study in research meaning

What is Research? Definition, Types, Methods and Process

By Nick Jain

Published on: July 25, 2023

Table of Contents

Types of Research Methods

Research process: how to conduct research, top 10 best practices for conducting research in 2023, what is research.

Research is defined as a meticulous and systematic inquiry process designed to explore and unravel specific subjects or issues with precision. This methodical approach encompasses the thorough collection, rigorous analysis, and insightful interpretation of information, aiming to delve deep into the nuances of a chosen field of study. By adhering to established research methodologies, investigators can draw meaningful conclusions, fostering a profound understanding that contributes significantly to the existing knowledge base.

This dedication to systematic inquiry serves as the bedrock of progress, steering advancements across sciences, technology, social sciences, and diverse disciplines. Through the dissemination of meticulously gathered insights, scholars not only inspire collaboration and innovation but also catalyze positive societal change.

In the pursuit of knowledge, researchers embark on a journey of discovery, seeking to unravel the complexities of the world around us. By formulating clear research questions, researchers set the course for their investigations, carefully crafting methodologies to gather relevant data. Whether employing quantitative surveys or qualitative interviews, data collection lies at the heart of every research endeavor. Once the data is collected, researchers meticulously analyze it, employing statistical tools or thematic analysis to identify patterns and draw meaningful insights. These insights, often supported by empirical evidence, contribute to the collective pool of knowledge, enriching our understanding of various phenomena and guiding decision-making processes across diverse fields. Through research, we continually refine our understanding of the universe, laying the foundation for innovation and progress that shape the future.

Research embodies the spirit of curiosity and the pursuit of truth. Here are the key characteristics of research:

• Systematic Approach: Research follows a well-structured and organized approach, with clearly defined steps and methodologies. It is conducted in a systematic manner to ensure that data is collected, analyzed, and interpreted in a logical and coherent way.
• Objective and Unbiased: Research is objective and strives to be free from bias or personal opinions. Researchers aim to gather data and draw conclusions based on evidence rather than preconceived notions or beliefs.
• Empirical Evidence: Research relies on empirical evidence obtained through observations, experiments, surveys, or other data collection methods. This evidence serves as the foundation for drawing conclusions and making informed decisions.
• Clear Research Question or Problem: Every research study begins with a specific research question or problem that the researcher aims to address. This question provides focus and direction to the entire research process.
• Replicability: Good research should be replicable, meaning that other researchers should be able to conduct a similar study and obtain similar results when following the same methods.
• Transparency and Ethics: Research should be conducted with transparency, and researchers should adhere to ethical guidelines and principles. This includes obtaining informed consent from participants, ensuring confidentiality, and avoiding any harm to participants or the environment.
• Generalizability: Researchers often aim for their findings to be generalizable to a broader population or context. This means that the results of the study can be applied beyond the specific sample or situation studied.
• Logical and Critical Thinking: Research involves critical thinking to analyze and interpret data, identify patterns, and draw meaningful conclusions. Logical reasoning is essential in formulating hypotheses and designing the study.
• Contribution to Knowledge: The primary purpose of research is to contribute to the existing body of knowledge in a particular field. Researchers aim to expand understanding, challenge existing theories, or propose new ideas.
• Peer Review and Publication: Research findings are typically subject to peer review by experts in the field before being published in academic journals or presented at conferences. This process ensures the quality and validity of the research.
• Iterative Process: Research is often an iterative process, with findings from one study leading to new questions and further research. It is a continuous cycle of discovery and refinement.
• Practical Application: While some research is theoretical in nature, much of it aims to have practical applications and real-world implications. It can inform policy decisions, improve practices, or address societal challenges.

These key characteristics collectively define research as a rigorous and valuable endeavor that drives progress, knowledge, and innovation in various disciplines.

Research methods refer to the specific approaches and techniques used to collect and analyze data in a research study. There are various types of research methods, and researchers often choose the most appropriate method based on their research question, the nature of the data they want to collect, and the resources available to them. Some common types of research methods include:

1. Quantitative Research: Quantitative research methods focus on collecting and analyzing quantifiable data to draw conclusions. The key methods for conducting quantitative research are:

Surveys- Conducting structured questionnaires or interviews with a large number of participants to gather numerical data.

Experiments-Manipulating variables in a controlled environment to establish cause-and-effect relationships.

Observational Studies- Systematically observing and recording behaviors or phenomena without intervention.

Secondary Data Analysis- Analyzing existing datasets and records to draw new insights or conclusions.

2. Qualitative Research: Qualitative research employs a range of information-gathering methods that are non-numerical, and are instead intellectual in order to provide in-depth insights into the research topic. The key methods are:

Interviews- Conducting in-depth, semi-structured, or unstructured interviews to gain a deeper understanding of participants’ perspectives.

Focus Groups- Group discussions with selected participants to explore their attitudes, beliefs, and experiences on a specific topic.

Ethnography- Immersing in a particular culture or community to observe and understand their behaviors, customs, and beliefs.

Case Studies- In-depth examination of a single individual, group, organization, or event to gain comprehensive insights.

3. Mixed-Methods Research: Combining both quantitative and qualitative research methods in a single study to provide a more comprehensive understanding of the research question.

4. Cross-Sectional Studies: Gathering data from a sample of a population at a specific point in time to understand relationships or differences between variables.

5. Longitudinal Studies: Following a group of participants over an extended period to examine changes and developments over time.

6. Action Research: Collaboratively working with stakeholders to identify and implement solutions to practical problems in real-world settings.

7. Case-Control Studies: Comparing individuals with a particular outcome (cases) to those without the outcome (controls) to identify potential causes or risk factors.

8. Descriptive Research: Describing and summarizing characteristics, behaviors, or patterns without manipulating variables.

9. Correlational Research: Examining the relationship between two or more variables without inferring causation.

10. Grounded Theory: An approach to developing theory based on systematically gathering and analyzing data, allowing the theory to emerge from the data.

11. Surveys and Questionnaires: Administering structured sets of questions to a sample population to gather specific information.

12. Meta-Analysis: A statistical technique that combines the results of multiple studies on the same topic to draw more robust conclusions.

Researchers often choose a research method or a combination of methods that best aligns with their research objectives, resources, and the nature of the data they aim to collect. Each research method has its strengths and limitations, and the choice of method can significantly impact the findings and conclusions of a study.

Learn more: What is Research Design?

Conducting research involves a systematic and organized process that follows specific steps to ensure the collection of reliable and meaningful data. The research process typically consists of the following steps:

Step 1. Identify the Research Topic

Choose a research topic that interests you and aligns with your expertise and resources. Develop clear and focused research questions that you want to answer through your study.

Step 2. Review Existing Research

Conduct a thorough literature review to identify what research has already been done on your chosen topic. This will help you understand the current state of knowledge, identify gaps in the literature, and refine your research questions.

Step 3. Design the Research Methodology

Determine the appropriate research methodology that suits your research questions. Decide whether your study will be qualitative , quantitative , or a mix of both (mixed methods). Also, choose the data collection methods, such as surveys, interviews, experiments, observations, etc.

Step 4. Select the Sample and Participants

If your study involves human participants, decide on the sample size and selection criteria. Obtain ethical approval, if required, and ensure that participants’ rights and privacy are protected throughout the research process.

Step 5. Information Collection

Collect information and data based on your chosen research methodology. Qualitative research has more intellectual information, while quantitative research results are more data-oriented. Ensure that your data collection process is standardized and consistent to maintain the validity of the results.

Step 6. Data Analysis

Analyze the data you have collected using appropriate statistical or qualitative research methods . The type of analysis will depend on the nature of your data and research questions.

Step 7. Interpretation of Results

Interpret the findings of your data analysis. Relate the results to your research questions and consider how they contribute to the existing knowledge in the field.

Step 8. Draw Conclusions

Based on your interpretation of the results, draw meaningful conclusions that answer your research questions. Discuss the implications of your findings and how they align with the existing literature.

Step 9. Discuss Limitations

Acknowledge and discuss any limitations of your study. Addressing limitations demonstrates the validity and reliability of your research.

Step 10. Make Recommendations

If applicable, provide recommendations based on your research findings. These recommendations can be for future research, policy changes, or practical applications.

Step 11. Write the Research Report

Prepare a comprehensive research report detailing all aspects of your study, including the introduction, methodology, results, discussion, conclusion, and references.

Step 12. Peer Review and Revision

If you intend to publish your research, submit your report to peer-reviewed journals. Revise your research report based on the feedback received from reviewers.

Make sure to share your research findings with the broader community through conferences, seminars, or other appropriate channels, this will help contribute to the collective knowledge in your field of study.

Remember that conducting research is a dynamic process, and you may need to revisit and refine various steps as you progress. Good research requires attention to detail, critical thinking, and adherence to ethical principles to ensure the quality and validity of the study.

Learn more: What is Primary Market Research?

Best practices for conducting research remain rooted in the principles of rigor, transparency, and ethical considerations. Here are the essential best practices to follow when conducting research in 2023:

1. Research Design and Methodology

• Carefully select and justify the research design and methodology that aligns with your research questions and objectives.
• Ensure that the chosen methods are appropriate for the data you intend to collect and the type of analysis you plan to perform.
• Clearly document the research design and methodology to enhance the reproducibility and transparency of your study.

2. Ethical Considerations

• Obtain approval from relevant research ethics committees or institutional review boards, especially when involving human participants or sensitive data.
• Prioritize the protection of participants’ rights, privacy, and confidentiality throughout the research process.
• Provide informed consent to participants, ensuring they understand the study’s purpose, risks, and benefits.

3. Data Collection

• Ensure the reliability and validity of data collection instruments, such as surveys or interview protocols.
• Conduct pilot studies or pretests to identify and address any potential issues with data collection procedures.

4. Data Management and Analysis

• Implement robust data management practices to maintain the integrity and security of research data.
• Transparently document data analysis procedures, including software and statistical methods used.
• Use appropriate statistical techniques to analyze the data and avoid data manipulation or cherry-picking results.

5. Transparency and Open Science

• Embrace open science practices, such as pre-registration of research protocols and sharing data and code openly whenever possible.
• Clearly report all aspects of your research, including methods, results, and limitations, to enhance the reproducibility of your study.

6. Bias and Confounders

• Be aware of potential biases in the research process and take steps to minimize them.
• Consider and address potential confounding variables that could affect the validity of your results.

7. Peer Review

• Seek peer review from experts in your field before publishing or presenting your research findings.
• Be receptive to feedback and address any concerns raised by reviewers to improve the quality of your study.

8. Replicability and Generalizability

• Strive to make your research findings replicable, allowing other researchers to validate your results independently.
• Clearly state the limitations of your study and the extent to which the findings can be generalized to other populations or contexts.

9. Acknowledging Funding and Conflicts of Interest

• Disclose any funding sources and potential conflicts of interest that may influence your research or its outcomes.

10. Dissemination and Communication

• Effectively communicate your research findings to both academic and non-academic audiences using clear and accessible language.
• Share your research through reputable and open-access platforms to maximize its impact and reach.

By adhering to these best practices, researchers can ensure the integrity and value of their work, contributing to the advancement of knowledge and promoting trust in the research community.

Learn more: What is Consumer Research?

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Research 101: Understanding Research Studies

One of the secrets of science is to understand the language of science, and science’s primary language is the research study . Research studies allow scientists to communicate with one another and share results of their work. There are many different kinds of research and many varying fields of research. And although journals were designed to help professionals communicate such research findings with one another, many times professionals in one field don’t significantly interact with (or are even aware of) researchers in a different field than themselves (e.g., a neuropsychologist may not keep up on the same research findings as a neurologist). This article reviews the major types of research done in the social, behavioral and brain sciences and provides some guideposts to better evaluate the context in which to place new research.

Types of Research

The basis of a scientific research study follows a common pattern:

• Define the question
• Gather information and resources
• Form hypotheses
• Perform an experiment and collect data
• Analyze the data
• Interpret the data and draw conclusions
• Publish results in a peer-reviewed journal

While there are dozens of types of research, most research done falls into one of five categories: clinical case studies; small, non-randomized studies or surveys; large, randomized clinical studies; literature reviews; and meta-analytic studies. Studies can also occur in widely varying fields, from psychology, pharmacology and sociology (what I’ll call “behavioral and treatment studies”), to genetics and brain scans (what I’ll call “organic studies”) to animal studies. Some fields contribute results that are more instantly relevant, while others’ results may help researchers develop new tests or treatments decades from now.

Clinical Case Studies

A clinical case study involves reporting on a single case (or series of cases) that the researcher or clinician has tracked over a period of some significant time (usually months or even years). Many times, such case studies emphasize a narrative or more subjective approach, but may also include objective measures. For instance, a researcher might publish a case study about the positive effects of cognitive-behavioral psychotherapy for a person with depression. The researcher measured the client’s level of depression with an objective measure such as the Beck Depression Inventory, but also describes in detail the client’s progress with specific cognitive-behavioral techniques , such as doing regular “homework” or keeping a journal of one’s thoughts.

The clinical case study is a very good research design for generating and testing hypotheses that may be used in larger studies. It is also a very good manner for disseminating the effectiveness of specific or novel techniques for individuals, or for those that may have a fairly uncommon set of diagnoses. However, generally a clinical case study’s results are not able to be generalized to a broader population. A case study is therefore of limited value to the general population.

Small Studies and Survey Research

There’s no specific criteria that differentiates a “small study” from a “large study,” but I place any non-randomized study in this category, as well as pretty much all survey research. Small studies are generally conducted on student populations (because students are often required to be a research subject for their university psychology classes), involve less than 80 to 100 participants or subjects, and often lack at least one of the core, important research components most often found in larger studies. This component can be the lack of true randomization of subjects, a lack of heterogeneity (e.g., no diversity in the population being studied), or a lack of a control group (or a relevant control group, e.g. a placebo control).

Most survey research also falls into this category, because it also lacks one of these core research components. For instance, a lot of survey research asks participants to identify themselves as having a particular problem, and if they do, then they fill out the survey. While this will almost guarantee the researchers interesting results, it’s also not very generalizable.

The upshot is that while these studies often provide interesting insights and information that can be used for future research, people shouldn’t read too much into these research findings. They are important data points in our overall understanding of the subject. When you take 10 or 20 of these data points and string them together, they should provide a fairly clear and consistent picture about the topic. If the results don’t provide such a clear picture, then there is likely more work to be done in the subject area before meaningful conclusions can be made. Literature reviews and meta-analyses (discussed below) help professionals and individuals better understand such findings over time.

Large, Randomized Studies

Large, randomized studies that draw from diverse populations and include relevant, appropriate control groups are considered the “gold standard” in research. So why aren’t they done more often? Such large studies, often done at multiple geographic locations, are very expensive to run because they include dozens of researchers, research assistants, statisticians, and other professionals as well as hundreds, and sometimes thousands, of subjects or participants. But the findings from such research are robust and can be generalized to others far more easily, so their value to research is important.

Large studies are not immune to problems found in other kinds of research. It’s just that the problems tend to have a much smaller effect, if there are any, since the number of subjects is so large and mixed (heterogeneous). When properly designed and using accepted statistical analyses, large research studies provide both individuals and professionals with solid findings that they can act upon.

Literature Reviews

A literature review is pretty much what it describes. Virtually all peer-reviewed, published research includes what might be called a “mini literature review” in its introduction. In this section of a study, the researchers review previous studies to put the current study into some context. “Research X found 123, Research Y found 456, so we hope to find 789.”

