Identify
Explore
Discover
Discuss
Summarise
Describe
Last, format your objectives into a numbered list. This is because when you write your thesis or dissertation, you will at times need to make reference to a specific research objective; structuring your research objectives in a numbered list will provide a clear way of doing this.
To bring all this together, let’s compare the first research objective in the previous example with the above guidance:
Research Objective:
1. Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.
Checking Against Recommended Approach:
Q: Is it specific? A: Yes, it is clear what the student intends to do (produce a finite element model), why they intend to do it (mimic cup/shell blows) and their parameters have been well-defined ( using simplified experimentally validated foam models to represent the acetabulum ).
Q: Is it measurable? A: Yes, it is clear that the research objective will be achieved once the finite element model is complete.
Q: Is it achievable? A: Yes, provided the student has access to a computer lab, modelling software and laboratory data.
Q: Is it relevant? A: Yes, mimicking impacts to a cup/shell is fundamental to the overall aim of understanding how they deform when impacted upon.
Q: Is it timebound? A: Yes, it is possible to create a limited-scope finite element model in a relatively short time, especially if you already have experience in modelling.
Q: Does it start with a verb? A: Yes, it starts with ‘develop’, which makes the intent of the objective immediately clear.
Q: Is it a numbered list? A: Yes, it is the first research objective in a list of eight.
1. making your research aim too broad.
Having a research aim too broad becomes very difficult to achieve. Normally, this occurs when a student develops their research aim before they have a good understanding of what they want to research. Remember that at the end of your project and during your viva defence , you will have to prove that you have achieved your research aims; if they are too broad, this will be an almost impossible task. In the early stages of your research project, your priority should be to narrow your study to a specific area. A good way to do this is to take the time to study existing literature, question their current approaches, findings and limitations, and consider whether there are any recurring gaps that could be investigated .
Note: Achieving a set of aims does not necessarily mean proving or disproving a theory or hypothesis, even if your research aim was to, but having done enough work to provide a useful and original insight into the principles that underlie your research aim.
Be realistic about what you can achieve in the time you have available. It is natural to want to set ambitious research objectives that require sophisticated data collection and analysis, but only completing this with six months before the end of your PhD registration period is not a worthwhile trade-off.
Each research objective should have its own purpose and distinct measurable outcome. To this effect, a common mistake is to form research objectives which have large amounts of overlap. This makes it difficult to determine when an objective is truly complete, and also presents challenges in estimating the duration of objectives when creating your project timeline. It also makes it difficult to structure your thesis into unique chapters, making it more challenging for you to write and for your audience to read.
Fortunately, this oversight can be easily avoided by using SMART objectives.
Hopefully, you now have a good idea of how to create an effective set of aims and objectives for your research project, whether it be a thesis, dissertation or research paper. While it may be tempting to dive directly into your research, spending time on getting your aims and objectives right will give your research clear direction. This won’t only reduce the likelihood of problems arising later down the line, but will also lead to a more thorough and coherent research project.
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Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw…
Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw up a pocket-friendly plan. Where do you begin? The first step is to do your research.
Before that, you make a mental list of your objectives—finding reasonably-priced hotels, traveling safely and finding ways of communicating with someone back home. These objectives help you focus sharply during your research and be aware of the finer details of your trip.
More often than not, research is a part of our daily lives. Whether it’s to pick a restaurant for your next birthday dinner or to prepare a presentation at work, good research is the foundation of effective learning. Read on to understand the meaning, importance and examples of research objectives.
What are the objectives of research, what goes into a research plan.
Research is a careful and detailed study of a particular problem or concern, using scientific methods. An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It’s an essential component of success.
Over the years, businesses have started emphasizing the need for research. You’ve probably noticed organizations hiring research managers and analysts. The primary purpose of business research is to determine the goals and opportunities of an organization. It’s critical in making business decisions and appropriately allocating available resources.
Here are a few benefits of research that’ll explain why it is a vital aspect of our professional lives:
One of the greatest benefits of research is to learn and gain a deeper understanding. The deeper you dig into a topic, the more well-versed you are. Furthermore, research has the power to help you build on any personal experience you have on the subject.
Research encourages you to discover the most recent information available. Updated information prevents you from falling behind and helps you present accurate information. You’re better equipped to develop ideas or talk about a topic when you’re armed with the latest inputs.
Research provides you with a good foundation upon which you can develop your thoughts and ideas. People take you more seriously when your suggestions are backed by research. You can speak with greater confidence because you know that the information is accurate.
Take any leading nonprofit organization, you’ll see how they have a strong research arm supported by real-life stories. Research also becomes the base upon which real-life connections and impact can be made. It even helps you communicate better with others and conveys why you’re pursuing something.
As we’ve already established, research is mostly about using existing information to create new ideas and opinions. In the process, it sparks curiosity as you’re encouraged to explore and gain deeper insights into a subject. Curiosity leads to higher levels of positivity and lower levels of anxiety.
Well-defined objectives of research are an essential component of successful research engagement. If you want to drive all aspects of your research methodology such as data collection, design, analysis and recommendation, you need to lay down the objectives of research methodology. In other words, the objectives of research should address the underlying purpose of investigation and analysis. It should outline the steps you’d take to achieve desirable outcomes. Research objectives help you stay focused and adjust your expectations as you progress.
The objectives of research should be closely related to the problem statement, giving way to specific and achievable goals. Here are the four types of research objectives for you to explore:
Also known as secondary objectives, general objectives provide a detailed view of the aim of a study. In other words, you get a general overview of what you want to achieve by the end of your study. For example, if you want to study an organization’s contribution to environmental sustainability, your general objective could be: a study of sustainable practices and the use of renewable energy by the organization.
Specific objectives define the primary aim of the study. Typically, general objectives provide the foundation for identifying specific objectives. In other words, when general objectives are broken down into smaller and logically connected objectives, they’re known as specific objectives. They help define the who, what, why, when and how aspects of your project. Once you identify the main objective of research, it’s easier to develop and pursue a plan of action.
Let’s take the example of ‘a study of an organization’s contribution to environmental sustainability’ again. The specific objectives will look like this:
To determine through history how the organization has changed its practices and adopted new solutions
To assess how the new practices, technology and strategies will contribute to the overall effectiveness
Once you’ve identified the objectives of research, it’s time to organize your thoughts and streamline your research goals. Here are a few effective tips to develop a powerful research plan and improve your business performance.
Your research objectives should be SMART—Specific, Measurable, Achievable, Realistic and Time-constrained. When you focus on utilizing available resources and setting realistic timeframes and milestones, it’s easier to prioritize objectives. Continuously track your progress and check whether you need to revise your expectations or targets. This way, you’re in greater control over the process.
Create a plan that’ll help you select appropriate methods to collect accurate information. A well-structured plan allows you to use logical and creative approaches towards problem-solving. The complexity of information and your skills are bound to influence your plan, which is why you need to make room for flexibility. The availability of resources will also play a big role in influencing your decisions.
After you’ve created a plan for the research process, make a list of the data you’re going to collect and the methods you’ll use. Not only will it help make sense of your insights but also keep track of your approach. The information you collect should be:
Logical, rigorous and objective
Can be reproduced by other people working on the same subject
Free of errors and highlighting necessary details
Current and updated
Includes everything required to support your argument/suggestions
Data analysis is the most crucial part of the process and there are many ways in which the information can be utilized. Four types of data analysis are often seen in a professional environment. While they may be divided into separate categories, they’re linked to each other.
The most commonly used data analysis, descriptive analysis simply summarizes past data. For example, Key Performance Indicators (KPIs) use descriptive analysis. It establishes certain benchmarks after studying how someone has been performing in the past.
The next step is to identify why something happened. Diagnostic analysis uses the information gathered through descriptive analysis and helps find the underlying causes of an outcome. For example, if a marketing initiative was successful, you deep-dive into the strategies that worked.
It attempts to answer ‘what’s likely to happen’. Predictive analysis makes use of past data to predict future outcomes. However, the accuracy of predictions depends on the quality of the data provided. Risk assessment is an ideal example of using predictive analysis.
The most sought-after type of data analysis, prescriptive analysis combines the insights of all of the previous analyses. It’s a huge organizational commitment as it requires plenty of effort and resources. A great example of prescriptive analysis is Artificial Intelligence (AI), which consumes large amounts of data. You need to be prepared to commit to this type of analysis.
Once you’ve collected and collated your data, it’s time to review it and draw accurate conclusions. Here are a few ways to improve the review process:
Identify the fundamental issues, opportunities and problems and make note of recurring trends if any
Make a list of your insights and check which is the most or the least common. In short, keep track of the frequency of each insight
Conduct a SWOT analysis and identify the strengths, weaknesses, opportunities and threats
Write down your conclusions and recommendations of the research
When we think about research, we often associate it with academicians and students. but the truth is research is for everybody who is willing to learn and enhance their knowledge. If you want to master the art of strategically upgrading your knowledge, Harappa Education’s Learning Expertly course has all the answers. Not only will it help you look at things from a fresh perspective but also show you how to acquire new information with greater efficiency. The Growth Mindset framework will teach you how to believe in your abilities to grow and improve. The Learning Transfer framework will help you apply your learnings from one context to another. Begin the journey of tactful learning and self-improvement today!
Explore Harappa Diaries to learn more about topics related to the THINK Habit such as Learning From Experience , Critical Thinking & What is Brainstorming to think clearly and rationally.
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Methodology
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.
First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :
Second, decide how you will analyze the data .
Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.
Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.
Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.
For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .
If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .
Qualitative | to broader populations. . | |
---|---|---|
Quantitative | . |
You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.
Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).
If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.
Primary | . | methods. |
---|---|---|
Secondary |
In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .
In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .
To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.
Descriptive | . . | |
---|---|---|
Experimental |
Research method | Primary or secondary? | Qualitative or quantitative? | When to use |
---|---|---|---|
Primary | Quantitative | To test cause-and-effect relationships. | |
Primary | Quantitative | To understand general characteristics of a population. | |
Interview/focus group | Primary | Qualitative | To gain more in-depth understanding of a topic. |
Observation | Primary | Either | To understand how something occurs in its natural setting. |
Secondary | Either | To situate your research in an existing body of work, or to evaluate trends within a research topic. | |
Either | Either | To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study. |
Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.
Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.
Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:
Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .
Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).
You can use quantitative analysis to interpret data that was collected either:
Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.
Research method | Qualitative or quantitative? | When to use |
---|---|---|
Quantitative | To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations). | |
Meta-analysis | Quantitative | To statistically analyze the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner. |
Qualitative | To analyze data collected from interviews, , or textual sources. To understand general themes in the data and how they are communicated. | |
Either | To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words). |
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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.
Research bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.
In statistics, sampling allows you to test a hypothesis about the characteristics of a population.
The research methods you use depend on the type of data you need to answer your research question .
Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.
Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).
In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .
In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.
Other students also liked, writing strong research questions | criteria & examples.
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Introduction.
Research objectives play a crucial role in any research study. They provide a clear direction and purpose for the research, guiding the researcher in their investigation. Understanding research objectives is essential for conducting a successful study and achieving meaningful results.
In this comprehensive review, we will delve into the definition of research objectives, exploring their characteristics, types, and examples. We will also discuss the relationship between research objectives and research questions, as well as provide insights into how to write effective research objectives. Additionally, we will examine the role of research objectives in research methodology and highlight the importance of them in a study. By the end of this review, you will have a comprehensive understanding of research objectives and their significance in the research process.
