found that RTHA patients tend to have unrealistically high expectations regarding pain relief, improvement in movement, and implant longevity. Furthermore, distressed patients are less likely to have their expectations fulfilled postoperatively in the short term [ 25 ]. Given poorer outcomes with revision surgery versus primary THA, these expectations are unlikely to be fulfilled and may result in patient dissatisfaction [ 8 , 12 , 14 ]. Only one study [ 12 ] assessed how fulfillment of these expectations correlated with postoperative satisfaction, revealing a moderate positive correlation with expectations of pain and walking ability. However, overall, there is a paucity of research concerning expectations following RTHA procedures, despite the higher risk of complications [ 28 ]. Additionally, there is significant variability in the way expectations are measured.

Important areas that need to be addressed in future research include (1) The theoretical framework of expectations; (2) the measurement of expectations; (3) the correlation of psychological and other demographic factors and (4) the relationship between fulfilled expectations and satisfaction.

Firstly, none of the papers in this review provided a definition of patient expectations. The absence of a consistent theoretical framework for expectations lends itself to an increased propensity for the heterogeneous use of terminology and measurements. If left unaddressed, this can lead to research plagued by discontinuity and poor methodological quality. In the past, several reviews [ 29 , 30 , 31 ] have acknowledged patient expectations as being a complex multifaceted construct. Kravitz [ 31 ] made a distinct delineation between value (reflecting the patient’s wishes/hopes) and probability expectations (the likelihood that an event will occur). Furthermore, Bandura [ 32 ] separated efficacy from outcome expectations. Given the different perspectives on expectations, it is necessary to utilize a consistent framework to allow for accurate classification and subsequent assessment. For example, Hobbs et al. [ 33 ] successfully utilized the International Classification of Functioning, Disability and Health (ICF) framework to classify patients’ expectations in primary THA. This involved assigning patients’ expectations to one of three domains: activity limitations, impairments to bodily function and structure, and participation restrictions. It was found that patients generally focused more on the recovery of valued activities rather than the reversal of their functional impairment. In future RTHA research investigating patient expectations, researchers should aim to map their findings to each of the core ICF constructs. If performed consistently, this has the potential to lead to more uniformity of definitions, better integration of data amongst different studies and improved validation of measurement instruments. Additionally, this method could be used to ascertain whether certain expectation domains, e.g., impairment, activity limitations or participation restriction expectations are predictors of patient reported outcome measures (PROMs).

As mentioned previously, the lack of a consistent theoretical framework for patient expectations has likely contributed to the absence of a valid and standardized measurement tool. This prevents the effective integration and comparison of data across studies [ 22 ]. Each study in this review implemented a unique instrument that was only used for one investigation. They often lacked a rationale behind their development, or data on reliability and validity, which limits the credibility of evidence collected. This issue has affected both primary THA research and research in other fields such as psychotherapy, where, for example, Constantino et al. [ 34 ] reported that the majority (67%) of measurements were of poor quality. A possible strategy may be to either adapt an already well-established patient-reported outcome tool (such as the WOMAC) or use a theory-guided approach, with testing in independent samples to gather data on reliability, construct validity and predictive validity. Alternatively, the Hospital for Special Surgery Total Hip Replacement Expectations Survey (HSS-HRES) could be used for RTHA patients. This survey is a well-validated 18-question expectations survey that is graded on a 5-point Likert scale and has been used effectively in past THA research [ 35 ]. Regardless, future researchers should aim to use a validated instrument.

Additionally, half of the studies included in this review measured patients’ expectations in the postoperative period. This is not optimal and increases the risk of bias, as the patients may not be able to accurately recall their preoperative expectations due to the time elapsed [ 36 ]. Furthermore, since patient dissatisfaction is secondary to a disequilibrium between expectations and fulfilled expectations [ 37 ], patients may therefore alter their expectations to match their current status, to prevent dissatisfaction [ 38 ]. A Canadian study in 2006, reported this phenomenon regarding total knee arthroplasty, where 35% of patients over- or underestimated their preoperative level of functioning [ 39 ]. However, there is another issue purported by Haanstra et al. which pertains to the timing of expectation measurement [ 22 ]. Given that patients’ expectations are likely to be widely influenced by their doctor, it is possible that the longer the patient is in contact with them and the later their expectations are measured, the more realistic and reliable they may be. Currently no investigation has measured the influence of time of measurement, but it is a variable to keep in mind, which could be offset by collecting data at different time points.

Moreover, only one study in this review collected data in the pre- and postoperative period to assess the percentage of fulfilled expectations, and only this study analyzed the correlation between fulfilled expectations and satisfaction [ 12 ]. Whilst expectations are an important preoperative factor, it is the fulfillment of these expectations that has been shown to be the more significant determinant of patient-reported outcomes and satisfaction [ 40 ]. High expectations are not inherently detrimental, but unrealistic expectations are [ 40 ]. Therefore, it is important to assess the percentage of patients with fulfilled expectations, as this information can be used to foster realistic, high expectations through effective preoperative education.

If patients are to be measured in the postoperative period, the length of the follow-up period needs to be addressed, as it may influence findings. Barlow et al. found that expectations may take up to two years post-surgery before they are fulfilled, due to function having the potential to improve for up to two years, alluding to the existence of a timing bias [ 41 ].

Finally, half of the available literature did not include a multivariate analysis of confounding variables such as age, gender, ethnicity and preoperative education level despite their influence on patient expectations [ 35 , 42 ]. Furthermore, psychological factors (depression, optimism and catastrophizing), which may interact with expectations or treatment outcomes, were rarely analyzed [ 22 ]. Future research should try to delineate these factors for further consideration.

A promising area of focus for future research is the consenting process. Patient recall of the consenting process, and the relevant risks and outcomes, is frequently poor [ 43 ]. A recent study demonstrated that patients undergoing THA, who were consented with the generic consent form, only recalled 0.67 risks four weeks after surgery. In contrast, those who were given a surgery-specific consent form, recalled 1.43 risks on average [ 44 ]. This surgery-specific consent form listed potential adverse events alongside appropriate explanations. With regards to RTHA, this could be implemented with the addition of a section on postoperative outcomes. This would help to ensure that patients have a better comprehension of the procedure and retain more information. This may, therefore, lead to more realistic expectations that can be fulfilled.

This study has limitations that need to be considered. Firstly, a meta-analysis was not possible due to the heterogeneity in the papers included and the poor standard of reporting. And so, we performed a qualitative analysis. However, a thorough, definitive analysis of the data is not possible using this method. Secondly, only a limited number of studies were available for review, due to the lack of research in this area. As a result, there are limited data available to analyse, which may not fully represent patient expectations. The data were also relatively old, with only 2 references being < 10 years ago. Patient expectations may have improved since then with changes in perioperative information. Therefore, the strength of conclusions made in the paper may not be accurate and should be taken with caution. Although a limitation, this highlights a clear deficit in current research that needs to be addressed.

As conclusions from RTHA literature are limited, we can look at adjacent literature concerning total knee arthroplasty (TKA), to better understand what patients tend to expect with a joint replacement procedure. Similarly, TKA patients have been shown to have unrealistically high expectations regarding postoperative pain, function and recovery [ 45 ]. Moreover, patient satisfaction has been shown to be highly correlated with expectation fulfillment [ 45 ]. Recent research has demonstrated improvements in patients’ WOMAC pain and satisfaction scores at over 1 year post operation in TKA patients, by setting realistic expectations [ 46 ]. Although a different procedure/patient demographic, these findings are similar to the current evidence base for RTHA and reinforce the importance of setting appropriate baseline patient expectations through perioperative counselling, to foster better PROMs.

A definitive conclusion is limited by the sparse data available. However, the current literature demonstrates that revision THA patients tend to have unrealistic expectations with regards to pain relief, function and implant longevity. Realistic patient education prior to surgery is necessary to avoid expectation/outcome mismatch and hence dissatisfaction. Nevertheless, this review demonstrates the lack of adequate research on patients’ expectations in revision THA, both in terms of absolute numbers, and methodological quality. More research is needed, which utilizes a standardized approach in assessment, in order to foster a better understanding of the relationship between patient expectations and postoperative outcome measures. Only then, can this information be effectively applied clinically to improve the outcome of revision THAs. We suggest counselling of patients before surgery and using a procedure-specific consent. As to collection of pre- and postoperative data—postoperative data should be collected at different points of time as the patients’ outcomes improve with time and so will the outcome and expectations. Patients-reported outcomes are a better tool to assess the patient outcomes.

Availability of data and materials

Not applicable.


Total Hip Arthroplasty

Revision Total Hip Arthroplasty

National Heart, Lung and Blood Institute

Western Ontario and McMaster Universities Arthritis Index

Patient reported outcome measure

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O.M. was involved in the literature search, analysis and evaluation of data and writing all sections of the paper; S.R.S. was involved in the literature search and analysis of the data. SRS contributed to the editing of the written sections; A.M. was involved in the literature search and the editing of written sections; S.K. was involved in the topic of the review and overview of the project. All authors read and approved the final manuscript.

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Mohammad, O., Shaarani, S., Mohammad, A. et al. Patients’ expectations surrounding revision total hip arthroplasty: a literature review. Arthroplasty 6 , 28 (2024). https://doi.org/10.1186/s42836-024-00250-6

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Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre

  • Hassane Alami 1 , 2 , 3 , 4 ,
  • Pascale Lehoux 1 , 2 ,
  • Chrysanthi Papoutsi 4 ,
  • Sara E. Shaw 4 ,
  • Richard Fleet 5 , 6 &
  • Jean-Paul Fortin 5 , 6  

BMC Health Services Research volume  24 , Article number:  701 ( 2024 ) Cite this article

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Artificial intelligence (AI) technologies are expected to “revolutionise” healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explore and understand the systemic challenges and implications of their integration in a leading Canadian academic hospital.

Semi-structured interviews were conducted with 29 stakeholders concerned by the integration of a large set of AI technologies within the organisation (e.g., managers, clinicians, researchers, patients, technology providers). Data were collected and analysed using the Non-Adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework.

Among enabling factors and conditions, our findings highlight: a supportive organisational culture and leadership leading to a coherent organisational innovation narrative; mutual trust and transparent communication between senior management and frontline teams; the presence of champions, translators, and boundary spanners for AI able to build bridges and trust; and the capacity to attract technical and clinical talents and expertise.

Constraints and barriers include: contrasting definitions of the value of AI technologies and ways to measure such value; lack of real-life and context-based evidence; varying patients’ digital and health literacy capacities; misalignments between organisational dynamics, clinical and administrative processes, infrastructures, and AI technologies; lack of funding mechanisms covering the implementation, adaptation, and expertise required; challenges arising from practice change, new expertise development, and professional identities; lack of official professional, reimbursement, and insurance guidelines; lack of pre- and post-market approval legal and governance frameworks; diversity of the business and financing models for AI technologies; and misalignments between investors’ priorities and the needs and expectations of healthcare organisations and systems.

Thanks to the multidimensional NASSS framework, this study provides original insights and a detailed learning base for analysing AI technologies in healthcare from a thorough socio-technical perspective. Our findings highlight the importance of considering the complexity characterising healthcare organisations and systems in current efforts to introduce AI technologies within clinical routines. This study adds to the existing literature and can inform decision-making towards a judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems.

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According to the Organisation for Economic Co-operation and Development (OECD), artificial intelligence (AI) refers to “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment” [ 1 ]. Unlike conventional software, many AI systems indeed have learning capabilities and self-correcting error mechanisms that allow them to improve the accuracy of their results based on the feedback they receive [ 1 , 2 ].