Sometimes, however, the number of studies in a particular area of study is so large and covers so many results that it’s difficult to understand exactly what our understanding is at the moment. To help give researchers a better understanding and context for future research, a literature review may be conducted and published as its own “study.” This will basically be a comprehensive, large-scale review of all studies in a particular area published within the past 10 or 20 years. The review will describe the research efforts, expand on specific findings, and may draw some general conclusions that can be gleaned from such a global review. These reviews are usually fairly subjective and are mainly for other professionals. Their use to the general public is limited and they almost never produce new findings of interest.

Meta-Analytic Studies

A meta-analysis is similar to a literature review in that it seeks to examine all previous research in a very specific topic area. However, unlike a literature review, a meta-analytic study takes the review one important step further – it actually pulls together all of the previous study’s data and analyzes it with additional statistics to draw global conclusions about the data. Why bother? Because so much research is published in many fields that it’s virtually impossible for an individual to draw any solid conclusions from the research without such a global review that pulls together all that data and statistically analyzes it for trends and solid findings.

The key to meta-analytic studies is to understand that researchers can alter the results of such a review by being particular (or not very particular) about the kinds of studies they include in their review. If, for instance, the researchers decide to include non-randomized studies in their review, they will often get different findings than if they hadn’t included them. Sometimes researchers will require certain statistical procedures to have been performed in order for the study to be included, or certain data thresholds to be met (e.g., we’ll only examine studies that had more than 50 subjects). Depending upon what criteria researchers choose to include in their meta-analysis, it will effect the results of the meta-analysis.

Meta-analytic studies, when done properly, are important contributions to our scientific knowledge and understanding. When a meta-analysis is published, it generally acts as a new foundation for other studies to build upon. It also synthesizes a great deal of previous knowledge into a more digestable Chunk of Knowledge for everyone.

Three General Categories of Research

While we’ve discussed the five general types of research in behavioral and mental health, there are also three other categories to consider.

Behavioral & Treatment Studies

Behavioral or treatment studies examine specific behaviors, treatments or therapies and see how they work on people. In psychology and sociology, most research conducted is of this nature. Such research provides direct insights into human behavior or therapeutic techniques that may be of value for treating a specific kind of disorder. This kind of research also helps us better understand a specific health or mental health concern, and how it manifests itself in a certain group of people (e.g., teenagers versus adults). This is the most “actionable” type of research – research that professionals and individuals can take action based upon its findings.

Organic Studies

Research that examines brain structures, neurochemical reactions via PET or other brain imaging techniques, gene research, or research that examines other organic structures in a human body falls under this category. In most cases, such research helps further our understanding of the human body and how it functions, but doesn’t provide immediate insight or help in dealing with a problem today, or suggest new treatments that will be readily available. For instance, researchers often publish findings about how a particular gene may be correlated with a specific disorder. While such findings may eventually lead to some sort of medical test being developed for the disorder, it may be a decade or two before a finding of this nature translates into an actual test or new treatment method.

While such research is vitally important to our eventual better understanding of how our brains and bodies function, research in this category tends not to have much importance today for people dealing with a mental disorder or mental health problem.

Animal Studies

Research is sometimes conducted on an animal to better understand how a specific organ system (such as the brain) reacts to changes, or how an animal’s behavior may be altered by specific social or environmental changes. Animal research, mostly on rats, in the 1950’s and 1960’s focused on studying animal behavior which, in psychology, led to the field of behaviorism and behavior therapy . More recently, the focus of animal studies has been on their biological makeup, to examine certain brain structures and genes related to health or mental health issues.

While certain animals have organ systems that may be very similar to human organ systems, results from animal studies are not automatically generalizable to humans. Animal studies are therefore of limited value to the general population. Research news based upon an animal study generally means any possible significant treatments from such a study are at least a decade or more away from being introduced. In many cases, no specific treatments are developed from animal studies, instead they are used to better understand how a human organ system functions or reacts to a change.

Research in the social sciences and in pharmacology is important because it helps us not only better understand human behavior (both normal and dysfunctional behavior), but also to find more effective and less time-consuming treatments to help with a person is suffering from an emotional or mental health issue.

The best kind of research – large-scale, randomized studies – are also the most rare because of their cost and the amount of resources needed to undertake them. Smaller-scale studies also contribute important data points along the way, inbetween the larger studies, while meta-analyses and literature reviews helps us gain a more global perspective and understanding of our knowledge so far.

While animal research and studies into the brain’s structures and genes are important to contributing to our overall better understanding of how our brains and bodies function, behavioral and treatment research provide concrete data that can generally be used immediately to help people improve their lives.

Last medically reviewed on May 17, 2016

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Research Basics

• What Is Research?
• Types of Research
• Secondary Research | Literature Review
• Developing Your Topic
• Primary vs. Secondary Sources
• Evaluating Sources
• Responsible Conduct of Research
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A good working definition of research might be:

Research is the deliberate, purposeful, and systematic gathering of data, information, facts, and/or opinions for the advancement of personal, societal, or overall human knowledge.

Based on this definition, we all do research all the time. Most of this research is casual research. Asking friends what they think of different restaurants, looking up reviews of various products online, learning more about celebrities; these are all research.

Formal research includes the type of research most people think of when they hear the term “research”: scientists in white coats working in a fully equipped laboratory. But formal research is a much broader category that just this. Most people will never do laboratory research after graduating from college, but almost everybody will have to do some sort of formal research at some point in their careers.

So What Do We Mean By “Formal Research?”

Casual research is inward facing: it’s done to satisfy our own curiosity or meet our own needs, whether that’s choosing a reliable car or figuring out what to watch on TV. Formal research is outward facing. While it may satisfy our own curiosity, it’s primarily intended to be shared in order to achieve some purpose. That purpose could be anything: finding a cure for cancer, securing funding for a new business, improving some process at your workplace, proving the latest theory in quantum physics, or even just getting a good grade in your Humanities 200 class.

What sets formal research apart from casual research is the documentation of where you gathered your information from. This is done in the form of “citations” and “bibliographies.” Citing sources is covered in the section "Citing Your Sources."

Formal research also follows certain common patterns depending on what the research is trying to show or prove. These are covered in the section “Types of Research.”

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Definition of research

 (Entry 1 of 2)

Definition of research  (Entry 2 of 2)

transitive verb

intransitive verb

• disquisition
• examination
• exploration
• inquisition
• investigation
• delve (into)
• inquire (into)
• investigate
• look (into)

Examples of research in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'research.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Middle French recerche , from recercher to go about seeking, from Old French recerchier , from re- + cerchier, sercher to search — more at search

1577, in the meaning defined at sense 3

1588, in the meaning defined at transitive sense 1

Phrases Containing research

• marketing research
• market research
• operations research
• oppo research

research and development

• research park
• translational research

Dictionary Entries Near research

Cite this entry.

“Research.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/research. Accessed 26 Apr. 2024.

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Kids definition of research.

Kids Definition of research  (Entry 2 of 2)

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Significance of a Study: Revisiting the “So What” Question

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

16k Accesses

Every researcher wants their study to matter—to make a positive difference for their professional communities. To ensure your study matters, you can formulate clear hypotheses and choose methods that will test them well, as described in Chaps. 1, 2, 3 and 4. You can go further, however, by considering some of the terms commonly used to describe the importance of studies, terms like significance, contributions, and implications. As you clarify for yourself the meanings of these terms, you learn that whether your study matters depends on how convincingly you can argue for its importance. Perhaps most surprising is that convincing others of its importance rests with the case you make before the data are ever gathered. The importance of your hypotheses should be apparent before you test them. Are your predictions about things the profession cares about? Can you make them with a striking degree of precision? Are the rationales that support them compelling? You are answering the “So what?” question as you formulate hypotheses and design tests of them. This means you can control the answer. You do not need to cross your fingers and hope as you collect data.

You have full access to this open access chapter,  Download chapter PDF

Part I. Setting the Groundwork

One of the most common questions asked of researchers is “So what?” What difference does your study make? Why are the findings important? The “so what” question is one of the most basic questions, often perceived by novice researchers as the most difficult question to answer. Indeed, addressing the “so what” question continues to challenge even experienced researchers. It is not always easy to articulate a convincing argument for the importance of your work. It can be especially difficult to describe its importance without falling into the trap of making claims that reach beyond the data.

That this issue is a challenge for researchers is illustrated by our analysis of reviewer comments for JRME . About one-third of the reviews for manuscripts that were ultimately rejected included concerns about the importance of the study. Said another way, reviewers felt the “So what?” question had not been answered. To paraphrase one journal reviewer, “The manuscript left me unsure of what the contribution of this work to the field’s knowledge is, and therefore I doubt its significance.” We expect this is a frequent concern of reviewers for all research journals.

Our goal in this chapter is to help you navigate the pressing demands of journal reviewers, editors, and readers for demonstrating the importance of your work while staying within the bounds of acceptable claims based on your results. We will begin by reviewing what we have said about these issues in previous chapters. We will then clarify one of the confusing aspects of developing appropriate arguments—the absence of consensus definitions of key terms such as significance, contributions, and implications. Based on the definitions we propose, we will examine the critical role of alignment for realizing the potential significance of your study. Because the importance of your study is communicated through your evolving research paper, we will fold suggestions for writing your paper into the discussion of creating and executing your study.

We laid the groundwork in Chap. 1 for what we consider to be important research in education:

In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to support the improvement of learning opportunities for all students…. If there is no way to imagine a connection to improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Of course, you might prefer another “ultimate purpose” for research in education. That’s fine. The critical point is that the argument for the importance of the hypotheses you are testing should be connected to the value of a long-term goal you can describe. As long as most of the educational community agrees with this goal, and you can show how testing your hypotheses will move the field forward to achieving this goal, you will have developed a convincing argument for the importance of your work.

In Chap. 2 , we argued the importance of your hypotheses can and should be established before you collect data. Your theoretical framework should carry the weight of your argument because it should describe how your hypotheses will extend what is already known. Your methods should then show that you will test your hypotheses in an appropriate way—in a way that will allow you to detect how the results did, and did not, confirm the hypotheses. This will, in turn, allow you to formulate revised hypotheses. We described establishing the importance of your study by saying, “The importance can come from the fact that, based on the results, you will be able to offer revised hypotheses that help the field better understand an issue relevant for improving all students’ learning opportunities.”

The ideas from Chaps. 1 , 2 , and 3 go a long way toward setting the parameters for what counts as an important study and how its importance can be determined. Chapter 4 focused on ensuring that the importance of a study can be realized. The next section fills in the details by proposing definitions for the most common terms used to claim importance: significance, contributions, and implications.

You might notice that we do not have a chapter dedicated to discussing the presentation of the findings—that is, a “results” chapter. We do not mean to imply that presenting results is trivial. However, we believe that if you follow our recommendations for writing your evolving research paper, presenting the results will be quite straightforward. The key is to present your results so they can be most easily compared with your predictions. This means, among other things, organizing your presentation of results according to your earlier presentation of hypotheses.

Part II. Clarifying Importance by Revisiting the Definitions of Key Terms

What does it mean to say your findings are significant? Statistical significance is clear. There are widely accepted standards for determining the statistical significance of findings. But what about educational significance? Is this the same as claiming that your study makes an important contribution? Or, that your study has important implications? Different researchers might answer these questions in different ways. When key terms like these are overused, their definitions gradually broaden or shift, and they can lose their meaning. That is unfortunate, because it creates confusion about how to develop claims for the importance of a study.

By clarifying the definitions, we hope to clarify what is required to claim that a study is significant , that it makes a contribution , and that it has important implications . Not everyone defines the terms as we do. Our definitions are probably a bit narrower or more targeted than those you may encounter elsewhere. Depending on where you want to publish your study, you may want to adapt your use of these terms to match more closely the expectations of a particular journal. But the way we define and address these terms is not antithetical to common uses. And we believe ridding the terms of unnecessary overlap allows us to discriminate among different key concepts with respect to claims for the importance of research studies. It is not necessary to define the terms exactly as we have, but it is critical that the ideas embedded in our definitions be distinguished and that all of them be taken into account when examining the importance of a study.

We will use the following definitions:

Significance: The importance of the problem, questions, and/or hypotheses for improving the learning opportunities for all students (you can substitute a different long-term goal if its value is widely shared). Significance can be determined before data are gathered. Significance is an attribute of the research problem , not the research findings .

Contributions : The value of the findings for revising the hypotheses, making clear what has been learned, what is now better understood.

Implications : Deductions about what can be concluded from the findings that are not already included in “contributions.” The most common deductions in educational research are for improving educational practice. Deductions for research practice that are not already defined as contributions are often suggestions about research methods that are especially useful or methods to avoid.

Significance

The significance of a study is built by formulating research questions and hypotheses you connect through a careful argument to a long-term goal of widely shared value (e.g., improving learning opportunities for all students). Significance applies both to the domain in which your study is located and to your individual study. The significance of the domain is established by choosing a goal of widely shared value and then identifying a domain you can show is connected to achieving the goal. For example, if the goal to which your study contributes is improving the learning opportunities for all students, your study might aim to understand more fully how things work in a domain such as teaching for conceptual understanding, or preparing teachers to attend to all students, or designing curricula to support all learners, or connecting learning opportunities to particular learning outcomes.

The significance of your individual study is something you build ; it is not predetermined or self-evident. Significance of a study is established by making a case for it, not by simply choosing hypotheses everyone already thinks are important. Although you might believe the significance of your study is obvious, readers will need to be convinced.

Significance is something you develop in your evolving research paper. The theoretical framework you present connects your study to what has been investigated previously. Your argument for significance of the domain comes from the significance of the line of research of which your study is a part. The significance of your study is developed by showing, through the presentation of your framework, how your study advances this line of research. This means the lion’s share of your answer to the “So what?” question will be developed as part of your theoretical framework.

Although defining significance as located in your paper prior to presenting results is not a definition universally shared among educational researchers, it is becoming an increasingly common view. In fact, there is movement toward evaluating the significance of a study based only on the first sections of a research paper—the sections prior to the results (Makel et al., 2021 ).

In addition to addressing the “So what?” question, your theoretical framework can address another common concern often voiced by readers: “What is so interesting? I could have predicted those results.” Predictions do not need to be surprising to be interesting and significant. The significance comes from the rationales that show how the predictions extend what is currently known. It is irrelevant how many researchers could have made the predictions. What makes a study significant is that the theoretical framework and the predictions make clear how the study will increase the field’s understanding toward achieving a goal of shared value.

An important consequence of interpreting significance as a carefully developed argument for the importance of your research study within a larger domain is that it reveals the advantage of conducting a series of connected studies rather than single, disconnected studies. Building the significance of a research study requires time and effort. Once you have established significance for a particular study, you can build on this same argument for related studies. This saves time, allows you to continue to refine your argument across studies, and increases the likelihood your studies will contribute to the field.

Contributions

As we have noted, in fields as complicated as education, it is unlikely that your predictions will be entirely accurate. If the problem you are investigating is significant, the hypotheses will be formulated in such a way that they extend a line of research to understand more deeply phenomena related to students’ learning opportunities or another goal of shared value. Often, this means investigating the conditions under which phenomena occur. This gets complicated very quickly, so the data you gather will likely differ from your predictions in a variety of ways. The contributions your study makes will depend on how you interpret these results in light of the original hypotheses.

Contributions Emerge from Revisions to your Hypotheses

We view interpreting results as a process of comparing the data with the predictions and then examining the way in which hypotheses should be revised to more fully account for the results. Revising will almost always be warranted because, as we noted, predictions are unlikely to be entirely accurate. For example, if researchers expect Outcome A to occur under specified conditions but find that it does not occur to the extent predicted or actually does occur but without all the conditions, they must ask what changes to the hypotheses are needed to predict more accurately the conditions under which Outcome A occurred. Are there, for example, essential conditions that were not anticipated and that should be included in the revised hypotheses?