A research objective is defined as a clear and concise statement that outlines the specific goals and aims of a research study. These objectives are designed to be specific, measurable, achievable, relevant, and time-bound (SMART), ensuring they provide a structured pathway to accomplishing the intended outcomes of the project. Each objective serves as a foundational element that summarizes the purpose of your study, guiding the research activities and helping to measure progress toward the study’s goals. Additionally, research objectives are integral components of the research framework , establishing a clear direction that aligns with the overall research questions and hypotheses. This alignment helps to ensure that the study remains focused and relevant, facilitating the systematic collection, analysis, and interpretation of data.
Characteristics of research objectives include:
By incorporating these characteristics into research objectives, researchers can ensure that their study is focused, achievable, and contributes to the body of knowledge in their field.
Research objective can be broadly classified into general and specific objectives. General objectives are broad statements that define the overall purpose of the research. They provide a broad direction for the study and help in setting the context. Specific objectives, on the other hand, are detailed objectives that describe what will be researched during the study. They are more focused and provide specific outcomes that the researcher aims to achieve. Specific objectives are derived from the general objectives and help in breaking down the research into smaller, manageable parts. The specific objectives should be clear, measurable, and achievable. They should be designed in a way that allows the researcher to answer the research questions and address the research problem.
In addition to general and specific objectives, research objective can also be categorized as descriptive or analytical objectives. Descriptive objectives focus on describing the characteristics or phenomena of a particular subject or population. They involve surveys, observations, and data collection to provide a detailed understanding of the subject. Analytical objectives, on the other hand, aim to analyze the relationships between variables or factors. They involve data analysis and interpretation to gain insights and draw conclusions.
Both descriptive and analytical objectives are important in research as they serve different purposes and contribute to a comprehensive understanding of the research topic.
Here are some examples of research objectives in different fields:
1. Objective: To identify key characteristics and styles of Renaissance art.
This objective focuses on exploring the characteristics and styles of art during the Renaissance period. The research may involve analyzing various artworks, studying historical documents, and interviewing experts in the field.
2. Objective: To analyze modern art trends and their impact on society.
This objective aims to examine the current trends in modern art and understand how they influence society. The research may involve analyzing artworks, conducting surveys or interviews with artists and art enthusiasts, and studying the social and cultural implications of modern art.
3. Objective: To investigate the effects of exercise on mental health.
This objective focuses on studying the relationship between exercise and mental health. The research may involve conducting experiments or surveys to assess the impact of exercise on factors such as stress, anxiety, and depression.
4. Objective: To explore the factors influencing consumer purchasing decisions in the fashion industry.
This objective aims to understand the various factors that influence consumers’ purchasing decisions in the fashion industry. The research may involve conducting surveys, analyzing consumer behavior data, and studying the impact of marketing strategies on consumer choices.
5. Objective: To examine the effectiveness of a new drug in treating a specific medical condition.
This objective focuses on evaluating the effectiveness of a newly developed drug in treating a particular medical condition. The research may involve conducting clinical trials, analyzing patient data, and comparing the outcomes of the new drug with existing treatment options.
These examples demonstrate the diversity of research objectives across different disciplines. Each objective is specific, measurable, and achievable, providing a clear direction for the research study.
Research objectives and research questions are essential components of a research project. Research objective describe what you intend your research project to accomplish. They summarize the approach and purpose of the project and provide a clear direction for the research. Research questions, on the other hand, are the starting point of any good research. They guide the overall direction of the research and help identify and focus on the research gaps .
The main difference between research questions and objectives is their form. Research questions are stated in a question form, while objectives are specific, measurable, and achievable goals that you aim to accomplish within a specified timeframe. Research questions are broad statements that provide a roadmap for the research, while objectives break down the research aim into smaller, actionable steps.
Research objectives and research questions work together to form the ‘golden thread’ of a research project. The research aim specifies what the study will answer, while the objectives and questions specify how the study will answer it. They provide a clear focus and scope for the research project, helping researchers stay on track and ensure that their study is meaningful and relevant.
When writing research objectives and questions, it is important to be clear, concise, and specific. Each objective or question should address a specific aspect of the research and contribute to the overall goal of the study. They should also be measurable, meaning that their achievement can be assessed and evaluated. Additionally, research objectives and questions should be achievable within the given timeframe and resources of the research project. By clearly defining the objectives and questions, researchers can effectively plan and execute their research, leading to valuable insights and contributions to the field.
Writing research objective is a crucial step in any research project. The objectives provide a clear direction and purpose for the study, guiding the researcher in their data collection and analysis. Here are some tips on how to write effective research objective:
1. Be clear and specific
Research objective should be written in a clear and specific manner. Avoid vague or ambiguous language that can lead to confusion. Clearly state what you intend to achieve through your research.
2. Use action verbs
Start your research objective with action verbs that describe the desired outcome. Action verbs such as ‘investigate’, ‘analyze’, ‘compare’, ‘evaluate’, or ‘identify’ help to convey the purpose of the study.
3. Align with research questions or hypotheses
Ensure that your research objectives are aligned with your research questions or hypotheses. The objectives should address the main goals of your study and provide a framework for answering your research questions or testing your hypotheses.
4. Be realistic and achievable
Set research objectives that are realistic and achievable within the scope of your study. Consider the available resources, time constraints, and feasibility of your objectives. Unrealistic objectives can lead to frustration and hinder the progress of your research.
5. Consider the significance and relevance
Reflect on the significance and relevance of your research objectives. How will achieving these objectives contribute to the existing knowledge or address a gap in the literature? Ensure that your objectives have a clear purpose and value.
6. Seek feedback
It is beneficial to seek feedback on your research objectives from colleagues, mentors, or experts in your field. They can provide valuable insights and suggestions for improving the clarity and effectiveness of your objectives.
7. Revise and refine
Research objectives are not set in stone. As you progress in your research, you may need to revise and refine your objectives to align with new findings or changes in the research context. Regularly review and update your objectives to ensure they remain relevant and focused.
By following these tips, you can write research objectives that are clear, focused, and aligned with your research goals. Well-defined objectives will guide your research process and help you achieve meaningful outcomes.
Research objectives play a crucial role in the research methodology . In research methodology, research objectives are formulated based on the research questions or problem statement. These objectives help in defining the scope and focus of the study, ensuring that the research is conducted in a systematic and organized manner.
The research objectives in research methodology act as a roadmap for the research project. They help in identifying the key variables to be studied, determining the research design and methodology, and selecting the appropriate data collection methods .
Furthermore, research objectives in research methodology assist in evaluating the success of the study. By setting clear objectives, researchers can assess whether the desired outcomes have been achieved and determine the effectiveness of the research methods employed. It is important to note that research objectives in research methodology should be aligned with the overall research aim. They should address the specific aspects or components of the research aim and provide a framework for achieving the desired outcomes.
The research objectives of a study play a crucial role in guiding the research process, ensuring that the study is focused, purposeful, and contributes to the advancement of knowledge in the field. It is important to note that the research objectives may evolve or change as the study progresses. As new information is gathered and analyzed, the researcher may need to revise the objectives to ensure that they remain relevant and achievable.
In summary, research objectives are essential components in writing an effective research paper . They provide a roadmap for the research process, guiding the researcher in their investigation and helping to ensure that the study is purposeful and meaningful. By understanding and effectively utilizing research objectives, researchers can enhance the quality and impact of their research endeavors.
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Part of the book series: SpringerBriefs in Criminology ((BRIEFSCRIMINOL))
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The chapter illustrates both the objective and the methodology of the research presented in the book. Possible evaluation research designs are reviewed, highlighting their strengths and weaknesses and analysing which one is the more suitable for the purposes of the present research – i.e. a natural experiment with one group(s) post-test only design, using a non-equivalent qualitative pre-test. Then, strategies for data gathering and analysis are presented. In more detail, the methodology used consisted of systematic keyword searches on the three mayor social media platforms – i.e. Twitter, Facebook, and Instagram – after the implementation of the SCP measures in order to identify and analyse contents linked to the illegal online trade of medicines. The keyword list comprises 76 terms of two different types: 36 names of medicines, both generic and branded names, and 8 general terms in 5 languages – i.e. 40 keywords overall – referring to disease or condition and the medicines that are intended to treat them, or their therapeutic category. In order to assess the impact of the SCP interventions, data was analysed ‘vertically’ (i.e. by social media and by therapeutic category) and ‘horizontally’ (i.e. across social media and therapeutic category). Results (presented in Chap. 5 ) were compared to the situation existing before the implementation of the measures by using six qualitative indicators.
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The last five keywords included a list of different medicines mainly used to treat serious diseases, i.e. (a) expensive medicines to treat hepatitis C (Sovaldi and Harvoni); (b) a medicine to treat infertility in women (Clomid); (c) a medicine to treat breast cancer (Nolvadex); and (d) a medicine to treat alcoholism (Disulfiram).
Several attentions have been given to possible ethical issues in research activities investigating social media. For instance, please see Social Data Science Lab, 2018 ; Williams, Burnap, & Sloan, 2017 .
On Facebook does not exist a specific searching category grouping ‘recent’ posts.
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Faculty of Law, University of Trento, Trento, Italy
Gabriele Baratto
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Baratto, G. (2020). Research Objective and Methodology. In: The Illegal Trade of Medicines on Social Media. SpringerBriefs in Criminology. Springer, Cham. https://doi.org/10.1007/978-3-030-57582-3_4
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This report presents the findings from a public dialogue on the use of data in Scotland commissioned by the Scottish Government to explore the ethics of data-led projects. The purpose of the panel was to inform approaches to data use by the Scottish Government and public sector agencies in Scotland.
The Scottish Government has stated a commitment to using data and digital technologies in an ethical way for the benefit of the people of Scotland. [5]
During the pandemic the Data and Intelligence Network ( DIN ) was set up by the Scottish Government as a dedicated team, providing additional capabilities to ensure that data were utilised effectively and ethically to address key challenges relating to COVID -19. The DIN operated from within the Scottish Government, providing skills and expertise to a wide range of organisations across Scotland’s public sector and providing support with their data-led projects at the height of the COVID -19 pandemic. The projects that the DIN advised on presented ethical dilemmas in how to reconcile the privacy, rights and freedoms of people in Scotland with rapid, proactive, and responsible use of information. The need for urgent and decisive action during the COVID -19 pandemic meant that data-led projects were fast-tracked to implementation, and the opportunities for consideration of public views on the social and ethical implications of the data use were limited.
In an increasingly data driven world, good governance is required to ensure public data are used effectively, ethically and appropriately. Engaging the public – those whose data is used in research, planning and service development and delivery – helps to develop trustworthy and robust frameworks for how government and other agencies collect, analyse and use data. Public engagement can take many forms and have multiple purposes, but an overriding aim is to promote better policy and decision making, often through deliberative engagement. [6]
The Scottish Government, together with Research Data Scotland ( RDS ), decided to build on the work done by the DIN which had started to expose some of the ethical challenges of data-led projects. The Scottish Government and RDS agreed to convene a public panel to explore the ethics of past data-led projects supported by the DIN , and possible future projects to inform approaches to data use by the Scottish Government and public sector agencies in Scotland.
