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Selecting Research Area
Selecting a research area is the very first step in writing your dissertation. It is important for you to choose a research area that is interesting to you professionally, as well as, personally. Experienced researchers note that “a topic in which you are only vaguely interested at the start is likely to become a topic in which you have no interest and with which you will fail to produce your best work” [1] . Ideally, your research area should relate to your future career path and have a potential to contribute to the achievement of your career objectives.
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The importance of selecting a relevant research area that is appropriate for dissertation is often underestimated by many students. This decision cannot be made in haste. Ideally, you should start considering different options at the beginning of the term. However, even when there are only few weeks left before the deadline and you have not chosen a particular topic yet, there is no need to panic.
There are few areas in business studies that can offer interesting topics due to their relevance to business and dynamic nature. The following is the list of research areas and topics that can prove to be insightful in terms of assisting you to choose your own dissertation topic.
Globalization can be a relevant topic for many business and economics dissertations. Forces of globalization are nowadays greater than ever before and dissertations can address the implications of these forces on various aspects of business.
Following are few examples of research areas in globalization:
- A study of implications of COVID-19 pandemic on economic globalization
- Impacts of globalization on marketing strategies of beverage manufacturing companies: a case study of The Coca-Cola Company
- Effects of labour migration within EU on the formation of multicultural teams in UK organizations
- A study into advantages and disadvantages of various entry strategies to Chinese market
- A critical analysis of the effects of globalization on US-based businesses
Corporate Social Responsibility (CSR) is also one of the most popular topics at present and it is likely to remain so for the foreseeable future. CSR refers to additional responsibilities of business organizations towards society apart from profit maximization. There is a high level of controversy involved in CSR. This is because businesses can be socially responsible only at the expense of their primary objective of profit maximization.
Perspective researches in the area of CSR may include the following:
- The impacts of CSR programs and initiatives on brand image: a case study of McDonald’s India
- A critical analysis of argument of mandatory CSR for private sector organizations in Australia
- A study into contradictions between CSR programs and initiatives and business practices: a case study of Philip Morris Philippines
- A critical analysis into the role of CSR as an effective marketing tool
- A study into the role of workplace ethics for improving brand image
Social Media and viral marketing relate to increasing numbers of various social networking sites such as Facebook, Twitter, Instagram, YouTube etc. Increasing levels of popularity of social media among various age groups create tremendous potential for businesses in terms of attracting new customers.
The following can be listed as potential studies in the area of social media:
- A critical analysis of the use of social media as a marketing strategy: a case study of Burger King Malaysia
- An assessment of the role of Instagram as an effective platform for viral marketing campaigns
- A study into the sustainability of TikTok as a marketing tool in the future
- An investigation into the new ways of customer relationship management in mobile marketing environment: a case study of catering industry in South Africa
- A study into integration of Twitter social networking website within integrated marketing communication strategy: a case study of Microsoft Corporation
Culture and cultural differences in organizations offer many research opportunities as well. Increasing importance of culture is directly related to intensifying forces of globalization in a way that globalization forces are fuelling the formation of cross-cultural teams in organizations.
Perspective researches in the area of culture and cultural differences in organizations may include the following:
- The impact of cross-cultural differences on organizational communication: a case study of BP plc
- A study into skills and competencies needed to manage multicultural teams in Singapore
- The role of cross-cultural differences on perception of marketing communication messages in the global marketplace: a case study of Apple Inc.
- Effects of organizational culture on achieving its aims and objectives: a case study of Virgin Atlantic
- A critical analysis into the emergence of global culture and its implications in local automobile manufacturers in Germany
Leadership and leadership in organizations has been a popular topic among researchers for many decades by now. However, the importance of this topic may be greater now than ever before. This is because rapid technological developments, forces of globalization and a set of other factors have caused markets to become highly competitive. Accordingly, leadership is important in order to enhance competitive advantages of organizations in many ways.
The following studies can be conducted in the area of leadership:
- Born or bred: revisiting The Great Man theory of leadership in the 21 st century
- A study of effectiveness of servant leadership style in public sector organizations in Hong Kong
- Creativity as the main trait for modern leaders: a critical analysis
- A study into the importance of role models in contributing to long-term growth of private sector organizations: a case study of Tata Group, India
- A critical analysis of leadership skills and competencies for E-Commerce organizations
COVID-19 pandemic and its macro and micro-economic implications can also make for a good dissertation topic. Pandemic-related crisis has been like nothing the world has seen before and it is changing international business immensely and perhaps, irreversibly as well.
The following are few examples for pandemic crisis-related topics:
- A study into potential implications of COVID-19 pandemic into foreign direct investment in China
- A critical assessment of effects of COVID-19 pandemic into sharing economy: a case study of AirBnb.
- The role of COVID-19 pandemic in causing shifts in working patterns: a critical analysis
Moreover, dissertations can be written in a wide range of additional areas such as customer services, supply-chain management, consumer behaviour, human resources management, catering and hospitality, strategic management etc. depending on your professional and personal interests.
[1] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited.
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Chapter 12: Field Research: A Qualitative Research Technique
12.4 Getting In and Choosing a Site
When embarking on a field research project, there are two major aspects to consider. The first is where to observe and the second is what role you will take in your field site. Your decision about each of these will be shaped by a number of factors, over some of which you will have control and others you will not. Your decision about where to observe and what role to play will also have consequences for the data you are able to gather and how you analyze and share those data with others. We will examine each of these contingencies in the following subsections.
Your research question might determine where you observe, by, but because field research often works inductively, you may not have a totally focused question before you begin your observations. In some cases, field researchers choose their final research question once they embark on data collection. Other times, they begin with a research question but remain open to the possibility that their focus may shift as they gather data. In either case, when you choose a site, there are a number of factors to consider. These questions include:
- What do you hope to accomplish with your field research?
- What is your topical/substantive interest?
- Where are you likely to observe behaviour that has something to do with that topic?
- How likely is it that you will actually have access to the locations that are of interest to you?
- How much time do you have to conduct your participant observations?
- Will your participant observations be limited to a single location, or will you observe in multiple locations?
Perhaps the best place to start, as you work to identify a site or sites for your field research, is to think about your limitations . One limitation that could shape where you conduct participant observation is time. Field researchers typically immerse themselves in their research sites for many months, sometimes even years. As demonstrated in Table 12.1 “Field Research Examples”, other field researchers have spent as much or even more time in the field. Do you have several years available to conduct research, or are you seeking a smaller-scale field research experience? How much time do you have to participate and observe per day? Per week? Identifying how available you’ll be in terms of time will help you determine where and what sort of research sites to choose. Also think about where you live and whether travel is an option for you. Some field researchers move to live with or near their population of interest. Is this something you might consider? How you answer these questions will shape how you identify your research site. Where might your field research questions take you?
In choosing a site, also consider how your social location might limit what or where you can study. The ascribed aspects of our locations are those that are involuntary, such as our age or race or mobility. For example, how might your ascribed status as an adult shape your ability to conduct complete participation in a study of children’s birthday parties? The achieved aspects of our locations, on the other hand, are those about which we have some choice. In field research, we may also have some choice about whether, or the extent to which, we reveal the achieved aspects of our identities.
Finally, in choosing a research site, consider whether your research will be a collaborative project or whether you are on your own. Collaborating with others has many benefits; you can cover more ground, and therefore collect more data, than you can on your own. Having collaborators in any research project, but especially field research, means having others with whom to share your trials and tribulations in the field. However, collaborative research comes with its own set of challenges, such as possible personality conflicts among researchers, competing commitments in terms of time and contributions to the project, and differences in methodological or theoretical perspectives (Shaffir, Marshall, & Haas, 1979). When considering something that is of interest to you, consider also whether you have possible collaborators. How might having collaborators shape the decisions you make about where to conduct participant observation?
This section began by asking you to think about limitations that might shape your field site decisions. But it makes sense to also think about the opportunities —social, geographic, and otherwise—that your location affords. Perhaps you are already a member of an organization where you would like to conduct research. Maybe you know someone who knows someone else who might be able to help you access a site. Perhaps you have a friend you could stay with, enabling you to conduct participant observations away from home. Choosing a site for participation is shaped by all these factors—your research question and area of interest, a few limitations, some opportunities, and sometimes a bit of being in the right place at the right time.
Choosing a Role
As with choosing a research site, some limitations and opportunities beyond your control might shape the role you take once you begin your participant observation. You will also need to make some deliberate decisions about how you enter the field and who you will be once you are in.
In terms of entering the field, one of the earliest decisions you will need to make is whether to be overt or covert. As an overt researcher, you enter the field with your research participants having some awareness about the fact that they are the subjects of social scientific research. Covert researchers, on the other hand, enter the field as though they are full participants, opting not to reveal that they are also researchers or that the group they’ve joined is being studied. As you might imagine, there are pros and cons to both approaches. A critical point to keep in mind is that whatever decision you make about how you enter the field will affect many of your subsequent experiences in the field.
As an overt researcher, you may experience some trouble establishing rapport at first. Having an insider at the site who can vouch for you will certainly help, but the knowledge that subjects are being watched will inevitably (and understandably) make some people uncomfortable and possibly cause them to behave differently than they would, were they not aware of being research subjects. Because field research is typically a sustained activity that occurs over several months or years, it is likely that participants will become more comfortable with your presence over time. Overt researchers also avoid a variety of moral and ethical dilemmas that they might otherwise face.
As a covert researcher, “getting in” your site might be quite easy; however, once you are in, you may face other issues. Some questions to consider are:
- How long would you plan to conceal your identity?
- How might participants respond once they discover you’ve been studying them?
- How will you respond if asked to engage in activities you find unsettling or unsafe?
Researcher, Jun Li (2008) struggled with the ethical challenges of “getting in” to interview female gamblers as a covert researcher. Her research was part of a post-doctoral fellowship from the Ontario Problem Gambling Research Centre to study female gambling culture. In response to these ethical aspects, she changed her research role to overt; however, in her overt role female gamblers were reluctant to “speak their minds” to her (p. 100). As such, she once again adjusted her level of involvement in the study to one who participated in female gambling culture as an insider and observed as an outsider. You can read her interesting story .
Beyond your own personal level of comfort with deceiving participants and willingness to take risks, it is possible that the decision about whether or not to enter the field covertly will be made for you. If you are conducting research while associated with any federally funded agency (and even many private entities), your institutional review board (IRB) probably will have something to say about any planned deception of research subjects. Some IRBs approve deception, but others look warily upon a field researcher engaging in covert participation. The extent to which your research site is a public location, where people may not have an expectation of privacy, might also play a role in helping you decide whether covert research is a reasonable approach.
Having an insider at your site who can vouch for you is helpful. Such insiders, with whom a researcher may have some prior connection or a closer relationship than with other site participants, are called key informants. A key informant can provide a framework for your observations, help translate what you observe, and give you important insight into a group’s culture. If possible, having more than one key informant at a site is ideal, as one informant’s perspective may vary from another’s.
Once you have made a decision about how to enter your field site, you will need to think about the role you will adopt while there. Aside from being overt or covert, how close will you be to participants? In the words of Fred Davis (1973), [12] who coined these terms in reference to researchers’ roles, “will you be a Martian, a Convert, or a bit of both”? Davis describes the Martian role as one in which a field researcher stands back a bit, not fully immersed in the lives of his subjects, in order to better problematize, categorize, and see with the eyes of a newcomer what’s being observed. From the Martian perspective, a researcher should remain disentangled from too much engagement with participants. The Convert, on the other hand, intentionally dives right into life as a participant. From this perspective, it is through total immersion that understanding is gained. Which approach do you feel best suits you?
In the preceding section we examined how ascribed and achieved statuses might shape how or which sites are chosen for field research. They also shape the role the researcher adopts in the field site. The fact that the authors of this textbook are professors, for example, is an achieved status. We can choose the extent to which we share this aspect of our identities with field study participants. In some situations, sharing that we are professors may enhance our ability to establish rapport; in other field sites it might stifle conversation and rapport-building. As you have seen from the examples provided throughout this chapter, different field researchers have taken different approaches when it comes to using their social locations to help establish rapport and dealing with ascribed statuses that differ from those of their “subjects
Whatever role a researcher chooses, many of the points made in Chapter 11 “Quantitative Interview Techniques” regarding power and relationships with participants apply to field research as well. In fact, the researcher/researched relationship is even more complex in field studies, where interactions with participants last far longer than the hour or two it might take to interview someone. Moreover, the potential for exploitation on the part of the researcher is even greater in field studies, since relationships are usually closer and lines between research and personal or off-the-record interaction may be blurred. These precautions should be seriously considered before deciding to embark upon a field research project
Field Notes
The aim with field notes is to record your observations as straightforwardly and, while in the field, as quickly as possible, in a way that makes sense to you . Field notes are the first—and a necessary—step toward developing quality analysis. They are also the record that affirms what you observed. In other words, field notes are not to be taken lightly or overlooked as unimportant; however, they are not usually intended for anything other than the researcher’s own purposes as they relate to recollections of people, places and things related to the research project.
Some say that there are two different kinds of field notes: descriptive and analytic. Though the lines between what counts as description and what counts as analysis can become blurred, the distinction is nevertheless useful when thinking about how to write and how to interpret field notes. In this section, we will focus on descriptive field notes. Descriptive field notes are notes that simply describe a field researcher’s observations as straightforwardly as possible. These notes typically do not contain explanations of, or comments about, those observations. Instead, the observations are presented on their own, as clearly as possible. In the following section, we will define and examine the uses and writing of analytic field notes more closely.
Analysis of Field Research Data
Field notes are data. But moving from having pages of data to presenting findings from a field study in a way that will make sense to others requires that those data be analyzed. Analysis of field research data is the focus in this final section of the chapter.
From Description to Analysis
Writing and analyzing field notes involves moving from description to analysis. In Section 12.4 “Field Notes”, we considered field notes that are mostly descriptive in nature. In this section we will consider analytic field notes. Analytic field notes are notes that include the researcher’s impressions about his observations. Analyzing field note data is a process that occurs over time, beginning at the moment a field researcher enters the field and continuing as interactions happen in the field, as the researcher writes up descriptive notes, and as the researcher considers what those interactions and descriptive notes mean.
Often field notes will develop from a more descriptive state to an analytic state when the field researcher exits a given observation period, with messy jotted notes or recordings in hand (or in some cases, literally on hand), and sits at a computer to type up those notes into a more readable format. We have already noted that carefully paying attention while in the field is important; so is what goes on immediately upon exiting the field. Field researchers typically spend several hours typing up field notes after each observation has occurred. This is often where the analysis of field research data begins. Having time outside of the field to reflect upon your thoughts about what you have seen and the meaning of those observations is crucial to developing analysis in field research studies.
Once the analytic field notes have been written or typed up, the field researcher can begin to look for patterns across the notes by coding the data. This will involve the iterative process of open and focused coding that is outlined in Chapter 10, “Qualitative Data Collection & Analysis Methods.” As mentioned in Section 12.4 “Field Notes”, it is important to note as much as you possibly can while in the field and as much as you can recall after leaving the field because you never know what might become important. Things that seem decidedly unimportant at the time may later reveal themselves to have some relevance.
As mentioned in Chapter 10, analysis of qualitative data often works inductively. The analytic process of field researchers and others who conduct inductive analysis is referred to as grounded theory (Glaser & Strauss, 1967; Charmaz, 2006). The goal when employing a grounded theory approach is to generate theory. Its name not only implies that discoveries are made from the ground up but also that theoretical developments are grounded in a researcher’s empirical observations and a group’s tangible experiences. Grounded theory requires that one begin with an open-ended and open-minded desire to understand a social situation or setting and involves a systematic process whereby the researcher lets the data guide her rather than guiding the data by preset hypotheses.
As exciting as it might sound to generate theory from the ground up, the experience can also be quite intimidating and anxiety-producing, since the open nature of the process can sometimes feel a little out of control. Without hypotheses to guide their analysis, researchers engaged in grounded theory work may experience some feelings of frustration or angst. The good news is that the process of developing a coherent theory that is grounded in empirical observations can be quite rewarding, not only to researchers, but also to their peers, who can contribute to the further development of new theories through additional research, and to research participants who may appreciate getting a bird’s-eye view of their every day.
Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
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What's the difference between 'research topic' and 'research area'?
I am writing an essay to apply for a summer research project and is supposed to write about 'general research topic that interests me' and 'area I would like to focus'. I'm kind of confused about these two terms. What's the difference?
For example, if I'm interested in computer science, where should I write it?
p.s. I have asked this question in English Language & Usage site but didn't get answer. So I suppose that these two words may only have difference in academic field?
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2 Answers 2
A research area is what a research topic is placed into, but is much broader than the scope of the topic. For example a research area can be human physiology, computer science (as you mentioned) or even relate to a specific field within these broader terms such as cardiac electrophysiology or machine learning respectively.
A research topic would be a specific question, hypothesis or problem you wish to investigate and answer which is under the scope of your research area. That is to say, my research area is in neuroscience/neurophysiology and my research topic is investigating the mechanisms of neuronal communication, as an example.
You would want to say topics that interest you which relate to a certain problem that you may be aware of, whereas in the research area you would want to outline your inclinations towards a particular field of academia.
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While a topic is narrower than an area (for example, your area may be "solid state physics" and your topic "semiconductor tuning based on dopage"), it's probably true that for most people there is little difference between the two terms as far as colloquial usage is concerned.
In other words, don't obsess about the difference -- though, if you want, consider the "area" a broader term.
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Home » Delimitations in Research – Types, Examples and Writing Guide
Delimitations in Research – Types, Examples and Writing Guide
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Delimitations
Definition:
Delimitations refer to the specific boundaries or limitations that are set in a research study in order to narrow its scope and focus. Delimitations may be related to a variety of factors, including the population being studied, the geographical location, the time period, the research design , and the methods or tools being used to collect data .
The Importance of Delimitations in Research Studies
Here are some reasons why delimitations are important in research studies:
- Provide focus : Delimitations help researchers focus on a specific area of interest and avoid getting sidetracked by tangential topics. By setting clear boundaries, researchers can concentrate their efforts on the most relevant and significant aspects of the research question.
- Increase validity : Delimitations ensure that the research is more valid by defining the boundaries of the study. When researchers establish clear criteria for inclusion and exclusion, they can better control for extraneous variables that might otherwise confound the results.
- Improve generalizability : Delimitations help researchers determine the extent to which their findings can be generalized to other populations or contexts. By specifying the sample size, geographic region, time frame, or other relevant factors, researchers can provide more accurate estimates of the generalizability of their results.