There are many application areas for AI in healthcare, for example: diagnosis, treatment, monitoring (e.g., chronic diseases), and patient compliance [ 3 ]. In certain experimental settings, AI technologies have been shown to be more effective than clinicians (e.g., diagnostic accuracy, more personalised diagnostics) [ 4 , 5 , 6 , 7 ]. Several have already been approved for clinical use in real-world care and services [ 8 ]. These technologies are seen as a lever for evidence-based clinical decision-making and practice and for value-based care and services [ 9 , 10 , 11 ]. Research indicates their potential to contribute to better monitoring, detection, and diagnosis of diseases, to the reduction of clinical risk, and to the discovery of new drugs and treatments [ 4 , 9 , 12 , 13 , 14 ]. The use of AI technologies could help to reduce diagnostic and therapeutic errors [ 2 ], contribute to the optimisation of clinicians’ work, and help reduce waiting times by reorganising clinical and administrative tasks, and supporting coordination [ 10 , 14 ]. Many scholars also argue that AI technologies could contribute to reducing healthcare costs by decreasing hospital (re)admissions, medical visits, and treatments [ 14 , 15 ].

A predominant and enthusiastic discourse in the academic literature and media reports is that AI technologies will revolutionise and radically change healthcare in the coming years [ 2 , 16 , 17 , 18 ]. There is an explosion of AI offerings in the market [ 19 ]. In 2018, the global AI market in healthcare was valued at around US$1.4 billion and is expected to grow to US$17.8 billion by 2025 [ 14 ]. In North America, the market for AI in healthcare had exceeded US$1.15 billion by 2020 [ 14 ]. In this context, healthcare organisations and systems are increasingly being solicited (or even pressured) to integrate these technologies, even when evidence of real clinical added value is lacking and many social and ethical as well as adoption, routinisation, and practical issues remain to be clarified [ 16 , 18 ]. According to Topol (2019), who reviewed healthcare workforce readiness for a digital future: “Despite all the promises of AI technology, there are formidable obstacles and pitfalls. The state of AI hype has far exceeded the state of AI science, especially when it pertains to validation and readiness for implementation in patient care” [ 4 ]. Liu et al. (2019) reported that few published studies on AI had results from real-world healthcare contexts [ 20 ]. These findings were corroborated during the COVID-19 pandemic [ 21 , 22 , 23 ]. Wynants et al. (2020) identified 232 AI models for prediction or diagnosis of COVID-19, none of which were appropriate for clinical use and only two showing potential for future clinical use [ 24 ]. Roberts et al. (2021) analysed 415 AI models for COVID-19 detection and concluded similarly [ 25 ].

This gap between the promise and reality of AI technologies in healthcare could be explained by the fact that efforts have historically focused on technology development, market penetration, and commercialisation. Limited work has been done to look specifically at the conditions and factors necessary for the integration of AI technologies into routine clinical care [ 14 , 17 ]. While technical problems (e.g., performance, unreliability) have been regularly put forward as a reason for the difficulties of integrating these technologies into healthcare organisations and systems [ 26 ], they explain only a small part of the problem. Broader socio-technical conditions and factors rather explain many of these difficulties [ 18 , 26 ].

The social scientific literature on health innovations has shown that the introduction of technologies into healthcare organisations and systems is a complex phenomenon [ 27 ]. This is particularly true for many AI technologies, which are sometimes described in the medical literature as disruptive innovation due to their evolving and autonomous nature [ 28 , 29 , 30 ]. Their implementation and use may require rethinking and/or redesigning existing governance frameworks and care models as well as new clinical, organisational, regulatory, and technological processes, business models, capabilities, and skills [ 18 ]. These changes involve, and impact on, a variety of stakeholders who may have divergent or even antagonistic expectations, goals, and visions towards technology [ 31 , 32 , 33 , 34 , 35 , 36 ].

To contribute to addressing current knowledge gaps, the goal of this study is to explore and understand the challenges of integrating AI technologies within a large academic hospital in Canada (referred to as “the City hospital”). We aim to answer two questions:

How do multiple interacting influences facilitate and constrain the integration of AI technologies within the City hospital?

What learning can we derive for policy and practice for better integration of AI technologies in healthcare organisations and systems?

The study is not limited to a specific AI technology or clinical area but encompasses all 87 AI technology-based initiatives developed and used to varying extent in this hospital. Where relevant, we specify the type of AI involved to contextualise the factors, conditions, or challenges described.

Theoretical framework

To make sense of the complexity underpinning the AI integration efforts in the City hospital, we used an adapted version of the Nonadoption, Abandonment, and challenges to Scale-up, Spread, and Sustainability (NASSS) framework developed by Greenhalgh et al. [ 27 ], which supports an exhaustive sociotechnical approach to health innovation. Following this adapted version, we present the seven dimensions of the framework in a different order from the original version in order to make sense of the narrative within the organisation studied, thereby covering: 1) the organisation; 2) the condition(s) or illness; 3) the technology or technologies; 4) the value proposition; 5) the adopter system(s) (e.g., staff, patient, caregivers); 6) embedding and adaptation over time; and 7) the wider system [ 27 ]. See Fig.  1 for a description of the seven dimensions.

figure 1

An adapted version of the NASSS framework (adapted from Greenhalgh et al. [ 27 ])

There were many reasons for adopting the NASSS framework over other frameworks. First, it stems from a hermeneutic systematic review, supported by empirical case studies of technology implementation in healthcare [ 27 , 37 ], and its key strength lies in its synthesis of 28 technology implementation frameworks, that is informed by several theoretical perspectives [ 27 , 37 ]. Second, it was developed to fill an important gap “on technology implementation—specifically, to address not just adoption but also nonadoption and abandonment of technologies and the challenges associated with moving from a local demonstration project to one that is fully mainstreamed and part of business as usual locally (scale-up), transferable to new settings (spread), and maintained long term through adaptation to context over time (sustainability)” [ 27 , 37 ]. Third, in contrast to the deterministic logic of many existing frameworks, the NASSS framework is characterised by its dynamic aspect, particularly in terms of interaction and adaptation over time. Indeed, a large part of the literature in the field has a tendency to “assume that the issues to be addressed [are] simple or complicated (hence knowable, predictable, and controllable) rather than complex (that is, inherently not knowable or predictable but dynamic and emergent)” [ 27 , 37 ]. Therefore, major failures of large and ambitious technology projects may be underestimated and their complexity for healthcare organisations and systems tossed away [ 27 , 37 ]. Fourth, whereas decision-makers and technology promoters as well as a part of the specialised literature often adopt a linear, predictable, and rational vision of change [ 38 ], the sociotechnical stance of the NASSS framework highlights the importance of examining how technology and the changes associated with it are perceived, interpreted, negotiated, and enacted by individuals and groups [ 33 , 39 , 40 ]. The same applies to AI technologies that may require transformation and/or redesign of services, a profound reconfiguration of clinical and organisational practices, and challenges to professional identities and practices [ 17 , 33 , 40 ]. Certain types of AI technologies also evolve autonomously over time – a particular characteristic that can be explicitly conceptualised through the NASSS framework [ 27 , 41 ]. Overall, the NASSS framework was developed to be used reflectively, to stimulate conversation and generate ideas, which is one of our study’s aspirations.

We conducted a qualitative study within the City hospital (Quebec, Canada) [ 42 ]. The latter had initiated several projects to integrate AI technologies in its care and service offer. Decision-makers and managers expressed a need for (independent) insights into the micro-, meso-, and macro-level systemic implications of the integration of these technologies within the organisation [ 43 ].

Presentation of the organisation

The City hospital is one of the largest academic hospitals in Canada. It offers specialised and sub-specialised services to adult patients. It treats around 500,000 patients annually. It employs over 14,000 people. It also houses one of the largest medical research centres in the country, with an academic mission to produce and disseminate knowledge and research results. It also presents itself as an organisation with state-of-the-art facilities and equipment. It has been ranked by the U.S-based magazine Newsweek as one of the world’s top 250 Best Smart Hospitals for 2021. It hosts one of the largest annual digital innovation events in Canada.

At the time of the study, the City hospital had over 115 digital health projects (Table  1 ), with 87 of these involving AI. Around 95% (≈82/87) of the AI technologies were in the development/experimentation or early implementation phase. Only four were integrated into services. Approximately 72% (≈62/87) of the AI technologies identified within the organisation were for the diagnosis, treatment and/or monitoring of complex chronic or acute conditions: cancers, neurological (e.g., epilepsy), and ocular conditions.


We identified a purposive sample of key stakeholders, with the aim of capturing diverse perspectives and experiences [ 44 ]. We conducted internet searches and consulted reports and documents produced by the City hospital to identify potential participants, who were drawn from distinct roles and varied levels of involvement in the development, implementation, and use of AI technologies.

A personalised invitation email was sent to each potential participant explaining the project and why they were invited to participate. Two reminders were sent in case of non-response. Respondents were invited to indicate other participants (i.e., snowballing) [ 45 ]. This resulted in a sample of senior and middle managers/decision-makers, clinicians (e.g., physicians, nurses), clinicians/informaticians/researchers, technology assessment specialists, procurement specialists, lawyers, patients, and technology providers. Patients were identified through patient partners (volunteers) collaborating with the City hospital. Of the 42 invitations sent, 29 people agreed to participate. Table 2 shows participant profiles, many of whom cumulated multiple professional and/or experiential backgrounds.

Data collection

Between March and July 2021, the first author (HA) conducted 29 interviews in French (27) and English (2), using the Zoom™ videoconferencing platform (interviews lasted 30–90 min). Prior to the interview, a consent form summarising the objectives of the project was shared. Interviews were audio recorded with the permission of the participant and transcribed verbatim by HA. The questions were formulated according to the dimensions of the NASSS framework and informed by documents shared by the City hospital (e.g., list of projects and technologies). HA first tested the qualitative interview guide with two respondents prior to the start of the study. No major revision of the initial version of the guide was required. He took notes during and after the interviews and subsequently used them to contextualise the analyses. The interview guide slightly evolved depending on the participants’ responses as new information emerged. By adapting the interview guide, we were able to capture both expected and unanticipated tensions and practical challenges, grounding the discussion in participant experiences to avoid vague or abstract responses. Given that the same person (HA) co-developed the guide and conducted the interviews in French and English, this minimised the risk of variability that could arise from having different people collecting data in different languages. Interview data and document analysis, alongside our knowledge of the context (team members have been involved in various research and evaluation projects on digital technologies and innovations in Quebec and Canadian healthcare organisations and systems for several years) guided triangulation of data sources [ 46 ].

Data analysis

Data were coded and analysed with Dedoose™ software. HA performed the first round of analysis and developed a preliminary coding scheme. In the second round, the scheme was refined, challenged, and discussed iteratively by the second author (PL) [ 43 ]. We conducted a deductive-inductive thematic analysis. The deductive analysis was guided by the NASSS framework (Fig.  1 ) [ 27 ]. Drawing on its seven dimensions, we created codes to capture the micro, meso and macro-level challenges and implications associated with the integration of AI technologies in the City hospital. The inductive analysis aimed to capture emerging themes not covered by the framework [ 44 , 47 ]. After agreeing on the different themes identified, we concluded that none required the addition of new dimensions, as all identified themes fitted within the NASSS framework. Data saturation was reached for the themes and observations reported in the findings. Given the importance of context in the NASSS framework, we sought to understand and clarify the contextual elements where respondents had different views or judgements. We decided not to disclose certain details either because the participants requested it or to ensure confidentiality. However, this information was useful to contextualise and better understand other findings and events. Our findings are illustrated with participant quotes organised around key themes of the NASSS framework (translated from French to English when needed) (Table 5 in Appendix ). The letter P used in quotes refers to “participant”, followed by numbers designating the order in which interviews were transcribed.