The aim of this public panel was to explore perceptions and understanding of public sector data-led projects in order to produce a set of ethical guidelines that the Scottish Government and public sector organisations should follow when using data about citizens. The key research objectives of the panel itself were to explore:
Broader objectives of the project were to:
The public dialogue reported here builds on previous public engagements in Scotland on the use of data (key insights from which are summarised in appendix A). [8]
Ipsos, along with its partners at the University of Edinburgh, designed and facilitated a public panel that was funded and guided by the Scottish Government and UK Research and Innovation’s Sciencewise programme, an internationally recognised public engagement programme which enables policy makers to develop socially informed policy. The specific methodology used with the public panel is known as a “public dialogue”. [9] Public dialogue is a process during which members of the public interact with scientists, stakeholders and policy makers to deliberate on issues relevant to future policy and research decisions.
The panel brought together a group of 25 people from across Scotland to learn about the topic of data use by the Scottish Government and public sector agencies. The panel met over six three-hour online workshops [10] between September and December 2022 to answer the following key question:
Over the course of the public dialogue, participants reviewed different data-led projects that the DIN had been involved in previously or were considering involvement in. The panel listened to presentations from experts, learned about the issues, discussed them, and then drew conclusions together to form a set of ethical guidelines which are presented in this report.
Further details about the process (including an overview of each session with dates, times, content and specialists) can be found in appendix D but the overarching design of the dialogue is summarised in figure 1.2 below.
Alongside the online meetings, an online community helped support ongoing engagement with panellists, facilitating continued discussion and reflection.
An oversight group – comprising Scottish Government representatives, Research Data Scotland representatives, and independent experts from academia and civil society – met regularly to advise on the methodology. The oversight group provided checks and challenges over the course of the project to ensure the design of the panel was appropriate, relevant and robust. A list of oversight group members and meeting times is detailed in appendix B.
Participants were recruited using a civic lottery approach, [11] which involves inviting a random selection of households to participate. They were recruited to be broadly reflective of the Scottish population in terms of age, gender, region, ethnicity, disability and education. Ethnic minority groups were over-sampled to ensure sufficient representation of these groups. An attitudinal measure was also included in the selection process to ensure a range of views were represented in terms of trust in the Scottish Government and public sector agencies to use data for the public good. The recruitment process is outlined in more detail in appendix C.
Overall, 30 people were selected to join the panel and 25 participated throughout. A table summarising the demographic profile of the final selected and confirmed sample can be found in appendix C.
To support and enable participation in all workshops, participants were each paid £400 for joining the online sessions and online community. Where necessary, participants were provided with equipment, such as headsets, laptops or internet dongles and were supported with training on how to use the technology and access the meeting platform.
Discussion guides and stimulus materials were developed by Ipsos and reviewed by the Scottish Government, Sciencewise and the oversight group. A range of specialists joined at different points in the dialogue to provide information that would be useful for participants’ learning and deliberation. In the first session, specialists included academics and professionals who explained key concepts to support participants’ discussions (including the role of the DIN , the legal context of data use and an introduction to data ethics). In the following sessions, those involved in the data-led projects being reviewed by the panel provided overviews of these, while academics and representatives from independent research institutes provided alternative perspectives on the projects to help participants consider different views on the use of data about citizens.
Presentations were either delivered live or recorded in advance and played live during the sessions. Some specialists presented in plenary and then stayed to answer questions that arose during breakout discussions. Others presented in smaller groups, remaining in the groups afterwards to take questions directly from participants. Any questions that were not answered during the live sessions were compiled in a Question and Answer (Q&A) document (see appendix E).
The guidelines set out and discussed in this report are intended for consideration in the possible future use of data about citizens by the public sector.
This report synthesises the diverse expressions of participants to draw out major themes of discussions and to draw attention to the way that the panel – individually and collectively – made sense of a complex topic, describing what mattered to them and why. On occasion, the report refers to verbatim assertions by participants and their understanding of the issues. These are not intended as authoritative statements of fact, but they tell us something important about how the issues can be perceived and understood by members of the public.
A robust and systematic analysis approach was used, with conclusions based on groups that are reflective of the diversity of the wider public. The deliberative nature of the project allowed for ongoing analysis throughout fieldwork, which ensured that emerging principles and themes - both from workshop discussions and online community activities - could be played back to participants as the dialogue progressed. Analysis does not seek to quantify findings nor does it indicate statistical significance from a representative sample. A more detailed summary of the analytical approach to the dialogue can be found in appendix D.
This report offers a constructive insight into public perspectives on the key questions posed to them after receiving and deliberating on essential information relevant to the questions.
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BMC Medical Education volume 24 , Article number: 891 ( 2024 ) Cite this article
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Imaging techniques play a central role in modern medicine and therefore it would be beneficial for all medical students to incorporate radiology education in medical school curricula. However, a formal undergraduate radiology curriculum with well-defined learning objectives remains lacking in The Netherlands. This study aims to qualitatively ascertain opinions from clinicians (radiologists and non-radiologists) with regard to radiology education in the medical school curricula, including topics, teaching methods and strategies.
A qualitative study with in-depth semi-structured interviews was conducted. Inclusion was carried out until saturation was achieved, after which 2 additional interviews were held. Interviews were conducted using open-ended questions, following a predefined topic list. The constant comparative method was applied in order to include new questions when unexpected topics arose during the interviews. All interviews were transcribed verbatim and coded using a thematic analysis approach. Codes were organized into categories and themes by discussion between the researchers.
Forty-four clinicians were interviewed (8 radiologists, 36 non-radiologists). The three main themes that were derived from the interviews were: (1) expectations of indispensable knowledge and skills on radiology, (2) organization of radiology education within the medical curriculum and (3) promising educational innovations for the radiology curriculum. The qualitative study design provides more in-depth knowledge on clinicians’ views on educational topics.
The themes and statements of this study provided new insights into educational methods, timing of radiology education and new topics to teach. More research is needed to gain consensus on these subjects and inclusion of the opinion of medical students with regard to radiology education is needed.
• Radiology education in medical curricula was considered important by all interviewees
• Integrating radiology and anatomy in Longitudinal learning communities (LLC’s) could be a promising educational strategy
• Integration of ultrasound education in medical curricula should be investigated further
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Imaging technologies play a central role in the practice of modern medicine. Therefore, it is not surprising that previous studies suggest that all medical students would benefit from (basic) knowledge concerning medical imaging technologies and radiology [ 24 , 37 , 63 ]. However, radiology education is not well integrated in the medical curricula [ 21 , 25 , 29 , 37 ] and students’ lacking knowledge can be potentially dangerous [ 19 , 63 ]. In turn, medical students (including interns) and residents reported a lack of confidence when interpreting radiology examinations, including (chest) radiographs [ 19 , 48 ]. Moreover, lacking radiological knowledge was found to be correlated with an overutilization of medical imaging services [ 27 ], leading to increased societal healthcare-related expenses. Consequently, a need for radiology education in medical schools is recognized among teachers, medical students and curriculum designers [ 1 , 29 , 37 , 42 , 44 , 47 , 48 , 52 , 61 ]. Albeit, the learning objectives of such a radiology curriculum remains a topic of debate [ 61 ]. Therefore, proper identification of useful learning objectives for radiology education in medical curricula should be carried out [ 23 , 54 , 60 , 61 ]. The first step of defining learning objectives is to determine which educational topics are important to teach [ 26 , 34 , 60 , 5 ].
When defining these, it is important to identify the opinions of both clinicians (radiologists and non-radiologists) and medical students since both groups influence which topics are considered important to teach during medical school [ 39 ]. Opinions on this topic diverse, due to the fast technological developments in this broad field, which covers nearly every medical discipline for diagnostic and therapeutic purposes [ 23 , 34 , 63 ]. Several studies have previously aimed to determine radiology curriculum topics by questioning different groups of physicians (both radiologists and non-radiologists) and educational experts using questionnaires [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 , 61 ]. Overall, these studies provided lists of interpretative and non-interpretative skills that respondents agreed on what should be taught in medical school regarding radiology. The most commonly mentioned interpretative skill concerned the systematic approach of reading chest radiographs [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 ]. Suggested non-interpretative skills were more diverse and included (a) the basic physical mechanisms of ionizing radiation, including knowledge on radiation risks [ 32 , 36 , 53 , 53 , 54 , 55 , 55 , 61 ], (b) the principles of justification of procedures (e.g., knowing when to use intravenous contrast agents) [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 , 61 ], and comprehension of the role, indications and limitations of diagnostic imaging (and interventional) techniques [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 , 61 ].
Nevertheless, the aforementioned studies used a survey-based approach in which rather pre-determined information is collected from a large group of participants [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 ]. This study aimed to build on this work by employing an inductive, qualitative approach, allowing for the opportunity to acquire participants’ opinions without any influence of preset questions and to explore these answers to gain more detailed information on a broad range of topics [ 22 , 58 ]. Therefore, it is possible to gain a more accurate insight into the wide diversity of current ideas on education on imaging technology that are continuously changing. Limitations of qualitative research, on the other hand, concern the labor-intensive nature of such studies, which explains why in most fields, qualitative data are lacking. Also, qualitative data are more subjective than quantitative data as the interviewee has more control over the content of the data. Therefore, unnecessary quantification of qualitative data should be avoided as it falsely suggests objective, statistically proven results [ 10 , 38 ].
Consequently, there is a recognized need for enhanced radiology education in medical schools among teachers, students, and curriculum designers. This study aimed to 1) Identify key topics that should be included in a radiology curriculum, 2) Determine effective teaching methods for radiology education and 3) Propose strategies for integrating radiology education into existing medical school curricula. Therefore, we qualitatively investigated the perspectives of clinicians (both radiologists and non-radiologists) on radiology education in medical curricula.
An exploratory inductive qualitative study focusing on the role of radiology education in medical curricula was performed. A pragmatic qualitative approach was used with the aim to identify topics in radiology education that clinicians considered important to embed in the medical curriculum. A sample of clinicians involved in medical education in the Netherlands was asked to provide their insights using in-depth semi-structured interviews. Interviews were performed following an inductive iterative process using the constant comparative method [ 31 ]. This implies that if new topics arose during interviews, it was possible to explore these topics and thereby allowing new topics to be added to the interview guide during the experiment. The interview guide is provided in Table 1 . After interviewing, a thematic approach was used to analyze the data.
Relevant scientific literature was reviewed on learning objectives and teaching methods in radiology education in medical school. After reviewing the available literature, two researchers (F.H. en D.H.) constructed a topic list. An inductive iterative interviewing process was carried out using the constant comparative method [ 51 ]. Therefore, new topics could be added to the topic list during the interviews.
A list of eligible clinicians was constructed by reviewing hospitals and general practitioners within the training region of the university medical center in the east of The Netherlands (OpleidingsRegio Oost-Nederland). The contact person of each practice or department that provided a mandatory internship within the medical curriculum or an elective internship in radiology was contacted by e-mail in order to recruit eligible clinicians. Only clinical specialties embedding radiological imaging in their daily clinical practice were deemed eligible. Therefore, clinicians of the department of psychiatry, dermatology and ophthalmology were excluded from this study. The remaining clinicians were eligible if they participated in any medical curriculum in the Netherlands, regardless of being involved in the Bachelor’s or Master’s phase. Additionally, clinicians needed to be board-certified and actively working medical specialists, general practitioners or residents in radiology. Moreover, board-certified radiologists of the same training region who were involved in (any) medical curriculum in the Netherlands were included to provide more insight into what these “imaging experts” considered important to teach. Eligible clinicians were contacted by use of e-mail. After no initial response, the eligible clinicians were contacted again two weeks later. A third reminder was sent after a longer period of time, which varied from two weeks to three months. If no response was received, the participant was excluded from further inclusion.