- Enhance feasibility : Delimitations help researchers identify the resources and time required to complete the study. By setting realistic parameters, researchers can ensure that the study is feasible and can be completed within the available time and resources.
- Clarify scope: Delimitations help readers understand the scope of the research project. By explicitly stating what is included and excluded, researchers can avoid confusion and ensure that readers understand the boundaries of the study.
Types of Delimitations in Research
Here are some types of delimitations in research and their significance:
Time Delimitations
This type of delimitation refers to the time frame in which the research will be conducted. Time delimitations are important because they help to narrow down the scope of the study and ensure that the research is feasible within the given time constraints.
Geographical Delimitations
Geographical delimitations refer to the geographic boundaries within which the research will be conducted. These delimitations are significant because they help to ensure that the research is relevant to the intended population or location.
Population Delimitations
Population delimitations refer to the specific group of people that the research will focus on. These delimitations are important because they help to ensure that the research is targeted to a specific group, which can improve the accuracy of the results.
Data Delimitations
Data delimitations refer to the specific types of data that will be used in the research. These delimitations are important because they help to ensure that the data is relevant to the research question and that the research is conducted using reliable and valid data sources.
Scope Delimitations
Scope delimitations refer to the specific aspects or dimensions of the research that will be examined. These delimitations are important because they help to ensure that the research is focused and that the findings are relevant to the research question.
How to Write Delimitations
In order to write delimitations in research, you can follow these steps:
- Identify the scope of your study : Determine the extent of your research by defining its boundaries. This will help you to identify the areas that are within the scope of your research and those that are outside of it.
- Determine the time frame : Decide on the time period that your research will cover. This could be a specific period, such as a year, or it could be a general time frame, such as the last decade.
- I dentify the population : Determine the group of people or objects that your study will focus on. This could be a specific age group, gender, profession, or geographic location.
- Establish the sample size : Determine the number of participants that your study will involve. This will help you to establish the number of people you need to recruit for your study.
- Determine the variables: Identify the variables that will be measured in your study. This could include demographic information, attitudes, behaviors, or other factors.
- Explain the limitations : Clearly state the limitations of your study. This could include limitations related to time, resources, sample size, or other factors that may impact the validity of your research.
- Justify the limitations : Explain why these limitations are necessary for your research. This will help readers understand why certain factors were excluded from the study.
When to Write Delimitations in Research
Here are some situations when you may need to write delimitations in research:
- When defining the scope of the study: Delimitations help to define the boundaries of your research by specifying what is and what is not included in your study. For instance, you may delimit your study by focusing on a specific population, geographic region, time period, or research methodology.
- When addressing limitations: Delimitations can also be used to address the limitations of your research. For example, if your data is limited to a certain timeframe or geographic area, you can include this information in your delimitations to help readers understand the limitations of your findings.
- When justifying the relevance of the study : Delimitations can also help you to justify the relevance of your research. For instance, if you are conducting a study on a specific population or region, you can explain why this group or area is important and how your research will contribute to the understanding of this topic.
- When clarifying the research question or hypothesis : Delimitations can also be used to clarify your research question or hypothesis. By specifying the boundaries of your study, you can ensure that your research question or hypothesis is focused and specific.
- When establishing the context of the study : Finally, delimitations can help you to establish the context of your research. By providing information about the scope and limitations of your study, you can help readers to understand the context in which your research was conducted and the implications of your findings.
Examples of Delimitations in Research
Examples of Delimitations in Research are as follows:
Research Title : “Impact of Artificial Intelligence on Cybersecurity Threat Detection”
Delimitations :
- The study will focus solely on the use of artificial intelligence in detecting and mitigating cybersecurity threats.
- The study will only consider the impact of AI on threat detection and not on other aspects of cybersecurity such as prevention, response, or recovery.
- The research will be limited to a specific type of cybersecurity threats, such as malware or phishing attacks, rather than all types of cyber threats.
- The study will only consider the use of AI in a specific industry, such as finance or healthcare, rather than examining its impact across all industries.
- The research will only consider AI-based threat detection tools that are currently available and widely used, rather than including experimental or theoretical AI models.
Research Title: “The Effects of Social Media on Academic Performance: A Case Study of College Students”
Delimitations:
- The study will focus only on college students enrolled in a particular university.
- The study will only consider social media platforms such as Facebook, Twitter, and Instagram.
- The study will only analyze the academic performance of students based on their GPA and course grades.
- The study will not consider the impact of other factors such as student demographics, socioeconomic status, or other factors that may affect academic performance.
- The study will only use self-reported data from students, rather than objective measures of their social media usage or academic performance.
Purpose of Delimitations
Some Purposes of Delimitations are as follows:
- Focusing the research : By defining the scope of the study, delimitations help researchers to narrow down their research questions and focus on specific aspects of the topic. This allows for a more targeted and meaningful study.
- Clarifying the research scope : Delimitations help to clarify the boundaries of the research, which helps readers to understand what is and is not included in the study.
- Avoiding scope creep : Delimitations help researchers to stay focused on their research objectives and avoid being sidetracked by tangential issues or data.
- Enhancing the validity of the study : By setting clear boundaries, delimitations help to ensure that the study is valid and reliable.
- Improving the feasibility of the study : Delimitations help researchers to ensure that their study is feasible and can be conducted within the time and resources available.
Applications of Delimitations
Here are some common applications of delimitations:
- Geographic delimitations : Researchers may limit their study to a specific geographic area, such as a particular city, state, or country. This helps to narrow the focus of the study and makes it more manageable.
- Time delimitations : Researchers may limit their study to a specific time period, such as a decade, a year, or a specific date range. This can be useful for studying trends over time or for comparing data from different time periods.
- Population delimitations : Researchers may limit their study to a specific population, such as a particular age group, gender, or ethnic group. This can help to ensure that the study is relevant to the population being studied.
- Data delimitations : Researchers may limit their study to specific types of data, such as survey responses, interviews, or archival records. This can help to ensure that the study is based on reliable and relevant data.
- Conceptual delimitations : Researchers may limit their study to specific concepts or variables, such as only studying the effects of a particular treatment on a specific outcome. This can help to ensure that the study is focused and clear.
Advantages of Delimitations
Some Advantages of Delimitations are as follows:
- Helps to focus the study: Delimitations help to narrow down the scope of the research and identify specific areas that need to be investigated. This helps to focus the study and ensures that the research is not too broad or too narrow.
- Defines the study population: Delimitations can help to define the population that will be studied. This can include age range, gender, geographical location, or any other factors that are relevant to the research. This helps to ensure that the study is more specific and targeted.
- Provides clarity: Delimitations help to provide clarity about the research study. By identifying the boundaries and limitations of the research, it helps to avoid confusion and ensures that the research is more understandable.
- Improves validity: Delimitations can help to improve the validity of the research by ensuring that the study is more focused and specific. This can help to ensure that the research is more accurate and reliable.
- Reduces bias: Delimitations can help to reduce bias by limiting the scope of the research. This can help to ensure that the research is more objective and unbiased.
About the author
Muhammad Hassan
Researcher, Academic Writer, Web developer
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- Types of Research Designs Compared | Guide & Examples
Types of Research Designs Compared | Guide & Examples
Published on June 20, 2019 by Shona McCombes . Revised on June 22, 2023.
When you start planning a research project, developing research questions and creating a research design , you will have to make various decisions about the type of research you want to do.
There are many ways to categorize different types of research. The words you use to describe your research depend on your discipline and field. In general, though, the form your research design takes will be shaped by:
- The type of knowledge you aim to produce
- The type of data you will collect and analyze
- The sampling methods , timescale and location of the research
This article takes a look at some common distinctions made between different types of research and outlines the key differences between them.
Table of contents
Types of research aims, types of research data, types of sampling, timescale, and location, other interesting articles.
The first thing to consider is what kind of knowledge your research aims to contribute.
Type of research | What’s the difference? | What to consider |
---|---|---|
Basic vs. applied | Basic research aims to , while applied research aims to . | Do you want to expand scientific understanding or solve a practical problem? |
vs. | Exploratory research aims to , while explanatory research aims to . | How much is already known about your research problem? Are you conducting initial research on a newly-identified issue, or seeking precise conclusions about an established issue? |
aims to , while aims to . | Is there already some theory on your research problem that you can use to develop , or do you want to propose new theories based on your findings? |
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The next thing to consider is what type of data you will collect. Each kind of data is associated with a range of specific research methods and procedures.
Type of research | What’s the difference? | What to consider |
---|---|---|
Primary research vs secondary research | Primary data is (e.g., through or ), while secondary data (e.g., in government or scientific publications). | How much data is already available on your topic? Do you want to collect original data or analyze existing data (e.g., through a )? |
, while . | Is your research more concerned with measuring something or interpreting something? You can also create a research design that has elements of both. | |
vs | Descriptive research gathers data , while experimental research . | Do you want to identify characteristics, patterns and or test causal relationships between ? |
Finally, you have to consider three closely related questions: how will you select the subjects or participants of the research? When and how often will you collect data from your subjects? And where will the research take place?
Keep in mind that the methods that you choose bring with them different risk factors and types of research bias . Biases aren’t completely avoidable, but can heavily impact the validity and reliability of your findings if left unchecked.
Type of research | What’s the difference? | What to consider |
---|---|---|
allows you to , while allows you to draw conclusions . | Do you want to produce knowledge that applies to many contexts or detailed knowledge about a specific context (e.g. in a )? | |
vs | Cross-sectional studies , while longitudinal studies . | Is your research question focused on understanding the current situation or tracking changes over time? |
Field research vs laboratory research | Field research takes place in , while laboratory research takes place in . | Do you want to find out how something occurs in the real world or draw firm conclusions about cause and effect? Laboratory experiments have higher but lower . |
Fixed design vs flexible design | In a fixed research design the subjects, timescale and location are begins, while in a flexible design these aspects may . | Do you want to test hypotheses and establish generalizable facts, or explore concepts and develop understanding? For measuring, testing and making generalizations, a fixed research design has higher . |
Choosing between all these different research types is part of the process of creating your research design , which determines exactly how your research will be conducted. But the type of research is only the first step: next, you have to make more concrete decisions about your research methods and the details of the study.
Read more about creating a research design
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Normal distribution
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Ecological validity
Research bias
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
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What is research locale?
Insight from top 5 papers.
Research locale refers to the specific geographical area or location where research is conducted [4] . It involves studying and analyzing the social, economic, or environmental conditions of a particular place or region [1] [4] . Researchers may focus on understanding the local dynamics, processes, and relationships within that specific locale [4] . The concept of research locale is important in various fields, such as health management, where studying epidemics in poverty-stricken areas can provide solutions for global health crises [2] . Additionally, research locale plays a role in calibration equipment, where mathematical models are used to analyze and calibrate current transformers in specific locations [3] . Researchers may adopt different modes of response when conducting research in a specific locale, such as franchise, margin, or locale, depending on their relationship with metropolitan centers and their use of local empirical materials [5] .
Source Papers (5)
Title | Insight |
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- 1 Talk with Paper | |
1 Talk with Paper | |
- 1 Talk with Paper | |
- 7 Talk with Paper | |
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Related Questions
Manila city serves as a research locale due to its unique urban landscape characterized by intense class segregation, rapid urbanization, and the intertwining of formal and informal sectors. The city's spatial organization showcases extreme inequality, with affluent enclaves juxtaposed against informal settlements of the urban poor . This setting has emerged from historical processes like rapid population growth, city-building initiatives, and urban restructuring, making Manila a prime example of "late urbanization" and a vivid case of class dynamics shaped by market forces . Additionally, Manila's urbanization has led to the emergence of organized groups within informal settlements, advocating for habitat defense and security of tenure, showcasing the resilience and progress of these communities despite setbacks . The city's ongoing urbanization and the government-led programs for revitalization, such as the Pasig River Rehabilitation Program, further highlight the need for comprehensive planning strategies and community empowerment policies .
Localized corrosion refers to intense metal surface attacks at specific sites, often leading to structural failures. It includes various modes such as pitting, crevice corrosion, intergranular corrosion, and dealloying, each influenced by different factors like anionic species, stagnant solutions, grain boundaries, and selective dissolution of elements. Localized corrosion complexity arises from dynamic changes in corrosion mechanisms due to environmental variabilities, making it challenging to predict and understand fully. Factors like local heterogeneities, electrochemical environments, and microbiological influences play crucial roles in accelerating degradation, especially in marine environments. Experimental studies on different alloys exposed to chloride solutions highlight the impact of water content on pitting and repassivation potentials, shedding light on the mechanisms underlying localized corrosion resistance.
The locale applicable for documentary analysis researches varies across different fields. In the field of History of Education, researchers focus on methodological approaches to document analysis, aligning data interpretation with epistemological and theoretical choices . Similarly, in the context of exploring local history and culture, sporting libraries, often overlooked, provide unique resources like books, maps, and pictures that complement traditional institutes in studying local communities . Furthermore, in the assessment of factors influencing the implementation of medical respites, documentary analysis of newspaper articles proves effective in identifying themes related to external forces of change such as funding, community resistance, and the healthcare system . These diverse examples showcase how different locales offer valuable insights for conducting documentary analysis research in various disciplines.
Research locale in 2020 refers to the specific geographical location or area where research is conducted. It is important to conduct research in the actual setting or context in order to address the specific challenges and issues faced in that particular area . Research performed in situ, particularly in poverty-stricken areas, can bring solutions to major health crises and benefit health management worldwide . In the field of urban planning, research on local landscapes and urban design is necessary to understand the complex interactions between public spaces, urban functions, and cultural identity . In the context of current transformer calibration, research focuses on developing mathematical models and calibration equipment that accurately simulate the working conditions of locale current transformers . In the field of climate research, local interpolation methods are used to model and analyze the spatial variations of temperature within a specific territory .
Local context refers to the specific information or characteristics within a limited area or region. It is often used to provide necessary semantic or spatial details for understanding a word, text, or object. In linguistics, local context can be horizontal or vertical, depending on its relationship to a word or text. Horizontal context supplies the semantic environment for a word, while vertical context supplies the semantic environment for a text. In other fields, such as computer science and image processing, local context is used to capture the local ordering of words or the local characteristics of objects. It can be represented through various techniques, such as sparse coding or attention networks. Local context plays a crucial role in enhancing understanding and performance in different domains.
Trending Questions
Indigenous food systems (IFS) are diverse and shaped by the intricate relationships between land, culture, and community. These systems vary significantly across regions and cultures, influenced by historical contexts and environmental factors. Understanding these differences is crucial for appreciating the resilience and adaptability of Indigenous communities. ## Key Characteristics of Indigenous Food Systems - **Cultural Significance**: IFS are deeply rooted in the cultural practices and traditions of Indigenous peoples, emphasizing the importance of community and shared resources. For instance, the Anishinaabe emphasize community-based food sovereignty, where collective harvesting and sharing are vital. - **Diversity of Practices**: IFS include a range of practices such as hunting, fishing, gathering, and agriculture, tailored to local ecosystems. In North America, many Indigenous groups rely on seasonal hunting and gathering, showcasing a profound connection to their environment. - **Response to Environmental Changes**: Climate change and pollution are altering IFS, prompting communities to adapt their practices. Research indicates that Indigenous groups in Canada, the U.S., Australia, and Aotearoa are experiencing similar challenges and responses due to shared colonial histories. While IFS are often viewed through a lens of food insecurity, it is essential to recognize the resilience and agency of Indigenous communities in maintaining their food systems despite external pressures. This perspective highlights the ongoing efforts to revitalize and sustain traditional practices in the face of modern challenges.
The proportion of telehealth users among primary care healthcare providers varies significantly across regions and countries, influenced by factors such as socioeconomic status, healthcare infrastructure, and patient demographics. ## Regional Variations in Telehealth Usage - In Portugal, 38% of primary care patients reported using telehealth during the COVID-19 pandemic, with telephone consultations being the most common (90.3%). - A study in Aotearoa New Zealand found that 38% of young people had used telehealth, with a preference for phone consultations over video calls. ## Factors Influencing Telehealth Adoption - Socioeconomic factors play a crucial role; older age, marital status, and unmet healthcare needs were positively associated with telehealth use in Portugal. - In the U.S., Federally Qualified Health Centers adapted telehealth to serve vulnerable populations, highlighting the importance of addressing health equity. Despite the growing adoption of telehealth, challenges such as technological barriers and patient hesitance remain prevalent, indicating that while telehealth has potential, its effectiveness is contingent on addressing these disparities.
The comparison between Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs) reveals that ViTs often outperform CNNs in various applications, particularly in tasks requiring fine-grained classification and global feature extraction. This performance advantage is attributed to the self-attention mechanisms inherent in transformers, which allow for better handling of long-range dependencies in data. ## Performance in Agricultural Applications - In a study on tomato maturity stage prediction, the ViT achieved a testing accuracy of 98.67%, significantly surpassing CNN models, which ranged from 88.52% to 93.15% accuracy. - Similarly, the TCNet model, which integrates CNN and transformer features, demonstrated superior performance in detecting unharvested rice regions, achieving 97.88% Intersection over Union and 98.95% accuracy. ## Medical Imaging Efficacy - In breast cancer classification, ViTs achieved an accuracy of 99.81%, outperforming traditional CNNs. This highlights the potential of transformers in critical medical applications where precision is paramount. ## Generalization and Robustness - The Convolution-enhanced Vision Transformer (Conv-ViT) showed exceptional performance in locomotion mode recognition, achieving 98.87% accuracy, indicating that the combination of CNN and transformer architectures can yield robust results. While ViTs demonstrate superior performance in many contexts, it is essential to consider that CNNs still hold value, particularly in scenarios where local feature extraction is crucial. The choice between these architectures may depend on specific application requirements and computational resources.
Vision Transformers (ViTs) demonstrate superior performance over Convolutional Neural Networks (CNNs) in specific scenarios, particularly in tasks requiring the capture of global relationships and long-range dependencies. This advantage stems from their unique architecture and mechanisms. ## Enhanced Global Context Capture - ViTs utilize self-attention mechanisms, allowing them to effectively capture global relationships within images, which is particularly beneficial in complex tasks like land cover classification and domain-specific applications. - In a comparative study, ViTs achieved higher accuracy (0.81) than CNNs (0.64) in unseen domain-specific tasks, showcasing their ability to generalize better to novel problems. ## Efficient Feature Integration - Hybrid models, such as the Hybrid Network Transformer (Hyneter), combine local and global feature extraction, outperforming traditional CNNs in object detection tasks by significant margins. - ViTs can be optimized for efficiency, balancing the number of parameters and computational costs, which enhances their deployment in real-world applications. While ViTs excel in capturing global context and adapting to new tasks, they may still struggle with small object detection compared to CNNs, indicating that the choice of architecture should be task-dependent.