Findings are reported as a narrative account [ 48 ]. This is critical in allowing us to capture the complexity of the subject, the explanatory and interpretative dimensions, and the varied stories and perspectives gained from participants in making sense of the issues around the adoption of AI technologies.

We present the findings according to the seven dimensions of the adapted version of the NASSS framework (Fig.  1 ). To ensure fluidity in the presentation of the findings, the participant roles are used as a general category to help the reader identify certain tensions between the viewpoints and perspectives expressed. In this sense, there is no pretension of generalisation given the small number of respondents in each category. The analyses are intended primarily to provide high-level dynamics related to each dimension of the NASSS framework and not those specific to the types of AI discussed.

The organisation

For the technology providers we interviewed, the City hospital has several internationally renowned clinicians, both in the clinical field and in the use of AI. Several managers and clinicians also reported that senior management is known to value and encourage technological innovation, which has led to the creation of a “data lake” that allows the integration of data from different clinical systems (e.g., clinical records, laboratories, vital signs, imaging), which is a major asset for the development and/or validation of certain AI technologies. According to technology providers, access to the specialised expertise of clinicians who know the data is as important as access to the data itself. These clinicians play an important role as a trusted guarantor (or legitimising authority) for AI with other clinicians, decision-makers/managers, patients, and citizens. In the words of one clinician-manager, the relationship and communication between these clinicians and the City hospital’s senior management is generally perceived as positive. He pointed out that this synergy helps to mitigate some of the issues and conflicting visions and expectations of AI.

According to a technology provider, because of the characteristics of Quebec’s single-payer and universal health system, the City hospital allows for holistic management of patients suffering from several pathologies or requiring different care and treatments. He added that this unique advantage enables the development of AI technologies with a broad spectrum of action (i.e., compared to those developed in contexts where care is fragmented between different hospitals and/or clinics). Despite this asset, there is a broad agreement among the interviewees that the City hospital is characterised by significant complexity that has the potential to impact its ability to realise the value promise of AI technologies.

Use of AI technologies in the City hospital necessarily involves different departments, committees, and stakeholders (e.g., Information technology -IT- department, procurement department, project office, professional services department). According to several managers, clinicians, and industry providers, the roles and mandates for these different groups and stakeholders are not always clear. Coordination and communication between teams and/or departments are sometimes difficult or non-existent. According to a manager, this results in confusion and tension about expectations, visions, and responsibilities. He pointed out that difficulties experienced by some AI projects were due to a department or committee not being engaged at the right time (e.g., as a result of legal and/or procurement framework, Cloud storage space, professional services department). For managers and clinicians, a horizontal body should have been established to coordinate and ensure coherence and communication between the different initiatives and stakeholders, with the aim enabling mutual effort, coordination, and accountability. For another manager, by ensuring an initial screening of technologies proposed by industry, such a body would avoid the influx of useless technologies to clinical teams and associated time and resource costs.

Both industry and organisation respondents agree that the City hospital doesn’t always have the capacity to meet the initial and recurring costs and investments required for the successful integration of AI. To overcome this funding problem, at least partly, an interviewee told us that the organisation is obliged to open its doors to industry for co-development, or as a testing ground, of AI technologies. This sub-contracting allows the City hospital to benefit from a free user licence for a fixed period or for life. However, it was reported that this partnership contracts model (e.g., co-development or serving as a testing ground for the industry) is likely to lock the organisation into a technology-centric logic, with no real margin of manoeuvre to choose technologies that really meet its needs. There are multiple projects under this partnership model within the organisation. Several technologies could simply end up being only partially developed because the technology provider has withdrawn, or the technology was abandoned. Within such a context, several managers and clinicians recognise that it is difficult to create a real organising vision that supports and enables AI within the City hospital.

According to managers and clinicians, these partnerships with industry imply an over-solicitation of the clinical teams as, in addition to their clinical and administrative work, they must dedicate time to testing and experimenting with the various technologies presented by the technology providers. In this regard, several organisation and industry respondents pointed out that clinicians in the City hospital are not valued or remunerated for their contribution to the development and/or experimentation of technologies. It is not uncommon for some clinicians to feel that industry benefits from their clinical expertise without any real return on investment for them. Technology providers interviewed refuted this point. For them, the difficulties in integrating their technologies into the organisation are essentially due to the opposition of some influential clinician-researchers who are themselves developing in-house similar technologies. In the words of one industry respondent, this is a conflict of interest and unfair competition. Nonetheless, technology providers support the importance of creating incentives to encourage clinicians to collaborate with industry. On their part, several clinicians and managers consider that the organisation should value in-house initiatives more highly because they emerge from the needs and expectations of the field. However, there is agreement that the organisation does not have the financial and human resources to support these initiatives. In addition, according to one manager, as a public entity, the City hospital does not have a mandate to develop and/or commercialise technologies. At some point, a company would have to be involved to ensure commercialisation.

Managers, clinicians, and industry acknowledge that the nature and extent of the changes associated with the integration of AI within the organisation are still largely unknown. For example, it is very difficult to assess financial implications over time. Two managers reported that the City hospital paid an additional CA$20,000 to CA$30,000/year for the storage and management of its data. This cost was not initially budgeted but subsequently required by the Cloud service provider who had estimated the size of the data. According to the same respondents, such “little surprises” could lead to some technologies being abandoned along the way, even if they are clinically relevant, either because the organisation cannot afford the costs or the Quebec’s Ministry of Health and Social Services (known as MSSS) refuses to cover them.

Both industry and organisation respondents reported that many AI technologies require access, sometimes in quasi-real time and without human intervention, to large amounts of data of various types. Unanimously, interviewees acknowledge that the organisation’s rules and procedures do not currently allow this (or very barely). Technology providers are calling for easier access to data. However, on the organisational side, several managers consider that such rules and procedures need to be further strengthened. Some of them emphasised the importance of having a Specialist digital lawyer to ensure that these issues are addressed when contracts are signed. They also add that there should also be a Chief data officer to ensure adequate and coherent governance between the various initiatives that involve clinical-administrative data.

The condition(s) or illnesses

Most of the AI technologies identified (72% ≈62/87) within the City hospital are directed at the diagnosis, treatment and/or monitoring of complex chronic or acute conditions (e.g., cancers, neurological, ocular conditions) (Table  1 ). These conditions generally require ongoing or periodic support and monitoring over long periods of time with significant implications for patients and their families, and for the financial sustainability of the healthcare system. They also require complex, individualised, and evolving service models to continue to meet the needs of patients and their families. Several interviewees underscore that the use of AI could reduce waiting times and the costs of managing these pathologies. For a technology provider, these technologies are also expected to help identify new patterns and digital biomarkers that would facilitate the diagnosis and treatment of poorly characterised and/or unpredictable diseases.

For several respondents, this focus on specific diseases is partly due to the nature of the technologies available on the market. These technologies are addressing pathologies mainly through image analysis and/or signal quantification. This makes them more easily measurable, therefore more attractive to technology developers seeking rapid market access.

The technology or technologies

There are diverging perceptions between clinicians, managers, technology providers, and patients on what makes AI attractive, reliable, and mature enough for clinical use and/or interoperable with existing systems.

According to a manager, some of the technologies proposed to the City hospital under the label “AI” are, in fact, expert systems with advanced calculation software. Branding the products in this way is a strategy used by some companies to attract investment and/or obtain contracts. While an AI designation increases the market value of the technology, it does not necessarily increase the clinical value. For another manager, this labelling of AI products is also partly due to the organisation’s pressure on technology providers to integrate AI. This is a significant step for technology companies as, compared to traditional software, AI technologies require specific regulatory requirements, technical infrastructure, expertise, and resources.

Several participants raised emerging security issues specific to AI. This is not only about the security of the technology and infrastructure, but also about the security of the algorithm itself. The latter could be hacked and modified, which can have a direct clinical impact on the patient. According to a manager, being able to recombine data from different sources, AI technologies could easily re-identify individuals. On their side, technology providers pointed out that these security issues are mainly due to the City hospital’s obsolete systems and technology infrastructure. They underscore how their technologies conform to the best security and quality standards and norms on the market, and that unlike public organisations they have the best IT expertise. An industry respondent added that, since the customer is the guarantor of their added value on the market, they also regard data security as central to their reputation and brand image. If an incident occurs, the company could simply lose customers or even go bankrupt.

Some AI technologies need to run on an integrated technological platform or operating system (e.g., electronic health record -EHR-) that allows for optimal data flow and exchange between the different technological systems and organisational departments as well as across healthcare system organisations. Respondents agree that the City hospital’s departments generally have outdated and disparate systems and infrastructures that are frequently not interoperable. However, several managers, clinicians, and technology providers argue that this is a common problem for the whole healthcare system, as an integrated and interoperable EHR does not exist. In this regard, for a population of over 8 million people in Quebec, there are over 30 million patient identification cards. A patient may have several cards with a fragmented EHR in several organisations. Similarly, one interviewee stressed that the equipment used (e.g., scanner, magnetic resonance imaging -MRI) in the City hospital does not always meet the requirements for AI. In some situations, it is difficult to know where the data is, or how it is processed and collected by certain technologies or equipment. Problems with internet connection and data transmission via Wi-Fi are also reported.

There is a consensus that AI technologies need high-quality data. Both industry and organisation respondents highlighted that a significant amount of clinical-administrative data (e.g., handwritten clinical notes) and patient records are still scanned in portable document format (PDF), which is not usable for planned AI. For technology providers, the meaningful use of data, which raises the question of the purpose of the data collection, is missing within the organisation and should be given more consideration.

For its AI programme, the City hospital works with many specialised start-ups and small- and medium-sized enterprises (SU/SMEs). One such technology provider stresses that the survival of their company depends on their ability to seek liquidity in the financial market (e.g., venture capital). This means that they are necessarily accountable to their shareholders who may be looking for the fastest and most profitable exit events possible (i.e., when an investor sells his/her shares in a company to collect cash profits). This approach brings challenges for the City hospital in terms of working relationships, technology development, and continuity of care. For instance, SU/SMEs can be bought by multinationals or simply disappear (e.g., bankruptcy), or a company may stop a technology or cease to update it. According to a manager, the City hospital does not necessarily have the capacity to maintain these technologies on an ad hoc basis or replace them with others. Another interviewee added that sometimes the organisation has no guarantee of recovering data hosted or operated by these technology providers or their subcontractors (e.g., Cloud services).

The value proposition

Stakeholders interviewed have divergent definitions of what constitutes the perceived, anticipated and/or actual value of a technology and the parameters to be considered for measuring it (e.g., safety, efficacy, and effectiveness criteria). About 95% were still in development/experimentation or implementation.

Several technology providers mainly express the value of their technology in terms of its potential to improve healthcare and its efficiency. They pointed to significant consumption of resources by the healthcare system while at the same time being unable to meet the healthcare needs of the population. For these interviewees, AI can solve the problem whilst modernising the healthcare system. In this regard, for a supplier, to realise such value, the City hospital, and the healthcare system in general, must be willing to take some risks. He stressed that if the latter wait for AI to be perfect and risk-free before using it, the technology will never be integrated, and its value promise never delivered to the population.