This study was approved by the ethics committee of the Netherlands Association of Medical Education (NVMO, case number 2023.2.9). Before being interviewed, clinicians confirmed to participate in the study. Informed consent was obtained from all clinicians prior to the interview in which the clinicians consented to have the interview audio-recorded for further analyses. Moreover, all methods were carried out in accordance with relevant guidelines and regulations. All recorded data was stored on a secured disc, to which only one researcher (F.H.) had access. Transcribed data was stored and analyzed anonymously.
Individual semi-structured interviews were conducted by one of the researchers (F.H.). Clinicians decided in which way the interviews were held: in person, via electronic telecommunication software (i.e. Skype version 8.65.0.78; Skype Technologies, Luxembourg City, Luxembourg Palo Alto, CA, United States) or by telephone. In addition, four clinicians provided extensive answers to interview questions via e-mail. These data were also used in the data analysis. The interviews started with a short introduction of the research content followed by an open question on the participant’s thoughts on this matter. During the interviews, the interviewer used open-ended questions and encouraged the clinicians to speak openly and express their opinions, thoughts and considerations. The interviewer explained that there were no relations with the board of examiners, the university medical center educational board or the educational management team. In order to ensure reliable data, all interviews were audio-recorded and transcribed verbatim afterwards. Each transcript was thereafter analyzed using direct content analysis [ 30 ]. Starting after the first interview had taken place; transcriptions were coded line-by-line, through which a code list was created. Coding was continued after each interview. Inclusion of new participants was halted when no new topics and codes arose from this process, indicating that data saturation occurred. To confirm data saturation, two additional interviews were held. When confirmed, inclusion of new participants was stopped.
The interview transcripts were analyzed qualitatively. The first four transcripts were independently analyzed by two researchers (F.H. and B.v.W.). Coding results were compared and discrepancies were resolved by discussion. If necessary, a third more experienced investigator (D.H.) could be asked to help resolve issues. Since there were no major discrepancies, further coding and analysis were carried out independently by one of the researchers (F.H.), who met periodically with one of the other researchers (D.H.) to discuss codes and themes until consensus was reached. The coding process was performed using Atlas.ti software, version 8.2.29.0 (ATLAS.ti Scientific Software Development GmbH, Berlin, Germany). The constructed codebook was organized into categories and themes which arose after discussion of all the different codes between two of the researchers (F.H. and D.H.). Categories were used to group codes, which were then grouped into several themes. The categories and themes were shared with the other researchers in order to assess their validity.
A total of 97 eligible clinicians (radiologists; 10.3% and non-radiologists; 89.7%) were contacted by one of the researchers (F.H.) via e-mail between July and October 2020 (Table 2 ). Non-responders were excluded after a period of six months after the first e-mail was sent ( n = 44). Clinicians were also excluded if they expressed to have no active involvement in medical curricula ( n = 3) (Fig. 1 ). Of the included clinicians, four reactions were received via e-mail, while the other forty respondents provided their input by participating in an interview. The interviews lasted between 17 and 59 min. Participant characteristics are displayed in Table 2 .
Selection of the clinicians. 1 Six clinicians were not available due to lack of time . 2 Three contacted clinicians were excluded since they no longer worked for the specific training region
Ten categories of items were distilled from the transcribed codes, which were arranged in the following three themes (Fig. 2 ).
An overview of the subcategorized themes. Three themes accompanied by ten categories were derived from the interviews during the analysis after qualitative exploration of the opinions of clinicians and general practicioners on imaging technologies in medical school curricula
Anatomical knowledge.
Interviewees advocated that students need to be able to identify important anatomical landmarks and gross anatomical structures on the different radiologic imaging techniques. Knowledge of anatomy was believed to be the foundation of understanding a radiologic image by both radiologists and non-radiologists.
“It starts with that [knowledge of the human anatomy], as this forms the foundation of radiology. Then, you can also start interpreting medical images” – General Practitioner
“… but I sense that there is little attention for forming an idea on the anatomical relations. And in the end, that is the essence…” – Surgeon
Conversely, Computed Tomography scans (CT-scans) and Ultrasound (US) were suggested as ideal tools to teach anatomy in medical school. This was believed to benefit both anatomy education and radiology education. This combination provides clinical significance to anatomical structures as well as a three-dimensional insight into the anatomy. Furthermore, it would lead to early exposure to medical imaging in the curriculum. Magnetic Resonance Imaging scans (MRI-scans) were both suggested and dissuaded as a teaching tool because of their complexity.
Interviews with both radiologists and non-radiologists revealed that the ability to interpret a wide range of radiological studies should not be included as a learning objective in medical school. Learning to interpret specific radiological studies (e.g., CT study of the thorax, brain MRI) should be incorporated in post-academic education for residents in training, as there is a greater exposure to these specific radiological studies during this period. Nevertheless, interviewees stated four things a medical student should be able to do concerning radiographs: (1) distinguish abnormal from normal (recognizing gross abnormalities), (2) identify some very common pathologies (e.g., pulmonary infiltrates, common bone fractures, joint luxation, pulmonary edema, hemorrhage, ischemia and malignancies), (3) identify acute diagnoses (e.g., vertebral fractures and pneumothorax on radiographs) and (4) acquire a systematic approach when reading radiographs (both chest radiographies and musculoskeletal radiographies). The extent to which these skills should be mastered under supervision was scarcely discussed and varied greatly.
Knowledge on the techniques of the four major different imaging modalities (radiography, CT, MRI and ultrasound) was regarded important as this provides knowledge on (contra-)indications and strengths and weaknesses of each imaging modality. It can also help a student interpret medical images as it helps to understand which structures are visible and why they are displayed in the way they are (e.g., the differences in size while comparing an AP- and PA-radiograph). It could also help students to understand the content of a radiological report (e.g., helping to understand why radiologists discuss patient positioning in their reports).
“You have to know the basics. You can order radiographs, a CT-scan, or an ultrasound or an MRI-scan. And the reason why you would choose one option or another is always different, but you always visualize something with it. I consider it important to know what a specific imaging technique shows you.” – Emergency doctor.
More specifically, it was considered important to have knowledge on the basics of ionization radiation, including its hazardous effects. For MR imaging, knowledge of the basic differences between T1-weighted-, T2-weighted-, and fluid-attenuation inversion recovery (FLAIR) sequences were disclosed as important subjects to master for medical students.
In addition, the impact that a radiological examination has on a patient (both mentally as well as physically) should also be embedded in the medical curriculum. This would also help future healthcare professionals to inform their patients properly in order to achieve well-informed consent.
“...I think that it is good to know because we receive a lot of questions from patients about radiologic studies” – General Practitioner
The most common (contra-)indications and limitations of the most frequently used modalities are seen as imperative knowledge which a student should acquire in medical school. This includes insights in accuracy rates of different radiological imaging methods and how these rates are influenced by other factors, as well as the costs of the different modalities. It should be noted that some clinicians mentioned that keeping up with the quickly changing indications could be a challenge and another participant did not find knowledge in indication important. All believed that you should always consult a radiologist when in doubt.
The benefits and drawbacks of the use of contrast agents, especially in CT imaging, and its (contra-)indications are worth emphasizing, for it has been mentioned multiple times in the interviews and is apart from one explicit modality.
“I believe that it is very important that you know which radiological examinations are available and what you can use each one of them for. I also believe that it is very important that students are aware of the costs of the different imaging modalities and that they also take this into account when making a decision. And that they realize which study is useful for a specific question” – General Practitioner.
As each medical specialty has some level of experience with certain radiological imaging methods, it is important that students learn which techniques are used in various settings.. This was reported as a learning goal which should be achieved through experience-based learning (i.e., during internships). Also, clinicians expressed that it was paramount that students learn to write a concise though complete request for radiological imaging. In addition, students need to learn to look critically and should learn how to implement the radiologist's conclusion in the clinical setting for further medical management and/or follow-up.
Finally, students should also learn to consult the radiologist when questions arise regarding the most optimal imaging method or the radiological conclusion and how to interpret it.
“Radiological findings are subjected to interpretation: someone sees an abnormality and expects it to be something. And those expectations are supported or undermined by the clinical presentation and you have to either provide this knowledge to the radiologist or have to take this into account yourself”—ENT-specialist.
“I noticed that they [students and junior doctors] have no comprehension of contrast agents and therefore just follow guidelines which state to ‘Check renal function’. They have no idea why and whether they have to order for contrast agents” – Radiologist.
Timing and emphasizing responsibilities.
Most interviewees were convinced that during the Bachelor’s phase (i.e., the first three years of the university curriculum), imaging technology education needs to focus on the differences between modalities from a technical point of view. During those three years, radiological images should be used to help students understand the technical basis of imaging and recognize anatomical structures. This should gradually evolve into using radiological images to recognize simple pathology at the end of the Bachelor’s phase (e.g., bone fractures, pneumonia, pneumothorax). During the Master’s phase (last three years of university curriculum), the interviewees considered applied radiology as an important learning goal. This education could then be combined with recapitulating the anatomy.
“I think that it should definitely be addressed in the Bachelor’s phase, but that the subjects in radiology that are embedded in an internship should be addressed in more detailed and specific way before that internship. I am actually getting thrilled by that idea”—General practitioner.
It was believed that students will get more familiar with radiology when learning about imaging technologies is combined with anatomy and repeated over the years. Doing this while emphasizing different aspects of radiology during different learning phases of students, was also believed to result in a greater feeling of competence for medical students, especially with regard to chest radiographs and musculoskeletal radiographs. Therefore, radiology education during the Master’s phase of medicine should also focus on basic, structured interpretation of chest radiographs.
Interviewees suggested incorporating Entrusted Professional Abilities (EPAs) for radiology in the internships, so that radiology knowledge can be reviewed and improved continuously. Therefore, the knowledge of radiology can be monitored during the internships in the same way the discipline of radiology is integrated through all the different specialisms in medicine.
Longitudinal subject planning.
The idea of Longitudinal Learning Communities (LLCs) in radiology was discussed during all interviews. LLCs were defined as a community-based approach to learning during a time period of more than 1 year, encouraging meaningful student interaction and small-group learning as well as peer-group evaluation. LLCs were believed to help students to develop a collaborative approach to clinical practice, particularly in radiology. Clinicians believed that a timely repetition of anatomical and radiological knowledge before an internship would result in an improved learning experience.
Three clinicians, all non-radiologists, did not support more radiology education in already overcrowded medical curricula. One participant explicitly expressed that an LLC in radiology would take up too much time. Other interviewees (both radiologists and non-radiologists), however, considered radiology to be important enough to devote attention to, for example by use of LLCs. One participant also suggested saving time by combining the LLC with anatomy and physiology education throughout the medical curriculum. The learning materials used in such LLCs on radiology education were discussed as well. Suggested teaching methods included e-learnings and interactive workgroups. Additionally, the use of clinical cases during education as a form of applied radiology was expressed by many. Nevertheless, discrepancies remained with regard to the different teaching forms. Proposed forms were interactive teaching forms, clinical cases, lectures, computer orientated education, e-learnings, workshops, self-study, seminars, learning during the internships themselves (via specific educational moments, multidisciplinary meetings, during consulting hours at the outpatient department, radiology meetings, before surgery or via assignments). Clinicians expressed that they found it difficult to decide which educational methods would create the best learning environment for students.
Some additions to the described LLC were mentioned during the interviews. Several clinicians, both radiologists and non-radiologists, suggested adding practical ultrasound education to the LLC’s. One participant highlighted the importance of recapitulation shortly before practical education, also called in-time learning. This person believed that students would benefit more from good references, so they would know where to look when they need it and have clear learning objectives for radiology during their internships.