Land use and land cover (LULC) classification significantly influences urban planning and development by providing essential data for informed decision-making. The integration of advanced remote sensing technologies and deep learning methodologies enhances the accuracy and efficiency of LULC classification, which is crucial for effective urban management. ## Importance of Accurate Classification - **Urban Planning**: Accurate LULC classification informs zoning laws, infrastructure development, and resource allocation, ensuring sustainable urban growth. - **Environmental Monitoring**: It aids in tracking environmental changes, facilitating timely interventions for urban sustainability. ## Technological Advancements - **Deep Learning Techniques**: The use of convolutional neural networks (CNNs) and transfer learning has improved classification accuracy, achieving up to 92% accuracy in urban contexts. - **Remote Sensing Integration**: Combining remote sensing with AI technologies provides real-time data, enhancing urban planning efficiency. While the advancements in LULC classification present numerous benefits, challenges remain, such as the need for large labeled datasets and the potential for inaccuracies in traditional methods. Addressing these issues is vital for maximizing the impact of LULC classification on urban development.
Educational resources and simple solutions for your research journey
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Decoding the Scope and Delimitations of the Study in Research
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Scope and delimitations of the study are two essential elements of a research paper or thesis that help to contextualize and convey the focus and boundaries of a research study. This allows readers to understand the research focus and the kind of information to expect. For researchers, especially students and early career researchers, understanding the meaning and purpose of the scope and delimitation of a study is crucial to craft a well-defined and impactful research project. In this article, we delve into the core concepts of scope and delimitation in a study, providing insightful examples, and practical tips on how to effectively incorporate them into your research endeavors.
Table of Contents
What is scope and delimitation in research
The scope of a research paper explains the context and framework for the study, outlines the extent, variables, or dimensions that will be investigated, and provides details of the parameters within which the study is conducted. Delimitations in research , on the other hand, refer to the limitations imposed on the study. It identifies aspects of the topic that will not be covered in the research, conveys why these choices were made, and how this will affect the outcome of the research. By narrowing down the scope and defining delimitations, researchers can ensure focused research and avoid pitfalls, which ensures the study remains feasible and attainable.
Example of scope and delimitation of a study
A researcher might want to study the effects of regular physical exercise on the health of senior citizens. This would be the broad scope of the study, after which the researcher would refine the scope by excluding specific groups of senior citizens, perhaps based on their age, gender, geographical location, cultural influences, and sample sizes. These then, would form the delimitations of the study; in other words, elements that describe the boundaries of the research.
The purpose of scope and delimitation in a study
The purpose of scope and delimitation in a study is to establish clear boundaries and focus for the research. This allows researchers to avoid ambiguity, set achievable objectives, and manage their project efficiently, ultimately leading to more credible and meaningful findings in their study. The scope and delimitation of a study serve several important purposes, including:
- Establishing clarity: Clearly defining the scope and delimitation of a study helps researchers and readers alike understand the boundaries of the investigation and what to expect from it.
- Focus and relevance: By setting the scope, researchers can concentrate on specific research questions, preventing the study from becoming too broad or irrelevant.
- Feasibility: Delimitations of the study prevent researchers from taking on too unrealistic or unmanageable tasks, making the research more achievable.
- Avoiding ambiguity: A well-defined scope and delimitation of the study minimizes any confusion or misinterpretation regarding the research objectives and methods.
Given the importance of both the scope and delimitations of a study, it is imperative to ensure that they are mentioned early on in the research manuscript. Most experts agree that the scope of research should be mentioned as part of the introduction and the delimitations must be mentioned as part of the methods section. Now that we’ve covered the scope and delimitation meaning and purpose, we look at how to write each of these sections.
How to write the scope of the study in research
When writing the scope of the study, remain focused on what you hope to achieve. Broadening the scope too much might make it too generic while narrowing it down too much may affect the way it would be interpreted. Ensure the scope of the study is clear, concise and accurate. Conduct a thorough literature review to understand existing literature, which will help identify gaps and refine the scope of your study.
It is helpful if you structure the scope in a way that answers the Six Ws – questions whose answers are considered basic in information-gathering.
Why: State the purpose of the research by articulating the research objectives and questions you aim to address in your study.
What: Outline the specific topic to be studied, while mentioning the variables, concepts, or aspects central to your research; these will define the extent of your study.
Where: Provide the setting or geographical location where the research study will be conducted.
When : Mention the specific timeframe within which the research data will be collected.
Who : Specify the sample size for the study and the profile of the population they will be drawn from.
How : Explain the research methodology, research design, and tools and analysis techniques.
How to write the delimitations of a study in research
When writing the delimitations of the study, researchers must provide all the details clearly and precisely. Writing the delimitations of the study requires a systematic approach to narrow down the research’s focus and establish boundaries. Follow these steps to craft delimitations effectively:
- Clearly understand the research objectives and questions you intend to address in your study.
- Conduct a comprehensive literature review to identify gaps and areas that have already been extensively covered. This helps to avoid redundancies and home in on a unique issue.
- Clearly state what aspects, variables, or factors you will be excluding in your research; mention available alternatives, if any, and why these alternatives were rejected.
- Explain how you the delimitations were set, and they contribute to the feasibility and relevance of your study, and how they align with the research objectives.
- Be sure to acknowledge limitations in your research, such as constraints related to time, resources, or data availability.
Being transparent ensures credibility, while explaining why the delimitations of your study could not be overcome with standard research methods backed up by scientific evidence can help readers understand the context better.
Differentiating between delimitations and limitations
Most early career researchers get confused and often use these two terms interchangeably which is wrong. Delimitations of a study refer to the set boundaries and specific parameters within which the research is carried out. They help narrow down your focus and makes it more relevant to what you are trying to prove.
Meanwhile, limitations in a study refer to the validity and reliability of the research being conducted. They are those elements of your study that are usually out of your immediate control but are still able to affect your findings in some way. In other words, limitation are potential weaknesses of your research.
In conclusion, scope and delimitation of a study are vital elements that shape the trajectory of your research study. The above explanations will have hopefully helped you better understand the scope and delimitations meaning, purpose, and importance in crafting focused, feasible, and impactful research studies. Be sure to follow the simple techniques to write the scope and delimitations of the study to embark on your research journey with clarity and confidence. Happy researching!
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Scope and Delimitations in Research
Delimitations are the boundaries that the researcher sets in a research study, deciding what to include and what to exclude. They help to narrow down the study and make it more manageable and relevant to the research goal.
Updated on October 19, 2022
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All scientific research has boundaries, whether or not the authors clearly explain them. Your study's scope and delimitations are the sections where you define the broader parameters and boundaries of your research.
The scope details what your study will explore, such as the target population, extent, or study duration. Delimitations are factors and variables not included in the study.
Scope and delimitations are not methodological shortcomings; they're always under your control. Discussing these is essential because doing so shows that your project is manageable and scientifically sound.
This article covers:
- What's meant by “scope” and “delimitations”
- Why these are integral components of every study
- How and where to actually write about scope and delimitations in your manuscript
- Examples of scope and delimitations from published studies
What is the scope in a research paper?
Simply put, the scope is the domain of your research. It describes the extent to which the research question will be explored in your study.
Articulating your study's scope early on helps you make your research question focused and realistic.
It also helps decide what data you need to collect (and, therefore, what data collection tools you need to design). Getting this right is vital for both academic articles and funding applications.
What are delimitations in a research paper?
Delimitations are those factors or aspects of the research area that you'll exclude from your research. The scope and delimitations of the study are intimately linked.
Essentially, delimitations form a more detailed and narrowed-down formulation of the scope in terms of exclusion. The delimitations explain what was (intentionally) not considered within the given piece of research.
Scope and delimitations examples
Use the following examples provided by our expert PhD editors as a reference when coming up with your own scope and delimitations.
Scope example
Your research question is, “What is the impact of bullying on the mental health of adolescents?” This topic, on its own, doesn't say much about what's being investigated.
The scope, for example, could encompass:
- Variables: “bullying” (dependent variable), “mental health” (independent variable), and ways of defining or measuring them
- Bullying type: Both face-to-face and cyberbullying
- Target population: Adolescents aged 12–17
- Geographical coverage: France or only one specific town in France
Delimitations example
Look back at the previous example.
Exploring the adverse effects of bullying on adolescents' mental health is a preliminary delimitation. This one was chosen from among many possible research questions (e.g., the impact of bullying on suicide rates, or children or adults).
Delimiting factors could include:
- Research design : Mixed-methods research, including thematic analysis of semi-structured interviews and statistical analysis of a survey
- Timeframe : Data collection to run for 3 months
- Population size : 100 survey participants; 15 interviewees
- Recruitment of participants : Quota sampling (aiming for specific portions of men, women, ethnic minority students etc.)
We can see that every choice you make in planning and conducting your research inevitably excludes other possible options.
What's the difference between limitations and delimitations?
Delimitations and limitations are entirely different, although they often get mixed up. These are the main differences:
![the research location meaning the research location meaning](https://prismic-io.s3.amazonaws.com/aje-cms-production/scope-and-delimitations-in-research-chart1.png)
This chart explains the difference between delimitations and limitations. Delimitations are the boundaries of the study while the limitations are the characteristics of the research design or methodology.
Delimitations encompass the elements outside of the boundaries you've set and depends on your decision of what yo include and exclude. On the flip side, limitations are the elements outside of your control, such as:
- limited financial resources
- unplanned work or expenses
- unexpected events (for example, the COVID-19 pandemic)
- time constraints
- lack of technology/instruments
- unavailable evidence or previous research on the topic
Delimitations involve narrowing your study to make it more manageable and relevant to what you're trying to prove. Limitations influence the validity and reliability of your research findings. Limitations are seen as potential weaknesses in your research.
Example of the differences
To clarify these differences, go back to the limitations of the earlier example.
Limitations could comprise:
- Sample size : Not large enough to provide generalizable conclusions.
- Sampling approach : Non-probability sampling has increased bias risk. For instance, the researchers might not manage to capture the experiences of ethnic minority students.
- Methodological pitfalls : Research participants from an urban area (Paris) are likely to be more advantaged than students in rural areas. A study exploring the latter's experiences will probably yield very different findings.
Where do you write the scope and delimitations, and why?
It can be surprisingly empowering to realize you're restricted when conducting scholarly research. But this realization also makes writing up your research easier to grasp and makes it easier to see its limits and the expectations placed on it. Properly revealing this information serves your field and the greater scientific community.
Openly (but briefly) acknowledge the scope and delimitations of your study early on. The Abstract and Introduction sections are good places to set the parameters of your paper.
Next, discuss the scope and delimitations in greater detail in the Methods section. You'll need to do this to justify your methodological approach and data collection instruments, as well as analyses
At this point, spell out why these delimitations were set. What alternative options did you consider? Why did you reject alternatives? What could your study not address?
Let's say you're gathering data that can be derived from different but related experiments. You must convince the reader that the one you selected best suits your research question.
Finally, a solid paper will return to the scope and delimitations in the Findings or Discussion section. Doing so helps readers contextualize and interpret findings because the study's scope and methods influence the results.
For instance, agricultural field experiments carried out under irrigated conditions yield different results from experiments carried out without irrigation.
Being transparent about the scope and any outstanding issues increases your research's credibility and objectivity. It helps other researchers replicate your study and advance scientific understanding of the same topic (e.g., by adopting a different approach).
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How do you write the scope and delimitations?
Define the scope and delimitations of your study before collecting data. This is critical. This step should be part of your research project planning.
Answering the following questions will help you address your scope and delimitations clearly and convincingly.
- What are your study's aims and objectives?
- Why did you carry out the study?
- What was the exact topic under investigation?
- Which factors and variables were included? And state why specific variables were omitted from the research scope.
- Who or what did the study explore? What was the target population?
- What was the study's location (geographical area) or setting (e.g., laboratory)?
- What was the timeframe within which you collected your data ?
- Consider a study exploring the differences between identical twins who were raised together versus identical twins who weren't. The data collection might span 5, 10, or more years.
- A study exploring a new immigration policy will cover the period since the policy came into effect and the present moment.
- How was the research conducted (research design)?
- Experimental research, qualitative, quantitative, or mixed-methods research, literature review, etc.
- What data collection tools and analysis techniques were used? e.g., If you chose quantitative methods, which statistical analysis techniques and software did you use?
- What did you find?
- What did you conclude?
Useful vocabulary for scope and delimitations
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When explaining both the scope and delimitations, it's important to use the proper language to clearly state each.
For the scope , use the following language:
- This study focuses on/considers/investigates/covers the following:
- This study aims to . . . / Here, we aim to show . . . / In this study, we . . .
- The overall objective of the research is . . . / Our objective is to . . .
When stating the delimitations, use the following language:
- This [ . . . ] will not be the focus, for it has been frequently and exhaustively discusses in earlier studies.
- To review the [ . . . ] is a task that lies outside the scope of this study.
- The following [ . . . ] has been excluded from this study . . .
- This study does not provide a complete literature review of [ . . . ]. Instead, it draws on selected pertinent studies [ . . . ]
Analysis of a published scope
In one example, Simione and Gnagnarella (2020) compared the psychological and behavioral impact of COVID-19 on Italy's health workers and general population.
Here's a breakdown of the study's scope into smaller chunks and discussion of what works and why.
Also notable is that this study's delimitations include references to:
- Recruitment of participants: Convenience sampling
- Demographic characteristics of study participants: Age, sex, etc.
- Measurements methods: E.g., the death anxiety scale of the Existential Concerns Questionnaire (ECQ; van Bruggen et al., 2017) etc.
- Data analysis tool: The statistical software R
Analysis of published scope and delimitations
Scope of the study : Johnsson et al. (2019) explored the effect of in-hospital physiotherapy on postoperative physical capacity, physical activity, and lung function in patients who underwent lung cancer surgery.
The delimitations narrowed down the scope as follows:
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Snowdon C, Brocklehurst P, Tasker R, et al. Death, bereavement and randomised controlled trials (BRACELET): a methodological study of policy and practice in neonatal and paediatric intensive care trials. Southampton (UK): NIHR Journals Library; 2014 Jul. (Health Technology Assessment, No. 18.42.)
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Death, bereavement and randomised controlled trials (BRACELET): a methodological study of policy and practice in neonatal and paediatric intensive care trials.
Chapter 5 the research setting.
- The importance of context
A central feature of qualitative research is the examination of the context in which a phenomenon is situated, experienced and constructed, and contextualisation is one of the standards by which qualitative studies are judged. 112 , 113 This can involve a relatively quick description of key features of a given setting to orientate the reader, or it can be part of the analysis itself, with description providing the foundation for later conceptualisation of the data. 114 At the most extreme end of the methodological spectrum, some anthropologists immerse themselves as participants in their setting of interest, seeking to understand through direct experience the multidimensional complexity of its workings and effects.
Context is not just the backdrop against which interesting experiences occur; it is a collection of shaping forces that affect experiences in subtle and not-so-subtle ways. It is an environment, an atmosphere perhaps, which is integrated into personal narratives, experienced, interpreted and reinterpreted over time. Attempts to understand a context or setting, and the responses it engenders, can be challenging, as some elements are clearly evident but others are less easily discernable, especially perhaps to those involved. For the BRACELET study this task is complicated by the fact that it effectively considers multiple settings in the form of five NIC RCTs, each viewed from multiple perspectives. Each trial has its own particular set of circumstances and operates in unique ways. For this study then it is appropriate to consider contexts within contexts.
This does, however, raise the methodological question of whether analysis of unique situations can illuminate other situations, a question that has its parallel in the issue of transferability of results for quantitative research. Some qualitative researchers argue that it is not the responsibility of the researcher to address comparability or transferability of qualitative research findings as the researcher sets up only the ‘sending context’; the reader considers the ‘receiving context’, working out from detailed and rich descriptions how much of the research findings can be applied to their context of interest. 113 In the BRACELET study, the involvement of five NIC RCTs helps in this matter, increasing the receiving range, but it also adds to the complexity of the task. Although exploring and examining multidimensional contexts is a complex endeavour, it increases the value of the research as it has allowed the BRACELET study team to address both trial-specific and comparative questions.
In this chapter we consider in detail particular elements of the larger context in which trials are developed and implemented, and within that larger context explore key aspects of the design and conduct of the five trials. Data are drawn from information gathered during the course of conducting the study, from the NIC RCT publications and from some of the interviews with senior clinicians and trial team members. The aim of this chapter is to develop insights into the research settings of the core trials as products of a NIC research community and as shaping forces that drive and mediate personal experiences. This will provide a basis for the presentation of qualitative data, which will describe and explore those experiences in later chapters. We will return to the task of contextualising the data relating to parental experiences around the birth and care of their babies in Chapter 6 , where the NICU into which research is introduced will be described.
One way of contextualising a phenomenon is to use ‘thick description’ 115 to give a sense of the sample, and to convey the fine detail and texture of the setting. This allows researchers’ own impressions, based on information and details gathered in the field, and interviewees’ own words to be used to promote a sense of their particular insights and understandings. Both strategies give greater depth to the account of the research settings considered in the BRACELET study, the background and foreground into which NIC RCTs are introduced.
- Research in neonatal intensive care
The relevance of specialty
Different specialties in medicine are thought to have their own features and characteristics, some of which have been the focus of in-depth study. A number of researchers have set out to understand the environment and ways of working of a specialty, such as Bosk 116 on an American genetic clinic; Atkinson 117 on the work of UK haematologists; Smith and colleagues 118 on the acquisition of expertise amongst UK anaesthetists; and Mesman 119 on practice in Dutch NIC. They have also explored the ways in which a subgroup in a specialty might function in the light of a specific purpose or context, for instance surgical teams working in a war zone. 120
How a specialty responds to and manages its research has not been explored for many areas of medicine. When such data exist they can be helpful indicators of cultures within cultures that can grow up around research, offering the opportunity to parallel or draw contrasts with other specialties. One area where there are useful data on this topic is surgery, where the use of RCTs is not particularly common, 121 – 123 and where concern has been expressed about the standard of research that is produced. 124 , 125 Some of the difficulties identified by studies in this setting relate to particular challenges of working with a research protocol in surgery, for instance blinding is difficult 126 and concerns exist that variations in the skills of different surgeons may affect delivery of a trial intervention, undermining faith in RCTs as useful tools in surgical research. 127 A disinclination among surgeons to embrace the concept of uncertainty that underpin trials methods and ethics is also thought to be a barrier to research. 128 These attitudes may be changing as support for RCTs has been shown among younger surgeons who will gradually gain precedence in the field. 129 , 130
It seems reasonable to suggest that there is a link between the features of a research culture and experiences of research collaboration and participation. Where RCTs are less common, and where practitioners are less familiar with or unsupportive of their science and their conduct, this will shape the ways in which trials are implemented, and how they are implemented, in turn, will affect how they are experienced. A useful starting point for the BRACELET study is therefore to consider how RCTs are developed and run in NIC.