A manager reported that many AI technologies in the City hospital were at a value promise stage (i.e., with anticipated, rather than actual value stage). Other interviewees consider that this value promise remains relatively speculative, based on vague projections and estimates. In this regard, from the organisation’s perspective, the perceived value of AI technologies is mainly about improved clinical quality and safety, and performance. The expectation to achieve this value is to have tailor-made AI technologies adapted to the setting, clinical contexts, and ways of working. However, focusing on tailored AI solutions can sometimes be a major constraint for technology providers. According to several interviewees, suppliers prefer to commercialise generic technologies that can be easily marketed elsewhere with minimum modification (plug-and-play). Several managers and clinicians added that the costs involved in implementing and adapting the technology to the local context are regularly underestimated by these suppliers. The latter often lack an understanding of the complexity of clinical practices. For example, one company stopped working with the City hospital because it considered that its clinical needs are too specific for the AI technology to be cost-effective.

Because of its status as a leading academic hospital, the City hospital is highly sought after by the AI industry. Several interviewees recognise that the organisation is used to showcase and legitimise the technology’s value proposition, hence its market value and potential for widespread commercialisation. A technology provider also reported that the organisation serves as a gateway to the healthcare systems of Quebec and other Canadian provinces. At the same time, according to organisation respondents, the City hospital benefits from media coverage, which gives it a competitive advantage in attracting talent and expertise. However, divergence over the actual added value of certain technologies may constitute a source of tension between senior management and clinical teams. Some AI technologies are likely to exacerbate workload and staff burnout (e.g., technologies intended for the optimisation of clinical-administrative processes). For a manager, since AI technologies are still considered over and above other priorities, their impact on the quality of work and clinicians’ satisfaction is not really taken into consideration in the organisation’s assessment of their value (e.g., flexibility, alignment with clinical-administrative workflows). He added that the City hospital has difficulty in moving the value of these innovations from the Triple Aim to the Quadruple Aim: “improving the patient experience, the population health and the quality of work and satisfaction of healthcare providers, and reducing costs” [ 49 ].

The organisation’s clinical-administrative data, which is used to develop and/or operate some AI technologies, may contain biases and may not be representative of the general population. For several interviewees, AI technologies may also not respond to the contextual realities and needs of some populations (e.g., indigenous, rural, or minority people). Patients and organisation respondents also pointed out that these populations are rarely involved in the design, development, and implementation of AI technologies within the City hospital. Several interviewees recognise that assessing the added value of AI technologies by population segment is essential, but very difficult to achieve.

The adopter system(s)

Interviewees overwhelmingly agree that certain AI technologies could have a direct impact on the patient-clinician relationship. Some progressive diseases require human care and support over time. For AI technologies designed to monitor chronic diseases, some patients fear being lost from sight by their healthcare providers. According to several patients, it is important to ensure that they always have the possibility of in-person meeting with their clinician. As a patient pointed out, technology could never understand their subjective experience with the disease better than the clinician. For this and another patient, listening and empathy are sometimes more important in a care pathway than medication and technology. They mentioned that the therapeutic relationship goes beyond the simple dimension of the disease.

According to a patient, some patients registered with the City hospital can have up to 5 technology applications, sometimes non-interoperable. Some of these technologies do not operate on older Apple- or Android-supported smartphones, making it hard for several patients to use them unless they upgrade their hardware. Technologies may also require access to patient-generated data at home. Patients, clinicians, and managers stressed that patients may not have the technology and equipment and/or a good internet connection, but also the social and cultural capital (e.g., literacy, family network) to fully benefit from the potential of these technologies. They recognise that these technologies could lead to additional costs and expenses for these patients. Even when they have the technology, they may need technical support at any time of the day (24/7) as the disease “has no working days”, as a patient notes. This support is not automatically provided by the organisation and not all patients have a family/friend network that can be mobilised when needed. Paradoxically, technology could exacerbate the disease burden for these patients.

Several respondents reported that the adoption and use of certain AI technologies typically requires a reorganisation, or even a redesign, of clinical practices, of the organisation of services, and of the modes of governance and control within the City hospital. According to clinicians and managers, these changes could be associated with a feeling of loss of professional autonomy, identities, values, and skills. In the words of a manager, AI technologies could cause an erosion of information asymmetry (in favour of the organisation and the MSSS) and challenge clinicians’ autonomy of practice. The erosion and reduction of the scope of expertise due to the replacement of part of the clinical activity by AI was also pointed. However, several respondents relativised these fears, stressing that it is rather the clinicians trained in AI (e.g., clinician-informatician, clinician-data scientist) who will replace the others. This new expertise will have to be institutionalised and valued. This could imply a revision of the boundaries of professional jurisdictions (e.g., reserved acts) and of certain negotiated orders and privileges, and therefore of powers (e.g., nurse vs. general practitioner; general practitioner vs. specialist physician). Managers and technology providers pointed out that a technology that provides real added value for patients will never be integrated into practice if clinicians perceive it as a threat to them.

It was reported that the effort to integrate AI within the City hospital is occurring in a context where clinicians are under great pressure with high workloads. Some emphasised that they have no time to waste on these technologies, particularly those imposed on them by senior management and/or industry. They also expressed a feeling of innovation fatigue. Managers and clinicians acknowledge that this lack of time, but also of engagement, has a negative impact on the success of technology training and promotion initiatives within the organisation, and therefore its subsequent adoption and use. In addition, clinicians involved in technology integration efforts are mainly volunteers (e.g., champions, super-users). As the contribution to innovation is not considered a clinical activity, it is not remunerated nor recognised in their performance indicators. According to several clinicians and managers, this point is a significant barrier to clinicians’ engagement, especially to embrace the necessary changes and adaptations, and to construct meaning and develop new identities with regards to AI.

There is agreement that the need for continuous monitoring and follow-up of some AI technologies in everyday clinical practice made the role of IT teams more critical to clinical practice. According to a manager, this is a major change as clinical and IT teams have historically evolved in silos. In this regard, it is difficult to align cultures and languages within the City hospital in the midst of developing AI technologies and services. For some clinicians, the increasing adoption of AI in their practice may make them dependent on IT teams (potentially conflicting with their autonomy of practice). To address this issue, an interviewee emphasised the importance of the presence of translators or boundary spanners with a hybrid clinical-IT profile to bridge and build a healthy collaborative space between clinical and IT teams. These translators could also act as a bridge between clinical teams and technology providers. The same respondent reported that such a role is already played by members of the City hospital’s Innovation Pole team and several clinicians.

Several managers and clinicians, acknowledge that the blind confidence and lack of critical distance could affect the use of certain AI technologies in clinical decision-making. In this regard, they see the problem of transparency and explainability of AI decisions (black box). According to an interviewee, the problems of data quality and bias are serious enough to be doubly vigilant on this point. A technology provider recognised the importance of clinicians being able to understand how the decision is made by the AI (e.g., parameters retained or excluded) and whether such a decision is right or wrong. To do so, clinicians may need technical support from AI experts, which the City hospital does not necessarily have. According to several respondents, it is difficult for public organisations to recruit AI experts, as the latter are more attracted by the private sector where working conditions and remuneration are very advantageous.

Embedding and adaptation over time

The City hospital’s IT systems are theoretically well secured for AI or associated technologies needed for its functioning. Indeed, any new technology for clinical-administrative use should meet strict criteria for safety and effectiveness. They should be licensed and/or authorised by the IT department or regulatory agencies. However, several managers and clinicians recognise that, once implemented, numerous technologies are not necessarily monitored and controlled over time. The result is a complex, fragmented, and non-interoperable technology environment that is difficult to manage and update, but also vulnerable to cyber-attacks. Some AI technologies are likely to dysfunction and/or operate and evolve awkwardly in such an environment, which could pose patient safety issues.

According to industry, clinicians, and managers, the lifecycle of AI technologies (i.e., the period during which they can function adequately without major upgrades and avoid replacement by new and better technologies) is often very short, and potentially only a few months. The City hospital should be able to upgrade its technology systems and equipment continuously. The costs can be significant. In this regard, equipment and devices (e.g., scanner, MRI) required for the functioning of certain AIs may be considered obsolete after only five years of use. The data they generate is no longer usable, which has a direct impact on their clinical reliability (e.g., ability to detect cancer). To remedy this problem, some technology providers offer to lease equipment. According to the latter, City hospital could then benefit from the latest equipment, with embedded AI, with no obligation to purchase. A technology provider explained that such a model involves the organisation to engage in service contracts over varying periods of time with the supplier. Such contracts usually include the implementation, maintenance, and upgrading of the equipment and associated technologies. The same respondent emphasised that this proximity model would also allow for a feedback process, necessary to adapt to the evolving needs and expectations of clinical teams. However, for several managers, this model raises concerns about the risk of locking the City hospital into a dependency relationship with a single supplier. They reported that this “chaining” could, among other things, increase the supplier’s control of the organisation’s data. To illustrate this point, an interviewee indicated that a technology provider has already “forced” the City hospital to pay for access to its own data (hosted/stored on the supplier’s servers). The same person reported that suppliers want to benefit from an annuity/rent, i.e., a continuous flow of money over time.

The wider system

A gap exists between those who call for a pragmatic approach (e.g., test-and-error, sandbox logic) and those who call for the consolidation of the precautionary principle (i.e., decision-makers adopt precautionary measures when scientific evidence about a human health or environmental hazard is uncertain and the stakes high) [ 50 ]. For several suppliers, the precautionary principle is a major obstacle to the integration of these technologies into the healthcare system. They stressed that regulation should be made more flexible, because zero risk does not exist in healthcare. An interviewee pointed out that the autonomous and evolving nature of some AI technologies will inevitably lead to failures and unforeseen incidents. Instead, lessons should be learned from these malfunctions and incidents to improve the technology. The Post-Market Approval/Post Market Surveillance model adopted in the USA was given as an example. This approach is rejected by other several managers and clinicians who consider that the lives and safety of patients cannot be subject to “hazardous test-and-error”.

Respondents are unanimous in stating that the authorisation, contracting, and financing process of AI technologies by the MSSS, which mainly focuses on the initial purchase price (capital equipment, which results in the procurement of technology with a fixed price, often the lowest, of which the organisation becomes the owner), is no longer adapted to the reality of AI technologies (Table  3 ). Firstly, many AIs operate with a “Software as a Service (SaaS)” business model. It is a monthly or yearly subscription for the organisation. According to technology providers, this model is justified by the fact that these technologies require continuous monitoring, control, and maintenance over time. Some respondents also called for the adoption of the “Value-Based Procurement (VBP)” business model. In this case, the suppliers are paid according to the value generated by their technology (e.g., 10% of the savings made over a patient’s entire care and service cycle). As these technologies are not cheap, there is a risk that they could be excluded from current tendering processes. According to several managers, the tender model does not consider the costs required for the implementation and adaptation of the technology to the local context. Examples where additional costs were required at the time of implementation, not initially foreseen, are relatively common. However, interviewees recognise that VBP is still difficult to implement. Because of the evolving nature of certain AIs, their value could change over time. Currently, it is difficult to ensure their continuous evaluation and monitoring due to the fragmentation of services and the lack of an integrated EHR, as well as trained and qualified human resources (e.g., collection, organisation, structuring, visualisation, and analysis of AI technology usage data), among other things.