‘…I strongly believe that just in time learning would be a valuable option. If you simply teach students in-time where to find specific knowledge on radiology, they will use it when they need it the most. Then, all they need to do is practice their knowledge” – Geriatrician.
‘If you learn about radiological examinations relevant in the clinical practice that you are about to embark in, you will learn the basics just prior to your internship and the clinical context will help you to complete the picture. Together, I would consider this a rich learning experience for students” – Radiologist.
Due to a lack of time in the medical curriculum, most of the interviewees would not opt for the incorporation of a mandatory internship in radiology. Nevertheless, it was considered an important elective internship. Only one participant believed it was important to create time for a mandatory internship.
On the other hand, interviewees expressed that some practical experience in radiology for all medical students would be beneficial to: (1) gain insight into the tasks of a radiologist, (2) become aware of one’s own strengths and limitations regarding reading radiological examinations and (3) learn how to establish an optimal collaboration between radiologist and clinician. It was mentioned that such “intern days” could be integrated into the proposed LLCs in radiology or in various internships such as emergency and internal medicine or surgery.
“I consider it a good idea to offer it as an internship for choice, apart from the LLC”- Internal medicine doctor
There was some discussion with regard to learning the skill of interpretation of a chest radiograph and the skill to perform a point-of-care ultrasound (POCUS). Chest radiography in itself takes a prominent place in radiology education and was believed to deserve a specific view on learning goals. There is an emerging use of POCUS in health care and the opinions on what should be taught on this subject diverse widely. Some interviewees thought that integrating POCUS as an intra-curricular learning goal would take up too much time to really let students master this skill. On the other hand, others were eager to implement teaching POCUS in the medical curriculum as it could serve as an extension on the physical examination with immediate results, low costs and high mobility with hand-held devices. It was mentioned that since so little is taught on ultrasound, there is so much to gain out of a bit more education.
“If you ask me, we will all throw out our stethoscope and let everyone have an ultrasound machine and I do believe that time will come. I just do not know how soon” – Emergency doctor
This study elucidated the views of both radiologists and non-radiologists and grouped these views in three themes: 1) Expectations with regard to educational topics in radiology education; 2) Teaching strategies with regard to radiology education; and 3) Promising educational strategies in radiology education.
These findings are largely corroborated by others. For example, Subramaniam et al. [ 53 , 55 , 55 ] also showed that radiology education should include the teaching of (contra-)indications for different imaging techniques, skills to systematically review chest and musculoskeletal radiographs, skills to identify gross abnormalities on radiographs and teaching students how to fit important findings in the clinical setting. However, contradictory to the studies of Subramaniam et al., interviewees did not express the reading of abdominal radiographs as an educational topic, which can be explained by the ongoing development of radiology in the clinical setting [ 2 , 57 ]. At the time of the publication of the papers of Subramaniam et al., abdominal radiographs had a more prominent clinical role than today.
Interviewees in this study stated that basic anatomical knowledge is needed to fully comprehend imaging studies. However, as less time is being assigned to anatomy education in medical curricula [ 18 , 35 , 4 ], learning about radiological examinations could become more complicated for students. Also, as Kourdioukova et al. [ 33 ] mention in their paper, Problem Based Curricula create a building block approach in which radiology and radiologic anatomy is relatively underrepresented in examinations. Integration of applied anatomy and applied radiology has been commonly suggested to optimize quality of anatomy and radiology education in modern medical curricula, [ 4 , 14 , 28 , 36 ]. This was also objectified as radiology small group teaching significantly improved anatomy scores [ 8 , 9 ] and radiology skills [ 40 ]. Additionally, combining radiology and anatomy education has been described to be easily implementable in existing preclinical curricula, because it requires few additional resources [ 62 ]. Integration of radiology education with other disciplines has also been suggested [ 42 ]. Interestingly, in the current study, MRI sequence which were considered basic knowledge comprised T1-weighted images, T2-weighted images and FLAIR images, whereas other sequences were not mentioned. Fat suppression techniques were not discussed, although several advantages are well-known in for example neuroradiology [ 56 ] and imaging of the musculoskeletal system [ 16 ]. Also, the use of diffusion-weighted imaging was not mentioned as part of the basic knowledge that a medical student must obtain. Possibly, clinicians omitted these sequence as the physical concepts are somewhat more complex to explain to students during rotations. However, the exact motives remain elusive. Together with the positive feedback to the LLC in the interviews of this study, a balanced integration of radiology education in various subjects of teaching could be a promising next step for radiology educators.
Other innovative teaching methods which might play a role in the future of anatomy and radiology education, such as augmented reality, virtual reality and combined use of these techniques with radiological data were not mentioned during the interviews. Nevertheless, several publications point out the possible advantages of each individual technique [ 6 , 3 , 12 , 13 , 41 ].
Although in this study chest radiographs were considered an important educational topic in medical school, there was a wide diversity in opinion to what extent a student should master this subcategory of imaging technologies. Even though this study was not able to provide results to what extent of supervision level or entrusted professional activity a medical student should master this skill, this study was the first that objectified this wide diversity in opinions. We believe this should be investigated more profoundly to be able to create a properly adjusted learning objective on this topic. Especially since Eisen and colleagues found that only 15% of their study population, consisting of medical students, interns, residents and fellows, felt capable to interpret chest radiographs independently in an academic medical center setting [ 19 ]. This lack of confidence has been found by others as well [ 7 , 11 ].
Lastly, teaching ultrasound was a topic of debate in our study, which was widely discussed among the interviewees. This observed discrepancy is in line with literature on this topic [ 36 , 50 ]. Although ultrasound has been described as an educational tool to improve anatomy knowledge, physical examination skills, increase diagnostic accuracy and advance patient safety, the evidence regarding the effects of ultrasound education on these outcomes is very limited [ 20 ]. Nevertheless, various studies reported that medical students consider ultrasound education as valuable [ 15 , 17 , 46 , 49 , 59 ]. Despite this increased demand of ultrasound education in medical school, studies showed that hands-on education of ultrasound is taught at a minority of universities in Europe and the United States [ 43 , 45 ]. More research is needed to either create insight into the learning objectives of ultrasound in medical curricula or to chart the potential benefits of teaching ultrasound in medical school. Additionally, the effects of using ultrasound for educational goals on learning outcomes should be studied as well.
The major strength of this study was the qualitative study design as a recent review highlighted that quality research is needed to investigate when and how radiology should be included in medical education [ 8 , 9 ]. A second strength concerns the exploration of the thoughts and opinions of a wide variety of clinicians included in this study. The sparse availability of recent scientific literature on the teaching of a dynamic subject like medical imaging illustrates that this is a relatively understudied domain and, simultaneously, shows the importance of the present work. This work, however, is not without its limitations. One limitation of this study was formed by the strictly defined inclusion criteria which only allowed clinicians from one region within The Netherlands to participate. The ideas on this topic within this region can differ from others since every training region has its own personal and cultural view on certain subjects and specific spearheads. This limitation regarding generalizability of the reported themes might also exist for the clinicians’ views on radiology education in countries other than The Netherlands. Secondly, this study population cannot be considered as a generalizable population of clinicians which are involved in medical education. For example, the number of radiologists participating in this study was larger as compared to the number of general practitioners (Table 2 ). Therefore, radiologists were overrepresented in the study population. In addition, some medical disciplines, such as psychiatry, ophthalmology and dermatology were excluded from this interview study due to the fact that these clinicians do not frequently encounter radiology. However, the risk of potential bias is limited as the nature of this study and research question did not warrant the inclusion of these clinicians. Furthermore, a limitation of the qualitative study design concerns the relative subjectivity of the results as participants hold control over the content of the data. This prevents quantification of the results and warrants future studies to investigate the statistical significance of the here described findings [ 10 , 38 ]. Additionally, it must be noted that clinicians are no education experts. Future implementation of these results should be carried out in close collaboration with education experts.
This qualitative study provided more in-depth knowledge on well-known topics with regard to radiology education in medical curricula. More knowledge with regard to educational methods, timing of radiology education was distilled and several new topics arose. This includes thoughts on educating ultrasound skills to undergraduates and the views on a longitudinal learning community in radiology in order to integrate imaging technologies in a problem based medical curriculum. It was recommended that radiology education should be more embedded in the medical curriculum and various educational strategies and topics to achieve this were suggested. Nevertheless, to which extent these educational topics should be mastered, what resulting learning objectives will need to entail and how to evaluate them need further research.
The dataset generated from the interviews and analyzed during the current study are not publicly available since individual privacy could potentially be compromised but are available from the corresponding author on reasonable request.
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The authors would like to acknowledge Beau van Woudenberg, MSc, for his help with coding the interviews and with his valuable insights into qualitative research methods. No potential conflict of interest was reported.
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Frederike S. Harthoorn, Sascha W. J. Scharenborg, Monique Brink, Liesbeth Peters-Bax & Dylan Henssen
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Harthoorn, F.S., Scharenborg, S.W.J., Brink, M. et al. Radiology education for medical students: a qualitative exploration of educational topics, teaching methods and future strategies. BMC Med Educ 24 , 891 (2024). https://doi.org/10.1186/s12909-024-05879-0
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Background: Dual task paradigms are thought to offer a quantitative means to assess cognitive reserve and the brain’s capacity to allocate resources in the face of competing cognitive demands. The most common dual task paradigms examine the interplay between gait or balance control and cognitive function. However, gait and balance tasks can be physically challenging for older adults and may pose a risk of falls.
Objective: We introduce a novel, digital dual-task assessment that combines a motor-control task (the “ball balancing” test), which challenges an individual to maintain a virtual ball within a designated zone, with a concurrent cognitive task (the backward digit span task [BDST]).
Methods: The task was administered on a touchscreen tablet, performance was measured using the inertial sensors embedded in the tablet, conducted under both single- and dual-task conditions. The clinical use of the task was evaluated on a sample of 375 older adult participants (n=210 female; aged 73.0, SD 6.5 years).
Results: All older adults, including those with mild cognitive impairment (MCI) and Alzheimer disease–related dementia (ADRD), and those with poor balance and gait problems due to diabetes, osteoarthritis, peripheral neuropathy, and other causes, were able to complete the task comfortably and safely while seated. As expected, task performance significantly decreased under dual task conditions compared to single task conditions. We show that performance was significantly associated with cognitive impairment; significant differences were found among healthy participants, those with MCI, and those with ADRD. Task results were significantly associated with functional impairment, independent of diagnosis, degree of cognitive impairment (as indicated by the Mini Mental State Examination [MMSE] score), and age. Finally, we found that cognitive status could be classified with >70% accuracy using a range of classifier models trained on 3 different cognitive function outcome variables (consensus clinical judgment, Rey Auditory Verbal Learning Test [RAVLT], and MMSE).
Conclusions: Our results suggest that the dual task ball balancing test could be used as a digital cognitive assessment of cognitive reserve. The portability, simplicity, and intuitiveness of the task suggest that it may be suitable for unsupervised home assessment of cognitive function.
Recent research has suggested that up to 40% of dementia cases [ 1 ] can be delayed or prevented through early identification of impairment and adherence to recommended lifestyle modifications [ 2 ]. Furthermore, recent developments in pharmaceutical intervention suggest that the progression of Alzheimer dementia can be delayed through amyloid plaque removal [ 3 ].