Consider an example from a recently published study (Wang et al., 2021 ). A team of researchers investigated the following research question: “How are students’ perceptions of their parents’ expectations related to students’ mathematics-related beliefs and their perceived mathematics achievement?” The researchers predicted that students’ perceptions of their parents’ expectations would be highly related to students’ mathematics-related beliefs and their perceived mathematics achievement. The rationale was based largely on prior research that had consistently found parents’ general educational expectations to be highly correlated with students’ achievement.

The findings showed that Chinese high school students’ perceptions of their parents’ educational expectations were positively related to these students’ mathematics-related beliefs. In other words, students who believed their parents expected them to attain higher levels of education had more desirable mathematics-related beliefs.

However, students’ perceptions of their parents’ expectations about mathematics achievement were not related to students’ mathematics-related beliefs in the same way as the more general parental educational expectations. Students who reported that their parents had no specific expectations possessed more desirable mathematics-related beliefs than all other subgroups. In addition, these students tended to perceive their mathematics achievement rank in their class to be higher on average than students who reported that their parents expressed some level of expectation for mathematics achievement.

Because this finding was not predicted, the researchers revised the original hypothesis. Their new prediction was that students who believe their parents have no specific mathematics achievement expectations possess more positive mathematics-related beliefs and higher perceived mathematics achievement than students who believe their parents do have specific expectations. They developed a revised rationale that drew on research on parental pressure and mathematics anxiety, positing that parents’ specific mathematics achievement expectations might increase their children’s sense of pressure and anxiety, thus fostering less positive mathematics-related beliefs. The team then conducted a follow-up study. Their findings aligned more closely with the new predictions and affirmed the better explanatory power of the revised rationale. The contributions of the study are found in this increased explanatory power—in the new understandings of this phenomenon contained in the revisions to the rationale.

Interpreting findings in order to revise hypotheses is not a straightforward task. Usually, the rationales blend multiple constructs or variables and predict multiple outcomes, with different outcomes connected to different research questions and addressed by different sets of data. Nevertheless, the contributions of your study depend on specifying the differences between your original hypotheses and your revised hypotheses. What can you explain now that you could not explain before?

We believe that revising hypotheses is an optimal response to any question of contributions because a researcher’s initial hypotheses plus the revisions suggested by the data are the most productive way to tie a study into the larger chain of research of which it is a part. Revised hypotheses represent growth in knowledge. Building on other researchers’ revised hypotheses and revising them further by more explicitly and precisely describing the conditions that are expected to influence the outcomes in the next study accumulates knowledge in a form that can be recorded, shared, built upon, and improved.

The significance of your study is presented in the opening sections of your evolving research paper whereas the contributions are presented in the final section, after the results. In fact, the central focus in this “Discussion” section should be a specification of the contributions (note, though, that this guidance may not fully align with the requirements of some journals).

Contributions Answer the Question of Generalizability

A common and often contentious, confusing issue that can befuddle novice and experienced researchers alike is the generalizability of results. All researchers prefer to believe the results they report apply to more than the sample of participants in their study. How important would a study be if the results applied only to, say, two fourth-grade classrooms in one school, or to the exact same tasks used as measures? How do you decide to which larger population (of students or tasks) your results could generalize? How can you state your claims so they are precisely those justified by the data?

To illustrate the challenge faced by researchers in answering these questions, we return to the JRME reviewers. We found that 30% of the reviews expressed concerns about the match between the results and the claims. For manuscripts that ultimately received a decision of Reject, the majority of reviewers said the authors had overreached—the claims were not supported by the data. In other words, authors generalized their claims beyond those that could be justified.

The Connection Between Contributions and Generalizability

In our view, claims about contributions can be examined productively alongside considerations of generalizability. To make the case for this view, we need to back up a bit. Recall that the purpose of research is to understand a phenomenon. To understand a phenomenon, you need to determine the conditions under which it occurs. Consequently, productive hypotheses specify the conditions under which the predictions hold and explain why and how these conditions make a difference. And the conditions set the parameters on generalizability. They identify when, where, and for whom the effect or situation will occur. So, hypotheses describe the extent of expected generalizability, and revised hypotheses that contain the contributions recalibrate generalizability and offer new predictions within these parameters.

An Example That Illustrates the Connection

In Chap. 4 , we introduced an example with a research question asking whether second graders improve their understanding of place value after a specially designed instructional intervention. We suggested asking a few second and third graders to complete your tasks to see if they generated the expected variation in performance. Suppose you completed this pilot study and now have satisfactory tasks. What conditions might influence the effect of the intervention? After careful study, you developed rationales that supported three conditions: the entry level of students’ understanding, the way in which the intervention is implemented, and the classroom norms that set expectations for students’ participation.

Suppose your original hypotheses predicted the desired effect of the intervention only if the students possessed an understanding of several concepts on which place value is built, only if the intervention was implemented with fidelity to the detailed instructional guidelines, and only if classroom norms encouraged students to participate in small-group work and whole-class discussions. Your claims of generalizability will apply to second-grade settings with these characteristics.

Now suppose you designed the study so the intervention occurred in five second-grade classrooms that agreed to participate. The pre-intervention assessment showed all students with the minimal level of entry understanding. The same well-trained teacher was employed to teach the intervention in all five classrooms, none of which included her own students. And you learned from prior observations and reports of the classroom teachers that three of the classrooms operated with the desired classroom norms, but two did not. Because of these conditions, your study is now designed to test one of your hypotheses—the desired effect will occur only if classroom norms encouraged students to participate in small-group work and whole-class discussions. This is the only condition that will vary; the other two (prior level of understanding and fidelity of implementation) are the same across classrooms so you will not learn how these affect the results.

Suppose the classrooms performed equally well on the post-intervention assessments. You expected lower performance in the two classrooms with less student participation, so you need to revise your hypotheses. The challenge is to explain the higher-than-expected performance of these students. Because you were interested in understanding the effects of this condition, you observed several lessons in all the classrooms during the intervention. You can now use this information to explain why the intervention worked equally well in classrooms with different norms.

Your revised hypothesis captures this part of your study’s contribution. You can now say more about the ways in which the intervention can help students improve their understanding of place value because you have different information about the role of classroom norms. This, in turn, allows you to specify more precisely the nature and extent of the generalizability of your findings. You now can generalize your findings to classrooms with different norms. However, because you did not learn more about the impact of students’ entry level understandings or of different kinds of implementation, the generalizability along these dimensions remains as limited as before.

This example is simplified. In many studies, the findings will be more complicated, and more conditions will likely be identified, some of which were anticipated and some of which emerged while conducting the study and analyzing the data. Nevertheless, the point is that generalizability should be tied to the conditions that are expected to affect the results. Further, unanticipated conditions almost always appear, so generalizations should be conservative and made with caution and humility. They are likely to change after testing the new predictions.

Contributions Are Assured When Hypotheses Are Significant and Methods Are Appropriate and Aligned

We have argued that the contributions of your study are produced by the revised hypotheses you can formulate based on your results. Will these revisions always represent contributions to the field? What if the revisions are minor? What if your results do not inform revisions to your hypotheses?

We will answer these questions briefly now and then develop them further in Part IV of this chapter. The answer to the primary question is “yes,” your revisions will always be a contribution to the field if (1) your hypotheses are significant and (2) you crafted appropriate methods to test the hypotheses. This is true even if your revisions are minor or if your data are not as informative as you expected. However, this is true only if you meet the two conditions in the earlier sentence. The first condition (significant hypotheses) can be satisfied by following the suggestions in the earlier section on significance. The second condition (appropriate methods) is addressed further in Part III in this chapter.

Implications

Before examining the role of methods in connecting significance with important contributions, we elaborate briefly our definition of “implications.” We reserve implications for the conclusions you can logically deduce from your findings that are not already presented as contributions. This means that, like contributions, implications are presented in the Discussion section of your research paper.

Many educational researchers present two types of implications: implications for future research and implications for practice. Although we are aware of this common usage, we believe our definition of “contributions” cover these implications. Clarifying why we call these “contributions” will explain why we largely reserve the word “implications” for recommendations regarding methods.

Implications for Future Research

Implications for future research often include (1) recommendations for empirical studies that would extend the findings of this study, (2) inferences about the usefulness of theoretical constructs, and (3) conclusions about the advisability of using particular kinds of methods. Given our earlier definitions, we prefer to label the first two types of implications as contributions.

Consider recommendations for empirical studies. After analyzing the data and presenting the results, we have suggested you compare the results with those predicted, revise the rationales for the original predictions to account for the results, and make new predictions based on the revised rationales. It is precisely these new predictions that can form the basis for recommending future research. Testing these new predictions is what would most productively extend this line of research. It can sometimes sound as if researchers are recommending future studies based on hunches about what research might yield useful findings. But researchers can do better than this. It would be more productive to base recommendations on a careful analysis of how the predictions of the original study could be sharpened and improved.

Now consider inferences about the usefulness of theoretical constructs. Our argument for labeling these inferences as contributions is similar. Rationales for predictions are where the relevant theoretical constructs are located. Revisions to these rationales based on the differences between the results and the predictions reveal the theoretical constructs that were affirmed to support accurate predictions and those that must be revised. In our view, usefulness is determined through this revision process.

Implications that do not come under our meaning of contributions are in the third type of implications, namely the appropriateness of methods for generating rich contributions. These kinds of implications are produced by your evaluation of your methods: research design, sampling procedures, tasks, data collection procedures, and data analyses. Although not always included in the discussion of findings, we believe it would be helpful for researchers to identify particular methods that were useful for conducting their study and those that should be modified or avoided. We believe these are appropriately called implications.

Implications for Practice

If the purpose of research is to better understand how to improve learning opportunities for all students, then it is appropriate to consider whether implications for improving educational practice can be drawn from the results of a study. How are these implications formulated? This is an important question because, in our view, these claims often come across as an afterthought, “Oh, I need to add some implications for practice.” But here is the sobering reality facing researchers: By any measure, the history of educational research shows that identifying these implications has had little positive effect on practice.

Perhaps the most challenging task for researchers who attempt to draw implications for practice is to interpret their findings for appropriate settings. A researcher who studied the instructional intervention for second graders on place value and found that average performance in the intervention classrooms improved more than in the textbook classrooms might be tempted to draw implications for practice. What should the researcher say? That second-grade teachers should adopt the intervention? Such an implication would be an overreach because, as we noted earlier, the findings cannot be generalized to all second-grade classrooms. Moreover, an improvement in average performance does not mean the intervention was better for all students.

The challenge is to identify the conditions under which the intervention would improve the learning opportunities for all students. Some of these conditions will be identified as the theoretical framework is built because the predictions need to account for these conditions. But some will be unforeseen, and some that are identified will not be informed by the findings. Recall that, in the study described earlier, a condition of entry level of understanding was hypothesized but the design of the study did not allow the researcher to draw any conclusions about its effect.

What can researchers say about implications for practice given the complexities involved in generalizing findings to other settings? We offer two recommendations. First, because it is difficult to specify all the conditions under which a phenomenon occurs, it is rarely appropriate to prescribe an educational practice. Researchers cannot anticipate the conditions under which individual teachers operate, conditions that often require adaptation of a suggested practice rather than implementation of a practice as prescribed.

Our second recommendation comes from returning to the purpose for educational research—to understand more fully how to improve learning opportunities for all students (or to achieve another goal of widely shared value). As we have described, understanding comes primarily from building and reevaluating rationales for your predictions. If you reach a new understanding related to improving learning opportunities, an understanding that could have practical implications, we recommend you share this understanding as an implication for practice.

For example, suppose the researcher who found better average performance of second graders after the intervention on place value had also studied several conditions under which performance improved. And suppose the researcher found that most students who did not improve their performance misunderstood a concept that appeared early in the intervention (e.g., the multiplicative relationship between positional values of a numeral). An implication for practice the researcher might share would be to describe the potential importance of understanding this concept early in the sequence of activities if teachers try out this intervention.

If you use our definitions, these implications for practice would be presented as contributions because they emerge directly from reevaluating and revising your rationales. We believe it is appropriate to use “Contributions” as the heading for this section in the Discussion section of your research paper. However, if editors prefer “Implications” we recommend following their suggestion.

We want to be clear that the terms you use for the different ways your study is important is not critical. We chose to define the terms significance, contributions, and implications in very specific and not universally shared ways to distinguish all the meanings of importance you should consider. Some of these can be established through your theoretical framework, some by the revisions of your hypotheses, and some by reflecting on the value of particular methods. The important thing, from our point of view, is that the ideas we defined for each of these terms are distinguished and recognized as specific ways of determining the importance of your study.

Part III. The Role of Methods in Determining Contributions

We have argued that every part of the study (and of the evolving research paper) should be aligned. All parts should be connected through a coherent chain of reasoning. In this chapter, we argue that the chain of reasoning is not complete until the methods are presented and the results are interpreted and discussed. The methods of the study create a bridge that connects the introductory material (research questions, theoretical framework, literature review, hypotheses) with the results and interpretations.

The role that methods play in scientific inquiry is to ensure that your hypotheses will be tested appropriately so the significance of your study will yield its potential contributions. To do this, the methods must do more than follow the standard guidelines and be technically correct (see Chap. 4 ). They must also fit with the surrounding parts of the study. We call this coherence.

Coherence Across the Phases of Scientific Inquiry

Coherence means the parts of a whole are fully aligned. When doing scientific inquiry, the early parts or phases should motivate the later phases. The methods you use should be motivated or explained by the earlier phases (e.g., research questions, theoretical framework, hypotheses). Your methods, in turn, should produce results that can be interpreted by comparing them with your predictions. Methods are aligned with earlier phases when you can use the rationales contained in your hypotheses to decide what kinds of data are needed to test your predictions, how best to gather these kinds of data, and what analyses should be performed (see Chap. 4 and Cai et al., 2019a ).

For a visual representation of this coherence, see Fig. 5.1 . Each box identifies an aspect of scientific inquiry. Hypotheses (shown in Box 1) include the rationales and predictions. Because the rationales encompass the theoretical framework and the literature review, Box 1 establishes the significance of the study. Box 2 represents the methods, which we defined in Chap. 4 as the entire set of procedures you will use, including the basic design, measures for collecting data, and analytic approaches. In Fig. 5.1 , the hypothesis in Box 1 points you to the methods you will use. That is, you will choose methods that provide data for analyses that will generate results or findings (Box 3) that allow you to make comparisons against your predictions. Based on those comparisons, you will revise your hypotheses and derive the contributions and implications of your study (Box 4).

The Chain of Coherence That Runs Through All Parts of a Research Study

We intend Fig. 5.1 to carry several messages. One is that coherence of a study and the associated research paper require all aspects of the study to flow from one into the other. Each set of prior entries must motivate and justify the next one. For example, the data and analyses you intend to gather and use in Box 2 (Methods) must be those that are motivated and explained by the research question and hypothesis (prediction and rationale) in Box 1.

A second message in the figure is that coherence includes Box 4, “Discussion.” Aligned with the first three boxes, the fourth box flows from these boxes but is also constrained by them. The contributions and implications authors describe in the Discussion section of the paper cannot go beyond what is allowed by the original hypotheses and the revisions to these hypotheses indicated by the findings.

Methods Enable Significance to Yield Contributions

We begin this section by identifying a third message conveyed in Fig. 5.1 . The methods of the study, represented by Box 2, provide a bridge that connects the significance of the study (Box 1) with the contributions of the study (Box 4). The results (Box 3) indicate the nature of the contributions by determining the revisions to the original hypotheses.

In our view, the connecting role played by the methods is often underappreciated. Crafting appropriate methods aligned with the significance of the study, on one hand, and the interpretations, on the other, can determine whether a study is judged to make a contribution.