The first data from the BRACELET study that gave some sense of research in this field came from Phase I, in which differences between the NIC and PIC settings were evident. There were more NIC RCTs overall and they involved collaboration with a large network of NICUs across the UK. They were more likely than the PIC RCTs to be initiated within the UK (89% of the NIC RCTs compared with 50% of the PIC RCTs were UK led) and most of international NIC trials, including the TOBY and INIS studies (two of the BRACELET core trials), were initiated and co-ordinated in the UK, with international partners joining the UK-led venture (6/10, were UK led). In the PIC setting the opposite was true; a minority of trials ( n = 2/10) were initiated and co-ordinated within the UK, and PICUs more commonly joined international trials run from outside the UK. Some of the larger NIC trials were co-ordinated through an experienced CTU (NPEU) and drew on the support of substantial teams of clinical and non-clinical experts in their TSCs and DMCs. Single-centre RCTs were carried out in both NIC and PIC settings in the same proportions (one-third of trials for each) and these trials could not draw on the same infrastructure and degree of support.
These differences in part reflect the longer history of NIC, for which a larger number of clinical centres have been established and where there has been more time for research to be integrated into practice. PIC is a relatively new area of paediatrics, and paediatric intensivists are members of a relatively new specialism, but as this specialty grows its research profile may well change: the recently completed CHiP trial is a landmark PIC RCT, the first large UK-led collaborative trial to be carried out in multiple UK centres. 131
The data that describe the profile of NIC RCTs identified in Phase I suggest a very active and committed research community, but it should be pointed out that much of the research work was concentrated in a subgroup of NICUs. There were many NICUs that were not involved in research, and even among those considered to be research-active according to the BRACELET study definition, i.e. they recruited at least one baby or child to at least one RCT in the 5-year period, many recruited rarely or sporadically and were not major contributors to research.
One of the primary informants, Philip, a senior clinical trials investigator, was well placed to give a sense of this uneven profile of research. He argued that the recent historical roots of neonatology have produced a research-orientated culture and community that is ‘ extremely familiar with trials ’ but that this did not necessarily cut across all of NIC:
[It’s not that long ago that neonatologists] ventilated the first baby . . . whereas if you think of [obstetrics] to a large extent practices have not changed for a very long time. We’ve been doing caesarean sections for a very long time, we’ve been doing forceps for a very, very long time. You know, there hasn’t been the same rate of change, whereas for neonatology, from ventilating the first baby and not being able to keep [any baby] under twenty-eight weeks alive to where we are now, has been a very rapid rate of change in an environment where there’s been a greater appreciation of evidence and different methodologies to get that. So neonatologists, I think, see the benefits of this research on their practice and are continuing to see that because there’s, there’s always new things to be done and evaluated and I think that’s just perhaps not the case in some other specialties . . . When you go into a room of neonatologists to talk about trials you often don’t have to start from the basic . . . You’re not constantly justifying why randomisation is important and why the last three trials . . . could produce no useful results . . . A lot of their practices have been determined by a trial, they’re very pro-trial, they’re very familiar with the methodology; they think they’re a good idea . . . You know there are so many neonatal units in this country who will be taking part in three or four trials at any one time and lots of other studies at the same time. I think they really see the neonatal unit as a place where clinical research really should be done to improve the care that they give ‘cos they’ve got real examples of where it has improved the care that they’ve given . . . It’s not universal, and there’ll be some neonatal units who’ve probably never taken part in research . . . some neonatal units, particularly Level 2 neonatal units [which] are staffed by paediatricians with an interest in neonatology as opposed to dedicated neonatologists, and I think that’s important to separate those two out.
The Phase I data suggest this same gradation of involvement in research, and this adds emphasis to the value of focusing closer in on the core trials and their core centres.
The neonatal core trials community
Randomised controlled trials are produced and implemented within communities of varying sizes – some local, some national and some international. The BRACELET study sample includes individuals and teams with experience in each of these dimensions, and so gives a useful window into the workings of the larger NIC RCTs community. The sample is bounded, however, in methodological terms by its involvement in the five core trials and it is an artefact of the BRACELET study method of recruitment to suggest that they are members of an actual ‘core trials community’. Nevertheless, it is helpful to conceptualise the 58 interviewees as forming such a collective, as collectively they have produced and shaped the core trials. In many respects the sample is highly connected as many of the interviewees are longstanding colleagues within and outwith research. At the same time, the sample involves some interviewees with few connections other than their core trial team role. The sampling approach has brought in senior triallists who have helped to drive forward NIC research, but it has also drawn in several interviewees who do not work in NIC medicine at all: they are clinicians in other specialties, statisticians, lay representatives, who are trial team members because of their particular expertise and experience. The interviewees are therefore both connected and separate, they form groups around a core trial but their interest and influence extends to other RCTs and beyond. They reflect the real constituents of trial teams but this mix and range of contributions to individual trials has rarely been tapped.
Useful information about the approach to RCTs in the core trial community started to emerge in preparation for the Phase II interviews, when the distribution of clinicians and trial team members across the trials suggested a highly collaborative field. This was confirmed as the sample was recruited. The extent of the interconnection of roles and responsibilities across the RCTs, as described in Chapter 6 , was effectively a finding in its own right. Some of the core trial team members took on multiple roles in their trials: 15/37 recruiting clinicians also had senior roles in the same trials. These were largely investigators recruiting to their ‘own’ RCT. The collaborative links across trials were also important, demonstrating how they draw on available experience and expertise in the wider research community. In fact the professional demographic of the sample as a whole gives an indication of the high level of clinical and research-related expertise that exists in this community. The sample of 58 individuals includes 17 professors (12 of whom are neonatologists, two are clinical academics in specialties other than neonatology, and three are non-clinical academic statisticians), and 21 non-professorial consultants. Eleven interviews were carried out with members of core trial DMCs. The invitation to serve on a DMC indicates a level of expertise and esteem that members had often accrued through their involvement with major RCTs.
The BRACELET study sample therefore highlights the experienced, multidisciplinary and interconnected nature of the core trial community, and demonstrates the well developed team-based infrastructure that has been established for some of the major trials it has generated.
Academic culture and research in the core centres
The BRACELET study sample includes a number of senior academic clinicians who have witnessed advances and some setbacks in NIC during their own careers. Some had been involved in landmark RCTs and took pride in the developments achieved. At least one senior academic clinician was interviewed in each of the core centres. Each was a professor in NIC medicine and had multiple roles in one or more of the core trials. They all acted as a recruiting clinician, as well as a trial team member and they therefore span every category in the BRACELET study clinician and trial team member sample (core trial team member, recruiting clinician, core centre staff, clinician and academic). They were useful informants as they not only described the research ethos that they felt existed in their centres, but also were able to place this in the larger context of the NIC research community.
Harvey, one of these senior academic clinicians is an emeritus professor at core centre A and had been an investigator for two of the core trials. He gave a sense of how a NIC research culture had grown out of neonatology’s earlier links with obstetrics, and how the new specialty, free of received wisdom, was able to be critical of its own new clinical practices.
Obstetricians way back were very interested in research . . . and how to manage placenta praevia and develop the very conservative management of that, which saved lots of women’s lives. Well, I suppose that was way back in the 1940s. I guess that since neonatal intensive care has been set up we’ve been interested in research – it’s a fairly new thing set up in the 1970s and I guess many of us had a sort of critical mind and didn’t want to adopt techniques and interventions until they’d been properly evaluated. And I think we’ve tried to keep that going now as a routine. I hope that the next generation of neonatologists will keep it going although there are pressures now on doing research.
He felt that the way that research was run in centre A had changed over the years, with a lessening emphasis on academic medicine.
Traditionally we’ve done a lot of research here and we’ve been the co-ordinating centre for many trials. I guess more lately we’ve been collaborators within other’s research. The real difficulty now is to get young training paediatricians to be interested in research, to take 2 years out to do an MD or 3 years to do a PhD. They get poor funds for that, they don’t see any benefit at the end of that for their career. They get promoted probably far more quickly for being able to do a clinical job than to have an academic interest or research interest.
A number of interviewees with a range of roles raised the issue of academic medicine, and research in particular, becoming increasingly difficult, but this did not appear to diminish the sense of its importance. Another emeritus professor, Noel, from core centre B, who sat on a DMC for one of the core trials, described his NICU as having ‘a very strong academic tradition:’
It probably has more papers than virtually any other NICU . . . so it’s very strong academically and clinically . . . The two previous Chairs . . . although general paediatricians, had a research interest in the newborn, both of them. That’s 25 years ago. And I was appointed and my main interest was neonatology, so it continued and I think gathered strength, and all the clinicians, whether they have academic appointments or not, publish here.
He felt that his centre has ‘a better recruitment to clinical trials probably than any other unit in the UK’ and mentioned several RCTs for which they had been the highest UK recruiters. He said that ‘the fact that people are academic is the major stimulus’ but also felt that the collegiate ethos among their consultants was an important factor, as was the fact that they organised recruitment so that it was carried out ‘almost invariably by the principal investigator or the research worker on the trial, rather than the registrar who happens to be on’.
This sense of a local academic culture driving research was also evident in the interview with Roger, a senior triallist and NIC consultant at core centre C. Roger was an investigator for one of the core trials, sat on the TSC for another, and on the DMCs for a further two core trials. He said that he hoped that his centre had ‘ a reputation for being scientifically based and research centred ’ and that the results of research were fed directly back into practice at core centre C.
I like to think that we have an evidence-based unit. For instance, all the consultants have higher degrees, which is unique in the country I think. All our protocols, as far as they can be, are evidenced based. And there’s a protocol for just about everything . . . in this place. And underneath each protocol, it has the references, so you can go and look up where the evidence came from, and we think this helps the juniors particularly to understand that what they’re doing isn’t just on the whim of a consultant, but it is actually based on some sort of science. Where we have protocols that are not evidence based, because there isn’t any evidence, we state it, we actually say that there is no evidence to support this, but this is what we’re doing. All the consultants agree to use the same protocols, so there’s no change from one consultant to another, and most of the consultants, well they’ve all been involved in research themselves.
Over the course of his career it had become increasingly important to Roger that the evidence base was directly applicable to the babies in his care. He described how he and his colleagues would evaluate a protocol and if necessary ‘made local adjustments’ to fit their practice and population. The way they now carried out research and applied its results was very different from the work that he had carried out himself many years previously, which had little application to practice or population. He described it as ‘pretty well pure science’.
[It] probably had no immediate benefit as far as the patients were concerned. It was almost physiology research we were doing with some of these children. The stuff that we’re involved in now is all with a fairly practical aim in sight . . . I think the sort of work that we’ve been engaged with here for the last 20 years has almost all been with an . . . immediate clinical application if the right answer comes up.
Both Noel and Roger discussed the importance of research collaboration, and both took on multiple roles in the core trials. Dominic, a NIC consultant and professor at core centre D, and investigator for one of the core trials, presented a different model of research:
When I first started [here] all the neonatologists were all academics. Now, that was unsustainable as the complexity of the NHS systems grew, and now it’s divided out into NHS and academic senior staff. But the culture’s still the same . . . There’s a very strong research culture here, and it’s something that everybody buys into.
He explained that much of the research that they carry out is initiated themselves:
We are a large academic unit. We have a lot of funding and therefore a large responsibility . . . and so we’re very self-driven. We – we are initiators rather than participators. We don’t mind participating, but actually one of the problems we have is the . . . opportunity cost of every trial. So every trial we go into means that that baby may be unavailable for another one so we have to be careful of what we enter. So we’re almost entirely self-starting in our research.
While Noel and Roger had described a collegiate approach to research in their centres, with consultants proposing new research to be discussed at a group level, Dominic described a different approach to the process of deciding whether or not to collaborate in an external trial.
We’re probably not representative because by and large I decide. And when I’ve decided I’ll talk to my consultant colleagues about it, and my senior lecturer colleagues about it. It’s a bit autocratic in that sense, but then we are a very single-mindedly driven group . . . Our goal as a research group . . . is to reduce the number of children that suffer brain damage and survive with brain damage. That’s our goal and we’re very focused on that, and we do a lot of things around that field. We’re not against being involved with other people’s trials.
Nicholas, a professor of neonatal medicine who was also an investigator in one of the core trials, described enthusiasm for collaboration in core centre E and the importance of integrating the conduct of research into everyday care.
We recruited highly to the oscillation trial, we recruited quite well to TOBY, we recruited to INIS and other things, and with minimum problems actually . . . One of the things we used to pride ourselves on [was that] we would always have four or five trials running at any one time . . . [P]arents would say to each other, you know, ‘which trial are you in?’ So it was a matter of fact we were doing that. That was part of our culture, part of the way we did things, and I think people were very accepting of it . . . They were just part of the unit culture so . . . it wasn’t a big deal to be on a trial, and that was the whole point about trying to run the unit that way, because you didn’t want it to be a big deal. You wanted it to be something that . . . you could discuss rationally with parents in the knowledge that, you know, these were things you did all the time. [It was] part of the philosophy of what we do.
These thoughts on the local research ethos from senior clinicians and triallists give a flavour of some of the different priorities and conditions that exist across this setting. They give a sense of the importance of academic medicine as part of a tradition and in driving ongoing research and practice; they show how research can shape and be integrated into practice, mapping on to care so that it becomes a normal part of the work of a NICU, and how the evidence that is produced then feeds back into future clinical practice in the form of revisions to the evidence base.
The core trials were a major part of the research field in which these clinicians and triallists were involved. In order to understand the views and experiences of those involved in these trials it is important that they are not treated as a single entity (RCTs), but that the particular features of each trial and the circumstances that were created are described and understood.
Narrative description of core trials
Although RCTs may share some methodological features such as randomisation or blinding, they cannot be treated in generic terms. Each trial has unique features. The conditions that are created around a trial stem from how it is set up, how it functions and how it is perceived and experienced by those involved. These conditions are central to a study such as BRACELET that seeks to understand practice and provision for parents and other participants. A first step towards understanding the shared and the unique features of the core trials is to describe their development, characteristics and something of the circumstances they create for clinicians, parents and the babies involved. The core trials considered in detail in the BRACELET study are INIS, TOBY, PROGRAMS, BOOST-II UK and the ExPN feeding study. They are considered, in turn, below.
International Neonatal Immunotherapy Study: non-specific intravenous immunoglobulin therapy for suspected or proven neonatal sepsis 95 , 96
Infection is a serious problem in NIC where it is a major cause of death and long-term disability. Immunoglobulin, a blood product containing human antibodies, was a promising treatment because newborn babies, those born preterm, have low levels of immunoglobulin and antibodies necessary for fighting infection. A number of RCTs had suggested that it may be helpful in the treatment of babies with a serious infection, but in order to demonstrate an effect on a common condition a large trial was needed. An international collaboration was set up and the resulting trial, INIS, recruited in 113 centres in nine countries. INIS was a placebo-controlled, double-blind randomised trial in which babies with a proven or suspected infection who were receiving antibiotics were allocated either to receive two doses of intravenous immunoglobulin or two doses of placebo. The trial primary outcome measure was a composite of death and disability at 2 years of age.
The majority of the babies involved in INIS were preterm. In each case, concern would be developing about the possibility or actuality of a developing infection. If a baby was showing signs of a serious infection then clinicians and parents would be aware of the threat to life that this represented. According to the trial protocol, enrolment could take place at any time during NICU stay and up to 28 days from expected date of delivery for babies readmitted with suspected or proven infection; this suggests that time would be available for discussion but, in fact, the likelihood of an infection meant that treatment should be initiated as soon as possible after diagnosis, and this introduced a degree of urgency into the enrolment process. The inclusion of ‘suspected infection’ in the eligibility criteria deliberately allowed clinicians a degree of interpretation over recruitment, and this resulted in considerable variation between recruiting centres. Some centres enrolled babies as they initiated antibiotic treatment on suspicion of an infection, but others did not do so unless they had a definite diagnosis. In some centres, this resulted in recruitment of babies at the sicker end of the spectrum permitted within the protocol. The intervention (two doses of immunoglobulin or placebo) was given using the intravenous access that was already in place. As the trial was double blind, neither clinicians nor parents knew whether or not a baby received the intervention.
The INIS trial was the largest trial identified in Phase I of the BRACELET study, and by the time the results were reported, it had recruited 3493 babies. (The figures reported for all of the core trials differ from figures collected for Phase I of the BRACELET study in that they refer to the whole trial and not just the 5-year period of interest, and are not restricted to recruitment in the UK.) Of these, 628 had died by 2 years, a mortality rate of 18.1%. (Mortality rates have been calculated from the number of recruits and the number of deaths reported in the trial papers. These figures do not necessarily appear in the papers themselves.) The trial showed no significant effect of the intervention. The results with 2-year follow-up data were published in 2011 (4–10 years since recruitment). The trial team had maintained contact with parents of surviving babies for follow-up purposes but not with bereaved parents. Results were sent to parents who had indicated at the 2-year follow-up that they wanted to receive them. All bereaved parents were contacted by post and offered the results. Not all parents were still living at the address registered with the trial at the time of their enrolment and it is therefore not known how many parents received this offer. All parents who received the results were given the option of being unblinded to their baby’s trial allocation.
TOBY: whole-body hypothermia for the treatment of perinatal asphyxial encephalopathy 97 – 99
Babies who are born after complicated deliveries can experience a potentially damaging lack of oxygen to the brain before or during birth (perinatal asphyxia, leading to hypoxic–ischaemic encephalopathy). The brain damage they experience occurs not only at the time of oxygen deprivation, but also evolves over some hours after the event (so-called ‘secondary neuronal death’). Historically, there was little to offer these babies in terms of clinical interventions, and outcomes for encephalopathic asphyxiated babies could include a wide range of neurological sequelae (e.g. severe motor and sensory disability, cerebral palsy and neurocognitive developmental delay). In recent years, it was becoming clear that that there was a potential time window after the initiating event in which it may be possible to intervene to prevent further damage from happening. Growing interest in the neuroprotective potential for hypothermia led to RCTs exploring two different methods of cooling: cooling only the head was used in the CoolCap trial, 132 whereas TOBY involved whole-body cooling. TOBY assessed whether cooling term babies for 72 hours to a temperature of 33–34 °C after they had suffered perinatal asphyxia, makes a difference to their chances of recovery. Babies in the treatment arm were compared with those in a control group who were given standard NIC without cooling. The primary outcome measure was combined death or disability at 18 months of age, as there was a concern that increased survival might be at the price of increased disability.