An individual's cognitive and behavioral performance is a combination of brain activity and cognitive reserve. Cognitive reserve can be conceptualized as a property of the brain that allows for better than expected performance, given the degree of life-course related brain changes and brain injury or disease [ 4 ]. Cognitive reserve can be influenced by multiple genetic and environmental factors, operating at various points or continuously across the lifespan. In the presence of disease, for example, a neurodegenerative disease such as Alzheimer disease, cognitive reserve is engaged to sustain function for as long as possible and minimize symptoms and disability. Thus, individuals with more cognitive reserve manifest symptoms or disability later than those with lower cognitive reserve; symptoms are less prominent or severe than might be expected for a given amount of pathology. Low cognitive reserve makes individuals with underlying brain pathology prone to episodes of confusion, delirium, and other acute decompensations when exposed to a stressor or insult, for example, elective surgery, infection, sleep, and deprivation. Individuals with mild cognitive impairment (MCI) and higher cognitive reserve can delay the development of dementia. Thus, assessment of cognitive reserve is important to predict an individual’s functional state and prognosis. In addition, cognitive reserve can be a powerful therapeutic target, as increasing cognitive reserve might reduce disability.
The brain’s resource allocation capacity has been studied extensively and is thought to provide insight into cognitive reserve and depend on prefrontal function. However, the nature and causality of this relationship is not as well understood. Dual task paradigms have long been thought to unlock deficits in the allocation of prefrontal resources [ 5 ]. Recent studies [ 6 - 8 ] have examined the impact of a cognitive task (eg, backward counting) on a participant’s gait or balance, and thus, are dependent on peripheral nerve and musculoskeletal factors often affected in older adults. Furthermore, gait and balance analysis may not be suitable or safe for use with older adults or those with comorbidities such as osteoarthritis, neuropathies, etc. A validated tool that can support objective characterization and quantitative evaluation of cognitive reserve safely and reliably in older adults, as well as early identification of cognitive decline in nonclinical settings, could be of clinical benefit in more accurately identifying those patients who would benefit most from early and targeted intervention.
We introduce a novel test of motor control, coordination, and attention—the “ball balancing” test, in which an individual is asked to maintain the position of a virtual ball in the center of a circular target area. Task performance is measured by examining the position of a virtual ball on the screen of a touchscreen tablet, estimated using the inertial sensors embedded in the tablet. The test can be easily adapted to a dual task condition, for example, by asking the individual to balance the ball while simultaneously doing a different, attention demanding task. The test can be completed comfortably and safely in a sitting position. In an initial version of a dual task paradigm, an individual’s ball balancing test performance was assessed while simultaneously conducting a backward digit span test (BDST).
We aimed to examine the use of the ball balancing test under single and dual conditions [as quantified using the inertial measurement unit (IMU) sensors embedded in the target device] in assessment of cognitive reserve and identification of cognitive impairment. While this task (and other dual task paradigms) is not primarily aimed at serving as a means to classify cognitive function, one may predict there should be a loss of cognitive reserve between MCI and dementia, given that cognitive reserve would be “used up” to sustain cognitive function and ultimately be no longer sufficient to prevent progression of deficit, impact on activities of daily living (ADL), and thus transition from MCI to dementia. We report the performance of the task in classifying cognitive status according to 3 different outcome measures (consensus clinical judgment, Rey Auditory Verbal Learning, and Mini Mental State Examination). Given that the outcome measures are imperfectly mutually correlated, it can be assumed that they may contain complementary information pertinent to assessment of cognitive function, which can be leveraged to examine cognitive reserve deficits.
Participants were seated in a comfortable and supportive chair and asked to hold a touchscreen tablet device (iPad Pro, Apple) parallel to the ground and tilt the screen as needed to keep a virtual ball within a target area—the ball was not perturbed during the test unless the tablet was moved by the participant.
Participants were asked to balance a virtual ball on a touchscreen tablet screen, the subsequent movement is measured by the IMU sensors embedded in the tablet and used to calculate the position of the virtual ball on the tablet screen. The ball balancing test was completed under both single task (ball balancing alone) as well as under dual task conditions, with participants completing a single trial of each. The dual task involved asking the participant to complete the ball balancing test while simultaneously completing a BDST. In the BDST, the participant is played an audio sequence of 4 digits and is prompted to repeat them in reverse order. The single task was 20 seconds in duration while the dual task was 45 seconds in duration.
A custom iOS application (Swift, iOS) was developed to conduct the ball balancing test, supporting single and dual tasks. IMU and ball position data were stored within the application in JSON format and exported for offline analysis. All analyses were conducted using MATLAB (R2017b, MathWorks; Figure 1 ).
The following two distinct approaches were used to analyze the data, that is, by examining: (1) the ball position on the screen (estimated from IMU data); and (2) the IMU data from the movement of the tablet during the test.
The position of the ball on the screen was calculated using the inertial sensor data as input to a kinematic model, which derives the ball placement on the screen using Newtonian mechanics and allowed plotting of ball displacement on the screen. The following parameters were calculated from the virtual ball displacement (values in parenthesis indicate variants of the calculated feature) ( Textbox 1 ).
For all ball position metrics, the displacement is normalized to the range [ 9 ], where the outer edge is the radius of the outer circle, while the radius of the inner circle is calculated based on the ratio of the inner circle radius to the outer circle. The percentage of time spent within the inner circle is calculated as the proportion of time where the resultant displacement is less than the radius of the inner circle less the radius of the ball. The radial symmetry is calculated as the sum of the first difference values of the resultant displacement from the center of the circle. It is intended to measure quadrant placement of the ball within the outer circle. To examine learning effects and changes in performance over the course of each test, the percentage of time within the inner circle is calculated for each 5-s epoch within the test. The mean, standard deviation, and first difference were then calculated across all epochs per test to provide a measure of intratest performance. A number of standard center of pressure measures [ 10 , 11 ] were also calculated based on time and frequency domain analysis of the ball displacement. Each ball position metric was calculated for each participant under single task (ST) and dual task (DT) conditions; the dual task cost was calculated as the percentage difference between the parameter value under DT conditions and the parameter value under ST conditions and can be expressed mathematically as –100*(DT-ST)/ST [ 12 ].
A “perfect score” was achieved when the ball was found to lie within the inner circle for 100% of the test. As it was possible to achieve a perfect score by placing the tablet flat on a table, we examined if perfect score tests had any effect on the overall results to rule out the possibility that certain participants were engaging less with the task but achieving a perfect score.
Inertial sensor data from the tablet device under both ST and DT conditions were processed using an adapted version of a previously reported algorithm [ 13 , 14 ]; this approach treats the IMU data as arising from motion about a rigid plane. Figure 2 below shows the IMU (triaxial accelerometer and triaxial gyroscope) data for a dual task ball balancing test.
For each test, 1 second of data was excluded from the start and end of each recording to remove artifacts due to tablet positioning. Any recordings less than 10 seconds were discarded. IMU data were resampled to 100 Hz as iPad IMU data can be unevenly sampled, leading to distortion in frequency domain signal features [ 15 ]. Signals were bandpass filtered using a fourth order Butterworth IIR filter, in the range 0.1-40 Hz and calibrated using a standard method [ 16 ].
The following parameters were calculated from the IMU data for each ball balancing test ( Textbox 2 ).
For each calculated parameter, the dual task cost was calculated as the percentage difference between the parameter value under dual task conditions and the parameter value under single task conditions. Figure 2 provides a 3D representation of the ball balancing test signal relative to the rigid plane.
To examine the association between the calculated ball balancing test parameters and cognitive function, we considered the 3 available neurocognitive measures (cohort status, Mini Mental State Examination [MMSE], and Rey Auditory Verbal Learning Test [RAVLT]), treated as either continuous variables or binary labels (eg, impaired or not impaired). Cohort status was treated as a 3-category label (healthy, MCI, and Alzheimer disease–related dementia [ADRD]). Similarly, the differences between the healthy and impaired subgroups (MCI and ADRD) were also examined using a Wilcoxon rank sum test. A Wilcoxon signed rank test was used to test for significant differences across task conditions.
The MMSE (total score) and RAVLT (long recall delay score) data were dichotomized into cognitively impaired and cognitively intact with values below a threshold of 28 for the MMSE [ 17 ] and age group thresholds for the RAVLT [ 18 ] used to identify impaired cognition.
Spearman rank correlation was used to examine the relationship between each feature with the MMSE and RAVLT, while the Wilcoxon rank sum test was used to test for differences between impaired and nonimpaired groups for each feature. A confusion matrix was calculated for each set of binary labels (impaired/nonimpaired) to see how well cohort status, MMSE-, and RAVLT-based categorization agree with each other.
To examine the association of each variable with cognitive function and allow for the effect of age, a linear mixed effects model analysis was conducted with age as a within-subjects’ factor and cohort status as a categorical response variable. ANOVA was then used to examine the effect of each factor on cohort status, while controlling for age. This analysis was repeated for each variant with binary cohort status as well as impaired and nonimpaired labels obtained from MMSE and RAVLT.
In addition, we aimed to examine if any of the calculated ball balancing parameters were associated with functional impairment, independent of cognitive impairment. We conducted a one-way ANOVA for each ball balancing parameter with functional impairment (as measured by the Functional Activity Questionnaire [FAQ], with a threshold greater than or equal to 6 denoting functional impairment), controlling for MMSE and age. This analysis was then repeated when controlling for RAVLT and age.
To determine how well ball balancing parameters (features) could classify “unseen” participants according to binary cognitive status (cognitively impaired or cognitively intact), we used a logistic regression classifier model with a sequential forward feature selection procedure [ 19 ] validated using 10-fold cross-validation. Interaction terms were included in the candidate feature set and separate models were produced for each condition and feature set (ST, DT, dual task cost, all features as well as age only).
A sample of 375 older adults (n=210 female; aged 73.0, SD 6.5 years). Completed a battery of cognitive and motor function tests as part of wider study on brain health. The Bio-Hermes research study is managed by the Global Alzheimer Platform (GAP) and seeks new solutions to monitor and maintain brain health. Each participant received a clinical examination, which included the MMSE [ 20 ], the RAVLT [ 21 ] and “cohort status,” which classified participants into 3 clinical categories (healthy, MCI, and ADRD), as determined by a panel of qualified clinicians. For RAVLT, 2 summary scores were examined: the RAVLT total score and the RAVLT long recall delay score. In addition, each participant completed an FAQ [ 9 ] to examine functional status including ADL.
The Bio-Hermes research study is managed by the GAP. The study was performed in accordance with the Declaration of Helsinki and its later amendments. The study procedures were explained to participants verbally and through written informed consent that was approved by the local IRB of each site participating in the GAP consortium (see the Bio-Hermes study website [ 22 ] for a list of study sites). If, in the opinion of the site principal investigator, the participant did not have the capacity to sign the informed consent form, a legally authorized representative was used to grant consent on behalf of the participant. Ethical approval was granted by each institution participating in the GAP consortium (reference number: Pro00046018). Inclusion criteria for the study were adults 60-85 years of age, fluent in the language of the tests used and the test site, and with an MMSE score of 20-30 at Screening. Exclusion criteria were extensive and based on underlying conditions. All data collected as part of this study were deidentified to confidentiality protection. Participants in the study were compensated in order to cover any time or expense they incurred as a result of completing the study.