If the hypotheses are established as significant, and if appropriate methods are used to test the predictions, the study will make important contributions even if the data are not statistically significant. We can say this another way. When researchers establish the significance of the hypotheses (i.e., convince readers they are of interest to the field) and use methods that provide a sound test of these hypotheses, the data they present will be of interest regardless of how they turn out. This is why Makel et al. ( 2021 ) endorse a review process for publication that emphasizes the significance of the study as presented in the first sections of a research paper.

Treating the methods as connecting the introductory arguments to the interpretations of data prevent researchers from making a common mistake: When writing the research paper, some researchers lose track of the research questions and/or the predictions. In other words, results are presented but are not interpreted as answers to the research questions or compared with the predictions. It is as if the introductory material of the paper begins one story, and the interpretations of results ends a different story. Lack of alignment makes it impossible to tell one coherent story.

A final point is that the alignment of a study cannot be evaluated and appreciated if the methods are not fully described. Methods must be described clearly and completely in the research paper so readers can see how they flow from the earlier phases of the study and how they yield the data presented. We suggested in Chap. 4 a rule of thumb for deciding whether the methods have been fully described: “Readers should be able to replicate the study if they wish.”

Part IV. Special Considerations that Affect a Study’s Contributions

We conclude Chap. 5 by addressing two additional issues that can affect how researchers interpret the results and make claims about the contributions of a study. Usually, researchers deal with these issues in the Discussion section of their research paper, but we believe it is useful to consider them as you plan and conduct your study. The issues can be posed as questions: How should I treat the limitations of my study? How should I deal with findings that are completely unexpected?

Limitations of a Study

We can identify two kinds of limitations: (1) limitations that constrain your ability to interpret your results because of unfortunate choices you made, and (2) limitations that constrain your ability to generalize your results because of missing variables you could not fit into the scope of your study or did not anticipate. We recommend different ways of dealing with these.

Limitations Due to Unfortunate Choices

All researchers make unfortunate choices. These are mistakes that could have been prevented. Often, they are choices in how a study was designed and/or executed. Maybe the sample did not have the characteristics assumed, or a task did not assess what was expected, or the intervention was not implemented as planned. Although many unfortunate choices can be prevented by thinking through the consequences of every decision or by conducting a well-designed pilot study or two, some will occur anyway. How should you deal with them?

The consequence of unfortunate choices is that the data do not test the hypotheses as precisely or completely as hoped. When this happens, the data must be interpreted with these constraints in mind. Almost always, this limits the researcher to making fewer or narrower claims than desired about differences and similarities between the results and the predictions. Usually this means conclusions about the ways in which the rationales must be revised require extra qualifications. In other words, claims about contributions of the study must be made with extra caution.

Research papers frequently include a subsection in the Discussion called “Limitations of the Study.” Researchers often use this subsection to identify the study’s limitations by describing the unfortunate choices, but they do not always spell out how these limitations should affect the contributions of the paper. Sometimes, it appears that researchers are simply checking off a requirement to identify the limitations by saying something like “The results should be interpreted with caution.” But this does not help readers understand exactly what cautions should be applied and it does not hold researchers accountable for the limitations.

We recommend something different. We suggest you do the hard work of figuring out how the data should be interpreted in light of the limitations and share these details with the readers. You might do this when the results are presented or when you interpret them. Rather than presenting your claims about the contributions of the study and then saying readers should interpret these with “caution” because of the study’s limitations, we suggest presenting only those interpretations and claims of contributions that can be made with the limitations in mind.

One way to think about the constraints you will likely need to impose on your interpretations is in terms of generalizability. Recall that earlier in this chapter, we described the close relationship between contributions and generalizability. When generalizability is restricted, so are contributions.

Limitations Due to Missing Variables

Because of the complexity of problems, questions, and hypotheses explored in educational research, researchers are unlikely to anticipate in their studies all the variables that affect the data and results. In addition, tradeoffs often must be made. Researchers cannot study everything at once, so decisions must be made about which variables to study carefully and which to either control or ignore.

In the earlier example of studying whether second graders improve their understanding of place value after a specially designed instructional intervention, the researcher identified three variables that were expected to influence the effect of the intervention: students’ entry level of understanding, implementation of the intervention, and norms of the classrooms in which the intervention was implemented. The researcher decided to control the implementation variable by hiring one experienced teacher to implement the intervention in all the classrooms. This meant the variable of individual teacher differences was not included in the study and the researcher could not generalize to classrooms with these differences.

Some researchers might see controlling the implementation of the intervention as a limitation. We do not. As a factor that is not allowed to vary, it constrains the generalizations a researcher can make, but we believe these kinds of controlled variables are better treated as opportunities for future research. Perhaps the researcher’s observations in the classroom provided information that could be used to make some predictions about which elements of the intervention are essential and which are optional—about which aspects of the intervention must be implemented as written and which can vary with different teachers. When revising the rationales to show what was learned in this study, the researcher could include rationales for new, tentative predictions about the effects of the intervention in classrooms where implementation differed in specified ways. These predictions create a genuine contribution of the study. If you use our definitions, these new predictions, often presented under “implications for future research,” would be presented as “contributions.”

Notice that if you follow our advice, you would not need to include a separate section in the Discussion of your paper labeled “Limitations.” We acknowledge, however, that some journal editors recommend such a subsection. In this case, we suggest you include this subsection along with treating the two different kinds of limitations as we recommend. You can do both.

Dealing with Unexpected Findings

Researchers are often faced with unexpected and perhaps surprising results, even when they have developed a convincing theoretical framework, posed research questions tightly connected to this framework, presented predictions about expected outcomes, and selected methods that appropriately test these predictions. Indeed, the unexpected findings can be the most interesting and valuable products of the study. They can range from mildly surprising to “Wow. I didn’t expect that.” How should researchers treat such findings? Our answer is based on two principles.

The first principle is that the value of research does not lie in whether the predictions are completely accurate but in helping the field learn more about the explanatory power of theoretical frameworks. That is, the value lies in the increased understanding of phenomena generated by examining the ability of theoretical frameworks (or rationales) to predict outcomes and explain results. The second principle, a corollary to the first, is to treat unexpected findings in a way that is most educative for the reader.

Based on our arguments to this point, you could guess we will say there will always be unexpected findings. Predicted answers to significant research questions in education will rarely, if ever, be entirely accurate. So, you can count on dealing with unexpected findings.

Consistent with the two principles above, your goal should be to use unexpected findings to understand more fully the phenomenon under investigation. We recommend one of three different paths. The choice of which path to take depends on what you decide after reflecting again on the decisions you made at each phase of the study.

The first path is appropriate when researchers reexamine their theoretical framework in light of the unexpected findings and decide that it is still a compelling framework based on previous work. They reason that readers are likely to have been convinced by this framework and would likely have made similar predictions. In this case, we believe that it is educative for researchers to (a) summarize their initial framework, (b) present the findings and distinguish those that were aligned with the predictions from those that were not, and (c) explain why the theoretical framework was inadequate and propose changes to the framework that would have created more alignment with the unexpected findings.

Revisions to initial hypotheses are especially useful if they include explanations for why a researcher might have been wrong (and researchers who ask significant questions in domains as complex as education are almost always wrong in some way). Depending on the ways in which the revised framework differs from the original, the authors have two options. If the revised framework is an expansion of the original, it would be appropriate for the authors to propose directions for future research that would extend this study. Alternatively, if the revised framework is still largely within the scope of the original study and consists of revisions to the original hypotheses, the revisions could guide a second study to check the adequacy of the revisions. This second study could be conducted by the same researchers (perhaps before the final manuscript is written and presented as two parts of the same report) or it could be proposed in the Discussion as a specific study that could be conducted by other researchers.

The second path is appropriate when researchers reexamine their theoretical framework in light of the unexpected findings and recognize serious flaws in the framework. The flaws could result from a number of factors, including defining elements of the framework in too general a way to formulate well-grounded hypotheses, failing to include a variable, or not accounting carefully enough for the previous work in this domain, both theoretical and empirical. In many of these cases, readers would not be well served by reading a poorly developed framework and then learning that the framework, which had not been convincing, did not accurately predict the results. Before scrapping the study and starting over, we suggest stepping back and reexamining the framework. Is it possible to develop a more coherent, complete, and convincing framework? Would this framework predict the results more accurately? If the findings remain unexpected based on the predictions generated by this revised, more compelling framework, then the first path applies.

It is likely that the new framework will better predict the findings. After all, the researchers now know the findings they will report. However, it is unlikely that the framework will accurately predict all the findings. This is because the framework is not built around the findings of this study of which authors are now aware (but have not yet been presented). Frameworks are built on research and theory already published. This means the redesigned framework is built from exactly the same empirical findings and theoretical arguments available before the study was conducted. The redesigned framework also is constrained by needing to justify exactly those methods used in the study. The redesigned framework cannot justify different methods or even slightly altered methods. The task for researchers is to show how the new theoretical framework necessarily generates, using the same methods, the predictions they present in the research paper. Just as before, it is unlikely this framework can account for all the findings. Just as before, after presenting the results the researchers should explain why they believe particular hypotheses were confirmed and why others should be revised, even in small ways, based on the findings reported. Researchers can now use these findings to revise the hypotheses presented in the paper. The point we are making is that we believe it is acceptable to reconstruct frameworks before writing research reports if doing so would be more educative for the reader.

Finally, the third path becomes appropriate when researchers, in reexamining their theoretical framework, trace the problem to a misalignment between the methods they used and the theoretical framework or the research questions. Perhaps the researchers recognize that the tasks they used did not yield data that could test the predictions and address the research questions. Or perhaps the researchers realize that the sample they selected would likely have been heavily influenced by a factor they failed to take into account. In other words, the researchers decide that the unexpected findings were due to a problem with the methods they used, not with the framework or the accompanying predictions. In this case, we recommend that the researchers correct the methodological problems and conduct the study again.

Part V. A Few Suggestions for Structuring Your Discussion Section

Writing the Discussion section of your research paper can be overwhelming given all our suggestions about what to include in this section. Here are a few tips that might help you create a simple template for this section.

We recommend the Discussion begin with a brief summary of the main results, especially those you will interpret in this section. This summary should not contain new data or results not previously presented in the paper.

The Discussion could then move to presenting the contributions in the ways we have described. To do this you could point out the ways in which the results differed from the predictions and suggest revisions to your rationales that would have better predicted the results. Doing this will show how the contributions of your study extend what is known beyond the research you drew on to build your original rationale. You can then propose how to extend your contributions to research by proposing future research studies that would test your new predictions. If you believe the revisions you make to your rationales produce new insights or understandings that could be helpful for educational practitioners, you can identify these contributions to practice as well. This comprises the bulk of the Discussion section.

If you have embedded the limitations in earlier sections of the paper, you will have presented your results and interpreted your findings constrained by these limitations. If you choose (or are asked) to describe limitations in the Discussion, you could identify the limitations and then point to the ways they affected your interpretations of the findings. Finally, the Discussion could conclude with the implications of the study for methodological choices that could improve research in the domain in which your study is located or how future studies could overcome the limitations you identified.

Because we are providing guidance on writing your research paper for publication, we will reiterate here that you should investigate the expectations and conventions of the journal to which you will submit your paper. Usually, it will be acceptable to use the terms “significance,” “contributions,” and “implications” as we have defined them. However, if the editors expect you to use the terms differently, follow the editors’ expectations. Our definitions in this chapter are meant to help you think clearly about the different ways you can make a case for the importance of your research. What matters is that you have carefully built and described a coherent chain of scientific inquiry that allows your study to translate the significance of your research problem into contributions to the field.

We began the chapter with the “So what?” question. The question looks simple and straightforward but is challenging and complicated. Its simple appearance can lead researchers to believe it should have a simple answer. But it almost never does. In this chapter, we tried to address the many complications that arise when answering the question. We hope you now have some new insights and new tools for answering the question in your next study.

Cai, J., Morris, A., Hohensee, C., Hwang, S., Robison, V., Cirillo, M., Kramer, S. L., & Hiebert, J. (2019a). Choosing and justifying robust methods for educational research. Journal for Research in Mathematics Education, 50 (4), 342–348. https://doi.org/10.5951/jresematheduc.50.2.0114

Article   Google Scholar  

Makel, M. C., Hodges, J., Cook, G. B., & Plucker, J. A. (2021). Both questionable and open research practices are prevalent in education research. Educational Researcher, 50 (8), 493–504.

Wang, G., Zhang, S., & Cai, J. (2021). How are parental expectations related to students’ beliefs and their perceived achievement? Educational Studies in Mathematics., 108 , 429–450. https://doi.org/10.1007/s10649-021-10073-w

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). Significance of a Study: Revisiting the “So What” Question. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_5

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Educational resources and simple solutions for your research journey

Decoding the Scope and Delimitations of the Study in Research

Scope and delimitations of the study are two essential elements of a research paper or thesis that help to contextualize and convey the focus and boundaries of a research study. This allows readers to understand the research focus and the kind of information to expect. For researchers, especially students and early career researchers, understanding the meaning and purpose of the scope and delimitation of a study is crucial to craft a well-defined and impactful research project. In this article, we delve into the core concepts of scope and delimitation in a study, providing insightful examples, and practical tips on how to effectively incorporate them into your research endeavors.

Table of Contents

What is scope and delimitation in research

The scope of a research paper explains the context and framework for the study, outlines the extent, variables, or dimensions that will be investigated, and provides details of the parameters within which the study is conducted. Delimitations in research , on the other hand, refer to the limitations imposed on the study. It identifies aspects of the topic that will not be covered in the research, conveys why these choices were made, and how this will affect the outcome of the research. By narrowing down the scope and defining delimitations, researchers can ensure focused research and avoid pitfalls, which ensures the study remains feasible and attainable.

Example of scope and delimitation of a study

A researcher might want to study the effects of regular physical exercise on the health of senior citizens. This would be the broad scope of the study, after which the researcher would refine the scope by excluding specific groups of senior citizens, perhaps based on their age, gender, geographical location, cultural influences, and sample sizes. These then, would form the delimitations of the study; in other words, elements that describe the boundaries of the research.

The purpose of scope and delimitation in a study

The purpose of scope and delimitation in a study is to establish clear boundaries and focus for the research. This allows researchers to avoid ambiguity, set achievable objectives, and manage their project efficiently, ultimately leading to more credible and meaningful findings in their study. The scope and delimitation of a study serve several important purposes, including:

• Establishing clarity: Clearly defining the scope and delimitation of a study helps researchers and readers alike understand the boundaries of the investigation and what to expect from it.
• Focus and relevance: By setting the scope, researchers can concentrate on specific research questions, preventing the study from becoming too broad or irrelevant.
• Feasibility: Delimitations of the study prevent researchers from taking on too unrealistic or unmanageable tasks, making the research more achievable.
• Avoiding ambiguity: A well-defined scope and delimitation of the study minimizes any confusion or misinterpretation regarding the research objectives and methods.

Given the importance of both the scope and delimitations of a study, it is imperative to ensure that they are mentioned early on in the research manuscript. Most experts agree that the scope of research should be mentioned as part of the introduction and the delimitations must be mentioned as part of the methods section. Now that we’ve covered the scope and delimitation meaning and purpose, we look at how to write each of these sections.

How to write the scope of the study in research

When writing the scope of the study, remain focused on what you hope to achieve. Broadening the scope too much might make it too generic while narrowing it down too much may affect the way it would be interpreted. Ensure the scope of the study is clear, concise and accurate. Conduct a thorough literature review to understand existing literature, which will help identify gaps and refine the scope of your study.

It is helpful if you structure the scope in a way that answers the Six Ws – questions whose answers are considered basic in information-gathering.

Why: State the purpose of the research by articulating the research objectives and questions you aim to address in your study.