According to several managers, the difficulty of acquiring certain AI technologies through the tendering process is another reason why the City hospital prioritises partnership contracts (e.g., co-development or serving as a testing ground) over service contracts (e.g., procurement of technology and/or associated services) with suppliers. In the words of a manager, as long as the organisation does not incur expenses (e.g., having the technology at no cost for a given period or forever) from its operating budgets, it does not have to justify its actions to the MSSS. This strategy also allows the City hospital to accelerate the integration of these technologies into its care and service offer by avoiding the complex bureaucratic process of the MSSS. However, some interviewees reported that partnership contracts do not always allow for the sustainable use of the technology beyond the free-of-charge period. In some situations, the organisation would have to incur expenses after this period and sign a service contract. It would then have to go through the tendering process again. If the latter is won by a different supplier, the initial technology should then be withdrawn, which condemns the City hospital to a kind of eternal restart.

Several technology providers argue that the tendering model is a barrier to entry into healthcare for SU/SMEs, although they could offer AI technologies with real added value. Unlike large companies, SU/SMEs do not have sufficient financial and marketing capacity to offer low prices.

Several respondents, both in the City hospital and industry, pointed out that the Act on the protection of personal information is also seen as a major obstacle to AI in the healthcare system. Typically, when a patient is treated in a public healthcare organisation, his/her consent does not include the secondary use of his/her data for research or other purposes. Legally, AI technologies developed or tested with this data cannot be used and/or commercialised, at least theoretically. According to an organisation interviewee, overcoming this barrier would entail considering that once a patient is treated in a public healthcare organisation, he/she automatically consents to the secondary use of his/her data for service improvement and research purposes. Several patients interviewed agree with this approach. However, they insisted that patients should always be able to withdraw their consent if they so want (opt-out).

Also concerning data, several interviewees highlighted the central role and necessity of Cloud services (e.g., data storage, exchange, and management) for optimal and effective use of AI technologies. According to a manager, Cloud services providers are mainly multi/transnational companies. The latter have servers and relay points all over the world, which means that data could travel across national borders. This challenges regulatory sovereignty. The same interviewee reported that Quebec legislation requires that data be hosted on servers located on its territory. However, the City hospital does not always have the levers to verify and ensure that the providers really respect this requirement. Nor does it always have the possibility of knowing whether an incident (e.g., security breach, data leakage) has occurred if the company does not communicate the information to it. In the words of another manager, “[The City hospital] does not always have the capacity to [ensure the security and reliability of the technologies], so it is forced to trust [the suppliers]”. In the same vein, it does not always have the levers and means to ensure that the technology provider has destroyed and/or deleted the dataset when requested to do so. In addition, according to another interviewee, the definition of responsibilities in the event of a patient harm incident is a not fully resolved issue yet. The latter highlighted that compensation could involve large sums of money that neither the supplier nor the City hospital would want to pay. In this regard, by simply being identified as a potential liable party in the event of an incident, the organisation or company could see the amount of its insurance contract increase considerably because of the risks involved.

Many AI technologies used in clinical decision making are considered as “Software as a Medical Device (SaMD)”. There is still no clear framework for their assessment and approval in Quebec and Canada. In addition, professional federations and colleges, and medical insurance bodies have not yet taken clear positions on their use in clinical practice. According to several interviewees, the absence of solid clinical practice guidelines, protocols, remuneration models, and professional responsibility frameworks limits the possibility of clinicians using these technologies. As an illustration, a manager pointed to the complexity of identifying responsibilities in the event of an AI error (e.g., misdiagnosis or mistreatment). Since certain technologies can decide autonomously, part of the responsibility of the clinician is transferred to them. For the same interviewee, numerous questions have yet to be answered: to what extent does the technology replace the clinician (totally or partially) or not? With the “black box” problem, AI does not always allow for tracing and understanding the decision-making process. Even when it is possible, technology providers might refuse to give access to their algorithm for commercial confidentiality and market competitiveness reasons. It is then difficult to know the nature and/or origin of the fault. Moreover, there is also the question of whether AI should imply an obligation of results, instead of the obligation of means to which clinicians are presently committed. According to another manager, technology providers prefer to classify their technologies outside the SaMD category. In this way, the clinician remains solely responsible in the event of harm. Then, the supplier avoids paying damages that may be substantial. Indeed, compared to a clinician’s error, which is usually limited to a single patient, an AI technology’s error could affect many patients. However, providers explained this choice by the fact that technology approval processes, such as SaMD, are time-consuming and very expensive.

Other regulatory constraints are pointed out by several interviewees. AI technologies never arrive ready for clinical use (plug-and-play). There is often adaptation and alignment work to be done. Some changes and/or adaptations are made informally (e.g., bricolage, workarounds) by clinicians. According to a clinician and a manager, these modifications are sometimes crucial in their decisions to use the technology or not. However, from a regulatory perspective, once licensed and authorised, a technology should not generally be modified, at least theoretically. Currently, any changes require the approval of the City hospital’s IT teams or of a governmental regulatory agency. Although justified in terms of financial and safety risks, there is a consensus among interviewees that this process is rigid, time consuming, and inadequate for the reality of AI. In this regard, updates to AI technologies should be quasi-automatic and continuous, in the spirit of how the iPhone works, often without human intervention. In the words of a clinician, any delay or blockage could have a direct impact on the diagnosis or treatment of patients.

According to a manager, aspects related to the organisations’ performance criteria and, therefore of their funding by the government are not yet fully defined for AI. In Quebec, the activity-based funding model is being deployed to complement the dominant historical budget model. This new model generally considers the activity of physicians (e.g., diagnosis, treatment, surgery), paid essentially on a fee-for-service basis, in the calculation of the budget the organisation will receive from the MSSS. The activity of other healthcare professionals, mainly salaried by the organisation (e.g., nurses), is not considered the same way (or only slightly) in these calculations. Numerous AI technologies intended for (or assisting in) diagnosis or treatment could be supervised by healthcare professionals other than physicians. The impact of this development on the funding of healthcare organisations remains unknown. In the same vein, the respondent highlighted the problem of the fragmentation of funding between medical, medico-social, and social services in Quebec. For example, some AI technologies have a clinical added value and are therefore covered by the MSSS. However, the latter does not cover other aspects such as the improvement of the patient’s quality of life (e.g., Quality-adjusted life year -QALY-). As a result, the City hospital could be required to solicit different departments, ministries and/or agencies to capture the different value components of the same AI technology.

According to several interviewees, funding from the federal government would have a direct impact on the integration of AI technologies into the City hospital. They report that federal programmes make it possible to fund expensive infrastructure projects, from several hundred thousand to several million CA$. However, implementation and sustainability are mainly under the responsibility of the Quebec MSSS because health falls under provincial authority in Canada. There is sometimes a gap between federal funding and provincial priorities. According to a manager, the Quebec MSSS does not automatically fund the implementation and sustainability of federally funded technologies. As a result, several technologies could eventually be abandoned. For another interviewee, one of the important limitations is that federal funding is often very targeted and specific to particular technologies and/or clinical areas. It does not provide sufficient flexibility for organisations to use it according to local needs and contingencies.

Lastly, several respondents recognise that inter-organisational collaboration for sharing expertise and experience is essential for AI. However, the fragmentation, lack of communication and coordination across public healthcare organisations make it difficult to establish such a collaborative environment. For example, according to a clinician, to develop AI technologies with real added value, it would be necessary to have access to large amounts of patient data. She explained that the way to do this, while competing with other technologies from other countries, is to pool the databases of different healthcare organisations in Quebec and Canada. Such an inter-organisational network is essential in the evaluation and approval process of AI technologies, as they are to be tested on data from different healthcare organisations (e.g., urban and rural hospitals, primary care clinics). For the same respondent, such multicentre testing would ensure reliability and effectiveness in different clinical and technological settings across the country.

Summary of key lessons

Our study aimed to generate a better understanding of the conditions that facilitate or constrain the integration of AI technologies in a large healthcare organisation in Canada. By analysing a rich corpus of data using the NASSS framework, the study highlights seven lessons:

Firstly, an organisational culture and leadership that creates favourable conditions for AI is essential as well as the presence of clinical champions who act as ambassadors for AI. This is a lever to attract clinical and/or technical talent and expertise, but also companies in the field. The strategic alignment of the organisation’s clinical-administrative processes and infrastructures with AI technologies remains a major challenge. A lack of alignment could lead to partial integration of technologies or their abandonment, resulting in innovation fatigue among clinical and administrative teams. In a context where clinicians are over-solicited, they should be given the time needed to integrate the change, but also develop the professional expertise and identities that AI could require. It is also important that the technologies proposed to them are supported by evidence of improvements in patient care and services as well as in their work conditions and quality. The integration of AI within a hospital also involves a multitude of stakeholders whose activities and actions should be coherent and synergistic. Communication is fundamental to clarify roles, responsibilities, and mandates and requires a horizontal structure capable of coordinating actions and shaping a consistent organisational story about AI. The technologies proposed by the industry should be filtered so that those that really meet the needs on the ground are prioritised.

Secondly, financial and other incentives are needed to encourage clinicians to experiment and adapt these technologies to their practices. Investments in the development of AI technologies have so far focused on specific complex pathologies that present a great burden to patients and their families as well as to the healthcare system. To address these pathologies, AI mainly exploits image analysis and/or signal quantification, which makes it easier for suppliers to develop technologies and introduce them more quickly to the market. Yet, the sensitivity of safety and data protection issues implies that the hospital hires a lawyer specialising in digital technologies (to ensure that contracts are properly made) and a Chief data officer (for adequate and consistent data governance). Upgrading IT systems and infrastructure and recruiting new expertise hence require planning for both initial and recurring investments and expenditures.

Thirdly, the interoperability of AI technologies and the organisation’s systems and infrastructure are major obstacles to their routine use. Some technologies need quasi-real time access to data, which requires an integrated platform to ensure optimal data circulation between different IT systems and departments of the organisation, or even other organisations involved in the patient’s treatment. The qualification of some advanced software as AI could have financial and legal implications for the organisation. In addition to traditional clinical safety issues, the AI algorithm itself could be hacked and modified, resulting in harm to patients. By recombining data from various sources, individuals could be easily re-identified. These technologies could also require high-tech equipment with very short lifecycles, which the organisation may not have. Furthermore, many AI technologies are driven by SU/SMEs that could disappear from the market at any time. Hence, organisations should have the capacity to maintain the technology on an ad hoc basis or find an alternative and be able to recover and/or ensure the deletion of data by the initial supplier.

Fourth, the definition of the value of AI technologies is far from consensual as well as the expectations regarding what they can or should do. The ability to measure this value is of considerable complexity given the great contrast between the value proposition stated by suppliers, and sometimes by managers, and the actual value to clinicians and patients. The value of AI is not self-evident. Indeed, even if it has shown great performance in a laboratory context, this may not materialise in the real-world context of care and services. The value of some AI technologies also contrasts with the risks they raise given their evolutionary and autonomous nature. There are trade-offs between the precautionary principle, the need for some risk tolerance, and its clinical potential. Moreover, clinical practice may require very specific AI technologies, whereas suppliers tend to prioritise plug-and-play technologies with a potential for widespread commercialisation. The global value of AI could vary widely depending on the balance of the changes and transformations it requires and what it actually provides. This value may also change over time. Evaluating and monitoring AI’s value on an ongoing basis requires resources and expertise the organisation may lack, especially in view of the (re)production of bias across sub-groups of the population.