Because of the narrow treatment window, it was important to initiate cooling as soon as possible after birth. For the intervention to start early enough, randomisation and initiation of cooling had to take place within 6 hours of birth. All babies involved in the trial were transferred to a Level 3 NICU that was able to provide the specialist ‘cooling’ therapy. For the recruiting clinicians, the pace and setting of recruitment was a challenge. The difficulties that often preceded the development of perinatal asphyxia, and the consequences for babies and families that might ensue, meant that TOBY was conducted against a potentially litigious backdrop, with obstetric teams often being the focus of queries or enquiries about mismanagement. Recruiting NIC clinicians had to enter this difficult arena at a time of extreme crisis for parents and for babies. If babies were not born in a ‘cooling’ NICU, clinicians sometimes had to travel to the referring unit, assess the baby and discuss the trial with the parents, take consent, and randomise the baby within the stipulated 6 hours. If > 6 hours elapsed the baby could not be included in the RCT, even if this process was well under way. Whatever the challenges, it was an innovative and promising area of research and interviewees often presented their involvement very positively, seeing TOBY as a cutting edge, exciting and prestigious trial.
For the parents, the trial offered different challenges. By the time it was introduced they had been through extremely difficult experiences during labour and delivery, and their baby was unexpectedly receiving NIC with an uncertain future. They had to make rapid decisions about cooling and the RCT. Cooling was not otherwise available, and if parents wanted their baby to be cooled, the only route was the 50% chance of allocation to the intervention arm. In open trials, such as TOBY, in which it is not possible to conceal allocation, where babies are critically ill and the trial intervention may offer some hope, allocation to the control arm can be a very disappointing experience for parents. 54 For TOBY, parents also had to consider the issue of transfer and possible separation; if they were not in a cooling centre their baby would be transferred to the nearest available trial NICU and this included those allocated to the control arm, who would be transferred but not cooled. For some families this would involve separation of mother and baby if the mother was too sick post delivery to be moved. It could also involve care at some distance from the parental home.
The TOBY trial recruited 325 babies, and 86 had died by the age of 18 months, a mortality rate of 26.5%. The trial showed that cooling did not reduce the combined outcome of death or severe disability but did lead to improved neurological outcomes in survivors. The results and follow-up data were published in 2009. The trial team had maintained contact with parents through newsletters and change of address cards, and all parents who had indicated that they wanted to know the outcome of the trial, including those who were bereaved, were sent the results.
PROGRAMS: Prophylactic Granulocyte–macrophage colony-stimulating factor to reduce sepsis in preterm neonates 100 , 101
Like the INIS study, the PROGRAMS study focused on the problem of infection for vulnerable preterm babies in the short and long term, but in this RCT the intervention was not aimed at treating an infection: it was intended as prophylaxis for babies at risk of developing an infection. Neonates with neutropenia, a deficit of a particular type of white blood cell (neutrophils), are more likely to develop infections and research had suggested that a protein, GM-CSF, may address this deficit and so reduce the risk of infection. PROGRAMS was described by one of the trial investigators, Nicholas, as involving a ‘ subtle ’ intervention. The effects of GM-CSF could only be observed on blood tests and it was intended to maintain rather than change a situation (i.e. not developing an infection).
Most of the babies who were eligible for the PROGRAMS study were preterm, born at < 32 weeks’ gestation, and were small for gestational age (SGA). Often growth problems would have been detected antenatally, especially for twins where one baby is often smaller than the other, so parents may well have felt concern over the well-being of their baby for some time before birth. They may have expected for some weeks that their baby would be cared for in a NICU and poor growth may have been the stimulus for an induced delivery. There was no immediate urgency for enrolment into the PROGRAMS study as babies could be recruited up to 72 hours after birth and parents could be offered time to make their decision. The PROGRAMS study involved a daily subcutaneous injection for five days, only in the intervention group. This was potentially an important consideration for parents. For SGA babies with little subcutaneous fat, injections might be a concern and a barrier to participation for some parents. Babies in the control arm had ‘usual care’ (with no placebo injections).
The PROGRAMS study recruited babies in the period 2000–6. This was a longer recruitment period than intended as the trial was stopped for 18 months because of problems with the supply of GM-CSF. In all, 280 babies were recruited and 62 died before discharge – a mortality rate of 22.1%. The trial showed no significant effect of GM-CSF on rates of infection or on 2-year outcomes. Initial results were published in 2009 and 2-year outcomes in 2012. Parents who opted to receive newsletters (whether or not they were bereaved) were informed of the 2-year results of the RCT in 2012.
BOOST-II UK: benefits of oxygen saturation targeting 104 , 105
The BOOST-II UK study also involved very preterm neonates but focused on a different aspect of care. Delivery of supplemental oxygen has long been known to be an essential element of life support for extremely sick babies, but considerable uncertainty has existed over the correct level of oxygen to deliver: too little and babies can develop respiratory or neurological problems, which threaten their survival; too much and they can develop retinopathy of prematurity, which can cause full or partial blindness. The question of where pulse oximetry haemoglobin oxygen saturation ( S pO 2 ) thresholds should be set is of particular importance as ventilatory support and supplementary oxygen are central to NIC and the question has concerned neonatologists for many years. 133 , 134 This uncertainty is reflected in the variation in practice which was identified in preparation for the trial; units reported a wide range of S pO 2 targets as their standard practice. The BOOST-II UK study was designed as part of an international collaboration between UK, Australia and New Zealand, the USA and Canada to determine whether, within this wide range of standard practice, higher or lower S pO 2 levels are better for extremely preterm babies in NIC. The collaboration included plans for a prospective meta-analysis with ongoing trials.
The BOOST-II UK study involved babies born at < 28 weeks’ gestation, who were recruited within 12 hours of birth. They were allocated to either a higher or a lower target level of S pO 2 (i.e. targeted higher levels were 91–95%, and targeted lower levels were 85–89%). To achieve blinding, the trial pulse oximeters – the devices that monitored S pO 2 – were modified by the manufacturer so that although they worked as normal when saturations levels were < 85% or > 95%, they displayed and stored a figure that had been ‘offset’ either 3% above or 3% below the true value when saturation levels were within the 85–95% range. Using the trial oximeters centres therefore aimed to maintain all recruited babies within a range of 88–92%.
It was important to start delivery of the intervention quickly and so parents were approached as near to initiation of ventilatory support as was possible. Some women were approached antenatally if they were inpatients and it was clear that their baby would be born at < 28 weeks’ gestation, giving them time to discuss and consider the trial. Parents could also be approached in the hours before preterm delivery. Unlike the INIS and PROGRAMS studies through which delivery of the trial intervention might not be witnessed by parents, in the BOOST-II UK study the trial pulse oximeter was permanently visible at the bedside.
The BOOST-II UK study recruited 973 babies by the time it was stopped. Of these, 895 babies were reported in the early publication, of whom 173 died by 36 weeks postmenstrual age, a mortality rate of 19.3%. During the course of BOOST-II UK another trial, SUPPORT (Surfactant Positive Airway Pressure and Pulse Oximetry Randomized Trial), reported its findings, 135 suggesting increased survival with higher levels of S pO 2 . An interim analysis of the BOOST-II UK data from UK, Australia and New Zealand was therefore carried out. Data were pooled with the data from the SUPPORT Trial and a significant difference in mortality between higher and lower S pO 2 targets was identified, whereupon the DMCs recommended the trials should be stopped early. Following emergency meetings of the TSCs, the BOOST-II UK studies stopped recruitment on Christmas Eve 2010, and all hospitalised babies in the trial were transferred to be nursed with non-trial oximeters and their clinicians were informed that the higher oxygen target was associated with greater survival. These initial results were published in 2011 and were communicated to all parents as a study update. (Although the primary outcome is when the children are aged 2 years, we refer to this study update hereafter as results.)
The process of communicating the results of the BOOST-II UK study was very different from those used in the TOBY and INIS studies. Because the BOOST-II UK study was stopped early, findings were made public as soon as a publication was possible. The parents recruited later in the trial will therefore have been contacted within a relatively short time since the birth (and death) of their baby. This ranged from < 1 year to 4 years for the BOOST-II UK study; for the TOBY study it was 3–7 years, and for the INIS study (which took longer to recruit) it was 4–10 years before parents received the results.
Unlike the INIS and PROGRAMS studies, which showed no statistically or clinically significant benefits or harmful effect of the trial interventions, the BOOST-II UK RCTs generated data that allowed the team of investigators to make a recommendation to their NIC colleagues. The publication acknowledged the lack of follow-up data at that point, and while waiting for the outcome of disability-free survival to be determined (expected in 2014), the publication stated that the authors considered it prudent not to target a S pO 2 of 85–89% in infants born at < 28 weeks’ gestation.
ExPN: Extremely Preterm Nutrition feeding study – Improving post-natal head growth in very preterm infants: a randomised controlled trial of hyperalimentation 102 , 103
Providing extremely preterm babies with the nutrients that they need is difficult because they may be ventilated, too sick or too immature to suck, and their digestive systems are often unable to digest milk. Fluids and nutrition are given intravenously but growth may still be slow. Clinicians at a single centre were aware that in their local population they saw babies with smaller than expected head circumference at discharge and this was attributed to postnatal growth failure. Funds were sought for a research fellow to conduct a trial assessing the impact of giving additional calories and protein on head growth compared with a standard feeding regimen, with a follow-up to consider whether this might correlate to longer-term outcomes. ExPN was driven, in part, by uncertainty over the cost–benefit ratio of giving additional calories: an increase in glucose can potentially induce a ‘diabetic’-like state, which increases both the chances of hyperglycaemia and infection. Babies receiving the intervention may then require administration of insulin and treatment of infection. Infection, especially the possibility of necrotising enterocolitis (NEC), is a major threat to such small babies, and any possible increase in infection rates would be a major concern. The trial was partially blinded: the trial assessors were unaware of the allocation but parents and clinicians administering nutrition were not blinded. This caused a number of problems for the trial, as some clinicians, sensitised to the issue of postnatal growth failure in this population as a result of the trial, may have compensated babies in the standard feeding group by giving extra calories. However, there was a clear separation between the trial groups as significantly more calories and protein were given to the intervention group.
Babies were eligible for the ExPN study if they were born at < 29 weeks’ gestation. The trial included babies at the lowest gestations to be admitted to NIC, around 24 weeks’ gestation, an extremely high-risk population born at the limit of viability. It included a substantial proportion of twins who are at greater risk of preterm delivery and growth-related complications. In some cases mothers with an identified complication, such as twin–twin transfusion, may have had a planned delivery despite the early gestation. Delivery at this gestation can be an unstoppable crisis or can be preceded by a potentially lengthy period of threatened delivery with some women as inpatients, hoping to extend their pregnancy but expecting to give birth any day. Parents were asked to consider the trial within a week of the delivery and given that time frame there was no urgency over the decision, but some parents would still be in the very difficult immediate aftermath of unexpected preterm birth.
The ExPN study differed from the other core trials in several ways. It was conducted in a single centre with all recruitment taking place locally and carried out by only two clinicians. Often several babies were enrolled into the trial at the same time and parents could discuss this with other parents, and compare information and progress. The ExPN study explored the impact of food rather than a drug, gas or a medical device as in the other core trials, and this may have affected how parents viewed the potential risks and benefits.
Between 2004 and 2007, 142 babies were recruited to the trial, of whom 33 died by 9 months postmenstrual age, a mortality rate of 23.2%. The ExPN study demonstrated no significant effect of the intervention on growth, and there was no increased incidence of NEC or other infection between the trial groups. Initial trial results and follow-up data were published in 2008 with no feedback of results to parents.
- Complexity and the core trials
Many different components are present in the narrative descriptions of the five trials. Some are unique features of a single trial, others are shared with several trials. Collectively they are extremely complex, and this reflects a real complexity that exists in NIC research where the different demands and implications of a wide range of components are worked through in practice. Research active centres take part in multiple RCTs concurrently, and experienced triallists develop their own trials while at the same time are in demand to serve as experts on those of their colleagues in the field.
For our purposes it is helpful to draw out these different components of design and management as essential contextual features so that any implications and effects that they might have can be explored. Too often, studies consider reactions to trials in broad terms, without tracking back to these source elements which can shape experiences of collaboration in clinical centres and participation for trial participants and proxies. We therefore suggest the importance of thinking about the features of the core trials in terms of three broad categories: structural, procedural and synergistic components, as defined in Table 22 . How the components of each trial fit into these categories can then be taken into account in subsequent analysis.
Structural, procedural and synergistic components of the five core trials
Structural components of the core trials
Procedural components of the core trials
Synergistic components of the core trials
The features of the core trials described above are important aspects of the context that the BRACELET study was set up to explore, and the typology of components provides a useful framework for reflection on the different elements within a RCT. It is also a basis for further exploration, as the differences between trials highlighted above suggest the value of an even closer focus on the origins, effects and implications of the methodological decisions that were made, in illuminating further the contextual similarities and differences for each of the core trials.
Trial design issues for the core trials
The differences between the RCTs are complex but they are not haphazard. They are a product of a developmental process that produces a trial protocol with a specific set of research methods. The methods defined in a protocol have to be appropriate for use in the clinical arena of NIC, as they are passed into the hands of local clinicians who then dovetail them in their clinical practice. The developmental process is iterative as explained by one of the senior trial investigators:
Although . . . you might start off with the science . . . you have to then meld that with the practicality of it . . . You don’t sit down and just design a trial and then think, ‘Now we’ve got to think about the other aspects of it.’ It goes round and round and round and all of these things get taken into account . . . That’s why you need a group. That’s why you don’t have one person like me sitting there and designing something which is impossible to run.
The core trials all involved populations of babies at high risk of death. The core trial CIs and one lead neonatologist (appointed for one of the trials as the CI was not a neonatologist) were asked how their trial methods were shaped by the likelihood of death in their target populations (pseudonyms are not used in this section of the report to break the link between comments here, in which the interviewees are potentially identifiable, and views expressed elsewhere in this report). This raised discussion of several different methodological features of the trials. Their accounts of why particular features were set as they were, and what implications they had for their trial, demonstrate a number of shaping influences on trial design. These are explored below for the following features:
- eligibility criteria
- randomisation
- management of the control group
- outcome measures.
Eligibility criteria
One of the most important issues in a RCT is who should be included and excluded from the sample. 136 How the target population is defined will determine the boundaries around the evidence that can be produced and this important consideration was discussed for two of the trials: TOBY and INIS.
In the TOBY study, this issue was central to the trial design and a high threshold of severity for eligibility was set. (Babies were eligible if they had at least a 10-minute Apgar score of ≤ 5, or a continued need for resuscitation, or acidosis within 60 minutes after birth, as well as moderate to severe encephalopathy and either hypotonia, abnormal reflexes, an absent or weak suck, or clinical seizures. In addition, they had to have abnormal background activity for at least 30 minutes or seizures on amplitude integrated electroencephalography.) The CI commented.
Study design is a very important, is critical for the success of a clinical trial, and there are rules . . . you have to follow assiduously if the trial, you know, is going to be . . . useful . . . Selection criteria, if you want, are determined by the type of trial you’re doing. In the TOBY trial this was an early-phase study, even though it was a relatively large study and went over many years. It started out at a time when. . . no previous studies had been completed so it was one of the first clinical trials . . . Although it was large enough that some people would call it a phase-three trial, [it was] in effect an early-stage trial focused on . . . a very high-risk population.
The CI felt that the trial would have been very difficult to run had it included a lower-risk population of babies, but using a more narrowly defined population also raises some difficulties. It has implications for the evidence base generated, and affects the possibility of carrying out future research with a lower-risk population. Now that the TOBY study has shown cooling to be effective in improving neurological outcomes in survivors in a high-risk population, the CI felt that a trial in a low-risk population is unlikely.
That’s a dilemma for commissioners: . . . do they have to stick to the trial protocols, or do they start widening the protocols a bit to include children who didn’t quite meet the criteria but seem to have a similar problem? . . . The problem is that the group that were not included in the trial would have a low risk of adverse events, so you’d need a very, very large trial to demonstrate a small change in that group of babies, and I think because of that many people feel it’s not feasible to do that trial.
The focus on the highest risk babies raises other issues in the running as well as the design of the trial. One issue was how to determine whether a baby at the sicker end of the spectrum should in fact be enrolled. The trial eligibility criteria were very clearly determined at the lower threshold of eligibility, but the upper threshold was less clear. Babies who were moribund were to be excluded on the grounds of futility but how this should be determined was deliberately not defined in the eligibility criteria. The CI explained that whether or not a baby is on a trajectory towards death is difficult to determine:
If the baby’s bradycardic it’s quite clear the baby’s dying, but if the baby’s circulation is fine but is otherwise completely encephalopathic, you know, is that moribund? So I did not feel I could define it so clearly.
This was a real issue for the trial and there were cases where careful judgement was required as to whether or not an extremely sick baby might be included. The CI’s explanation of this conveys something of the fraught clinical circumstances in which the trial was set, and the close interweaving of the circumstances of care into research. He described a delicate balance between the need for good science and the desire to ‘ do something ’ for an extremely compromised baby:
People wanted to try and formalise this by having specific guidance and direction and I always felt it’s actually very difficult to specify the scenarios, and that anyway neonatal clinicians are having to deal with these grey areas all the time, with uncertainty all the time. And I just wanted the attending clinician to continue to have a say. Whether they felt, ‘actually, no, I don’t think this baby should be in your trial. I think, I think this baby’s going to die, and I think we should just redirect care around that . . .’. If they thought the baby was so ill it was moribund, or likely to be moribund, they did not need to make the referral. In practice, what we found was . . . that these were difficult cases, and clinicians were very keen to try and . . . do something active . . . I’ve been called to cases in other hospitals, where the baby clearly was very poorly and no intervention was going to – could possibly do anything, where the clinician felt the right thing to do would be to have the baby in the trial.
The clinical judgement about who should and should not be referred to the trial shapes the trial population and the inferences that can be drawn from the data that are produced. In the TOBY study it was important that very sick (but not moribund) babies were included so that the trial could explore whether or not cooling was helpful for those babies, but it was important that a wider range of very sick babies should be enrolled in the trial. This was another matter for clinical judgement in the recruiting centres.