Age was significantly different ( P <.001) across cohort status groups. The mean total MMSE scores for the sample was 26.3 (SD 3.0), mean total adjusted RAVLT score was 38.8 (SD 14.3), while mean RAVLT long delay score was 5.4 (3.5). According to cohort status, 132 participants were deemed cognitively normal, 116 were considered to have MCI and 126 had probable AD (ADRD), 1 participant did not have a valid cohort status label. Combining the MCI and ADRD classes to produce 2 classes (Impaired and Intact) produced 242 participants with cognitive impairment and 132 deemed intact. Using MMSE and FAQ cut-offs of 28 and 6, respectively, along with RAVLT age group thresholds [ 18 ] to categorize participants as impaired or unimpaired, allowed a comparison of these labels against binary cohort status. MMSE agreed with cohort status with 73.8% (277/375) accuracy, RAVLT total score agreed with cohort status 45.7% (171/375), while RAVLT long recall delay score agreed with 84.8% (318/375) accuracy. Pearson's correlation coefficient between MMSE and RAVLT total score was 0.43, while correlation coefficient between MMSE and RAVLT long delay recall score was 0.60 (see Figure 3 ).
All participants were able to complete the task under ST and DT conditions. The main metric of task performance was the percentage of time the virtual ball spent within the inner circle (“percentage time in circle”). Mean percentage time spent in the inner circle was 86.0% (SD 23.0%) and 66.1% (SD 35.8%) under ST and DT conditions, respectively, while the mean DT cost was 21.0% (SD 34.1%). Task performance was significantly different ( P <.05) across cognitive status groups and between ST and DT conditions ( Table 1 ). As expected, participants achieved lower performance under DT conditions with a higher mean percentage time within the inner circle and a lower proportion of “perfect score” tests (see Figures 4 and 5 ). Removing tests with “perfect” task performance (percentage time is circle equal to 100%) did not change this finding. Performance in the task declined with increased cognitive impairment, with best mean performance observed in the healthy group for both ST and DT and worst task performance in the ADRD group.
Task performance was statistically significantly different ( P <.05) across group and between conditions.
Group | Single task performance (%), mean (SD) | Dual task performance (%), mean (SD) | Dual task cost (%), mean (SD) |
All | 86.0 (23.0) | 66.1 (35.8) | 21.0 (34.1) |
Healthy | 92.6 (12.2) | 70.2 (34.0) | 18.8 (29.7) |
MCI | 87.5 (20.4) | 63.7 (37.0) | 21.9 (35.4) |
ADRD | 77.5 (30.0) | 63.9 (35.9) | 22.7 (37.1) |
Age is significantly different between impaired and nonimpaired groups. When controlling for age using ANOVA, a large number of calculated parameters below were significantly ( P <.05) different on the basis of 3 category cohort status.
Similarly, when using ANOVA with a binary cohort label and correcting for age, a large number of parameters were significantly ( P <.05) different on the basis of binary cognitive status. Figure 6 below details 2 IMU parameters where there were significant differences across groups when corrected for age.
A linear logistic regression classifier model based on ball balancing measures from the DT condition (including age and gender) compared against a model obtained from age only found that ball balancing parameters could classify cognitive status with 70.5% accuracy compared to 62.3% accuracy for age alone ( Table 2 ).
Ball balancing parameters | Age only | ||||||||
All | Male | Female | Mean | All | Male | Female | Mean | ||
Accuracy (%) | 66.67 | 72.12 | 68.93 | 66.06 | 58.57 | 62.32 | |||
Sensitivity (%) | 81.82 | 92.11 | 78.13 | 85.12 | 90.91 | 95.61 | 82.03 | 88.82 | |
Specificity (%) | 36.09 | 27.45 | 51.22 | 39.34 | 13.53 | 0.00 | 21.95 | 10.98 | |
Positive predictive value (%) | 69.96 | 73.94 | 71.43 | 72.69 | 65.67 | 68.13 | 62.13 | 65.13 | |
Negative predictive value (%) | 52.17 | 60.87 | 60.00 | 60.43 | 45.00 | 0.00 | 43.90 | 21.95 |
a Results are shown for a model based on ball balancing inertial measurement unit (IMU) parameters and a model based on age only. The best result per group is italicized. Results for separate gender stratified male and female models are reported as well as models based on All available data.
A small number of ball balancing parameters under both single and dual task conditions were significantly associated with functional impairment (as measured by the FAQ with a threshold of 6), independent of cognitive function (as measured by MMSE total score) and age. These parameters included dual task cost of task performance (percent time in circle), dual task median frequency acceleration and single task radial frequency. A similar analysis controlling for age and RAVLT long recall delay score found that several ball balancing parameters including median frequency acceleration and single task radial frequency were significantly associated with functional impairment.
A number of ball balancing parameters under both single and dual task conditions were significantly different on the basis of cognitive status (using RAVLT long recall delay score, with age bucketed thresholds) to define cognitive impairment) and correcting for age.
Pearson correlation coefficient was used to calculate the correlation between the RAVLT (long recall delay score) and each of the calculated ball balancing parameters per task condition. Weak correlations were observed for a number of parameters.
A linear logistic regression using RAVLT long recall delay score with age bucket thresholds to denote impairment yielded a mean classification accuracy of 70.43% compared to 57.03% for age alone ( Table 3 ).
Classification results for a model using age alone trained with the RAVLT long delay are also supplied. Results for separate genders stratified as male and female models are reported as well as models based on all available data.
Ball balancing parameters | Age only | ||||||||
All | Male | Female | Mean | All | Male | Female | Mean | ||
Accuracy (%) | 62.33 | 76.06 | 64.80 | 54.67 | 61.21 | 52.86 | 57.03 | ||
Sensitivity (%) | 40.51 | 30.69 | 47.87 | 39.28 | 74.36 | 100.00 | 14.89 | 57.45 | |
Specificity (%) | 30.56 | 35.94 | 31.03 | 33.49 | 33.33 | 0.00 | 83.62 | 41.81 | |
Positive predictive value (%) | 38.73 | 43.06 | 36.00 | 39.53 | 54.72 | 61.21 | 42.42 | 51.82 | |
Negative predictive value (%) | 32.16 | 24.73 | 42.35 | 33.54 | 54.55 | 0.00 | 54.80 | 54.80 |
a Italics are used to highlight the values most indicative of the true model accuracy.
A number of parameters under both single and dual task conditions were significantly different (using ANOVA and correcting for age) on the basis of cognitive status using MMSE, with a threshold of 28 to classify participants as cognitively impaired or cognitively unimpaired.
Pearson correlation coefficient was used to calculate the correlation between the MMSE (total score) and each of the calculated ball balancing parameters per task condition. Weak correlations were observed for a number of parameters.
A linear logistic regression using the MMSE total score with a threshold of 28 to denote impairment yielded a mean classification accuracy of 72.8% compared to 69.6% for age alone ( Table 4 ).
Classification results for a model using age alone trained with the MMSE are also supplied. Results for separate genders stratified as male and female models are reported as well as models based on all available data.
Ball balancing parameters | Age only | ||||||||||||||||||
All | M | F | Mean | All | M | F | Mean | ||||||||||||
Accuracy (%) | 71.52 | 72.86 | 72.19 | 69.60 | 67.27 | 70.48 | 68.87 | ||||||||||||
Sensitivity (%) | 90.80 | 94.64 | 96.64 | 95.64 | 99.23 | 98.21 | 97.32 | 97.76 | |||||||||||
Specificity (%) | 28.95 | 22.64 | 14.75 | 18.70 | 1.75 | 1.89 | 4.92 | 3.40 | |||||||||||
Positive predictive value (%) | 74.53 | 72.11 | 73.47 | 72.79 | 69.81 | 67.90 | 71.43 | 69.66 | |||||||||||
Negative predictive value (%) | 57.89 | 66.67 | 64.29 | 65.48 | 50.00 | 33.33 | 42.86 | 38.10 |
We introduce a novel dual task paradigm to evaluate cognitive reserve and prefrontal resource allocation that does not rely on gait and balance metrics and can, thus, be safely completed by older adults and those with falls risk. We found that older adults were able to complete the task regardless of their age or level of cognitive impairment. Even those with MCI and ADRD, as well as those with peripheral neuropathy, osteoarthritis, frailty, and other potential sources of gait and balance problems were able to complete the task reliably and safely.
A sample of 375 participants completed the dual task ball balancing test protocol. Participants ranged in age from 60 to 85 years and exhibited a wide range of cognitive ability. As predicted, participants achieved significantly higher ball balancing test performance under ST conditions (as measured by the percentage of test time, the ball was within the inner circle) compared to DT performance. Thus, along with the higher proportion of perfect tests under ST conditions, the findings confirm that participants were more challenged by the test under DT conditions and that task performance decreased with increasing cognitive impairment. We found that task performance was significantly improved in healthy individuals compared to those with MCI and that performance was worse again in those with ADRD.
A number of significant differences were observed between cognitively intact (unimpaired) and cognitively impaired participants for ball positioning and IMU parameters calculated during a ball balancing test, when correcting statistics for the effect of age, using cohort status, RAVLT long delay score, and MMSE to determine cognitive status.
Significantly decreased performance in the ball balancing test was observed during the DT compared to the ST. Similarly, decreased performance was observed for increasing levels of cognitive impairment. An interpretation of this result is that with increasing impairment, there needs to be greater reliance on cognitive reserve to sustain (or attempt to sustain) cognitive and functional performance. These results are in line with results reported in the literature for other DT paradigms, which suggest that task performance reduced during a DT as compared to an ST and that the reduction in task performance is increased with increased impairment [ 6 , 22 ]. As such, DT performance across different tasks becomes increasingly altered and with that increasingly correlated, while before the high DT cost suggesting impaired reserve (if present at all) might be detectable for some but not all DT conditions. Importantly, a number of ball balancing parameters, measured under both ST and DT conditions were found to be significantly associated with functional impairment (as measured by the FAQ score) independent of MMSE, RAVLT, and age. This suggests that differences observed between MCI to ADRD groups under dual task conditions are consistent with loss of cognitive reserve contributing to progression of clinical manifestation and impact on ADL [ 4 , 23 ]. The ball balancing dual task paradigm may, thus, offer a valuable, objective means to evaluate the risk of ADL impact and enable early detection of MCI-to-dementia transition risk [ 24 ].
Moderate classification performance (>70%) was also observed in classifying binary cognitive status using a logistic regression classifier model trained on each of the cognitive function outcome measures. This compared favorably to models based on age alone, which distinguished between impaired and unimpaired groups with ~60% accuracy. A simple linear classifier model (logistic regression) was used to obtain a baseline of classification performance; improved performance may be achieved through the addition of nonlinear interaction terms or the use of higher order classification methods (eg, support vector machines), given the wider data set and potential nonlinear statistical relationships between features. To provide an indication of how well the ball balancing test can distinguish cognitively impaired participants from cognitively intact participants, cross-validation and wrapper-based feature selection was used. This method ensures unbiased estimate of classifier performance on previously unseen participants [ 25 ].
Three cognitive function outcome measures were considered in analyzing the use of the ball balancing test in classifying cognitive status. Each outcome measure (MMSE, RAVLT, and cohort status) contains differing and potentially complementary information about cognitive status (as evidenced by the modest mutual correlation observed between each outcome measure). In future work, we will examine the ability of a model based on the weighted combination of the 3 outcomes in longitudinally predicting cognitive impairment on a statistically independent data set. Furthermore, future work may also seek to examine the relationship of the ball balancing test parameters with blood biomarkers [ 26 ] and brain structure and pathology [ 5 ].