Fifth, contrary to the rhetoric about their potential to humanise care, some AI technologies raise concerns about the patient-clinician relationship and, therefore, about quality of care. The risk of mechanisation of care and the difficulty of physically accessing healthcare providers is palpable. Digital literacy, technical support, and change management for clinicians and patients using these technologies are essential. For clinicians, AI technologies may imply redesigning clinical practice and service organisation, but also new governance and control strategies within the organisation. Although improbable, there is a real concern that AI could partially or totally replace the activity of clinicians. Hyper-dependence on technology raises concerns about the erosion of clinicians’ expertise and the risk of blind trust in the decisions made by AI. As a result, clinicians may worry about being subordinated to the IT teams that would play a central role in the production of care. This new reality highlights the central role of translators or boundary spanners in building bridges and trust between clinical and IT teams, but also with industry. On a larger scale, the technology-driven approach to AI could cause a deterioration in clinicians’ work conditions and quality.

Sixth, the evolving and self-learning nature of some AI technologies makes time critical, distinguishing them from previous licensed technologies that do not generally require a new approval review. IT teams should approve and validate any changes or adaptations, and this becomes difficult with some AI technologies that evolve autonomously and update themselves. Any delay or blockage could threaten the diagnostic or treatment quality of patients. Continuous monitoring and control over time is required to avoid malfunctions and incidents, but also to make the necessary improvements. In this regard, the increasingly short lifecycle of software and hardware challenges the technical and financial capacity of the organisation to adapt and evolve its systems, equipment, and infrastructure at the right pace. Evolutionary AI technologies create the need for close and sustainable relationships between the organisation and the technology providers, a new relationship that: 1) requires solid frameworks to identify and resolve conflicts of interest as they arise over time; and 2) must avoid lock-in and dependence upon a single provider.

Seventh, many socio-political, economic, and regulatory factors are decisive in the integration of AI technologies, which are mainly offered under SaaS and/or VBP business models. These models are in opposition to the current tender model in Quebec that emphasises the cheapest technology (capital equipment). The legal framework of the current model constitutes a barrier to entry for SU/SMEs, some with high value-added technologies. Established bureaucratic acquisition processes are inadequate for the very short lifecycle of AI technologies. Consent requirements for the use of patient data are misaligned with this new reality and are prompting consideration of an opt-out consent model. AI technologies increasing rely on Cloud services mainly offered by multinational companies with servers and relay points all over the world. Data governance is even more important as healthcare organisations and systems have limited resources and tools to ensure that data management and storage comply with applicable laws. Identifying liability in the event of harm could therefore be very complex. AI technologies classified as SaMD, on the other hand, have specific requirements for quality, efficiency, and clinical reliability. To date, the lack of reference technologies makes it difficult for regulatory agencies to assess and approve them. Established mechanisms and processes are not adapted to the complexity and very short lifecycle of AI. Ongoing evaluation and monitoring mechanisms in the real-world context seem necessary, but the high degree of uncertainty associated with them requires a balance between the precautionary principle and a laissez-faire integration in clinical routine. Beyond the lack of clear frameworks and directives from the MSSS and other regulatory bodies regarding the use of these technologies by clinicians, inter-organisational networks facilitating the sharing of expertise and experience are essential. The current context is characterised by fragmentation, and poor communication and coordination between organisations and government agencies, which hinders an integrated and coherent vision of AI at the healthcare system: provincial- and federal-level of governance.

Contribution to the existing literature

The results of this study contribute to knowledge in several ways. They shed a new and different light on the trend of recent years where the literature has mainly focused on the technical and promissory dimensions of AI. Our findings are consistent with those of Pumplun et al. (2021) and Petersson et al. (2022) who analysed implementation issues raised by AI technologies in healthcare in Germany and Sweden, respectively [ 3 , 51 ]. Studies on telehealth and EHR also reported results that corroborate ours on AI [ 26 , 31 , 32 , 34 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ]. In this regard, several authors pointed out the major contrast between the techno-optimistic discourse on the performance and efficiency of technology and the reality of services that are difficult to transform [ 56 , 57 , 58 ]. These experiences have shown that the difficulties encountered in the deployment of digital technologies are mainly due to the historical lack of attention paid to the sociotechnical factors and conditions necessary for their integration into healthcare organisations and systems. Hence, our study adds to the growing literature that considers technology in a complex sociotechnical transformation perspective that requires not only technological but also human, clinical, professional, organisational, socio-political, economic, regulatory, legal, and cultural changes [ 27 , 40 , 41 , 56 , 59 , 60 , 61 ]. Very limited attention has been paid to this perspective in examining AI to date, whereas our study clarifies its contribution and indicates some avenues for future research (Table  4 ) [ 3 , 18 , 26 , 51 ].

From a theoretical standpoint, our study provides an original contribution to the literature on health innovations. It is one of the first to demonstrate that the NASSS framework is relevant for the analysis of the integration of AI technologies in healthcare organisations and systems [ 51 ]. The study contributes to the knowledge on the importance of a sociotechnical perspective to understand the complexity and unpredictability of transformations related to disruptive innovations such as AI [ 27 , 51 , 62 ].

Implication for practice and policy

Our study provides new insights for decision-making and practice on the conditions required but also on the pitfalls to be avoided to ensure successful integration of AI technologies into healthcare organisations and systems. It shows that the pitfalls of the technocentric vision of digital health of the last thirty years in Quebec (and elsewhere too) could easily be repeated with AI technologies, but this time with more profound repercussions [ 31 , 32 , 33 , 35 , 36 , 63 ]. As Matheny et al. (2020) highlighted: “Disconnects between reality and expectations have led to prior precipitous declines in use of the technology, termed AI winters, and another such event is possible, especially in health care” [ 64 ]. In this regard, the various stakeholders must be aware that AI is more an object of transformation at all levels of healthcare system governance, than a simple “intrinsically good/bad” tool. Its successful integration depends on several structural conditions, namely, appropriate: regulatory and governance frameworks; funding, business, and remuneration models; definition of the value proposition; management of conflicts of interest; governance of data; cybersecurity strategies; training and expertise, models of care and service delivery; inter-professional collaboration; and up-to-date infrastructure and equipment.

Specifically, AI highlights the importance of rethinking the collaboration between healthcare organisations and systems, on the one hand, and technology providers, on the other hand. Indeed, their interests sometimes represent competing financial and political objectives between which a difficult balance must be established [ 65 ]. Given their disruptive nature at all levels of the healthcare system, IA technologies could generate tensions and require trade-offs between perceptions, expectations, interests, and agendas that may be divergent or even antagonistic (ex. industry and venture capital, decision-makers, managers, clinicians, patients). These dynamics and power relations influence the trajectory of AI technologies in healthcare, either positively or negatively [ 59 , 66 ]. Thus, if healthcare organisations and systems are not sufficiently equipped and prepared, “the AI landscape risks being shaped by early established companies and decisions made with insufficient evaluations in place due to pressures to embrace technology” [ 67 ].

In addition, one of the fundamental issues remains the lack of digital literacy and culture, and AI technology skills among healthcare professionals [ 68 ]. Currently, initial and continuing training programmes do not sufficiently integrate these technologies into the expertise that trainees (e.g., physicians, nurses) need to achieve to be authorised to practice. As reported in our study, without appropriate training, clinicians are unlikely to adopt in an appropriate way these technologies. Indeed, training is required to adapt provider protocols, administrative workflows, pathways, and business processes [ 67 ]. According to Mistry (2019), for such change to take place, healthcare professionals will need:1) to have access to education content enabling them to learn new skills as AI users and work differently; 2) to be able to train AI systems themselves for setting them up to perform specified tasks, which implies knowing what data to select and its quality; 3) to develop abilities to interpret AI outputs, including a solid understanding of its limitations and bounds of function; and 4) to know “how the system learns and what constitutes appropriate use, so that ethical norms are upheld and any introduction of biases is avoided” [ 67 ].

Strengths and limitations

This study offers one of the first holistic and multilevel analyses of the complexity of the changes and transformations associated with the integration of AI technologies into clinical routine, beyond technical issues. It is also part of the few studies that go beyond looking at one single AI technology and delves into the organisational and systemic complexity of integrating multiple AI technologies concurrently.

However, the study has limitations. By its qualitative nature, it has a high level of internal validity, but the transferability (or generalisability) of its findings is limited to similar healthcare organisations and systems. In other contexts, it can increase the awareness of different stakeholders regarding the importance of taking better account of the sociotechnical dimension of AI. Healthcare organisations and systems can vary considerably, hence the importance of contextualising the results.

The number of interviewees ( n  = 29) is relatively low in view of the large number of AI technologies covered in this study. Although we made great efforts to include a wide range of stakeholders, several people were unable to participate due to the COVID-19 context. This is the case for women heading technology companies, whereas decision-makers, managers, and clinicians were unable to participate because of their direct involvement in the management of the pandemic. However, the people who participated, through their expertise and experience, provided us with rich data, necessary for a detailed understanding of the challenges of integrating AI in healthcare organisations and systems. The application of a rigorous research approach, guided by best methodological practices and an exhaustive theoretical framework, has reinforced the reliability of our results.


AI in healthcare is still in its infancy. There are huge expectations that it will provide answers to major contemporary challenges in healthcare organisations and systems. This is reflected in the funding it receives from governments, but also in the interest of the financial and venture capital sector. The COVID-19 pandemic was a test case for AI, and it did not fully deliver. However, the pandemic has served as an accelerator for its experimentation, for example, through the relaxation of regulatory requirements and less resistance from some stakeholders. AI represents as much a logistical, psychological, cultural, and philosophical change, particularly in terms of what it could and should do in healthcare organisations and systems. It is a “new era” that requires a real critical examination to learn from the many past experiences with the digitalisation of healthcare organisations and systems. With AI, the nature, scale and complexity of the changes and transformations are at such a level and intensity that the implications could be profound for society. At present, little is known about how such an announced revolution may take shape and under what conditions. This study provides a unique learning base for analysing AI technologies in healthcare organisations and systems from a sociotechnical perspective using the NASSS framework. It adds to the existing literature and can better inform decision-making towards the judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author (HA) upon reasonable request. The data are not publicly available due to information that could compromise the privacy of the research participants.


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We thank the interviewees and the City hospital personnel for their availability throughout the study, even in the midst of the COVID-19 pandemic. The findings and conclusions presented in the text are those of the authors. They do not necessarily reflect the position of their organisations.

HA was supported by the In Fieri research programme (led by P), the International Observatory on the Societal Impacts of Artificial Intelligence and Digital Technologies, and the Institute for Data Valorization (IVADO), (Canada).

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HA and PL conceived and designed the study plan. HA and PL were responsible for data collection, analysis, and interpretation of results. HA, PL, CP, SES, RF and JPF were engaged in the drafting of the manuscript, and they all read and approved the final manuscript.

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Alami, H., Lehoux, P., Papoutsi, C. et al. Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre. BMC Health Serv Res 24 , 701 (2024). https://doi.org/10.1186/s12913-024-11112-x

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importance of literature review in qualitative research

Exploring strategic corporate sustainability management in family businesses: A systematic literature review

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importance of literature review in qualitative research

  • Simone Häußler   ORCID: orcid.org/0000-0003-1118-4733 1 &
  • Patrick Ulrich 1  

The escalating demands from legislative authorities and stakeholders for companies to adopt corporate sustainability measures underscore the growing importance of strategic sustainability management. Despite the efforts made by companies in this domain, the strategic management of sustainability in family businesses remains an under-researched area. To address this gap, we conducted a systematic literature review covering the period from 2006 to 2022, on the topic of strategic sustainability management in family businesses. Our investigation encompasses a content analysis of 98 relevant studies. Our research question is: “What aspects are taken into account by family businesses in their corporate sustainability strategies?” We tackle this issue through a methodological triangulation of qualitative and quantitative methods. Our results yield three clusters of strategies for corporate sustainability in family businesses: (1) Family values and succession planning; Stakeholder relations and communication; (2) Risk taking, Inventions, and Technologies; and (3) Entrepreneurship and Intrapreneurship. In addition, we systematically present a range of descriptive indicators, including the research methodologies applied and the geographic focus of the published literature. This research contributes significant insights for scholars and practitioners alike, providing valuable guidance in this field. Moreover, our study paves the way for further investigations into the strategies that influence sustainability within the context of family businesses. By shedding light on this critical area, we aim to foster a more sustainable and informed approach to corporate practices among family-owned enterprises.