[At the] early stage . . . we were in equipoise even for the sick babies. If we didn’t recruit them we didn’t know. We had this problem in TOBY that we were likely to be referred the sickest babies initially, and . . . if you only refer the sickest babies then there was no prospect of seeing any effect of your treatment . . . If you have a trial that went on as long as TOBY did . . .[with] numbers of centres increasing dramatically over the period . . . the type of patient you get referred changes as well. Centres who referred a few patients [at the start] are likely to refer more and more patients [and] centres only just starting on often start off with the bad cases.
One of the CIs interviewed here for another core trial also had links with TOBY and commented on the borderline for eligibility and the decisions that might be made in clinical centres. He felt that they should transcend concerns about which babies should and should not be entered:
In almost all interventions, those that are slightly less than extremely sick if you like, are the ones most likely to benefit, rather than the sickest ones, because the sickest ones are always likely to die, regardless of what you do, because they’ve gone too far . . . I think that when it comes to deciding whether to put a child in a trial, we try to capture everybody who’s eligible rather than say ‘Oh we’ll do this one and not this one.’ It doesn’t always work that way . . . everybody who’s eligible really ought to be going in, people shouldn’t be picking and choosing. We try not to do that here.
This overview from the CI and the view from within a referring centre suggest a dynamic between centres and a trial that can be fixed by local policy or can change over time, and which directly shapes the progress of a trial and the evidence it can produce.
A similar phenomenon was seen in the INIS study, in which, again, interpretation of eligibility criteria was dependent on clinical judgement, which would vary from centre to centre and clinician to clinician.
The eligibility criteria for INIS is so difficult because it’s confirmed or probable sepsis where there are loads of contaminants, so . . . the severity of sickness that babies were recruited at varied a lot between centres . . . [The centres] . . . made their decisions locally about . . . at what threshold they would recruit . . . Some was quite low and some was very high as in, you know, they were expecting these babies to die and this was the sort of last chance.
The CI went on to describe how this sometimes played out in the clinical centres:
There used to be ward rounds where the PI would say, ‘Why wasn’t this baby recruited to INIS?’ ‘Well it wasn’t sick enough.’ ‘What do you mean, it wasn’t sick enough?’ ‘Well . . . the white cell counts were only this and blah, blah’. . . There were these intense debates about whether that baby was or was not sick enough and there’s no right answer to that so I think it was quite difficult.
Trials can be characterised along a continuum from a pragmatic trial, which assesses an intervention within clinical practice, and usually has broad entry criteria reflecting clinical uncertainty, and emphasising an intention-to-treat (ITT) analysis, to an explanatory trial which evaluates an intervention within more tightly controlled conditions, to assess efficacy under ideal circumstances, often emphasising a per-protocol analysis. Many trials have elements of both characteristics. The design differences between the INIS study (a pragmatic RCT that looked at immunoglobulin in the wider context of everyday practice) and the TOBY study (which could be considered to have components of an explanatory trial, as it had tightly controlled eligibility criteria) are important here. Although they both open up discussion of who is and is not eligible and whether or not enrolment in the trial was appropriate, in fact the more open nature of the eligibility criteria for the INIS study mean that a wide variety of babies were included in the trial and this was ‘ entirely compatible with the protocol’ .
Randomisation
Once eligibility is confirmed and parental permission has been given, the next step is randomisation. Issues around the management of this aspect of RCT methods was discussed for two of the trials: the ExPN and BOOST-II UK studies.
Given the inclusion of extremely preterm babies in their trials, the investigators for both studies could anticipate that a proportion of their sample would come from multiple births. As siblings would be eligible for enrolment at the same time, an important consideration was how to manage their allocation in scientific and in compassionate terms. The trials used opposite randomisation policies. In the ExPN study, twins were randomised together to ensure allocation to the same treatment, and triplets and higher-order multiples were excluded. In the BOOST-II UK study, there was no exclusion of higher-order multiples and each baby was randomised individually, thus introducing the possibility of allocation to different arms of the trial. The CI for the ExPN study explained their rationale:
I took some advice on this, statistical advice, and they said I could [randomise twins together]. What we actually did was they were stratified for gestational age and for singleton, multiple, so we could analyse them apart, as well as together, without losing randomisation. And the twins were both randomised to the same intervention, control or intervention, and the reason I did that [was that] I felt that it was difficult for parents to have one twin treated one way, and one twin treated the other way.
Given these concerns about the impact of allocation for twins on parents, one option would have been to exclude twins from the trial. This would, however, have raised issues of statistical power, and of the applicability and clinical relevance of the trial. It was important that the ExPN study population should be representative of the clinical population so that the evidence would be clinically generalisable. The ExPN study CI commented:
I certainly didn’t want to exclude twins from the study because they make up [a] quarter of our babies, so they’ve got to be included.
In the BOOST-II UK study, babies of multiple births were randomised separately. Whereas in the ExPN study this methodological decision was led by the CI, in the BOOST-II UK study the randomisation policy for the CTU for all of its trials was the determining factor. This meant that the lead neonatologist, was not directly involved in setting this policy, but he said that he was ‘totally comfortable with it’ . In the ExPN study, one of the concerns was how parents would react to different outcomes for their babies if they had been allocated to different arms of the trial. This was not seen as problematic by the lead neonatologist for the BOOST-II UK study who felt confident in the explanation that could be given to parents.
I explain to parents that whatever happens with their baby we won’t know what was the explanation for that happening because their baby will be getting a whole package of measures, only one of which will be the trial, so ultimately they’ll know what happened to their baby, they might know what the trial showed, but not all babies in one arm of the trial will have the same result and all babies in the other arm the opposite.
He also argued that an individualised approach in the trial would be commensurate with individualised care which is given outside of the trial context.
We don’t treat twins exactly the same way throughout their course. We tailor their care to meet their needs so I don’t have a problem with them being randomised differently and I haven’t really had parents’ feedback to me that they do either . . . [A] lot of people feel strongly about it and it’s a question you’re always asked when you present to people a trial that you want them to participate in, but I think that . . . the clinicians almost feel more uncomfortable about it than anything I’ve ever heard expressed by the families . . . You have just got to make a decision about your protocol and it’s going to weaken the research to randomise them as pairs.
These issues may differ in a double-blind trial such as BOOST-II UK compared with a unblinded trial such as TOBY. Blinding is discussed further in the next section.
Management of the control group
On randomisation, babies are allocated to the intervention or the control arm of the RCT. Whether or not allocation to an intervention is concealed is an important issue in trial design. 137 The core trials varied in the extent to which allocation remained concealed after randomisation; the INIS study was a placebo-controlled, double-blind trial, the BOOST-II UK study was double blind, the ExPN and PROGRAMS studies were blinded only at the outcome assessment stage, and the TOBY study was an open trial.
In an open trial, in which the intervention brings about a major and obvious change to the management of a baby, important methodological and clinical decisions have to be made about the trial regimen for those allocated to the control arm who will not receive the trial intervention. With no blinding to allocation, management decisions are explicit and can feature prominently in the experiences of those involved. This issue has been faced previously in other NIC RCTs, notably the UK Collaborative extracorporeal membrane oxygenation (ECMO) trial, 138 for which all of the babies had severe respiratory failure. Those in the intervention arm were transferred to a specialist centre and those in the control arm continued receiving the standard of care in their original NICUs with no further changes to care. Allocation to standard of care was often experienced as ‘doing nothing’ and could be a difficult experience for parents. 54
The TOBY study also involved very ill term babies and evaluated an intervention that may be desired by clinicians as well as parents. In contrast with the ECMO trial, 138 all babies in the TOBY study, regardless of allocation, were cared for in Level 3 NICU cooling centres and this could involve transfer for babies in the control as well as in the intervention arm of the trial.
There were some babies in the TOBY study who were moved for the purposes of the trial (i.e. to assess whether cooling was neuroprotective) but for most of the babies in the control group a transfer in the TOBY study was consistent with their clinical needs. The CI explained that an essential clinical consideration related to the standard of care needed for asphyxiated babies, and said, ‘ these were very sick babies and needed to be in intensive care ’ and this could not always be offered in the less specialised units where some of the babies were born.
[T]he cooling centres were in effect the most specialised units . . . and most of the babies in the trial were born in those centres . . . [A] number of babies were born outside the treating centres . . . [T]he vast majority of those that were moved came from lower-level centres, and the package of care would not have been easily delivered in their hospital of birth.
The package of care to which the CI refers is the standard of care required for the baby and as a comparator within TOBY. This example highlights the ways in which the clinical characteristics of the population under study, and the methodological response to that, can shape a trial in ways which will then have a direct impact on what happens to babies and their families when a baby is enrolled into a trial. It shows how decisions about research cannot be separated from the duty of care in the clinical context in which they are set.
How the intervention for the control group might best be managed for the PROGRAMS study was an important methodological issue of a different type as it addressed clinicians’ responses to the allocation. The trial intervention involved daily subcutaneous injections for 5 days and the trial team wished to avoid giving five placebo injections to babies in the control group. Placebo injections would have concealed the allocation from the parents but not from the clinicians involved in the baby’s care or from the trial assessors. The CI described the concerns they had:
The result of the treatment was immediately obvious to anyone looking at the baby’s blood counts and, therefore, the whole purpose of the placebo was negated and that raised some very interesting methodological issues. I’m delighted that with the help of brainstorming amongst our collaborators, we came up with a very nifty way of, of dealing with it . . . [We made] sure that the outcome assessment was done blind to the results of the full blood counts . . . so it was done by an independent group of people . . . In other words, it wasn’t the clinician looking after the baby who was responsible for capturing the data that determined whether or not the baby had had an outcome but it was an independent group of people.
Whether or not the trials used a placebo, and how this might affect parents who go on to be bereaved, was a common point of discussion in the BRACELET interviews and this topic will be discussed further in Chapters 6 and 7 .
Outcome measures
An important element in the methods laid down for any trial is the setting of outcome measures. 136 Primary outcomes define what are considered to be the most important potential changes that might be observed in the trial population, and these will vary according to the population and the intervention being used. Death is a common primary outcome but this is not always relevant if a trial involves patients at low risk of death or assesses an intervention that is focused on affecting a particular aspect of care, length of stay or initiation of antibiotics. Trials are often looking for a number of potential changes and more than one primary outcome can be used. Secondary outcomes detect less important but significant changes such as side effects. Sometimes if the population is at high risk of death, mortality is included as a secondary outcome even if it is unlikely to be affected by the trial intervention per se. Death may also be part of a composite primary outcome even if the intervention is not predicted to affect the risk of death: rather it is included so that there can be an ITT analysis.
The five core trials all involved babies at risk of death but they each used different outcome measures, as shown in Table 26 .
Primary outcome measures for the five core trials
Although all of the core trials involved substantial mortality rates, and the likelihood of death in these critically ill populations could be predicted, not all of the trials measured death as an outcome. The ExPN study did not, but this trial focused on the effects of providing more of something that is considered standard care (i.e. extra nutrition rather than usual nutrition) and it is difficult to make a direct, short-term plausible biological link from more food to death. The primary outcome for the ExPN study was an increase in head circumference measurement at 36 weeks’ postmenstrual age (i.e. there is a potential link between more food and better growth in the short term). Secondary outcomes included a range of clinical events. Some, such as the development of NEC, would be a major threat to the life of a baby, but NEC, and not mortality, was the outcome measured, as there could be a biological connection between overfeeding and NEC. That is not to say that the trial team was not focused on the potential for mortality in their trial: they ensured that deaths in the trial population came under scrutiny. In the ExPN study there was no formal DMC but an expert neonatologist acted as a ‘ one man DMC ’. He was asked to look over the first 50 cases in the trial, and this raised some issues relating to mortality. On further analysis the effect ‘ disappeared ’ and the trial continued. Exactly the same issue was faced in the PROGRAMS trial: the DMC examined a possible difference in mortality between the arms, which proved to be an early trend that was not present in the final data set.
Some of the outcomes for the ExPN study were measured at 2 years, meaning that data collection was spread out over a longer time, with follow-up sometimes years after the initial involvement in a trial. This was managed in stages with multiple consent processes, and only the feeding element of the trial was raised with parents initially:
We wanted just to get them on the feeding bit and in fact, that was perhaps the most important bit because we wanted to look at the growth of the child. Subsequently we wanted to do the MRI because that would actually show you which bits of the brain hadn’t grown. Then we wanted to follow up to see whether it was all worth it . . . So there were three consents . . . and most people went through the whole lot. Quite a few opted out of MRI, but allowed the follow-up.
The inclusion of long-term outcomes has implications for data collection and the running of the trial. The outcome measure closest to the time of the intervention in any of the core trials was used in the PROGRAMS study, which looked at sepsis-free survival 14 days after trial entry. The very short time frame was set in this way because this trial was initially looking at whether it was possible to address neutropenia (see explanation above) and whether this in turn might affect infection rates. Both of these changes could be determined very quickly and so the primary outcome for this trial was measured at 14 days.
When combined or composite outcomes are used (such as death or disability, or sepsis-free survival), an outcome is said to have occurred if a participant experiences one or more of the events. 139 Composite outcomes offer the advantage that sample sizes can be lower and trials can therefore complete recruitment more quickly because there is no need to collect sufficient data to look at each outcome separately. But this approach brings with it some difficult issues, which are a particular challenge in this setting. One of the CIs explained how NIC trials differ from those in other specialties such as cancer.
In neonatal intensive care, almost all the deaths are at the beginning and then there’s nothing, there’s almost nothing later on so all your deaths are early and your disability has to wait until 2-years of age to assess . . . It’s a unique situation.
Predetermined outcomes are used to focus in on the key questions for a trial and to mark out the data that are required to answer those questions. They are used by DMCs to determine whether or not to recommend a trial should continue, and as this last quotation suggests, this can be a particularly difficult methodological and ethical issue in NIC RCTs. At interim analyses the DMC members see the trial data by allocation. They can therefore see, while a trial is still recruiting, whether or not there seems to be a difference in mortality between the groups. Sometimes, as in the case of the ExPN and PROGRAMS studies, further analysis will show that that difference is due to chance and will disappear as more data accrue. Sometimes, as in the BOOST-II UK study, an early difference in mortality will be sufficient to make it inappropriate to carry on with the trial, and the trial is stopped. It is difficult, however, if trials are not designed to look at death alone but at a composite outcome of death and longer-term disability combined as the primary outcome. If an intervention does have an effect, the essential question here is more subtle than simply a matter of survival; it is whether increased survival is associated with an increase in disability or lower disability. Mortality then is clearly only part of the question but this places the DMC in a difficult position.
You may be sitting on a difference in mortality waiting to get some supporting evidence that you aren’t getting an increase in severe disability which may offset the difference in mortality and what do we mean by offset, whose, whose judgement is that? . . . If the primary outcome is death or severe disability at 2 years and there’s no difference between the groups but one has a much lower risk of death and the other one has a much higher risk of disability . . . parents will interpret that result differently. Some will say, ‘I don’t care if my baby’s disabled, I want my baby to survive’ and others will say, ‘I don’t want a severely disabled baby, it’s not fair on the child . . . it would seem kinder for them.
This is exacerbated by the need to think beyond the confines of the trial in hand. If a trial is stopped early on the recommendation of a DMC because of a difference in mortality, this affects whether or not future trials may be funded and carried out in another attempt to address the longer-term question. One of the CIs explained that this is a major balancing problem when trials have composite outcomes:
You’re terrified of doing harm, and of being accused of not stopping it in time, but equally you don’t want to throw away the only opportunity you may well have of answering that question and benefiting children in the future.
This decision also shapes the evidence that is produced, which will, in turn, affect how an intervention is used or not used in practice. One of the CIs argued that for this reason it can be very important to push on:
Sometimes it is important to continue to get a very clear answer because, if the aim is to influence clinical practice for the betterment of the patients, there is a very strong argument for having a very clear answer which people can’t argue with. So having a result which is just significant may not persuade people to change their practice, in which case it may be justifiable and I use the term ‘may be’ because these are awful decisions, to go on to accumulate more deaths in order to change practice in order for the myriad of babies out there for years to come who may benefit from that intervention. Those are very, very difficult decisions for DMCs to take.
These very difficult decisions flow directly from the earlier methodological decisions that were made about outcome measures. Reducing the timing of the end point for assessment can help but it is not always possible. Two of the core trials, which had composite outcomes, the INIS and BOOST-II UK studies, measured these at 2 years after birth, as this is the point at which evidence of disability in preterm infants is becoming clear. The point at which death and disability was assessed was earlier for the TOBY study at 18 months following a term delivery. This difference is important, as it is possible – if a trial is set to recruit for a number of years – for some follow-up data to start to accrue during recruitment if the lag between birth and assessment of outcomes is not too great. One of the investigators explained that this difference is set, in part, by the trial population, but his comments also suggest that methodological opinion, which will vary between individuals, is also important. (This individual is not a CI but data from his interview were informative and so they are included here.)
We usually measure prem outcomes at 2 years you see. TOBY was 18 months [and] ECMO was 1 year . . . My view [is] that actually term babies you could do at a year. I still think TOBY should have been done at a year. But even so, your trial’s mainly over by the time you’ve got your outcome, so actually when you’re running the trial you, you really find that it’s very difficult for you to take cognisance of the disability side of the outcome.
Given these difficulties it was not surprising to hear CIs state that trials which do not use composite outcomes that are ascertained at different time points are more simple.
Components and considerations in the design and management of the trials
A range of components have been identified in the five core trials and categorised as structural, procedural and synergistic. The accounts of the lead researchers for these trials describing the development of these components suggests that key features of the trial designs are shaped by a number of considerations .
Four considerations were identified here: scientific issues, clinical issues, the impact on parents, and ethics. This list is not exhaustive, and other considerations, such as finance 51 and logistics, are also likely to exert their effects on design and management. It is useful, however, to highlight these four considerations, as the accounts of their relevance reported above show how such factors are incorporated into the trial designs. The data reported above also show how these considerations reflect the interest and concerns of different parties associated with trials: the trial investigators, the CTU, clinical colleagues and parents. This is shown in Figure 15 below. These different components and considerations can also be picked out in Table 27 in the description of one aspect of the trial that flows from an element in the design of the TOBY study.
Parties of influence and considerations in setting design features for the core trials.