What: Outline the specific topic to be studied, while mentioning the variables, concepts, or aspects central to your research; these will define the extent of your study.

Where: Provide the setting or geographical location where the research study will be conducted.

When : Mention the specific timeframe within which the research data will be collected.

Who : Specify the sample size for the study and the profile of the population they will be drawn from.

How : Explain the research methodology, research design, and tools and analysis techniques.

How to write the delimitations of a study in research

When writing the delimitations of the study, researchers must provide all the details clearly and precisely. Writing the delimitations of the study requires a systematic approach to narrow down the research’s focus and establish boundaries. Follow these steps to craft delimitations effectively:

• Clearly understand the research objectives and questions you intend to address in your study.
• Conduct a comprehensive literature review to identify gaps and areas that have already been extensively covered. This helps to avoid redundancies and home in on a unique issue.
• Clearly state what aspects, variables, or factors you will be excluding in your research; mention available alternatives, if any, and why these alternatives were rejected.
• Explain how you the delimitations were set, and they contribute to the feasibility and relevance of your study, and how they align with the research objectives.
• Be sure to acknowledge limitations in your research, such as constraints related to time, resources, or data availability.

Being transparent ensures credibility, while explaining why the delimitations of your study could not be overcome with standard research methods backed up by scientific evidence can help readers understand the context better.

Differentiating between delimitations and limitations

Most early career researchers get confused and often use these two terms interchangeably which is wrong. Delimitations of a study refer to the set boundaries and specific parameters within which the research is carried out. They help narrow down your focus and makes it more relevant to what you are trying to prove.

Meanwhile, limitations in a study refer to the validity and reliability of the research being conducted. They are those elements of your study that are usually out of your immediate control but are still able to affect your findings in some way. In other words, limitation are potential weaknesses of your research.

In conclusion, scope and delimitation of a study are vital elements that shape the trajectory of your research study. The above explanations will have hopefully helped you better understand the scope and delimitations meaning, purpose, and importance in crafting focused, feasible, and impactful research studies. Be sure to follow the simple techniques to write the scope and delimitations of the study to embark on your research journey with clarity and confidence. Happy researching!

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Background of The Study – Examples and Writing Guide

Table of Contents

Background of The Study

Definition:

Background of the study refers to the context, circumstances, and history that led to the research problem or topic being studied. It provides the reader with a comprehensive understanding of the subject matter and the significance of the study.

The background of the study usually includes a discussion of the relevant literature, the gap in knowledge or understanding, and the research questions or hypotheses to be addressed. It also highlights the importance of the research topic and its potential contributions to the field. A well-written background of the study sets the stage for the research and helps the reader to appreciate the need for the study and its potential significance.

How to Write Background of The Study

Here are some steps to help you write the background of the study:

Identify the Research Problem

Start by identifying the research problem you are trying to address. This problem should be significant and relevant to your field of study.

Provide Context

Once you have identified the research problem, provide some context. This could include the historical, social, or political context of the problem.

Review Literature

Conduct a thorough review of the existing literature on the topic. This will help you understand what has been studied and what gaps exist in the current research.

Identify Research Gap

Based on your literature review, identify the gap in knowledge or understanding that your research aims to address. This gap will be the focus of your research question or hypothesis.

State Objectives

Clearly state the objectives of your research . These should be specific, measurable, achievable, relevant, and time-bound (SMART).

Discuss Significance

Explain the significance of your research. This could include its potential impact on theory , practice, policy, or society.

Finally, summarize the key points of the background of the study. This will help the reader understand the research problem, its context, and its significance.

How to Write Background of The Study in Proposal

The background of the study is an essential part of any proposal as it sets the stage for the research project and provides the context and justification for why the research is needed. Here are the steps to write a compelling background of the study in your proposal:

• Identify the problem: Clearly state the research problem or gap in the current knowledge that you intend to address through your research.
• Provide context: Provide a brief overview of the research area and highlight its significance in the field.
• Review literature: Summarize the relevant literature related to the research problem and provide a critical evaluation of the current state of knowledge.
• Identify gaps : Identify the gaps or limitations in the existing literature and explain how your research will contribute to filling these gaps.
• Justify the study : Explain why your research is important and what practical or theoretical contributions it can make to the field.
• Highlight objectives: Clearly state the objectives of the study and how they relate to the research problem.
• Discuss methodology: Provide an overview of the methodology you will use to collect and analyze data, and explain why it is appropriate for the research problem.
• Conclude : Summarize the key points of the background of the study and explain how they support your research proposal.

How to Write Background of The Study In Thesis

The background of the study is a critical component of a thesis as it provides context for the research problem, rationale for conducting the study, and the significance of the research. Here are some steps to help you write a strong background of the study:

• Identify the research problem : Start by identifying the research problem that your thesis is addressing. What is the issue that you are trying to solve or explore? Be specific and concise in your problem statement.
• Review the literature: Conduct a thorough review of the relevant literature on the topic. This should include scholarly articles, books, and other sources that are directly related to your research question.
• I dentify gaps in the literature: After reviewing the literature, identify any gaps in the existing research. What questions remain unanswered? What areas have not been explored? This will help you to establish the need for your research.
• Establish the significance of the research: Clearly state the significance of your research. Why is it important to address this research problem? What are the potential implications of your research? How will it contribute to the field?
• Provide an overview of the research design: Provide an overview of the research design and methodology that you will be using in your study. This should include a brief explanation of the research approach, data collection methods, and data analysis techniques.
• State the research objectives and research questions: Clearly state the research objectives and research questions that your study aims to answer. These should be specific, measurable, achievable, relevant, and time-bound.
• Summarize the chapter: Summarize the chapter by highlighting the key points and linking them back to the research problem, significance of the study, and research questions.

How to Write Background of The Study in Research Paper

Here are the steps to write the background of the study in a research paper:

• Identify the research problem: Start by identifying the research problem that your study aims to address. This can be a particular issue, a gap in the literature, or a need for further investigation.
• Conduct a literature review: Conduct a thorough literature review to gather information on the topic, identify existing studies, and understand the current state of research. This will help you identify the gap in the literature that your study aims to fill.
• Explain the significance of the study: Explain why your study is important and why it is necessary. This can include the potential impact on the field, the importance to society, or the need to address a particular issue.
• Provide context: Provide context for the research problem by discussing the broader social, economic, or political context that the study is situated in. This can help the reader understand the relevance of the study and its potential implications.
• State the research questions and objectives: State the research questions and objectives that your study aims to address. This will help the reader understand the scope of the study and its purpose.
• Summarize the methodology : Briefly summarize the methodology you used to conduct the study, including the data collection and analysis methods. This can help the reader understand how the study was conducted and its reliability.

Examples of Background of The Study

Here are some examples of the background of the study:

Problem : The prevalence of obesity among children in the United States has reached alarming levels, with nearly one in five children classified as obese.

Significance : Obesity in childhood is associated with numerous negative health outcomes, including increased risk of type 2 diabetes, cardiovascular disease, and certain cancers.

Gap in knowledge : Despite efforts to address the obesity epidemic, rates continue to rise. There is a need for effective interventions that target the unique needs of children and their families.

Problem : The use of antibiotics in agriculture has contributed to the development of antibiotic-resistant bacteria, which poses a significant threat to human health.

Significance : Antibiotic-resistant infections are responsible for thousands of deaths each year and are a major public health concern.

Gap in knowledge: While there is a growing body of research on the use of antibiotics in agriculture, there is still much to be learned about the mechanisms of resistance and the most effective strategies for reducing antibiotic use.

Edxample 3:

Problem : Many low-income communities lack access to healthy food options, leading to high rates of food insecurity and diet-related diseases.

Significance : Poor nutrition is a major contributor to chronic diseases such as obesity, type 2 diabetes, and cardiovascular disease.

Gap in knowledge : While there have been efforts to address food insecurity, there is a need for more research on the barriers to accessing healthy food in low-income communities and effective strategies for increasing access.

Examples of Background of The Study In Research

Here are some real-life examples of how the background of the study can be written in different fields of study:

Example 1 : “There has been a significant increase in the incidence of diabetes in recent years. This has led to an increased demand for effective diabetes management strategies. The purpose of this study is to evaluate the effectiveness of a new diabetes management program in improving patient outcomes.”

Example 2 : “The use of social media has become increasingly prevalent in modern society. Despite its popularity, little is known about the effects of social media use on mental health. This study aims to investigate the relationship between social media use and mental health in young adults.”

Example 3: “Despite significant advancements in cancer treatment, the survival rate for patients with pancreatic cancer remains low. The purpose of this study is to identify potential biomarkers that can be used to improve early detection and treatment of pancreatic cancer.”

Examples of Background of The Study in Proposal

Here are some real-time examples of the background of the study in a proposal:

Example 1 : The prevalence of mental health issues among university students has been increasing over the past decade. This study aims to investigate the causes and impacts of mental health issues on academic performance and wellbeing.

Example 2 : Climate change is a global issue that has significant implications for agriculture in developing countries. This study aims to examine the adaptive capacity of smallholder farmers to climate change and identify effective strategies to enhance their resilience.

Example 3 : The use of social media in political campaigns has become increasingly common in recent years. This study aims to analyze the effectiveness of social media campaigns in mobilizing young voters and influencing their voting behavior.

Example 4 : Employee turnover is a major challenge for organizations, especially in the service sector. This study aims to identify the key factors that influence employee turnover in the hospitality industry and explore effective strategies for reducing turnover rates.

Examples of Background of The Study in Thesis

Here are some real-time examples of the background of the study in the thesis:

Example 1 : “Women’s participation in the workforce has increased significantly over the past few decades. However, women continue to be underrepresented in leadership positions, particularly in male-dominated industries such as technology. This study aims to examine the factors that contribute to the underrepresentation of women in leadership roles in the technology industry, with a focus on organizational culture and gender bias.”

Example 2 : “Mental health is a critical component of overall health and well-being. Despite increased awareness of the importance of mental health, there are still significant gaps in access to mental health services, particularly in low-income and rural communities. This study aims to evaluate the effectiveness of a community-based mental health intervention in improving mental health outcomes in underserved populations.”

Example 3: “The use of technology in education has become increasingly widespread, with many schools adopting online learning platforms and digital resources. However, there is limited research on the impact of technology on student learning outcomes and engagement. This study aims to explore the relationship between technology use and academic achievement among middle school students, as well as the factors that mediate this relationship.”

Examples of Background of The Study in Research Paper

Here are some examples of how the background of the study can be written in various fields:

Example 1: The prevalence of obesity has been on the rise globally, with the World Health Organization reporting that approximately 650 million adults were obese in 2016. Obesity is a major risk factor for several chronic diseases such as diabetes, cardiovascular diseases, and cancer. In recent years, several interventions have been proposed to address this issue, including lifestyle changes, pharmacotherapy, and bariatric surgery. However, there is a lack of consensus on the most effective intervention for obesity management. This study aims to investigate the efficacy of different interventions for obesity management and identify the most effective one.

Example 2: Antibiotic resistance has become a major public health threat worldwide. Infections caused by antibiotic-resistant bacteria are associated with longer hospital stays, higher healthcare costs, and increased mortality. The inappropriate use of antibiotics is one of the main factors contributing to the development of antibiotic resistance. Despite numerous efforts to promote the rational use of antibiotics, studies have shown that many healthcare providers continue to prescribe antibiotics inappropriately. This study aims to explore the factors influencing healthcare providers’ prescribing behavior and identify strategies to improve antibiotic prescribing practices.

Example 3: Social media has become an integral part of modern communication, with millions of people worldwide using platforms such as Facebook, Twitter, and Instagram. Social media has several advantages, including facilitating communication, connecting people, and disseminating information. However, social media use has also been associated with several negative outcomes, including cyberbullying, addiction, and mental health problems. This study aims to investigate the impact of social media use on mental health and identify the factors that mediate this relationship.

Purpose of Background of The Study

The primary purpose of the background of the study is to help the reader understand the rationale for the research by presenting the historical, theoretical, and empirical background of the problem.

More specifically, the background of the study aims to:

• Provide a clear understanding of the research problem and its context.
• Identify the gap in knowledge that the study intends to fill.
• Establish the significance of the research problem and its potential contribution to the field.
• Highlight the key concepts, theories, and research findings related to the problem.
• Provide a rationale for the research questions or hypotheses and the research design.
• Identify the limitations and scope of the study.

When to Write Background of The Study

The background of the study should be written early on in the research process, ideally before the research design is finalized and data collection begins. This allows the researcher to clearly articulate the rationale for the study and establish a strong foundation for the research.

The background of the study typically comes after the introduction but before the literature review section. It should provide an overview of the research problem and its context, and also introduce the key concepts, theories, and research findings related to the problem.

Writing the background of the study early on in the research process also helps to identify potential gaps in knowledge and areas for further investigation, which can guide the development of the research questions or hypotheses and the research design. By establishing the significance of the research problem and its potential contribution to the field, the background of the study can also help to justify the research and secure funding or support from stakeholders.

Advantage of Background of The Study

The background of the study has several advantages, including:

• Provides context: The background of the study provides context for the research problem by highlighting the historical, theoretical, and empirical background of the problem. This allows the reader to understand the research problem in its broader context and appreciate its significance.
• Identifies gaps in knowledge: By reviewing the existing literature related to the research problem, the background of the study can identify gaps in knowledge that the study intends to fill. This helps to establish the novelty and originality of the research and its potential contribution to the field.
• Justifies the research : The background of the study helps to justify the research by demonstrating its significance and potential impact. This can be useful in securing funding or support for the research.
• Guides the research design: The background of the study can guide the development of the research questions or hypotheses and the research design by identifying key concepts, theories, and research findings related to the problem. This ensures that the research is grounded in existing knowledge and is designed to address the research problem effectively.
• Establishes credibility: By demonstrating the researcher’s knowledge of the field and the research problem, the background of the study can establish the researcher’s credibility and expertise, which can enhance the trustworthiness and validity of the research.

Disadvantages of Background of The Study

Some Disadvantages of Background of The Study are as follows:

• Time-consuming : Writing a comprehensive background of the study can be time-consuming, especially if the research problem is complex and multifaceted. This can delay the research process and impact the timeline for completing the study.
• Repetitive: The background of the study can sometimes be repetitive, as it often involves summarizing existing research and theories related to the research problem. This can be tedious for the reader and may make the section less engaging.
• Limitations of existing research: The background of the study can reveal the limitations of existing research related to the problem. This can create challenges for the researcher in developing research questions or hypotheses that address the gaps in knowledge identified in the background of the study.
• Bias : The researcher’s biases and perspectives can influence the content and tone of the background of the study. This can impact the reader’s perception of the research problem and may influence the validity of the research.
• Accessibility: Accessing and reviewing the literature related to the research problem can be challenging, especially if the researcher does not have access to a comprehensive database or if the literature is not available in the researcher’s language. This can limit the depth and scope of the background of the study.

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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• Open access
• Published: 19 April 2024

A longitudinal cohort study on the use of health and care services by older adults living at home with/without dementia before and during the COVID-19 pandemic: the HUNT study

• Tanja Louise Ibsen 1 ,
• Bjørn Heine Strand 1 , 2 , 3 ,
• Sverre Bergh 1 , 4 ,
• Gill Livingston 5 , 6 ,
• Hilde Lurås 7 , 8 ,
• Svenn-Erik Mamelund 9 ,
• Richard Oude Voshaar 10 ,
• Anne Marie Mork Rokstad 1 , 11 ,
• Pernille Thingstad 12 , 13 ,
• Debby Gerritsen 14 &
• Geir Selbæk 1 , 15 , 16  

BMC Health Services Research volume  24 , Article number:  485 ( 2024 ) Cite this article

197 Accesses

Metrics details

Older adults and people with dementia were anticipated to be particularly unable to use health and care services during the lockdown period following the COVID-19 pandemic. To better prepare for future pandemics, we aimed to investigate whether the use of health and care services changed during the pandemic and whether those at older ages and/or dementia experienced a higher degree of change than that observed by their counterparts.