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1 Introduction

The pressure on companies to implement corporate sustainability is increasing from both the legislature and stakeholders (Tjahjadi et al. 2021 ). Sustainability management is no longer just an individual corporate decision but is increasingly becoming a competitive factor. Given new and stricter requirements (e.g. on the part of the European Commission to achieve the 2- or preferably 1.5-degree target), companies will be more strongly obliged in the future to disclose their business activities regarding sustainability (European Parliament Council 2021 ).

Sustainability can improve consumers’ perceptions of product value (Bruttel 2014 ; Gómez-Ortega et al. 2023 ). A literature review by Schäufele and Hamm ( 2017 ) indicates that manufacturing and marketing with sustainability attributes is a promising strategy for quality differentiation. They report that consumers understand sustainability as a quality indicator and are therefore willing to pay more for sustainable products. Thus, through sustainability, preferences are created and purchasing behavior is influenced, which offers companies a competitive advantage. Sustainability can also help companies improve their image and generate more sales and customer loyalty as society takes on more and more social responsibility (Samudro et al. 2018 ). Sustainable marketing encompasses both sustainable products and social and economic practices. Addressing each of these elements can have a positive impact on competition. In a review paper, Batista and Francisco (2018) identified sustainable strategies of companies and analyzed the competitive advantages resulting from each of the three categories: environmental, economic, and social strategies. Actions falling under the environmental category are fundamental to maintaining competitiveness as they result from competitive behaviors and practices aimed at meeting specific requirements (e. g., the European requirements for sustainability reporting under the Corporate Sustainability Reporting Directive) and achieving the necessary level in developed countries. Conversely, the neglect of environmental strategies can drastically limit the ability of companies to act and grow and may result in lost opportunities for long-term investment. In the category of economic strategies, the indirect economic impacts are the development of new markets, opportunities for generating new jobs, increased effort toward accessibility, and adaptation to new economic contexts. The results regarding the social category show that companies strive to add value to their businesses by valuing and retaining their talent.

A paradigm shift toward sustainability is evident not only from a practical standpoint but also from a scientific standpoint. Academic interest in corporate sustainability issues has intensified in recent years (Pranugrahaning et al. 2021 ), but not every form of enterprise has come with a fair balance of scientific results. Although family businesses make up the most common type of companies listed in Africa, Asia, Europe, and Latin America (Broccardo et al. 2019 ; Curado and Mota 2021 ), and they are estimated to account for over 70 percent of worldwide gross domestic product (De Massis et al. 2018 ; King et al. 2022 ), there is little evidence about sustainability management for this type of enterprise. Moreover, a clear distinction is lacking between family business and other types of companies. The main problem is defining what a family business is in the first place, as different definitions of family businesses can be found in the literature. While family businesses and non-family businesses can be small, medium, or large, they can also differ concerning their values and practices compared to non-family businesses (Behringer et al. 2019 ). Until now, certain core elements such as financial performance statements, familiarity, and corporate governance in family companies could be identified and considered in definitions (Astrachan and Zellweger 2008 ; Frank et al. 2010 ; Siebels and zu Knyphausen-Aufsess 2012 ; Harms 2014 ; Fries et al. 2019 ; Baltazar et al. 2023 ). However, a recent and comprehensive meta-analysis by Miroshnychenko et al. ( 2022 ) notes a possible negative environmental performance in companies that define themselves as having family ownership and management. The inclusion of sustainability in the term “family business,” in addition to the common characteristics of a family business such as family goals or vision and a long-term orientation, is essential to a contemporary definition (Miroshnychenko et al. 2022 ). Given the hitherto less pronounced but growing interest in the area of sustainability in family businesses (Le Breton-Miller and Miller 2016 ; Kammerlander 2022 ), definitions with a corresponding focus are once again being addressed. Chua et al. ( 1999 ) in their definitions of the term family business already included the pursuit of a corporate vision in a sustainable manner and thus serve as a starting point for further research (see for example Behringer et al. 2019 ). Concerning the above-mentioned aspects, the present study adds to the definition of Chua et al. ( 1999 ), which still appears to be up to date:

The family business is a business governed and/or managed intending to shape and pursue the vision of the business held by a dominant coalition controlled by members of the same family or a small number of families in a manner that is potentially sustainable [(importance of social and ecological aspects)] across generations of the family or families. (Chua et al. 1999 )

Most firms are family firms, but little is known about their approaches to sustainability (Clauß et al. 2022 ). It seems that despite increasing research in the area of sustainability, the knowledge of how to manage sustainability is limited in family businesses (Traxler and Greiling 2023 ). As López-Pérez et al. ( 2018 ) state, family businesses face complex issues affecting their governance and management that differ from those of non-family businesses. The results of their study suggest that the company profile (a family business vs. a non-family business) moderates the relationship between sustainability and company performance. Mariani et al. ( 2021 ) conducted a systematic review highlighting that family businesses and non-family businesses exhibit different behaviors in implementing Corporate Social Responsibility (CSR), with some studies indicating higher CSR performance among family businesses. As the influencing factors with which a company acts and the resulting adaptation of sustainability or the related performance are reported to differ between family businesses and other types of businesses, it would be of scientific value to analyze which strategies family businesses adapt to achieve corporate sustainability. Thus, this article focuses on strategies for corporate sustainability in family businesses and aims to analyze the latest literature. The research question is: What aspects are taken into account by family businesses in their corporate sustainability strategies? We expect the results to provide more clarity on why and how family businesses address the issue of sustainability and yield further insights into the corresponding content of the strategies. In addition, we provide detailed insights into the studies considered by breaking down the results according to geographical focus and the methods applied.

The literature review is considered a necessary tool for systematically evaluating and managing a given body of literature for a specific academic inquiry (Tranfield et al. 2003 ; Becker et al. 2018 ). Review articles can challenge established assumptions, identify critical problems and errors, and spark scientific dialogue on a topic (Kraus et al. 2022 ). However, we emphasize the systematic literature analysis, as it guarantees a high level of impact (Kraus et al. 2024 ) and transparency due to the structured implementation and clear presentation of content required. Thus, a systematic literature analysis exceeds the possibilities of narrative literature analysis (Hiebl 2023 ). Moreover, a systematic literature analysis requires a high commitment from researchers (Sauer and Seuring 2023 ) and enables them to design flexible databases of articles that can be easily updated and interrogated (Pickering and Byrne 2014 ). With the aim of presenting a clear picture of the strategies relating to sustainability in family firms in the recent literature, we conducted a systematic literature review based on the guidelines proposed by Briner and Denyer ( 2012 : 115). We used a systematic approach to identify relevant studies by combining two of the most comprehensive databases of scientific papers, Scopus ( 2023 ) and Web of Science ( 2023 ). In a preliminary search process, we searched all literature reviews that dealt with sustainability and family businesses. After reading the papers in full, we brainstormed relevant keywords and an established a set of exclusion criteria in order to define clear boundaries.

To this end, the following three limitations were set:

We considered only peer-reviewed scientific journals in English that had a management focus to ensure the identification of high-quality research and to narrow the scope of our review,

To capture the current scientific discourse and derive trends for the future, we focused mainly on the years 2006–2022.

Publications focusing on technical, political, or natural science focus were excluded.

A custom search string was developed and applied. The multi-part search string contained two keywords that logically limited the subject area. We searched the following term in either the abstract or the title: sustaina* (to ensure that the different variations such as “sustainability,” “sustainable development,” “business sustainability,” or “business sustainability” were captured). The first keyword was connected to a second phrase (specifically, “family business*” or “family firms” or “family enterprise” or “family-controlled firms”). In the first round, a total of 269 hits were achieved. To narrow down the hits in relation to the research question, we selected all journals related to management. This left 128 hits. After we removed the duplicates, 98 hits remained, which were read completely and subjected to content analysis. Compared to systematic literature analyses with a relatively similar context, the number of papers found appeared to be appropriate (for example, compare Morioka and de Carvalho 2016 ; Aarseth et al. 2017 ; Lim et al. 2019 ; Velte 2022 ). The authors individually read all of the abstracts and, if needed, the entire article to screen them for relevance. The selected sources were then evaluated and analyzed in terms of content. For the literature analysis and synthesis, a concept matrix based on Webster and Watson ( 2002 ) was used to structure the content of the results. This step is crucial to synthesizing and organizing a large volume of data and helps to provide an initial impression of the results. Consecutive steps can then be taken to further evaluate the data. Building on that initial analysis, we examined the results of the concept matrix using methodical triangulation (Fig. 1 ). We then conducted a qualitative content analysis (Mayring 2010 : 84) based on the research question “What aspects are taken into account by family businesses in their corporate sustainability strategies?” This was followed by a quantitative content analysis to break down the results according to geographical focus, year of publication, and applied methods (Benninghaus 2005 ).

figure 1

Methodical Triangulation

The process model of inductive category formation according to Mayring ( 2010 : 84) was used to analyze the results, as this method is highly appropriate for the inductive and qualitative investigation of large amounts of data. In addition, further descriptive analyses were conducted, which provided information on the year of publication, the methodology used, and the location of the study. According to the process model of inductive category formation (Mayring 2010 : 84), firstly, the subject of the analysis was defined. The body of literature consisted of 98 peer- reviewed papers. After that, the level of abstraction was set and the material revision and formulation of keywords were carried out. This was followed by a revision of the keywords and a final review of the material. The last step entailed the interpretation and analysis of content.

For the quantitative analysis, descriptive clusters (Benninghaus 2005 ) were used to classify the body of literature. Descriptive clusters are groupings or categories of similar data points or objects that are identified based on common characteristics or attributes. These clusters are often used in statistical data analysis to improve the structure and organization of large datasets. The content of the literature was assessed using two questions:

What research methodologies are applied?

Which location is the main focus of the publications?

This section presents the results of the literature research. Firstly, the qualitative results, based on the application of the process model of inductive category formation, are presented and the research question is answered. Following this, the results of the quantitative analysis, using descriptive clusters, are revealed. The quantitative analysis provides information about the indicators (applied methods and geographical focus of the publication) of the literature.