An example of components and considerations in the TOBY trial discussion
In order to understand experiences of taking part in a NIC RCT, whether as clinicians and trial team member or as a parent, it is necessary to understand the context in which those experiences are set. In this chapter we have considered different layers in that context, exploring the five core trials as products of a specialty, of trial development teams and their clinical colleagues in collaborating centres. At the most superficial level we considered the specific design features of the trials i.e. their structural components . This makes clear the overt ways in which a trial is set up (e.g. it may involve babies of a given gestation, it may use a placebo, it may involve transfer between hospitals). A focus on structural characteristics allows comparisons of trials with similar or different features. We also took note of the procedural components of a trial, i.e. the decisions that are made about the day-to-day running of research. They are of interest as they set up different patterns of contact between the trials and the parents, and this establishes the extent and terms of a relationship with a trial. These structural and procedural components provide a useful framework for thinking about the range of features which combine to produce a protocol. They are key contextual elements in the setting of interest to the BRACELET study and from these it is possible to start to see how a trial might work in practice, how it might shape experiences and which are the important questions to address, such as:
- What was it like to offer a trial to parents when the recruitment window was very tight?
- What was it like when you heard that your baby was not going to receive the trial treatment?
- Should bereaved parents be sent a copy of the trial results?
Why design features are set as they are is not often considered as part of the context of a RCT, but this is especially informative, as design is part of the ethos of a trial. Each methodological choice reflects a rationale and aspirations for the data to be collected, as well as a judgement about the management and care of the participants who will provide those data. The choices are driven by multiple considerations , by science, by clinical issues, by a sense of the personal impact on parents and by ethics. These are subjective considerations, however, and we have identified a number of parties of influence who may have different views on the considerations involved: investigators, CTUs, clinical centre staff and parents. As we have shown, people differ in what they think is good science, and can differ in their views of the right thing to do. The accounts of the different choice of randomisation method made for multiples by two CIs in the ExPN and BOOST-II UK studies make this point; both felt that their strategy was the most appropriate scientific method and both felt that it would be the most suitable approach for parents.
The team-based approach to protocol development described by a CI is used to ensure that a trial design is an agreed strategy, a product of multiple inputs, but this does not mean that subjectivity is removed. A strategy that works well at the analytical level for experienced triallists and statisticians may still seem to be odd science or inappropriate practice for clinicians who work outside research. The previously mentioned concern of surgeons that variations in surgical skills would undermine trial findings is a case in point. (This required an appreciation of the difference between an explanatory trial and a pragmatic trial. In the latter design, variation is accepted as it reflects clinical practice.) Many triallists have found that their well-considered design does not fit with the priorities of the clinicians, who have responsibility for its implementation. Clinicians sometimes adhere to a protocol, and sometimes modify or ‘tinker’ 140 with it to fit it with the prevailing sense of equipoise in their centre. 141 Just from this initial work with a small subset of the BRACELET study interviews it is possible to gain a sense of the push-and-pull that can exist between clinical trial teams and clinical centres. The CIs for the TOBY study and for the INIS study both described difficulties with the interpretation of eligibility criteria and for TOBY these changed over time. Only the sickest babies were recruited to the trial in the early days but, as confidence in the clinical centres grew, a wider range of babies were referred. With this shift in context will come different types of parental experiences. These synergistic components of a trial can be captured to some extent but can be subtle and elusive.
Some of these details can be found in the trial narratives that are heard in interviews. Individual trials gain reputations often in relation to their design, their outcome and because of the demands they made of clinicians and parents. One trial might be known for difficulties in recruitment, and another for generating concern or enthusiasm among colleagues. The TOBY study for instance, was often seen as an exciting trial that held promise for clinical practice. It was also the trial that required parents to make decisions at a time of major trauma. The BOOST-II UK study was the trial that has given the NICU community some guidance on oxygen targets for preterm neonates. It was also the trial that was stopped urgently on Christmas Eve because it showed increased survival in one arm.
In this chapter we have shown that there is not a single context to be considered in the BRACELET study but multiple nested and overlapping contexts. The trials that are considered here are produced by multidisciplinary teams who make a range of decisions about how they will be run. The trials’ structural and procedural components reflect the expertise and values of those teams. The implementation of trials in clinical centres introduces another contextual layer as methods are put into practice, but how this is done can change with location and over time, thus introducing an unpredictable degree of synergy into the context. We have also demonstrated that the five core trials are the responsibility of highly interlinked teams. Investigators who develop trial methods also recruit to their trials, and senior triallists who are steering one trial, as a member of its TSC may also be examining data on the DMC of another trial. Clinicians with no role in developing a trial, but who recruit or who support the running of a trial, work at the frontline with parents, and their views can be extremely influential, as they directly shape who is and is not referred to a trial. It is therefore important to see these trials in all of their complexity, their features, the course they take, and the legacy that they have in the field, as essential elements in the context considered in the BRACELET study.
Context then is more than the observable features of the trials. It is dynamic and synergistic, the product of scientific, clinical, interpersonal and ethical considerations, which are, in turn, subjective and mutable. These contextual features are essential to our understanding of the setting of the core trials and inform the analysis of our central research question about the management of bereavement in NIC RCTs.
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- Cite this Page Snowdon C, Brocklehurst P, Tasker R, et al. Death, bereavement and randomised controlled trials (BRACELET): a methodological study of policy and practice in neonatal and paediatric intensive care trials. Southampton (UK): NIHR Journals Library; 2014 Jul. (Health Technology Assessment, No. 18.42.) Chapter 5, The research setting.
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Reproductive rights took center stage during the Democratic National Convention’s first night in Chicago. But is the DNC offering free abortions and vasectomies to attendees, as some conservative social media users have claimed?
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RNC Research, an X account run by the Trump campaign and the Republican National Committee, posted Aug. 18, “Democrats are giving out ‘free abortions and vasectomies’ at their convention.”
Other users made similar claims on X.
A Planned Parenthood branch is providing free medication abortion, vasectomies and emergency contraception through a mobile health clinic in Chicago that’s running at the same time as the DNC. But the convention is not sponsoring or otherwise connected to these services.
Planned Parenthood Great Rivers, which is based in the St. Louis region, said Aug. 14 on X and Aug. 19 in a press release that its mobile health unit would be stationed Aug. 19 and 20 in Chicago’s West Loop neighborhood. Planned Parenthood Great Rivers said Aug. 17 that all of its appointment spots had been filled.
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The DNC is not being held in the West Loop. The event’s nighttime programming and speeches are at the United Center, a few blocks east of the West Loop. Daytime events are at the McCormick Place Convention Center, a few miles south of the West Loop, according to the DNC’s website .
The DNC’s website does not list Planned Parenthood as a partner, sponsor or vendor for the event, nor does it mention this mobile health clinic.
Planned Parenthood Great Rivers’ press release lists the Chicago Abortion Fund, a nonprofit group, and the Wieners Circle, a food vendor, as partners. It does not mention the DNC.
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A psychologist reveals the meaning behind 2 common types of nightmares.
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Ignoring the contents of your dreams might exacerbate your problems in waking life. Here's how you ... [+] can analyze your dreams to improve your waking hours.
We’ve all been there—waking up in a cold sweat, with your heart pounding after a nightmare so vivid, that it’s hard to remember what’s real. Whether it’s frantically running from a faceless pursuer, falling from a great height or being trapped in a room with no escape, these unsettling dreams can linger long after we’ve woken up.
While some dreams may be just our brain’s way of sorting through the day’s events, others, particularly nightmares, can be our mind’s way of working through real-life challenges and emotional conflicts.
Here are the meanings behind two common types of disturbing dreams, according to research on human consciousness.
1. Dreams Of Being Chased
In dreams of being chased, you might find yourself running away from an unknown figure, a threatening animal or even an intangible force. The sense of danger feels immediate, and no matter how fast you run, the pursuer seems to close in.
A study published this July in Frontiers In Psychology found that such dreams are associated with real-life experiences of having negative relationships with others.
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Researchers suggest that this can be explained by the “ threat simulation theory ” of dreaming, according to which dreams serve an evolutionary function by simulating threatening events to practice and improve the mechanisms for real-life threat perception and avoidance. This helps individuals rehearse responses to potential dangers in a safe environment.
The emotional threat of conflict or dissatisfaction in real-life relationships can create a need to prepare for confrontation or further emotional upheaval. When individuals experience tension or discord in their social interactions, their mind may simulate scenarios of being chased as a way of processing these emotional threats. This not only allows them to rehearse responses to potential conflicts but also serves as a psychological tool to manage anxiety and stress related to those relationships.
Moreover, the theory suggests that such dreams aren’t just random occurrences but are deeply rooted in our ancestral need for survival. In the past, being chased could have signified real physical threats from predators or hostile individuals. In the modern world, these threats often manifest as social or emotional challenges, and the brain uses dreams to work through them.
2. Dreams Of Being Suffocated
Dreams of being suffocated are often intensely distressing. In these dreams, you might find yourself in situations where it becomes increasingly difficult to breathe, as if an invisible force is pressing down on your chest or throat.
Alternatively, you might be trapped in a small, enclosed space, like a coffin or a sealed room, where the air seems to grow thinner and thinner. Or, you might feel like you’re being held underwater, unable to reach the surface for air or that someone or something is physically covering your mouth and nose.
Interestingly, another study published in Frontiers in Psychology by a team of Israeli researchers shows that dreams of suffocation are associated with experiencing psychological distress in one’s waking life as well as general sleep disturbances.
Physiologically, those who experience respiratory issues during sleep, such as sleep apnea, or breathing problems in their waking life report dreams of suffocation more frequently than those without such issues. This suggests that the body’s struggle to breathe can manifest in dreams as the terrifying sensation of being smothered or choked.
Psychologically, those with anxiety or distress related to breathing—perhaps due to a fear of suffocation or choking—are also more likely to have these kinds of nightmares. Researchers suggest that the connection between psychological distress and suffocation dreams is further supported by the phenomenon of sleep paralysis.
During sleep paralysis, individuals often experience a terrifying sensation of being unable to move, sometimes coupled with hallucinations of a malevolent presence sitting on their chest, making it hard to breathe.
This eerie experience, which can feel like being smothered, is related to both physical sensations (like shallow breathing and body paralysis) and psychological factors (such as anxiety and stress).
So, understanding the deeper meanings behind our nightmares can offer valuable insights into our emotional, physical and psychological well-being. They serve as an important reminder that our body and mind are intricately connected.
If you find yourself frequently experiencing these types of nightmares, it is important to explore any unresolved conflicts or stressors in your waking life. By listening to these signals and taking proactive steps to address them, you can work towards more restful sleep and a greater sense of inner peace.
Are you someone that’s intrigued by your dreams? Take this test to learn more about these feelings: Attitudes Toward Dreams Scale
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Research: Meaning and Purpose
- First Online: 27 October 2022
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- Kazi Abusaleh 4 &
- Akib Bin Anwar 5
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The objective of the chapter is to provide the conceptual framework of the research and research process and draw the importance of research in social sciences. Various books and research papers were reviewed to write the chapter. The chapter defines ‘research’ as a deliberate and systematic scientific investigation into a phenomenon to explore, analyse, and predict about the issues or circumstances, and characterizes ‘research’ as a systematic and scientific mode of inquiry, a way to testify the existing knowledge and theories, and a well-designed process to answer questions in a reliable and unbiased way. This chapter, however, categorizes research into eight types under four headings, explains six steps to carry out a research work scientifically, and finally sketches the importance of research in social sciences.
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Abusaleh, K., Anwar, A.B. (2022). Research: Meaning and Purpose. In: Islam, M.R., Khan, N.A., Baikady, R. (eds) Principles of Social Research Methodology. Springer, Singapore. https://doi.org/10.1007/978-981-19-5441-2_2
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- How have voters shifted their preferences since July?
- Harris’ supporters back her more strongly than Biden’s did last month
- Large gap in motivation to vote emerges between the candidates’ younger supporters
- Harris and Trump have gained ground with their own coalitions
- Share of ‘double negatives’ drops significantly with change in presidential candidates
- Views of Biden have changed little since his withdrawal from the 2024 presidential race
- Acknowledgments
- The American Trends Panel survey methodology
Nationally, Vice President Kamala Harris and former President Donald Trump are essentially tied among registered voters in the current snapshot of the presidential race: 46% prefer Harris, 45% prefer Trump and 7% prefer Robert F. Kennedy Jr.
Following Biden’s exit from the race, Trump’s support among voters has remained largely steady (44% backed him in July against Biden, while 45% back him against Harris today). However, Harris’ support is 6 percentage points higher than Biden’s was in July . In addition to holding on to the support of those who backed Biden in July, Harris’ bump has largely come from those who had previously said they supported or leaned toward Kennedy.
Harris performs best among the same demographic groups as Biden. But this coalition of voters is now much more likely to say they strongly support her: In July, 43% of Biden’s supporters characterized their support as strong – today, 62% of Harris’ do.
![the research location meaning Chart shows Black, Hispanic, Asian and younger voters back Harris by large margins, while Trump leads among older voters and those without a bachelor’s degree](https://www.pewresearch.org/wp-content/uploads/sites/20/2024/08/PP_2024.8.14_harris-trump_1-01.png?w=640)
Overall, many of the same voting patterns that were evident in the Biden-Trump matchup from July continue to be seen today. Harris fares better than Trump among younger voters, Black voters, Asian voters and voters with college degrees. By comparison, the former president does better among older voters, White voters and voters without a college degree.
But Harris performs better than Biden across many of these groups – making the race tighter than it was just a few weeks ago.
- In July, women’s presidential preferences were split: 40% backed Biden, 40% preferred Trump and 17% favored Kennedy. With Harris at the top of the ticket, 49% of women voters now support her, while 42% favor Trump and 7% back Kennedy.
- Among men, Trump draws a similar level of support as he did in the race against Biden (49% today, compared with 48% in July). But the share of men who now say they support Harris has grown (to 44% today, up from 38% last month). As a result, Trump’s 10-point lead among men has narrowed to a 5-point lead today.
Race and ethnicity
Harris has gained substantial ground over Biden’s position in July among Black, Hispanic and Asian voters. Most of this movement is attributable to declining shares of support for Kennedy. Trump performs similarly among these groups as he did in July.
- 77% of Black voters support or lean toward Harris. This compares with 64% of Black voters who said they backed Biden a few weeks ago. Trump’s support is unchanged (13% then vs. 13% today). And while 21% of Black voters supported Kennedy in July, this has dropped to 7% in the latest survey.
- Hispanic voters now favor Harris over Trump by a 17-point margin (52% to 35%). In July, Biden and Trump were tied among Hispanic voters with 36% each.
- By about two-to-one, Asian voters support Harris (62%) over Trump (28%). Trump’s support among this group is essentially unchanged since July, but the share of Asian voters backing Harris is 15 points higher than the share who backed Biden in July.
- On balance, White voters continue to back Trump (52% Trump, 41% Harris), though that margin is somewhat narrower than it was in the July matchup against Biden (50% Trump, 36% Biden).
While the age patterns present in the Harris-Trump matchup remain broadly the same as those in the Biden-Trump matchup in July, Harris performs better across age groups than Biden did last month. That improvement is somewhat more pronounced among voters under 50 than among older voters.
- Today, 57% of voters under 30 say they support Harris, while 29% support Trump and 12% prefer Kennedy. In July, 48% of these voters said they backed Biden. Trump’s support among this group is essentially unchanged. And 12% now back Kennedy, down from 22% in July.
- Voters ages 30 to 49 are now about evenly split (45% Harris, 43% Trump). This is a shift from a narrow Trump lead among this group in July.
- Voters ages 50 and older continue to tilt toward Trump (50% Trump vs. 44% Harris).
With Harris now at the top of the Democratic ticket, the race has become tighter.
![the research location meaning Chart shows Since Biden’s exit, many who previously supported RFK Jr. have shifted preferences, with most of these voters now backing Harris](https://www.pewresearch.org/wp-content/uploads/sites/20/2024/08/PP_2024.8.14_harris-trump_1-02.png?w=420)
Much of this is the result of shifting preferences among registered voters who, in July, said they favored Kennedy over Trump or Biden.
Among the same group of voters surveyed in July and early August, 97% of those who backed Biden a few weeks ago say they support or lean toward Harris today. Similarly, Trump holds on to 95% of those who supported him a few weeks ago.
But there has been far more movement among voters who previously expressed support for Kennedy. While Kennedy holds on to 39% of those who backed him in July, the majority of these supporters now prefer one of the two major party candidates: By about two-to-one, those voters are more likely to have moved to Harris (39%) than Trump (20%). This pattern is evident across most voting subgroups.
In July, Trump’s voters were far more likely than Biden’s voters to characterize their support for their candidate as “strong” (63% vs. 43%). But that gap is no longer present in the Harris-Trump matchup.
![the research location meaning Chart shows ‘Strong’ support for Harris is now on par with Trump’s and is much higher than Biden’s was in July](https://www.pewresearch.org/wp-content/uploads/sites/20/2024/08/PP_2024.8.14_harris-trump_1-03.png?w=310)
Today, 62% of Harris voters say they strongly support her, while about a third (32%) say they moderately support her. Trump’s voters are just about as likely to say they strongly back him today as they were in July (64% today, 63% then).
Kennedy’s voters make up a smaller share of voters today than a month ago – and just 18% of his voters say they strongly support him, similar to the 15% who said the same in July.
Across demographic groups, strong support for Harris is higher than it was for Biden
Among women voters who supported Biden in July, 45% said they did so strongly. That has grown to 65% today among women voters who support Harris.
![the research location meaning Chart shows Across demographic groups, Harris’ strong support far surpasses Biden’s a month ago](https://www.pewresearch.org/wp-content/uploads/sites/20/2024/08/PP_2024.8.14_harris-trump_1-04.png?w=420)
Increased intensity of support is similar among men voters who back the Democratic candidate: In July, 42% of men voters who supported Biden said they did so strongly. This has since grown to 59% of Harris’ voters who are men.
Across racial and ethnic groups, Harris’ supporters are more likely than Biden’s were to say they back their candidates strongly.
Among White voters, 43% who supported Biden in July did so strongly. Today, Harris’ strong support among White voters sits at 64%.
A near identical share of Harris’ Black supporters (65%) characterize their support for her as strong today. This is up from the 52% of Biden’s Black supporters who strongly backed him in July. Among Harris’ Hispanic supporters, 56% support her strongly, while 45% of Asian Harris voters feel the same. Strong support for Harris among these voters is also higher than it was for Biden in July.
Across all age groups, Harris’ strength of support is higher than Biden’s was. But the shift from Biden is less pronounced among older Democratic supporters than among younger groups.
Still, older Harris voters are more likely than younger Harris voters to describe their support as strong. For instance, 51% of Harris’ voters under 50 say they strongly support her, while 71% of Harris supporters ages 50 and older characterize their support as strong.