Data from the Norwegian Trøndelag Health Study (HUNT4 70 + , 2017–2019) were linked to two national health registries that have individual-level data on the use of primary and specialist health and care services. A multilevel mixed-effects linear regression model was used to calculate changes in the use of services from 18 months before the lockdown, (12 March 2020) to 18 months after the lockdown.

The study sample included 10,607 participants, 54% were women and 11% had dementia. The mean age was 76 years (SD: 5.7, range: 68–102 years). A decrease in primary health and care service use, except for contact with general practitioners (GPs), was observed during the lockdown period for people with dementia ( p  < 0.001) and those aged ≥ 80 years without dementia ( p  = 0.006), compared to the 6-month period before the lockdown. The use of specialist health services decreased during the lockdown period for all groups ( p  ≤ 0.011), except for those aged < 80 years with dementia. Service use reached levels comparable to pre-pandemic data within one year after the lockdown.

Older adults experienced an immediate reduction in the use of health and care services, other than GP contacts, during the first wave of the COVID-19 pandemic. Within primary care services, people with dementia demonstrated a more pronounced reduction than that observed in people without dementia; otherwise, the variations related to age and dementia status were small. Both groups returned to services levels similar to those during the pre-pandemic period within one year after the lockdown. The increase in GP contacts may indicate a need to reallocate resources to primary health services during future pandemics.

Trial registration

The study is registered at ClinicalTrials.gov, with the identification number NCT 04792086.

Peer Review reports

In Norway, similar to most European countries [ 1 , 2 , 3 ], the first wave of the COVID-19 pandemic lasted from 12 March to 15 June 2020 [ 4 ]. During this period, strict infection control measures were introduced to minimise the number of infected people. Health and care services were reduced or locked down, because health professionals were transferred to COVID-19-related services, or hospital wards were reserved for COVID-19 patients. Facilities such as day care services were closed to prevent the spread of infection through social contact, and some services were employed with digital technology. People were urged to stay at home to maintain social distancing and prevent the spread of the virus [ 4 ].

The strict infection control measures aimed mainly to prevent people from hospitalisation and/or death by COVID-19. By 13 November 2022 (last published data), Norway recorded 4,399 cumulative COVID-19-related deaths, of which approximately two-thirds occurred in 2022 (in people of an average age of 85.6 years in 2022) [ 5 ]. From March 2020 to March 2021, compared to the mean all-cause mortality from 2016 to 2019 as a reference, Norway recorded significantly lower all-cause mortality than those recorded by other European Union countries [ 6 ], indicating that Norway had a successful public health strategy. The topic being raised in the present paper, is how infection control measures affected the use of health and care services by the older population, to better prepare ourselves for future health crisis like a pandemic.

Older adults are particularly vulnerable to COVID-19 and at a higher risk of hospitalisation and death [ 7 ]. People with dementia are anticipated to have an even higher risk of mortality than that of people without dementia, because of an impaired immune system [ 8 ]. Fearing the virus, some older adults personally imposed strict infection control measures and cancelled scheduled healthcare appointments. A German study, including participants aged ≥ 73 years, has reported that approximately 30% of the participants reduced or cancelled their medical consultations during the first wave of the pandemic [ 1 ]. A qualitative study including participants aged 65–79 years from Portugal, Brazil, and the United Kingdom has reported that the majority refrained from face-to-face contact with their family doctors in the first wave of the pandemic, as it implied using public transport making social distancing difficult [ 2 ]. Some health and care services have been replaced with online or telephone consultations, which have been beneficial for some parts of the population and challenging for others, especially older adults [ 2 , 3 , 9 ].

People with dementia often need health and care services and practical assistance in their homes to manage their everyday lives [ 10 ]. A Norwegian study including 105 caregivers of people with dementia has reported that 60% experienced a reduction or full cessation of formal care during the first wave of the pandemic as the services were cancelled by the service provider [ 11 ]. This is in line with studies from Sweden and the USA, which reported a significant drop in the use of health and care services during this period [ 12 , 13 ]. However, how the use of primary and specialist healthcare services affected older adults, including people with dementia, as society began a cautious reopening after the first wave of the pandemic remains unclear. A study from the USA conducted a predictive analysis for the post-lockdown period (June 2020–October 2021) on inpatient, outpatient, and emergency services. They found that people with mild cognitive impairment (MCI), Alzheimer’s disease, and related dementia experienced greater and more sustained disruptions in primary and specialist health and care service use than those experienced by people without MCI or dementia [ 13 ].

In the present study, we used a large population-based dataset from the Norwegian Trøndelag Health Study (HUNT) [ 14 ], linked to national registry data on primary and specialist health and care services, to investigate whether the use of health and care services changed during the pandemic, and those with older ages and/or dementia had a higher degree of change than that observed in their counterparts.

Study design and setting

We used a longitudinal cohort design, linking participant data on sex, year of birth, and cognitive status from the HUNT4 70 + survey with later registry data on the use of health and care services from 12 September 2018 to 11 September 2021. This time period equals 18 months before- and 18 months after the Norwegian lockdown on 12 March 2020. This 36-month period was grouped into six periods of six months each, including three pre-lockdown periods (pre1, pre2, and pre3), one lockdown period, and two post-lockdown periods (post1 and post2) (Fig.  1 ). We included a longer lockdown period than the generally denoted period from March to June 2020, as the reopening started slowly, and many older adults imposed strict social distancing on themselves. The next period, 12 September 2020 to 11 March 2021 also included periods with restrictions on social life and activity, such as a maximum of five people gathering and recommendations for wearing a face mask where maintaining distance is difficult. In the last period from 12 March to 11 September 2021, all infection control measures were gradually lifted until Norway was completely reopened on 25 September 2021 [ 4 ]. Trøndelag, the county where the study was conducted, followed national infection control regulations.

Flow-chart of the study periods

Participants

The study included participants aged > 70 years in the fourth wave of the HUNT Study (HUNT4 70 +), which took place between September 2017 and March 2019. The HUNT is a population-based study that has invited the entire adult population from the same geographic area, North-Trøndelag, in four waves, first time in 1984 [ 14 ]. As North-Trøndelag does not comprise any large cities, a random sample of people aged > 70 years from a city in Trondheim (212,000 inhabitants) was also invited. In total, 11,675 participants were included, with 9,930 from North-Trøndelag (response rate 51%) and 1,745 from Trondheim (response rate 34%). We do not judge that there is likely to be any systematic bias introduced by the difference in response rates in different municipalities as the people living at home are similar populations.”. The participants answered a questionnaire that included socio-demographic and clinical data, and they attended a comprehensive clinical evaluation by health professionals [ 15 ]. Participants without sufficient information on their cognitive status ( n  = 202) and nursing home residents ( n  = 866) were excluded (Fig.  2 ). The mean age (76 years, SD 5.7 years) of those included was lower than that of those excluded (82 years, SD 7.9) ( p  < 0.001). The study population included 10,607 participants with complete data on cognitive status. We do not have information on dementia status on the population not included in HUNT4 70 + .

Flow-chart of included participants. HUNT4 70 + : The fourth wave of the Trøndelag health study, 70 year and older cohort

Dementia diagnosis

Two specialists from a diagnostic workgroup of nine medical doctors with comprehensive scientific and clinical expertise (geriatrics, old-age psychiatry, or neurology) independently diagnosed each patient with dementia using the Diagnostic and Statistical Manual of Mental Disorders-5 [ 16 ]. Discrepancies were resolved and consensuses were obtained by the involvement of a third expert. During the diagnostic process, the experts had access to all relevant information from the HUNT4 70 + dataset, such as education, function in activities of daily living, neuropsychiatric symptoms, onset and course of cognitive symptoms, cognitive tests (the Montreal Cognitive Assessment (MoCA) scale [ 17 ] and the Word List Memory Task (WLMT) [ 18 ], and structured interviews with the closest family proxy. A more comprehensive description of the diagnostic process has been published [ 15 ].

Health and care services

Data from two national registries were collected for the entire study period, from September 2018 to September 2021. Health and care services used in primary health care were obtained from The Norwegian Registry of Primary Health Care [ 19 ]. This registry includes individual-level data on municipal health services (contacts with general practitioners (GPs), emergency rooms, and physiotherapists) and care services (care, such as home nurses, and practical assistance in the recipient’s home, day care, respite services and short-term nursing home stays, municipal housing, and nursing home admission) [ 20 ]. Information on the use of specialist health services was based on data from the Norwegian Patient Registry (NPR) [ 21 ]. The NPR holds individual-level data on patients’ use of specialist health services (contacts with somatic hospitals, mental health care, and rehabilitation institutions). The NPR also registers whether the contact was an outpatient consultation, hospitalisation, or day-treatment [ 20 ].

Data were analysed using the STATA 16 software [ 22 ]. Participant characteristics are reported as means with SD, frequencies, or percentages, as appropriate. Those who were admitted to a nursing home ( n  = 364) or died ( n  = 821) during the study period were censored and participated in only half of the person-time during the study period. Duplicates were removed (3,293 observations). The mean number of health and care services per person in each period (with 95% confidence interval [CI]) was predicted from a multilevel mixed-effects linear regression model with random intercept, where random effects varied across the individuals. In the regression model, the number of services per person was the outcome variable and sex, age, cognitive status (no dementia/dementia), and period were covariates.Age and cognitive status are relevant confounders to address the aim of the present study, and sex is included as a key sociodemographic measure in epidemiological research. [ 23 , 24 ]. To allow for different time trends by cognitive status group, the interaction term period by cognitive status was included in the regression model. In the predictions, the adjusted variables were fixed at their mean values. The significance level was set at p  < 0.05. To investigate the use of health and care services before and during the pandemic, the number of care services implemented within each period and the number of contacts within each period for primary and specialist health services were aggregated. Hence, for care services, we used the date on which the service was implemented, for example the date on which practical assistance at home was implemented. For health services, we used the date when the service occurred, for example, the date a person had contact with a GP or the date a person had contact with a hospital, either for outpatient consultation, hospitalisation, or day-treatment.

In the Results section, we report significant differences between the lockdown period and all the pre- and post-lockdown periods, and between pre2 and post2, as these periods comprise the same seasonal months, one year before and one year after the lockdown, respectively.

The study included 10,607 participants, of whom 54% were women, and 11% had dementia (Table  1 ). The mean age of the participants on 1 January 2017 was 76 years (SD 5.7, range: 68–102 years), and 7,769 participants (73%) were < 80 years old. During the 36-month follow-up period, the study sample was reduced by 10% (from 10,607 to 9,568) due to censoring for death and/or nursing home admission (Table  2 ). The dropout rate was higher in those with dementia than in those without dementia (37% vs. 7%, p  < 0.001). During these 36-months, the total number of contacts with primary health services was 554,061, which corresponded to 9.2 contacts per person per 6-month period (Table  3 ). People with dementia had more contact with health services in the municipality than the contact made by those without dementia (11.3 vs. 8.8 contacts per person per 6-month period, p  < 0.001). The total number of care services implemented for our study population was 20,411, which corresponded to 0.3 care services per person per 6-month period. People with dementia received more care services than those received by people without dementia (1.2 vs. 0.2 care services per person per 6-month period, p  < 0.001). The total number of contacts with specialist health services was 141,994, which corresponded to 2.3 contacts per person per 6-month period. People with dementia had less contact with specialist health services than the contact made by those without dementia (2.2 vs. 2.6 contacts per person per 6-month period, p  < 0.001).

Primary health and care services

Health services.

During the 36-month study period, contact with GPs was the most used health service (66%), followed by physiotherapy services (30%), and contact with GPs in emergency rooms (4%).

The following model only presents contact with GPs, including GPs in emergency rooms, as contact with GPs was the most frequently used primary health service.

The age- and sex-adjusted model (Fig.  3 ) shows that for those aged < 80 years with dementia, the mean number of GP contacts during the lockdown period was higher than that during pre1 (1.27, p  < 0.001) and pre3 (0.82, p  = 0.002) and lower than that during post1 (1.67, p  < 0.001) and post2 (0.84, p  < 0.002). The mean number of GP contacts during post2 was higher than that during pre2 (0.32, p  < 0.001).

Mean number of registered contacts with general practitioners (GPs) per period, pre-lockdown, during lockdown and post-lockdown, including GPs at emergency rooms, for participants < 80 versus ≥ 80 years, divided in people with- or without dementia. Mean number of contacts was predicted in a mixed-effects linear regression model adjusted by period, cognitive status, sex, age, and the interaction period*cognitive status. In the predictions, the adjustment variables age and sex were fixed at the mean values

For those without dementia, the mean number of GP contacts during the lockdown was higher than that during pre1 (0.45, p  < 0.001) and pre2 (0.51, p  < 0.001) and lower than that during post1 (1.18, p  < 0.001) and post2 (0.59, p  < 0.001). The mean number of GP contacts during post2 was higher than that during pre2 (1.11, p  < 0.001).

For those aged ≥ 80 years with dementia, the mean number of GP contacts during the lockdown was higher than that during pre1 (1.45, p  < 0.001) and pre2 (0.96, p  = 0.015) and lower than that during post1 (2.31, p  < 0.001). The mean number of GP contacts during post2 was higher than that during pre2 (1.72, p  < 0.001).

For those without dementia, the mean number of GP contacts during the lockdown was higher than that during pre1 (1.15, p  < 0.001) and pre2 (0.91, p  < 0.001) and lower than that during post1 (1.86, p  < 0.001) and post2 (0.60, p  < 0.002). The mean number of GP contacts during post2 was higher than that during pre2 (1.51, p  < 0.001).

Care services

During the 36-month study period, care and practical assistance at home represented the largest service group (69%), followed by short-term nursing home stays and respite services (21%), nursing home admissions (4%), municipal housing (3%), and day care services (4%). The following model presents all combined care services.

The age- and sex-adjusted model (Fig.  4 ) shows that for those aged < 80 years with dementia, the mean number of care services implemented during the lockdown was lower than that during pre3 (0.37, p  < 0.001) and post1 (0.43, p  < 0.001). The mean number of care services implemented in post2 was higher than that during pre2 (0.13, p  = 0.039).

Mean number of care services implemented per period, pre-lockdown, during lockdown and post-lockdown, as health care and practical assistance in the home, day- and respite services, short-term institutional stay, and nursing home admission, for participants < 80 versus ≥ 80 years, divided in people with- and without dementia. Mean number of care services implemented was predicted in a mixed-effects linear regression model adjusted by period, cognitive status, sex, age, and the interaction period*cognitive status. In the predictions, the adjustment variables age and sex were fixed at the mean values

For those without dementia, the mean number of care services implemented during the lockdown was higher than that during pre1 (0.5, p  = 0.001) and pre2 (0.04, p  = 0.005) and lower than that during post1 (0.03, p  = 0.044). The mean number of care services implemented during post2 was higher than that during pre2 (0.07, p  < 0.001).

For those aged ≥ 80 years with dementia, the mean number of care services implemented during the lockdown was lower than that during pre3 (0.76, p  < 0.001).

For those without dementia, the mean number of care services implemented during the lockdown was higher than that during pre1 (0.22, p  = 0.001) and pre2 (0.17, p  = 0.011) and lower than that during pre3 (0.18, p  = 0.006) and post1 (0.18, p  = 0.007). The mean number of care services implemented during post2 was higher than that during pre2 (0.24, p  < 0.001).