A limitation of this implementation of the ball balancing test is that the virtual ball is not perturbed during the test (other than by the movement of the tablet). This means that placement of the tablet on a flat, stable surface would allow the participant to achieve “perfect” task performance. However, it should be noted that the presence of “perfect score” tests were not found to affect the group-wise findings. An additional limitation is potential usability issues in using this task with an older adult population, particularly those with cognitive fine motor or visual impairments. While the current study involved participants conducting the task under supervised conditions to ensure adequate adherence to the task protocol, there may have been participants in the cognitively impaired groups who struggled to understand the instructions even with the support of the research assistant. Furthermore, impairment to fine motor skills may have prevented some participants from performing to their full capacity. Such usability issues may be exacerbated if the task were to be conducted under unsupervised conditions and would need to be carefully considered in the protocol for future studies.
The ball balancing test is a novel dual task paradigm that may have use in assessment of cognitive reserve and identification of cognitive impairment. Participants with mild or severe cognitive impairment performed less well on the task than healthy participants, particularly when a DT was introduced. A simple cross-validated classifier model used inertial sensor derived parameters obtained during the task to distinguish between cognitively impaired and cognitively intact participants with 70% accuracy. As the ball balancing test can be delivered entirely through a touchscreen tablet device, does not require a controlled environment, and is relatively simple to understand, the task may be suitable for administration by nonexpert users or for unsupervised use in the home environment and could support remote, longitudinal assessment of cognitive function.
The data that support the findings of this study were collected as part of the Bio-Hermes study and are governed by the Global Alzheimer Platform (GAP) consortium agreement. We would like to thank Dante Smith for his help in determining kinematic position of the virtual ball during the task. We would also like to thank the patients and clinicians involved in the study.
The data sets generated and analyzed during this study are not publicly available due to the terms of the Global Alzheimer Platform (GAP) consortium agreement. However, the data are available from the corresponding author on reasonable request.
Data analysis was carried out by BG. All authors contributed to manuscript preparation and analysis plan.
APL is a co-founder and Chief Medical Officer of Linus Health and declares ownership of shares or share options in the company. APL serves as a paid member of the scientific advisory boards for Neuroelectrics, Magstim Inc, TetraNeuron, Skin2Neuron, MedRhythms, and Hearts Radiant. All other authors are employees of Linus Health and declare ownership of shares or share options in the company.
activities of daily living |
Alzheimer disease–related dementia |
backward digit span task |
dual task |
Global Alzheimer Platform |
inertial measurement unit |
mild cognitive impairment |
Mini Mental State Examination |
Rey Auditory Verbal Learning Test |
single task |
Edited by A Mavragani; submitted 09.06.23; peer-reviewed by H-F Hsieh, J Rider, B Poston; comments to author 21.11.23; revised version received 23.11.23; accepted 13.05.24; published 19.08.24.
©Barry Greene, Sean Tobyne, Ali Jannati, Killian McManus, Joyce Gomes Osman, Russell Banks, Ranjit Kher, John Showalter, David Bates, Alvaro Pascual-Leone. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.08.2024.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
Regional director who south-east asia ms saima wazed’s address at the regional consultation.
The World Health Organization has sought to achieve “Health for All” as its goal for the past 75 years. Not health for some, not health for many, but Health for All . This does not just mean health in a physical sense, but also well-being - as highlighted in our founding Constitution.
To achieve this goal, the Alma Ata Declaration of 1978 makes two important declarations:
First, that primary health care is essential for achieving Health for All;
And secondly, that primary health care must be based on scientific and socially acceptable methods including traditional medicine.
Thus, safe and effective traditional medicine has a definite and significant role in achieving our core objective.
Today, almost all countries of our South-East Asia Region have developed and implemented a national policy for Traditional medicine.
Nine countries have established formal training and education systems for traditional medicine practitioners, and six countries have co-located traditional medicine services within their health systems.
Five countries have national essential medicine policies on traditional medicine and have also provided financial protection for traditional medicine services.
We recently launched our WHO South-East Asia Regional Roadmap for Results and Resilience. This is a shared strategic framework for a healthier Region, and I’d like to reiterate some of the salient points.
Our roadmap lays out what we call the ‘Five Rs ’ :
R1: Reinforcing mental health, well-being and quality of life for all
R2: Reaffirming investment in women, girls, adolescents and vulnerable populations
R3: Realizing access to technology and innovations
R4: Raising capacity, knowledge management and research
R5: Refining WHO leadership and performance
This regional consultation is well aligned with our regional roadmap. It will help advance holistic health and well-being, and also strengthen research and knowledge management.
The global health landscape in general, and our Region in particular, and GPW14 and the WHO Transformation Agenda warrant that we enhance agility, accountability, and operational efficiency. These also compel us to champion key policy developments, such as the Global Strategy for Traditional M edicine , and system-strengthening initiatives such as setting up of the regional research priorities. These, of course, are the two important outcomes of this consultation.
We look forward to fast-tracking this agenda, in alignment with our Region-wide push to reorient health systems towards accessible, affordable, comprehensive and quality primary health care, in conjunction with the new Global Centre for Traditional Medicine.
We also look forward to the outcomes of this Regional consultation, which will help finalize the next WHO Global Strategy for Traditional Medicine, set to be launched next year. May the new Global strategy usher in a new era of scientific, evidence-based Traditional medicine delivering ancient wisdom with modern tools, technologies and innovations.
We also look forward to the outcomes of the deliberations to setup the regional research priorities. This will go a long way in streamlining efforts and resources into a more coordinated and focused manner and building required evidence.
At this consultative meeting and beyond, let us together build the strongest evidence for the safest, most impactful outcomes.
Let us act on Astana, Alma Ata, and the Gujarat declarations, accelerating a person-centred, holistic approach to health and well-being, for a biodiverse planet, and a healthier, more equitable and sustainable future for all.
I once again thank you and extend a very warm welcome to you all.
Media Contacts
Public Information and Advocacy Unit
WHO South-East Asia Regional Office
IMAGES
COMMENTS
Why are research objectives important? Research objectives are important because they: Establish the scope and depth of your project: This helps you avoid unnecessary research. It also means that your research methods and conclusions can easily be evaluated.; Contribute to your research design: When you know what your objectives are, you have a clearer idea of what methods are most appropriate ...
Formulating research objectives has the following five steps, which could help researchers develop a clear objective: 8. Identify the research problem. Review past studies on subjects similar to your problem statement, that is, studies that use similar methods, variables, etc.
What is research methodology? Research methodology simply refers to the practical "how" of a research study. More specifically, it's about how a researcher systematically designs a study to ensure valid and reliable results that address the research aims, objectives and research questions. Specifically, how the researcher went about deciding:
Research Objectives. Research objectives refer to the specific goals or aims of a research study. They provide a clear and concise description of what the researcher hopes to achieve by conducting the research.The objectives are typically based on the research questions and hypotheses formulated at the beginning of the study and are used to guide the research process.
How to choose a research methodology? Here are some important factors to consider when choosing a research methodology: 8 Research objectives, aims, and questions—these would help structure the research design.; Review existing literature to identify any gaps in knowledge.; Check the statistical requirements—if data-driven or statistical results are needed then quantitative research is the ...
Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section: ... Explain how the research methodology addresses the research question(s) and objectives; Research Methodology Types. Types of Research Methodology are as ...
1. Focus on your objectives and research questions. The methodology section should clearly show why your methods suit your objectives and convince the reader that you chose the best possible approach to answering your problem statement and research questions. 2.
Research Objectives: Examples ... Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use ...
Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives. Here is why Research methodology is important in academic and professional settings. Facilitating Rigorous Inquiry. Research methodology forms the backbone of rigorous ...
In order to write effective research aims and objectives, researchers should consider all aspects of their proposed work. For example, the sample(s) to be approached for participation in the primary data collection. Identifying research objectives that are SMART is key to ensuring key aspects of the work are considered prior to any data collection.
A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.
A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more. You can think of your research methodology as being a formula. One part will be how you plan on putting your research into ...
A research objective is defined as a clear and concise statement of the specific goals and aims of a research study. It outlines what the researcher intends to accomplish and what they hope to learn or discover through their research. Research objectives are crucial for guiding the research process and ensuring that the study stays focused and ...
Formulating research aim and objectives in an appropriate manner is one of the most important aspects of your thesis. This is because research aim and objectives determine the scope, depth and the overall direction of the research. Research question is the central question of the study that has to be answered on the basis of research findings.
Each method can be opted for and modified, depending on the type of research hypotheses and objectives. Qualitative vs quantitative research: When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people's experiences ...
1. Understanding the options. Before we jump into the question of how to choose a research methodology, it's useful to take a step back to understand the three overarching types of research - qualitative, quantitative and mixed methods -based research. Each of these options takes a different methodological approach.
Summary. One of the most important aspects of a thesis, dissertation or research paper is the correct formulation of the aims and objectives. This is because your aims and objectives will establish the scope, depth and direction that your research will ultimately take. An effective set of aims and objectives will give your research focus and ...
An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It's an essential component of success. Over the years, businesses have started emphasizing the need for research.
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
Research methodology is a way of explaining how a researcher intends to carry out their research. It's a logical, systematic plan to resolve a research problem. A methodology details a researcher's approach to the research to ensure reliable, valid results that address their aims and objectives. It encompasses what data they're going to collect ...
In research methodology, research objectives are formulated based on the research questions or problem statement. These objectives help in defining the scope and focus of the study, ensuring that the research is conducted in a systematic and organized manner. The research objectives in research methodology act as a roadmap for the research project.
The chapter illustrates both the objective and the methodology of the research presented in the book. Possible evaluation research designs are reviewed, highlighting their strengths and weaknesses and analysing which one is the more suitable for the purposes of the present research - i.e. a natural experiment with one group(s) post-test only design, using a non-equivalent qualitative pre-test.
Arthritis Care & Research is a rheumatology journal from the American College of Rheumatology and the Association of Rheumatology Health Professionals. Objective The aim was to estimate odds ratios of associations between family history of arthritis, osteoporosis, and carpal tunnel syndrome and prevalence in a real-world population, uncovering ...
The key research objectives of the panel itself were to explore: ... The specific methodology used with the public panel is known as a "public dialogue". [9] Public dialogue is a process during which members of the public interact with scientists, stakeholders and policy makers to deliberate on issues relevant to future policy and research ...
Relevant scientific literature was reviewed on learning objectives and teaching methods in radiology education in medical school. After reviewing the available literature, two researchers (F.H. en D.H.) constructed a topic list. ... Qualitative research methodology and numbers. Journal of Social Sciences. 2016;47(2):119-22.
Methods: The task was administered on a touchscreen tablet, performance was measured using the inertial sensors embedded in the tablet, conducted under both single- and dual-task conditions. The clinical use of the task was evaluated on a sample of 375 older adult participants (n=210 female; aged 73.0, SD 6.5 years).
Objectives Strong evidence suggests the occurrence of cerebral microbleeds (CMBs) in 5-13% of stroke patients within the first week after stroke onset. The aim of this work was to study risk factors associated with occurrence of CMBs in patients with stroke who received intravenous thrombolysis, and to clarify their impact on the clinical ...
The World Health Organization has sought to achieve "Health for All" as its goal for the past 75 years. Not health for some, not health for many, but Health for All. This does not just mean health in a physical sense, but also well-being - as highlighted in our founding Constitution. To achieve this goal, the Alma Ata Declaration of 1978 makes two important declarations:First, that primary ...