Today, about seven-in-ten of both Trump supporters (72%) and Harris supporters (70%) say they are extremely motivated to vote.
Motivation to vote is higher in both the Democratic and Republican coalitions than it was in July .
![the research location meaning Chart shows Older voters remain more motivated to vote, but Harris’ younger supporters are more motivated than Trump’s](https://www.pewresearch.org/wp-content/uploads/sites/20/2024/08/PP_2024.8.14_harris-trump_1-05.png?w=310)
These shifts have occurred across groups but are more pronounced among younger voters.
Today, half of voters under 30 say they are extremely motivated to vote, up 16 points since July. Motivation is up 11 points among voters ages 30 to 49 and 50 to 64, and up 6 points among those ages 65 and older.
Among the youngest voters, the increased motivation to vote is nearly all driven by shifts among Democratic supporters.
- In July, 38% of 18- to 29-year-old Trump voters said they were extremely motivated to vote. Today, a similar share of his voters (42%) report that level of motivation.
- But 18- to 29-year-old Harris supporters are far more likely to say they are extremely motivated to vote than Biden’s supporters in this age group were about a month ago. Today, 61% of Harris’ voters under 30 say this. In July, 42% of voters under 30 who supported Biden said they were extremely motivated to vote.
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The wonky reason you should expect higher electricity prices next year - Saving You Money
- Updated: Aug. 21, 2024, 4:07 p.m.
- | Published: Aug. 21, 2024, 8:52 a.m.
![the research location meaning power lines steelyard commons cleveland](https://www.cleveland.com/resizer/v2/5JDJ5NSADBG4XKCLLSNAF7YAKU.jpg?auth=33c618a4aa7e65f2c14cef95e24ab4d1e8f41dd60a8958059c5fccb30e146f28&width=500&quality=90)
Sunrise is seen through power lines in the Steelyard Commons area of Cleveland. File photo 2017 The Plain Dealer
- Sean McDonnell, cleveland.com
CLEVELAND, Ohio — The PJM Interconnection and its role in our everyday lives isn’t something most electric customers think about. But because of a quirk in the system called capacity auctions, Clevelanders are likely to see noticeable increases in the price they pay for electricity, perhaps as much as 25%.
Why? It’s a capacity issue, explained Matt Brakey, head of energy management firm Brakey Energy in Chagrin Falls.
The PJM Interconnection, which manages a grid that spans 13 states, has to make sure the grid has enough power even on its busiest days. It finds power plants to meet that demand in case of emergencies at auction, but prices were much more expensive this year.
And since the PJM is paying more, the price per kilowatt hour on our bills will be more starting in June.
This is admittedly a bit wonky of a topic. But it’s also a reminder of why we should shop for cheaper electricity.
What is the PJM and why does it matter
When we talk about utilities we usually talk about FirstEnergy, which owns Ohio Edison and the Illuminating Company. But a step above FirstEnergy is another entity called the PJM.
The PJM operates what’s known as “the grid” across 13 states, including Ohio and its neighbors. It’s tasked with coordinating between the power plants that pump electricity into that grid and the utilities that deliver it to homes and businesses.
Part of those duties is managing the wholesale markets. Another thing the PJM does is make sure the grid has enough capacity.
In simpler terms, there are 65 million people on the grid. And if every single person flips on their air conditioners at once, the PJM needs to make sure there’s enough power to serve them all simultaneously.
Brakey said the grid has to be ready to operate at the busiest hour of the year.
To do that, the PJM must find power plants willing to respond in case extra power is needed. It finds them at auction, and during the last auction in July , prices were high.
In 2023 the auction clearing price was $28.92 per megawatt-day. This time around it was $269.92. These new prices go into effect from June 2025 to May 2026.
This is an nine-fold increase, but it’s a small component of what goes into the prices we pay.
Brakey said there are two main reasons for this increase.
On one hand, coal and even natural gas power plants are being shut down, Brakey said. That means less electricity is available.
These natural gas and coal plants are also important for emergency use because they are “dispatchable,” which means they can be turned on or off when needed. If the grid needs a surge of power, a natural gas plant that is off can be quickly turned on.
There are not many new power plants coming online. But the electricity sources that are — solar and wind — cannot be turned on or off on a whim. They are on when the wind blows or when the sun shines.
Brakey said another part of this is data centers, the large buildings built to house the computer systems that handle storage or telecommunications. Some use as much electricity as a small city, and they’re becoming more common.
In its news release announcing the prices, the PJM said the high prices show that the balance between supply and demand in our area is being tightened.
“The market is sending a price signal that should incent investment in resources,” PJM President and CEO Manu Asthana said.
What does this mean for me?
Brakey estimates that residential customers will see prices go up on the electric portion of their utility bills. If you shop for electricity at energychoice.ohio.gov , this already seems apparent.
A 12-month fixed-price contract from Energy Harbor is 5.9 cents per kilowatt hour. But if you look for a 24-month contract it’s 7.9 cents.
The June 2025 to May 2026 period is going to be more expensive. So longer-term contracts will reflect this increase in prices.
It’s far too early to know how this might affect customers on the standard service offer, the default prices paid by FirstEnergy customers. Or how it may affect people using community aggregations, like NOPEC.
But in both cases those customers are affected by the wholesale electricity market and will probably see higher prices.
This is different than what we’ve seen over the last few years.
After the start of the Ukraine war, NOPEC’s rates skyrocketed in 2022, which prompted it to temporarily drop customers. Then in June 2023, the default rate for FirstEnergy customers called the “price to compare” doubled because the price the utility paid for electricity at auction also doubled.
When it comes to these PJM auctions, they’re going to affect everyone.
“There’s not going to be any place to hide from this,” Brakey said.
A refresher on energy shopping
There’s no easy way to get around these higher prices. But as always, it pays to comparison shop.
Most households in Ohio can shop for their own electricity supplier using Ohio’s Apples to Apples tool, found at energychoice.ohio.gov. There are exceptions, like Cleveland Public Power customers. But if you have Ohio Edison or the Illuminating Company, you can shop.
We can only shop for usage part of the bill, which can make up as much as half of our total bills.
Ohioans’ bills are split into two parts — usage and distribution. The usage part of a customer’s bill is what we’re charged for each kilowatt-hour of electricity we use. The distribution section of the bills are based on how much it costs FirstEnergy to distribute power to homes.
Saving You Money is cleveland.com and The Plain Dealer’s column about saving money. We want to know how we can help you save money. Send your questions and comments to [email protected] .
Read past columns at cleveland.com/topic/saving-you-money/ .
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McKinsey takes a hard look at the energy transition’s hard stuff
August 22, 2024 The McKinsey Global Institute (MGI) has conducted extensive research on the economic, financial and societal aspects of the net-zero transition, working with colleagues from our Sustainability and Global Energy and Materials Practices.
“We wanted to flip the paradigm in this report, and focus on the physical realities—the nuts and bolts—in the ‘here and now,’” explains Tiago Devesa , a senior fellow at MGI. “What are the technologies, supply chains, and infrastructure we need to run the high-performance low-emissions energy system of the future?”
In this post, Mekala Krishnan , the McKinsey Global Institute partner who led the research, and Tiago share what they learned.
![the research location meaning Image of a spinning sphere with dark hexagon shapes pealing off and floating away revealing a green sphere underneath.](https://www.mckinsey.com/~/media/mckinsey/mckinsey%20global%20institute/our%20research/the%20hard%20stuff%20navigating%20the%20physical%20realities%20of%20the%20energy%20transition/the-hard-stuff-thumb-1536x1536.jpg?cq=50&mh=145&car=16:9&cpy=Center)
The hard stuff: Navigating the physical realities of the energy transition
The energy transition is a physical transformation in its early stages. What challenges lie ahead?
Tell us about the scope of the research—what exactly does the “hard stuff” mean?
Tiago : Our team looked across seven domains that would have to be physically transformed, such as power, industry, and mobility. It’s a landscape with some 60,000 power plants; more than 1.5 billion vehicles on the roads; and 2 million kilometers of oil and gas pipelines. We interviewed our own as well as external experts about topics ranging from exciting innovations in industrial heat in Europe, to new lithium extraction technologies in Argentina, and the latest long-duration energy storage projects in China. We identified the 25 biggest physical challenges—and classified them into three levels of difficulty. So basically we are saying if we want to get the energy transition right, we need to look at its physical realities—the “hard stuff.”
What surprised you in this analysis?
Tiago: A couple things are a bit staggering. There has been tremendous momentum in recent years, especially in wind and solar power, electric cars, heat pumps. Climate finance has started to flow; and many companies have made considerable commitments.
But right now, we're only at about 10 percent of the deployment of ‘physical assets’—technologies and infrastructure—that we will need to meet global commitments by 2050. This is not an abstract dollar number, or goal, or theoretical pathway. It’s the physical world that exists around us today. So, despite all the momentum, we’re still in very early stages of the energy transition.
Mekala: I don't want to underestimate the task at hand: it is a huge bending of the so-called “emissions curve.” But what was fascinating is that of the 90 percent we have left to go, things are evenly split: half of the energy system-related emissions are in what we call “Level 1 and Level 2” challenges—things that are relatively easy to solve; it’s a matter of how to best deploy mature technologies. But the remaining 50 percent are what we call “Level 3—the harder challenges.
Can you give an example of a harder challenge?
Mekala: In some domains, including hydrogen, carbon capture, and industrial production, we’re sometimes at 1 percent deployment or even less of where we will eventually need to be.
![the research location meaning : Mekala Krishnan, McKinsey Global Institute partner and Tiago Devesa, McKinsey Global Institute senior fellow](https://www.mckinsey.com/~/media/mckinsey/about%20us/mckinsey%20blog/new%20research%20on%20the%20energy%20transition/mgi-energy-inline-mekala-tiago-1536x950.jpg?cq=50&mw=767&cpy=Center)
For example, many of the technologies to produce low-emissions steel are relatively nascent, with issues to solve. Then there is the challenge of scaling any new technology: we would need to retrofit massive facilities processing millions of tons of steel around the world. Third, we need to solve the adjacent problem of accessing enough low-emissions hydrogen and power, and their respective value chains—inputs that are needed for the manufacturing of decarbonized steel.
This illustrates what makes this work hard. We see this in cement, in plastics, in ammonia: the consistent theme of technology performance gaps, massive scaling needs, and entwined linkages.
But even in the case of Level 3 challenges, there are ways to make progress. For example, producing new, virgin steel in a low-emissions way is difficult, but recycling steel is pretty mature. We've been doing it for decades, it's fairly low-cost. So simply increasing the recycling share of steel can go quite a long way in abating emissions.
We are also seeing many new potential solutions: the Hybrit project in low-emissions steel, LEILAC in cement, and Hubei Yingchang in compressed air storage for long-duration energy storage. The task now is continuing to innovate to improve performance, reduce costs, and scale.
What are some examples of Level 1 challenges or easier wins?
Tiago: The average electric car being sold today can cover the needs of more than 70 percent of households, and high-end models more than 90 percent. There's still work to be done, but we're close there. Another example is air-source heat pumps, which can serve the needs of over 95 percent of the human population no matter where they live.
This is encouraging because these are two of the foundational technologies that we need to decarbonize mobility and buildings.
How are we helping companies interpret this research for their own sustainability work?
Mekala: They can use this understanding of the physical challenges to ask themselves three questions and calibrate their action:
The first is, “Based on Level 1 challenges which are relatively easy to address, what initiatives can I take today that will have an impact?”
A second is, “For our so-called Level 2 challenges, where there are constraints to scaling, where do I expect there to be bottlenecks, or hurdles in the medium-term, and how do we prepare for these?” For example, “how can I plan for a projected shortage in critical minerals in the period to 2030?”
A third question that relates to the very hardest challenges, “Can we play a role here? Where is the potential to create value for our business? And where do we need to innovate on individual technologies and form strategic partnerships to help solve some of them?”
What should readers take away from this work?
Mekala: The more I work on this topic, the more I am fascinated by how, while we can often talk about individual technologies, sectors, companies, or countries, at its core, what we are talking about is a system-wide transformation. I go back to our metaphor: we are not replacing the bulb, we are rewiring an entire house.
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Selecting Research Area. Selecting a research area is the very first step in writing your dissertation. It is important for you to choose a research area that is interesting to you professionally, as well as, personally. Experienced researchers note that "a topic in which you are only vaguely interested at the start is likely to become a ...
12.4 Getting In and Choosing a Site. When embarking on a field research project, there are two major aspects to consider. The first is where to observe and the second is what role you will take in your field site. Your decision about each of these will be shaped by a number of factors, over some of which you will have control and others you ...
This article takes you through the first steps of the research process, helping you narrow down your ideas and build up a strong foundation for your research project. Table of contents. Step 1: Choose your topic. Step 2: Identify a problem. Step 3: Formulate research questions. Step 4: Create a research design. Step 5: Write a research proposal.
A research area is what a research topic is placed into, but is much broader than the scope of the topic. For example a research area can be human physiology, computer science (as you mentioned) or even relate to a specific field within these broader terms such as cardiac electrophysiology or machine learning respectively.
Delimitations refer to the specific boundaries or limitations that are set in a research study in order to narrow its scope and focus. Delimitations may be related to a variety of factors, including the population being studied, the geographical location, the time period, the research design, and the methods or tools being used to collect data.
Types of Research Designs Compared | Guide & Examples. Published on June 20, 2019 by Shona McCombes.Revised on June 22, 2023. When you start planning a research project, developing research questions and creating a research design, you will have to make various decisions about the type of research you want to do.. There are many ways to categorize different types of research.
Research locale refers to the specific geographical area or location where research is conducted . It involves studying and analyzing the social, economic, or environmental conditions of a particular place or region . Researchers may focus on understanding the local dynamics, processes, and relationships within that specific locale . The concept of research locale is important in various ...
You will find, in this video, very important and interesting information not commonly available elsewhere on Study Area or Research Setting. This video is based on many years of practice and ...
A population is a complete set of people with specified characteristics, while a sample is a subset of the population. 1 In general, most people think of the defining characteristic of a population in terms of geographic location. However, in research, other characteristics will define a population.
impact of location on an individual academic scientist's productivity is particularly important. at the beginning of a Ph.D. scientist's career (Oyer 2006, Stephan and Levin 1992). The challenge in these studies is to establish that the research success of newcomers is due to the.
In clinical research a research site conducts all or part of a clinical trial.For clinical trials which recruit research participants in multiple locations, often the research will have a headquarters then multiple regional research sites to conduct the research in that region. In a network of research sites where all are recruiting study participants, sites with low recruitment benefit from ...
Research setting is the specific location (classroom, school, institution, etc.) where research is conducted. ... meaning that his/her very presence means the behaviour he/she is observing is not normal (see Chap. 3). Initiating Dialogues with Students and Teachers. Context is where students and teachers interact inside and outside classrooms ...
Methodology. Alongside a literature review of previous relevant work, a content analysis of university websites was undertaken in October 2017. The analysis was restricted to English-language websites from New Zealand, Australia, the United States, Canada, the United Kingdom, South Africa and Singapore because these are the education systems with which the research team are most familiar.
Simply put, research setting is the physical, social, or experimental context within which research is conducted. In a research paper, describing this setting accurately is crucial since the results and their interpretation may depend heavily on it. For example, in a paper that describes the social behavior of chimpanzees, the authors may need ...
Two main techniques have been used in the current research: location-based methods and time-based methods [ 1, 2 ]. Location-based methods are popular. K-Means and DBSCAN are the most widely used methods. Ashbrook and Starner [ 3] utilized KMeans to identify the home location of the users.
Download chapter PDF. Chapter 3 Research Setting and Methodology describes the research setting and the methods of research. It details the methodological framework of the study as the baseline description in obtaining the research materials. This section begins with the explanation of organizational ethnography as an approach to my research.
Abstractspiepr Abs1. Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain ...
You can group your items by any characteristic you wish. Perhaps you want to know where the research is coming from: you group by location of the researchers. Perhaps you want to know where the funding comes from: you group by funding source. We are librarians, so we group by the title of the journal. You then have a database, a list.
The scope of a research paper explains the context and framework for the study, outlines the extent, variables, or dimensions that will be investigated, and provides details of the parameters within which the study is conducted. Delimitations in research, on the other hand, refer to the limitations imposed on the study.
This one was chosen from among many possible research questions (e.g., the impact of bullying on suicide rates, or children or adults). Delimiting factors could include: Research design: Mixed-methods research, including thematic analysis of semi-structured interviews and statistical analysis of a survey; Timeframe: Data collection to run for 3 ...
The importance of context. A central feature of qualitative research is the examination of the context in which a phenomenon is situated, experienced and constructed, and contextualisation is one of the standards by which qualitative studies are judged. 112, 113 This can involve a relatively quick description of key features of a given setting to orientate the reader, or it can be part of the ...
State Location means any physical location where the State performs work. State Location may include state-owned, leased, or rented space. Place of Work means the designated site or location where the Work products are to be finally or permanently constructed or installed; Research Plan shall have the meaning set forth in Section 2.1.
RNC Research, an X account run by the Trump campaign and the Republican National Committee, posted Aug. 18, "Democrats are giving out 'free abortions and vasectomies' at their convention."
The emotional threat of conflict or dissatisfaction in real-life relationships can create a need to prepare for confrontation or further emotional upheaval.
Include research on the ownership, financials, and organizational structure of those businesses. Facilities and location. Consider the location of your competitor's offices or store and its online presence. Location is a key part of your competitor's strengths and weaknesses as it affects foot traffic, logistics and accessibility.
1. As an investigative process, it originates with a question. It attempts to satisfy an unanswered question that is in the mind of a researcher. 2. Research demands a clear articulation of a goal, and a clear statement of the problem is a pre-condition of any research. 3.
Nationally, Vice President Kamala Harris and former President Donald Trump are essentially tied among registered voters in the current snapshot of the presidential race: 46% prefer Harris, 45% prefer Trump and 7% prefer Robert F. Kennedy Jr. Following Biden's exit from the race, Trump's support ...
Emergency workers in southern Italy are still hunting for six people missing after a tornado sank a luxury yacht early Monday - prompting an air and naval operation off the coast of Sicily.
The PJM Interconnection and its role in our everyday lives isn't something most electric customers think about. But its playing a role in why your bills will go up.
August 22, 2024 The McKinsey Global Institute (MGI) has conducted extensive research on the economic, financial and societal aspects of the net-zero transition, working with colleagues from our Sustainability and Global Energy and Materials Practices. "We wanted to flip the paradigm in this report, and focus on the physical realities—the nuts and bolts—in the 'here and now ...