Specialist health services

During the study period, service provision from somatic hospitals was the most used service (96%), followed by mental health care (3%), and treatment at a rehabilitation institution (1%). Somatic hospital services included outpatient consultations (88%), hospitalisation (9%), and daily treatment (3%). The following model only presents contacts with somatic hospital services, as this is the most frequently used specialist health service.

The age- and sex-adjusted models (Fig.  5 ) show that for those aged < 80 years with dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during post1 (0.67, p  = 0.002) and post2 (0.48, p  = 0.025). The mean number of contacts with somatic hospital services in post2 was higher than that during pre2 (0.61, p  = 0.004).

Mean number of registered contacts with somatic hospital services per period, pre-lockdown, during lockdown and post-lockdown, for participants < 80 versus ≥ 80 years, divided in people with- or without dementia. Mean number of contacts was predicted in a mixed-effects linear regression model adjusted by period, cognitive status, sex, age, and the interaction period*cognitive status. In the predictions, the adjustment variables age and sex were fixed at the mean values

For those without dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during pre1 (0.16, p  = 0.002), pre3 (0.40, p  < 0.001), post1 (0.43, p  < 0.001), and post2 (0.34, p  < 0.001). The mean number of contacts with somatic hospital services in post2 was higher than that during pre2 (0.25, p  < 0.001).

For those aged ≥ 80 years with dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during pre2 (0.54, p  = 0.003), pre3 (0.46, p  = 0.011), post1 (0.44, p  = 0.022), and post2 (0.42, p  = 0.040).

For those without dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during pre3 (0.49, p  < 0.001), post1 (0.41, p  < 0.001), and post2 (0.41, p  < 0.001). The mean number of contacts with somatic hospital services in post2 was higher than that during pre2 (0.29, p  = 0.001).

This population-based study revealed that people with dementia experienced a larger decrease in the use of primary care services implemented during the lockdown than that experienced by people without dementia. Contact with GPs was maintained at a normal level or increased in both groups during the lockdown. The use of specialist health services decreased in both groups during the lockdown period except for those aged < 80 years with dementia. The use of primary health and care services, and specialist health services was at the same or higher-level post-lockdown (post2) as pre-lockdown (pre2). Collectively, these results indicate an increased burden on primary health services during the lockdown.

Both cognitive groups had a similar number of GP contacts during lockdown as pre-lockdown. Those aged < 80 years with dementia experienced an increased number of GP contacts during the lockdown compared to the numbers during the 6-month period before the lockdown (pre3). Furthermore, all the groups had an increased number of GP contacts in the first 6-months period post-lockdown (post1). Unfortunately, we were unable to identify whether the consultations were digital in our material; however, digital consultations may have contributed to maintaining contact with GPs during the pandemic. This corresponds with the results of a previous study which has reported that the Norwegian population experienced an increased use of telephone and video consultations during the pandemic [ 3 ]. However, a survey during the pandemic in the same study population as that of the present study (HUNT4 70 +) revealed that only 8% reported contact with healthcare professionals via screen-based media or telephone at least once a month during the pandemic [ 9 ]. In addition, a survey of video consultations among Norwegian GPs during the pandemic revealed that video consultations were unsuitable for the oldest population [ 25 ].

The results of the present study may indicate that GPs managed to serve older adults in Norway during the pandemic and that the cancellations of medical consultations described among older adults in other countries [ 1 , 2 ] have been less extensive in Norway. Meanwhile, contact with GPs may have shifted towards more severe cases, where patients in need of specialist health services who postponed contact because of COVID-19 used the primary care service. In addition, the increase in GP contact post-lockdown may imply an increased stress level among older adults and an increase in health problems during the lockdown, which will be discussed in more detail in a later section.

Our finding that people with dementia experienced a larger decrease in the number of care services implemented during the lockdown than that experienced by people without dementia is in line with those of earlier studies [ 11 , 13 ]. This is most likely a consequence of the fact that people with dementia use care services more often and thus, are more affected when such services are reduced or locked down. Interestingly, those with dementia in both age groups experienced a significant increase in new services implemented in the 6-month period before the lockdown (pre3). However, the possible cause for the increase in care services implemented, such as a reduction in other services or societal changes during this period, remains unconfirmed. The most likely explanation is an increase in service needs related to dementia progression, although some random fluctuations cannot be ruled out.

Care service providers have reported a deterioration in older adults’ health during the pandemic related to the absence of social support, which, in turn, has led to less support with meals, practical help, and physical activity [ 26 ]. Next of kin reported that people with dementia had a reduction in cognitive- and functional abilities because of the limited possibility of meaningful activities and mental stimulation when they had to stay at home [ 27 , 28 ]. Furthermore, a lack of social connections [ 29 ] and perceived social support [ 30 ] are associated with cognitive decline and depression. Based on these findings, it can be assumed that the need for care services may be the same or higher post-lockdown than that in the 6-month period before the pandemic (pre3). However, the number of care services implemented post-lockdown (post2) was at the same level as that at pre-lockdown (pre2).

This study revealed that somatic hospital services for those aged ≥ 80 years were the only services with a lower level of contact during the lockdown period than during the comparable pre-lockdown period (pre2). Both those with and without dementia had a decrease in somatic hospital services during the lockdown period, compared to the 6-months period before the lockdown. This corresponds with findings from an Italian study conducted in the autumn of 2020, reporting that hospitalisations and outpatient visits among older adults aged ≥ 65 years were reduced by 18.3% during the pandemic [ 31 ].

The decrease in the use of somatic hospital services during the lockdown observed in the present study was most likely related to strict infection control measures that prevented a widespread COVID-19 outbreak. Furthermore, it may be interpreted as a precautionary measure taken to minimize the risk of exposing older adults to hospitals, where a considerable number were affected by COVID-19. Hospital services experienced the greatest decline in activity during the lockdown due to preparedness for COVID-19 patients [ 32 ]. In the present study, all the groups returned to the same or a higher level of contact with somatic hospital services post-lockdown (post2), than they had pre-lockdown (pre2). Conversely, a study from the USA has suggested that people with dementia or MCI would experience more sustained disruption in primary and specialist health services than that experienced by people without such diagnoses [ 13 ]. Another study from the USA has revealed that those with comorbidities, often present among people with dementia, were at a higher risk of delayed or missed care during the pandemic [ 33 ]. The contrast in the findings may be related to differences in the healthcare system. In addition, the World Health Organization has reported disruptions in both primary and specialist health services worldwide two years into the pandemic. High-income countries reported fewer service disruptions than those reported by low-income ones [ 34 ]. The increase in GP contact post-lockdown in the present study may indicate that primary health services have been able to relieve specialist health services in Norway, so that people with dementia and others in need of specialist health services may be prioritised.

The variation in the frequency of contact with both somatic hospital services and GPs may be observed in the context of normal seasonal variations, where contact might be higher in the autumn and winter months (pre1, pre3, and post2) than in the spring and summer months (pre2, lockdown, and post2). However, the Norwegian Institute of Public Health has reported that the seasonal flu outbreak from December 2019 to March 2020, which corresponds with the 6-month period before the lockdown (pre3), was limited compared to those in previous years [ 35 ]. Thus, normal variations due to seasonal flu cannot provide a full explanation for more contact with GPs and somatic hospital services in the 6-month period before lockdown (pre3). The next seasonal flu, expected from December 2020 to March 2021 (post1), did not appear as expected, most likely because of the infection control measures in connection with the COVID-19 outbreak [ 36 , 37 ]. The increase in the frequency of contact with GPs and somatic hospital services detected in the 6-month period after the lockdown (post1) may be explained by the fact that people had less contact with these services for diseases other than COVID-19 during the first wave of the pandemic [ 32 ], and that these consultations accumulated when society started reopening. Furthermore, the increase in contact with GPs and somatic hospital services after the lockdown may be explained by the increased contact between people, which may have caused an increased spread of infections [ 37 ].

Finally, the increase in mental health problems during the pandemic [ 27 , 28 , 30 ], may have required additional medical supervision. Studies have reported an increase in depression among older adults during the pandemic, a related increase in the prescription of antidepressant medication [ 30 , 38 ], and the need for primary health services, such as GPs, and specialist services, such as hospital services [ 38 ].

Strength and limitations

The main strength of the present study is its large population-based survey sample merged with unique national registry data on primary and specialist health care services. This provided objective data regarding the participants’ service use. Despite the large study sample, all the participants were from the middle region of Norway, which may differ from the population in other parts of the country and outside Norway. Furthermore, the study sample was a homogenous group of participants mainly born in Norway, and the results cannot be generalised to other ethnic groups. Although the diagnostic process for dementia was thorough, the diagnosis was based on collected research data without access to imaging or biomarker data which may have caused misclassification. As our goal was to estimate the actual change in service use based on dementia status among younger and older adults, the analysis does not include health-related covariates such as comorbidity and functional level. Finally, the information on dementia status was collected from 2017 to 2019 and may have changed during the study period from September 2018 to September 2021.

The use of primary care and specialist health services was immediately reduced during the COVID-19 lockdown period. Within primary care services, people with dementia experienced a more pronounced reduction than that experienced by people without dementia; however, age and dementia status only demonstrated small variations. One year after the lockdown, service provisions returned to a level similar to or higher than that of one year before the lockdown for all groups. Our findings indicate that infection control and management limited the scope of action within care services and specialist health services during the lockdown, leaving GPs on the front line to manage medical problems and psychological stress in the population. In any future pandemic, the reallocation of resources for primary health services could make us better equipped to meet the needs of the population.

Availability of data and materials

The data that support the findings of this study are available from the HUNT database and the Norwegian registry database, Helsedata, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the HUNT database and the Norwegian registry database Helsedata.

Brandl C, Zimmermann ME, Günther F, Dietl A, Küchenhoff H, Loss J, Stark KJ, Heid IM. Changes in healthcare seeking and lifestyle in old aged individuals during COVID-19 lockdown in Germany: the population-based AugUR study. BMC Geriatr. 2022;22(1):34.

Article   CAS   PubMed   PubMed Central   Google Scholar  

von Humboldt S, Low G, Leal I. Health Service Accessibility, Mental Health, and Changes in Behavior during the COVID-19 Pandemic: A Qualitative Study of Older Adults. Int J Environ Res Public Health. 2022;19(7):4277.

Article   Google Scholar  

Tu K, Sarkadi Kristiansson R, Gronsbell J, de Lusignan S, Flottorp S, Goh LH, Hallinan CM, Hoang U, Kang SY, Kim YS, et al. Changes in primary care visits arising from the COVID-19 pandemic: an international comparative study by the International Consortium of Primary Care Big Data Researchers (INTRePID). BMJ Open. 2022;12(5):e059130.

Article   PubMed   Google Scholar  

Governmentof Norway: Timeline: News from Norwegian Ministries about the Coronavirus disease Covid-19 [ https://www.regjeringen.no/no/tema/Koronasituasjonen/tidslinje-koronaviruset/id2692402/ ]. Accessed 12 May 2023.

Norwegian Institute of Public Health: Dødelighet i Norge under koronapandemien 2020 til høsten 2022 [Mortality in Norway during the corona pandemic 2020 to autumn 2022] [ https://www.fhi.no/publ/2022/Dodelighet-under-pandemien/ ]. Accessed 22 June 2023.

Statistics Norway: Hvordan gikk det? Korona i Norge og EU [How did it go? Corona in Norway and EU] [ https://www.ssb.no/helse/faktaside/konsekvenser-av-korona ]. Accessed 22 June 2023.

Ho FK, Petermann-Rocha F, Gray SR, Jani BD, Katikireddi SV, Niedzwiedz CL, Foster H, Hastie CE, Mackay DF, Gill JMR, et al. Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants. PLoS ONE. 2020;15(11):e0241824.

Bianchetti A, Rozzini R, Guerini F, Boffelli S, Ranieri P, Minelli G, Bianchetti L, Trabucchi M. Clinical Presentation of COVID19 in Dementia Patients. J Nutr Health Aging. 2020;24(6):560–2.

Eriksen SRA, Selbæk G, Bjørkløf G, Tveito M, Bergh S, Langhammer A, Næss M, Ibsen T. Bruk av skjermbaserte medier blant eldre under covid-19-pandemien En HUNT-studie [Use of screen-based media among older people during the COVID-19 pandemic A HUNT study]. Sykepleien Forskning. 2022;17(88131):e-88131.

Google Scholar  

Bradbury KM, Moody E, Aubrecht K, Sim M, Rothfus M. Equity in Changes to Dementia Care in the Community during the First Wave of the COVID-19 Pandemic in High Income Countries: A Scoping Review. Societies. 2022;12(2):30.

Vislapuu M, Angeles RC, Berge LI, Kjerstad E, Gedde MH, Husebo BS. The consequences of COVID-19 lockdown for formal and informal resource utilization among home-dwelling people with dementia: results from the prospective PAN.DEM study. BMC Health Serv Res. 2021;21(1):1003.

Article   PubMed   PubMed Central   Google Scholar  

Ekman B, Arvidsson E, Thulesius H, Wilkens J, Cronberg O. Impact of the Covid-19 pandemic on primary care utilization: evidence from Sweden using national register data. BMC Res Notes. 2021;14(1):424.

Tannous J, Pan A, Bako A, Potter T, Jones SL, Janjan N, Smith ML, Seshadri S, Ory MG, Vahidy FS. COVID-19 associated disruptions in routine health care of people with mild cognitive impairment or dementia. Alzheimers Dement (Amst). 2022;14(1):e12323.

Åsvold BO, Langhammer A, Rehn TA, Kjelvik G, Grøntvedt TV, Sørgjerd EP, Fenstad JS, Heggland J, Holmen O, Stuifbergen MC, Vikjord SAA, Brumpton BM, Skjellegrind HK, Thingstad P, Sund ER, Selbæk G, Mork PJ, Rangul V, Hveem K, Næss M, Krokstad S. Cohort Profile Update: The HUNT Study. Norway Int J Epidemiol. 2023;52(1):80–91.

Gjøra L, Strand BH, Bergh S, Borza T, Brækhus A, Engedal K, Johannessen A, Kvello-Alme M, Krokstad S, Livingston G, et al. Current and Future Prevalence Estimates of Mild Cognitive Impairment, Dementia, and Its Subtypes in a Population-Based Sample of People 70 Years and Older in Norway: The HUNT Study. J Alzheimers Dis. 2021;79(3):1213–26.

American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5. Warshington, DC: American Psychiatric Association; 2013.

Book   Google Scholar  

Nasreddine Z, Phillips N, Bédirian V, Charbonneau S, Whitehead V, Collin I, Cummings J, Chertkow H. The montreal cognitive assessment, MoCA: A brief screening tool for mild cognitive impairment. JAGS. 2005;53:695–9.

Morris JC, Heyman A, Mohs RC, Hughes JP, van Belle G, Fillenbaum G, Mellits ED, Clark C. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology. 1989;39(9):1159–65.

Article   CAS   PubMed   Google Scholar  

Norwegian Registry for Primary Health Care [ https://helsedata.no/en/forvaltere/norwegian-directorate-of-health/norwegian-registry-for-primary-health-care-kpr/ ]. Accessed 12 May 2023.

Bakken IJ, Ariansen AMS, Knudsen GP, Johansen KI, Vollset SE. The Norwegian Patient Registry and the Norwegian Registry for Primary Health Care: Research potential of two nationwide health-care registries. Scand J Public Health. 2020;48(1):49–55.

Norwegian Patient Registry [ https://helsedata.no/en/forvaltere/norwegian-directorate-of-health/norwegian-patient-registry-npr/ ]. Accessed 12 May 2023.

StataCorp. Stata Statistical Software: Release 16. College Station: StataCorp LLC; 2019.