3.1 Strategies for corporate sustainability management in family businesses

After various stages of processing the material, and running the process model of inductive category formation, three clusters of strategies were identified, which are presented in the following:

Family values and succession planning

Stakeholder relations and communication The predominant focus of the analyzed publications revolved around themes concerning the internal and external relationships within family businesses. This aspect emerges as a pivotal and determining factor concerning sustainability in the context of family enterprises. Understanding and effectively managing the intricate dynamics between family members, as well as fostering productive collaborations with external stakeholders, appears to play a central role in shaping the sustainability strategies of family businesses. Family values, succession planning, and stakeholder engagement emerge as factors that influence the extent to which sustainable practices are integrated into the core operations of these firms. Furthermore, this emphasis on relationships underscores the significance of transparent communication and effective governance structures within family businesses. Establishing clear lines of communication and governance mechanisms can facilitate a shared vision for sustainability and foster collective commitment to long-term sustainability goals. For example, when a non- family business is accused of unethical behavior, it reflects badly on the company, whereas in a family business, it is the reputation of the family itself that is at stake (Curado and Mota 2021 ). García‐Sánchez et al. ( 2020 ) examined this circumstance with an international sample of 956 listed firms and found that family firms perform a higher level of CSR compared to non-family firms. A positive relationship between family firms and sustainability is likely to emerge due to internally driven motivations, such as personal or organizational values and ideas, that align with ESG (Environment, Social, Governance) criteria (Sun et al. 2024 ). Particularly in the case of an impending generational change, the family’s values are crucial, especially regarding sustainability issues (Astrachan et al. 2020 ; Anggadwita et al. 2020 ). Succession planning (Bozer et al. 2017 ; Wang et al. 2019 ; Porfírio et al. 2020 ; Rodriguez Serna et al. 2022a , b ; Rodriguez Serna et al. 2022a ) and the associated reorientation about sustainability issues, as well as Stakeholder relations (Alwadani and Ndubisi 2020 ; Nguyen et al. 2020 ), are the most significant strategies for family businesses.

Risk taking, Inventions, and Technologies

In non-family firms, risk taking refers to the propensity of the organization to engage in ventures, investments, or strategic decisions that involve uncertain outcomes and potential exposure to financial, operational, or reputational hazards. The extent of risk- taking behavior in these firms is often influenced by factors such as organizational culture, management’s risk appetite, market conditions, and regulatory environments. Successful risk taking in non-family firms requires a balance between calculated risk assessment and the pursuit of opportunities that align with the organization’s strategic objectives and risk management framework. The way that risk is managed differs between family and non-family firms, as the perception of operational risk positively affects the perception of financial risk only in family firms (Santos et al. 2022 ). This circumstance influences the risk behavior of family firms, especially in times of crisis. As an example, the conduct of family firms during the COVID-19 pandemic has been studied by several authors. Anggadwita et al. ( 2022 ) identified instances in which family firms during the COVID-19 pandemic developed and implemented resilience. Chaudhuri et al. ( 2022 ) highlight the important moderating influence of strategic intent for sustaining family firms in uncertain times. However, apart from times of crisis, disruptive and new technologies also play a major role, with Kazancoglu et al. ( 2021 ) identifying Industry 4.0 as a driver for family business resources to improve sustainability.

Entrepreneurship and intrapreneurship

An entrepreneur is an individual who identifies and exploits business opportunities, creates innovative ventures, and assumes significant risk in the pursuit of profit and market success. Entrepreneurs play a crucial role in economies by enhancing and advancing businesses (Gallardo-Vázquez et al. 2023 ). In contrast, an intrapreneur operates within an established organization, exhibiting entrepreneurial characteristics to drive innovation, develop new projects, and advance the organization’s objectives while often benefiting from the organization’s resources and support. Whereas entrepreneurs act independently and are active within their companies, intrapreneurs are only partially independent because they work within the company as employees (Cadar and Badulescu 2015 ). Both entrepreneurs and intrapreneurs are crucial when it comes to sustainability in family businesses. Woodfield et al. ( 2017 ) explore the linkage between sustainable entrepreneurship and family firms and argue that family firms go beyond seeking financial gain and provide non-economic benefits (such as security and employment) to people and society. Rachmawati et al. ( 2022 ) assess family business performance and offer an overview of strategies. They point out that entrepreneurial orientation and family involvement are important factors in performance appraisal in family firms. Jamil et al. ( 2022 ) explore entrepreneurial qualities that lead to family business sustainability and indicate four supporting factors (cognitive characteristics, leadership role, motivation, and personality traits). Yet there are also limitations in this regard. Martínez Bobillo et al. ( 2021 ) show that efficiency factors in the design and potentiation of the entrepreneurial orientation and innovation capacity by family firms are hindered by the institutional (regulatory, legal, labor, and educational) environment, while more traditional factors such as ownership concentration and firm size are dominant.

3.2 Quantitative analysis of indicators

After the previous qualitative evaluation of results, the quantitative evaluation and graphical illustration of indicators are presented below.

Based in the recommendations Curado and Mota ( 2021 ) and Herrera and de las Heras-Rosas ( 2020 ), the geographical backgrounds of the publications studied were systematically collected. It should be mentioned that the naming of a geographical focus is always closely related to the selection of the research method. A geographical context is crucial for a case study but not for meta-level investigations, such as a literature review. For this reason, the number of publications that cannot be assigned a geographical focus is relatively high (n=33), which left a set of 65 publications. Among the assignable results, Asia (n=27) and Europe (n=23) are the regions with the highest number of publications. The emphasis on these regions reflects the growing interest and prevalence of family businesses in these areas and their significance in contributing to sustainable development. Only a few publications indicated Africa, America, Australia, or South America as the geographic context (Fig. 2 ). The predominance of Asia and Europe as the geographic focus in most publications on sustainability in family firms could be attributed to several factors. Firstly, these regions are home to a significant number of family- owned enterprises, making them important contributors to the global economy and sustainability discourse. Secondly, Asia and Europe have witnessed a growing awareness and emphasis on sustainability issues, leading to an increased interest in studying sustainable practices within family businesses in these regions. Lastly, the availability of research funding, academic resources, and established networks of scholars and institutions in these areas may have facilitated the production and dissemination of research on this topic.

figure 2

Geographical context of the publications

According to the literature review by Seuring and Müller ( 2008 ), five different research methods were distinguished and each paper (n=98) was assigned to only one method (Fig. 3 ). Surveys (n=34) were the most frequently chosen method to tackle sustainability in family firms, followed by case studies (n=22) and models (n=19).

figure 3

Research methodologies applied

The prevalence of surveys as the most commonly used method in papers on sustainability in family firms could be attributed to several factors. First of all, surveys are well-suited for collecting quantitative data from a large sample of family businesses, allowing researchers to obtain comprehensive insights into the prevalence and nature of sustainability practices across a diverse range of companies. Furthermore, surveys provide a structured and standardized approach, enabling researchers to ask consistent questions and compare responses systematically. This enhances the reliability and validity of the findings, making surveys an attractive method for studying sustainability-related phenomena in family firms. Surveys offer a cost-effective and efficient means of data collection, particularly when compared to qualitative methods, which often require extensive time and resources for in-depth interviews or case studies. As sustainability in family firms remains a burgeoning research area, surveys allow researchers to cover a wide range of topics and gather data from a larger pool of respondents. Lastly, the anonymous nature of surveys can encourage respondents to provide more honest responses on sensitive topics, such as internal family dynamics or business strategies. This can lead to a more accurate representation of the actual practices and challenges faced by family firms concerning sustainability.

4 Discussion

Corporate strategy refers to the strategy used to achieve a company’s goals, i.e. to implement the company’s policy (Davies 2000 ). According to Porter ( 1996 ), the […] “essence of strategy is choosing to perform activities differently than rivals do.” A strategy can be considered as a means of deciding what actions to pursue (Evered 1983 ). In terms of corporate strategy, there are specifics in the case of family businesses. Corporate sustainability strategies encompass deliberate plans and initiatives aimed at fostering the enduring economic, social, and environmental sustainability of a company’s operations. These strategies entail a comprehensive evaluation of the ecological, societal, and economic consequences of business activities, coupled with the implementation of measures to mitigate adverse impacts and enhance positive contributions to society and the environment (Eweje 2011 ).

Various types of sustainability strategies can be identified, each serving distinct purposes (Baumgartner and Ebner 2010 ). Introverted strategies focus on risk mitigation, adhering to external standards and regulations to safeguard the company from potential liabilities. Extroverted strategies, on the other hand, emphasize the building of positive external relationships and securing the social license to operate effectively. Conservative strategies prioritize eco-efficiency and cleaner production as a means of enhancing resource efficiency. Lastly, visionary strategies adopt a holistic approach, incorporating sustainability considerations across all business activities. Based on the papers found in our review, we agree with these statements and emphasize that the inclusion of internal (issues such as family succession) and external relationships in sustainability strategies should be considered as a matter of urgency.

Chirapanda ( 2020 ) aimed to elucidate the main strategies for family firms to ensure the successful continuation of their enterprises. The author points out that of the family firms surveyed, 60 percent agree that corporate and management strategies must be established along with a properly thought-out succession plan (ibid). In addition to succession planning, conflict strategies are also an important topic in strategic considerations in family businesses, in contrast to non-family businesses. Wu et al. ( 2018 ) show that managing the level of conflict between family business board members at an appropriate level by studying the main cause of conflict and identifying its nature led to better performance and sustainable development of family businesses.

As other authors have also recently noted (Henschel et al. 2021 ), sustainability issues are a continuously growing trend for family businesses, which can be deduced from the increasing number of corresponding publications, especially since 2010. Although sustainability in family businesses is an under-researched field, there have been several recent literature reviews that deal with partial aspects. These include Henschel et al. ( 2021 ), who conducted a systematic literature review on the topic of family businesses and CSR. However, the evaluation method (bibliographic coupling analysis) led to a higher degree of abstraction of the results, with a focus on thematic connections and the contexts offered by the bibliographic coupling network visualization. In contrast, the present work goes significantly deeper to qualitatively explore the topics through inductive category formation.

Regarding the limitations of this work, we note that we have not considered peer-reviewed literature or literature not published in languages outside of English in the results of the literature analysis. We acknowledge that there may have been relevant literature in these sources that could have contributed to the summarized results. In addition, we limited our search to two digital databases, Scopus and WoS. Although these databases are extensive, some studies may have been overlooked.

5 Conclusion

Our study offers advice for colleagues and practitioners by highlighting key aspects of sustainability in family businesses. Future research can be developed on these topics and solutions can be offered to these companies. The study also gave family businesses an insight into potential areas for development and provided an overview of three clusters of strategies that have been captured in the recent literature on sustainable family businesses: (1) Family values and succession planning; Stakeholder relations and communication (2) Risk taking, Inventions, and Technologies (3) Entrepreneurship and Intrapreneurship. In addition, we offered insights into the studies considered by breaking down the results by geographical focus, methods applied, and year of publication. We recommend that future research be conducted on the following topics.

Regarding sustainability, strategies for family businesses’ internal as well as external relationships should be included. Core elements of the studies found relate internally to the topics of family values and succession planning and externally to the topics of stakeholder relationships, including maintaining the good reputation of the family name. We recommend a longitudinal study to follow up on the core elements identified, focusing on the long-term impact of sustainability strategies on the performance and resilience of family businesses and to identify best practices.

A future research direction could be to analyze the possibilities of implementing sustainability strategies based on company size regarding the resources required and in particular concerning technologies in the company, associated costs, and risks for family businesses. This could reveal whether larger family businesses with more capital, for example, are better able to drive forward technologies in terms of sustainability development.

Regarding the topic of family businesses and sustainability, it is important to strike a balance between efficiency/entrepreneurship, family factors, and the quality characteristics of sustainability. In this context, it would be interesting to examine the influence of family management structures and dynamics on the adoption and implementation of sustainability strategies and to analyze how family traditions, values, and decision-making processes influence the integration of sustainability into the core business strategy.

6 Data availability statement

Not applicable.

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Häußler, S., Ulrich, P. Exploring strategic corporate sustainability management in family businesses: A systematic literature review. Rev Manag Sci (2024). https://doi.org/10.1007/s11846-024-00776-8

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