Zhang X, Dupre ME, Qiu L, Zhou W, Zhao Y, Gu D. Age and sex differences in the association between access to medical care and health outcomes among older Chinese. BMC Health Serv Res. 2018;18(1):1004.

Bale TL, Epperson CN. Sex as a Biological Variable: Who, What, When, Why, and How. Neuropsychopharmacology. 2017;42(2):386–96.

Johnsen TM, Norberg BL, Kristiansen E, Zanaboni P, Austad B, Krogh FH, Getz L. Suitability of Video Consultations During the COVID-19 Pandemic Lockdown: Cross-sectional Survey Among Norwegian General Practitioners. J Med Internet Res. 2021;23(2):e26433.

Bell SA, Krienke L, Brown A, Inloes J, Rettell Z, Wyte-Lake T. Barriers and facilitators to providing home-based care in a pandemic: policy and practice implications. BMC Geriatr. 2022;22(1):234.

Rokstad AMM, Røsvik J, Fossberg M, Eriksen S. The COVID-19 pandemic as experienced by the spouses of home-dwelling people with dementia - a qualitative study. BMC Geriatr. 2021;21(1):583.

Tuijt R, Frost R, Wilcock J, Robinson L, Manthorpe J, Rait G, Walters K. Life under lockdown and social restrictions - the experiences of people living with dementia and their carers during the COVID-19 pandemic in England. BMC Geriatr. 2021;21(1):301.

Morina N, Kip A, Hoppen TH, Priebe S, Meyer T. Potential impact of physical distancing on physical and mental health: a rapid narrative umbrella review of meta-analyses on the link between social connection and health. BMJ Open. 2021;11(3):e042335.

Greenblatt-Kimron L, Shinan-Altman S, Alperin M, Levkovich I. Depression and Medicine Use among Older Adults during the COVID-19 Pandemic: The Role of Psychosocial Resources and COVID-19 Perceived Susceptibility. Int J Environ Res Public Health. 2023;20(4):3398.

Vigezzi GP, Bertuccio P, Amerio A, Bosetti C, Gori D, Cavalieri d’Oro L, Iacoviello L, Stuckler D, Zucchi A, Gallus S, et al. Older Adults’ Access to Care during the COVID-19 Pandemic: Results from the LOckdown and LifeSTyles (LOST) in Lombardia Project. Int J Environ Res Public Health. 2022;19(18):11271.

Helgeland J, Telle KE, Grøsland M, Huseby BM, Håberg S, Lindman ASE. Admissions to Norwegian Hospitals during the COVID-19 Pandemic. Scand J Public Health. 2021;49(7):681–8.

Smith M, Vaughan Sarrazin M, Wang X, Nordby P, Yu M, DeLonay AJ, Jaffery J. Risk from delayed or missed care and non-COVID-19 outcomes for older patients with chronic conditions during the pandemic. J Am Geriatr Soc. 2022;70(5):1314–24.

World Health Organization. Third round of the global pulse survey on continuity of essential health services during the COVID-19 pandemic: November–December 2021. In. Geneva: World Health Organization; 2022.

Norwegian Institute of Public Health: Influensasesongen i Norge 2019–2020 [Influenza season in Norway 2019–2020] [ https://www.fhi.no/publ/2020/influensasesongen-i-norge-2019-2020/ ]. Accessed 22 June 2023.

Norwegian Institute of Public Health: Influensasesongen i Norge 2021–2022 [Influenza season in Norway 2021–2022] [ https://www.fhi.no/publ/2022/influensasesongen-i-norge-2021-2022/ ]. Accessed 22 June 2023.

Oh KB, Doherty TM, Vetter V, Bonanni P. Lifting non-pharmaceutical interventions following the COVID-19 pandemic - the quiet before the storm? Expert Rev Vaccines. 2022;21(11):1541–53.

Greig F, Perera G, Tsamakis K, Stewart R, Velayudhan L, Mueller C. Loneliness in older adult mental health services during the COVID-19 pandemic and before: Associations with disability, functioning and pharmacotherapy. Int J Geriatr Psychiatry. 2021;37(1):10.

PubMed Central   Google Scholar  

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Acknowledgements

HUNT is a collaborative project between the HUNT Research Centre at the Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, the Trøndelag County Council, the Central Norway Regional Health Authority and the Norwegian Institute of Public Health. We would like to thank everyone who participated in HUNT 70+ for their valuable contributions to this research.

This study was supported by the Norwegian Health Association (grant no. 22687).

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The Norwegian National Centre for Ageing and Health (Ageing and Health), Vestfold Hospital Trust, Tønsberg, Norway

Tanja Louise Ibsen, Bjørn Heine Strand, Sverre Bergh, Anne Marie Mork Rokstad & Geir Selbæk

Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway

Bjørn Heine Strand

Department of Physical Health and Ageing, Norwegian Institute of Public Health, Oslo, Norway

Research Centre for Age-Related Functional Decline and Disease (AFS), Innlandet Hospital Trust, Ottestad, Norway

Sverre Bergh

Division of Psychiatry, University College London, London, UK

Gill Livingston

Camden and Islington NHS Foundation Trust, London, UK

Health Services Research Unit, Akershus University Hospital, Oslo, Norway

Hilde Lurås

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Centre for Research On Pandemics & Society (PANSOC), at Oslo Metropolitan University, Oslo, Norway

Svenn-Erik Mamelund

Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

Richard Oude Voshaar

Faculty of Health Sciences and Social Care, Molde University College, Molde, Norway

Anne Marie Mork Rokstad

Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Trondheim, Norway

Pernille Thingstad

Department of Health and Social Services, Trondheim Municipality, Trondheim, Norway

Department of Primary and Community Care, Research Institute for Medical Innovation, Radboudumc Alzheimer Center, Radboud University Medical Center, Nijmegen, Netherlands

Debby Gerritsen

Geir Selbæk

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GS led the study project and is responsible for the concept and design of the study, together with BHS, SB and TLI. BHS was a major contributor in the analysis prosses together with TLI. TLI, BHS, SB, GL, HL, SEM, ROV, AMMR, PT og GS contributed to interpreting the data. TLI drafted the paper, with substantially contributions from all the authors in revising the drafted work. DG made significant contributions on the revised version after peer review. All authors read and approved the final manuscript.

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This study was approved by the Regional Committee for Medical and Health Research Ethics of Norway (REK Southeast B 182575). All methods were carried out in accordance with REK’s guidelines which correspond to the Declaration of Helsinki. The present study is part of a larger project registered at ClinicalTrials.gov (identification number: NCT 04792086). Informed written consent was obtained from all participants in the HUNT4 70 + study. Participants with reduced capacity to consent were included if they had a next of kin who consented on their behalf. In the consent form, it was thoroughly described that collected data can be linked to other registers in order to carry out approved research projects, as has been done in the present project.

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Ibsen, T.L., Strand, B.H., Bergh, S. et al. A longitudinal cohort study on the use of health and care services by older adults living at home with/without dementia before and during the COVID-19 pandemic: the HUNT study. BMC Health Serv Res 24 , 485 (2024). https://doi.org/10.1186/s12913-024-10846-y

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Publisher Correction to: Exploring patient and caregiver perceptions of the meaning of the patient partner role: a qualitative study

• Anna Maria Chudyk 1 ,
• Roger Stoddard 2 ,
• Nicola McCleary 3 , 4 ,
• Todd A. Duhamel 5 , 6 ,
• Carolyn Shimmin 7 ,
• Serena Hickes 8 ,
• Pan-Canadian group of patient and public advisors &
• Annette S. H. Schultz 9  

Research Involvement and Engagement volume  10 , Article number:  40 ( 2024 ) Cite this article

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The Original Article was published on 28 November 2023

Publisher Correction to : Res Involv Engagem 9, 106 (2023).

https://doi.org/10.1186/s40900-023-00511-9

Following publication of the original article [ 1 ], the authors identified an error in the order of the authors since Annette S. H. Schultz should be indicated as the last author instead of the Pan-Canadian group of patient and public advisors. The publisher apologises to the authors and readers for the inconvenience caused by this mistake.

The incorrect author list reads:

Anna Maria Chudyk1*, Roger Stoddard2, Nicola McCleary3,4, Todd A. Duhamel5,6, Carolyn Shimmin7,

Serena Hickes8, Annette S. H. Schultz9 and Pan-Canadian group of patient and public advisors

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Chudyk AM, Stoddard R, McCleary N, et al. Exploring patient and caregiver perceptions of the meaning of the patient partner role: a qualitative study. Res Involv Engagem. 2023;9:106. https://doi.org/10.1186/s40900-023-00511-9 .

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Educational damage caused by the pandemic will mean poorer GCSE results for pupils well into the 2030s

Without a raft of equalising policies, the damaging legacy from COVID-19 school closures will be felt by generations of pupils.

The educational damage wrought by the COVID-19 pandemic will impact on children well into the 2030s, with generations of pupils set for the biggest declines in GCSE results for decades.

These are the devastating conclusions of a major new study from LSE, the University of Exeter and the University of Strathclyde. The report predicts that less than four in ten pupils in England in 2030 will achieve a grade 5 or above in English and Mathematics GCSEs – lower than the 45.3 per cent of pupils who achieved this benchmark in 2022/23.

The research, funded by the Nuffield Foundation, is the first to chart how school closures during COVID-19 hindered children’s socio-emotional and cognitive skills at age 5, 11, and 14, and predict how these will impact on future GCSE prospects and later life outcomes.

Socio-emotional skills include the ability to engage in positive social interactions, regulate emotions and maintain attention. Cognitive skills are measured by how well children perform in academic tests, reflecting maths, reading and writing skills.

The research finds that socio-emotional skills are just as important as cognitive skills for young people’s GCSE results. For example, 20 per cent of the best performing pupils in cognitive tests at age 14 but who had average socio-emotional skills fail to go on to attain five good GCSEs including English and Maths. Teenagers with strong socio-emotional skills were much more likely to achieve basic GCSEs.

A gender divide in the importance of different skills emerges in the teenage years. For boys, cognitive skills at age 14 are twice as important as socio-emotional skills in determining future GCSE prospects; for girls the opposite is true, with socio-emotional skills 50 per cent more impactful than cognitive skills.

The analysis uses the latest econometric techniques to develop a model of skill formation, based on just under 19,000 pupils in the Millennium Cohort Study. This was applied to later pupil cohorts to predict how GCSE results will be impacted by disruption from school closures during the pandemic.

Alongside an overall fall in GCSE results, the model points to a significant widening in socio-economic inequalities in GCSE results. The researchers use these results to estimate that the UK’s relative income mobility levels will decline by 12-15 per cent for generations of pupils leaving school over the next decade, a significant drop by international standards.

An international review as part of the work concludes that COVID-19 amplified long-term persistent education gaps across a range of OECD countries including the UK. Compared with most other nations, England’s pandemic response was heavily focused on academic catch-up with less emphasis on socio-emotional skills, extracurricular support, and wellbeing.

The report “A generation at risk: Rebalancing education in the post-pandemic era” was produced by Lee Elliot Major, Professor of Social Mobility at the University of Exeter; Andy Eyles; Professor Steve Machin from the Centre for Economic Performance (CEP) at the London School of Economics; and Esme Lillywhite from the University of Strathclyde. It proposes several low-cost policies with the potential to improve children’s outcomes, including:

• A national programme of trained undergraduate student tutors helping to boost the foundational skills of pupils, and enabling undergraduates to consider a career in teaching.
• Rebalancing Ofsted inspections to explicitly focus on how schools are performing for pupils from under-resourced backgrounds and credit schools excelling when serving under-resourced communities.
• Rebalancing the school calendar to improve teacher wellbeing, prevent holiday hunger, improve pupil prospects and help parents with child-care during the long summer break.

Professor of Social Mobility at the University of Exeter and LSE CEP Associate Professor Elliot Major said : “Without a raft of equalising policies, the damaging legacy from COVID-19 school closures will be felt by generations of pupils well into the next decade. Our review shows that COVID amplified long-term persistent education gaps in England and other countries.

“The policies we propose would rebalance the school system so that it supports all children irrespective of their backgrounds. A particular worry is a group of pupils who are falling significantly behind, likely to be absent from the classroom and to leave school without the basic skills needed to function and flourish in life. The decline in social mobility levels threatens to cast a long shadow over our society.”

LSE CEP Associate Andy Eyles added : “To our knowledge, this is the first time this type of analysis has been used in this way to assess the consequences of the pandemic in England. Our results suggest that to improve child outcomes, much greater emphasis is needed in schools on activities that improve both socio-emotional and cognitive skills.”

Esme Lillywhite from the University of Strathclyde and a research assistant at LSE CEP said: “Compared with most other nations, England’s pandemic response was heavily focused on academic catch-up with less emphasis on socio-emotional skills, extracurricular support, and wellbeing. Much more could be gained by closer international collaboration to learn what approaches have been promising elsewhere.”

Dr Emily Tanner, Programme Head at the Nuffield Foundation said : "The mounting evidence on the long-term impact of learning loss on young people's development shows how important it is for students to develop socio-emotional skills alongside academic learning. The insights from this report on timing and gender provide a useful basis for targeting effective interventions."

Behind the article

The Nuffield Foundation is an independent charitable trust with a mission to advance social well-being. It funds research that informs social policy, primarily in Education, Welfare, and Justice. The Nuffield Foundation is the founder and co-funder of the Nuffield Council on Bioethics, the Ada Lovelace Institute and the Nuffield Family Justice Observatory. The Foundation has funded this project, but the views expressed are those of the authors and not necessarily the Foundation.

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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Qualitative study.

Steven Tenny ; Janelle M. Brannan ; Grace D. Brannan .

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Last Update: September 18, 2022 .

• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. [2] Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” [5] As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. [5] At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. [2] Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”. [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. [4] It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. [2] It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. [6] Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. [2] For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.
• Criterion sampling-selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling-selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research. [13]

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or in combination with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation to not only help generate hypotheses which can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are.  Qualitative research provides researchers with a way to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many different ways, including the criteria for evaluating them. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. The correlating concepts in qualitative research are credibility, transferability, dependability, and confirmability. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept is on the left, and the qualitative concept is on the right:

• Internal validity--- Credibility
• External validity---Transferability
• Reliability---Dependability
• Objectivity---Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid so should qualitative researchers ensure that their work has credibility.  

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple methods of data collection to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable by also interviewing the magician, back-stage hand, and the person who "vanished." In qualitative research, triangulation can include using telephone surveys, in-person surveys, focus groups, and interviews as well as surveying an adequate cross-section of the target demographic.
• Peer examination: Results can be reviewed by a peer to ensure the data is consistent with the findings.

‘Thick’ or ‘rich’ description can be used to evaluate the transferability of qualitative research whereas using an indicator such as an audit trail might help with evaluating the dependability and confirmability.

• Thick or rich description is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was carried out. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data themselves, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original records of information should also be kept (e.g., surveys, notes, recordings).

One issue of concern that qualitative researchers should take into consideration is observation bias. Here are a few examples:

• Hawthorne effect: The Hawthorne effect is the change in participant behavior when they know they are being observed. If a researcher was wanting to identify factors that contribute to employee theft and tells the employees they are going to watch them to see what factors affect employee theft, one would suspect employee behavior would change when they know they are being watched.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens in an unconscious manner for the participant so it is important to eliminate or limit transmitting the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in artificial scenarios and/or with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative research by itself or combined with quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research does not exist as an island apart from quantitative research, but as an integral part of research methods to be used for the understanding of the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is important for all members of the health care team as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research.  Much of the qualitative research data acquisition is completed by numerous team members including social works, scientists, nurses, etc.  Within each area of the medical field, there is copious ongoing qualitative research including physician-patient interactions, nursing-patient interactions, patient-environment interactions, health care team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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