limitations in the research

How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

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The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. Study limitations are the constraints placed on the ability to generalize from the results, to further describe applications to practice, and/or related to the utility of findings that are the result of the ways in which you initially chose to design the study or the method used to establish internal and external validity or the result of unanticipated challenges that emerged during the study.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Theofanidis, Dimitrios and Antigoni Fountouki. "Limitations and Delimitations in the Research Process." Perioperative Nursing 7 (September-December 2018): 155-163. .

Importance of...

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and have your grade lowered because you appeared to have ignored them or didn't realize they existed.

Keep in mind that acknowledgment of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgment of a study's limitations also provides you with opportunities to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and discuss how they possibly impacted your results. Note that descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is generally less relevant in qualitative research if explained in the context of the research problem.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but provide cogent reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe a need for future research based on designing a different method for gathering data.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian! In cases when a librarian has confirmed that there is little or no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design ]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to the accuracy of what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency, but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, data, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this needs to be described. Also, include an explanation why being denied or limited access did not prevent you from following through on your study.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, event, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. NOTE :   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias. For example, if a previous study only used boys to examine how music education supports effective math skills, describe how your research expands the study to include girls.
• Fluency in a language -- if your research focuses , for example, on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic or to speak with these students in their primary language. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods. Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings!

After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitations of your study. Inflating the importance of your study's findings could be perceived by your readers as an attempt hide its flaws or encourage a biased interpretation of the results. A small measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated. Or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may very well be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Lewis, George H. and Jonathan F. Lewis. “The Dog in the Night-Time: Negative Evidence in Social Research.” The British Journal of Sociology 31 (December 1980): 544-558.

Yet Another Writing Tip

Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgment about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Boddy, Clive Roland. "Sample Size for Qualitative Research." Qualitative Market Research: An International Journal 19 (2016): 426-432; Huberman, A. Michael and Matthew B. Miles. "Data Management and Analysis Methods." In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444; Blaikie, Norman. "Confounding Issues Related to Determining Sample Size in Qualitative Research." International Journal of Social Research Methodology 21 (2018): 635-641; Oppong, Steward Harrison. "The Problem of Sampling in qualitative Research." Asian Journal of Management Sciences and Education 2 (2013): 202-210.

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What are the limitations in research and how to write them?

Learn about the potential limitations in research and how to appropriately address them in order to deliver honest and ethical research.

It is fairly uncommon for researchers to stumble into the term research limitations when working on their research paper. Limitations in research can arise owing to constraints on design, methods, materials, and so on, and these aspects, unfortunately, may have an influence on your subject’s findings.

In this Mind The Graph’s article, we’ll discuss some recommendations for writing limitations in research , provide examples of various common types of limitations, and suggest how to properly present this information.

What are the limitations in research?

The limitations in research are the constraints in design, methods or even researchers’ limitations that affect and influence the interpretation of your research’s ultimate findings. These are limitations on the generalization and usability of findings that emerge from the design of the research and/or the method employed to ensure validity both internally and externally. 

Researchers are usually cautious to acknowledge the limitations of their research in their publications for fear of undermining the research’s scientific validity. No research is faultless or covers every possible angle. As a result, addressing the constraints of your research exhibits honesty and integrity .

Why should include limitations of research in my paper?

Though limitations tackle potential flaws in research, commenting on them at the conclusion of your paper, by demonstrating that you are aware of these limitations and explaining how they impact the conclusions that may be taken from the research, improves your research by disclosing any issues before other researchers or reviewers do . 

Additionally, emphasizing research constraints implies that you have thoroughly investigated the ramifications of research shortcomings and have a thorough understanding of your research problem. 

Limits exist in any research; being honest about them and explaining them would impress researchers and reviewers more than disregarding them. 

Remember that acknowledging a research’s shortcomings offers a chance to provide ideas for future research, but be careful to describe how your study may help to concentrate on these outstanding problems.

Possible limitations examples

Here are some limitations connected to methodology and the research procedure that you may need to explain and discuss in connection to your findings.

Methodological limitations

Sample size.

The number of units of analysis used in your study is determined by the sort of research issue being investigated. It is important to note that if your sample is too small, finding significant connections in the data will be challenging, as statistical tests typically require a larger sample size to ensure a fair representation and this can be limiting. 

Lack of available or reliable data

A lack of data or trustworthy data will almost certainly necessitate limiting the scope of your research or the size of your sample, or it can be a substantial impediment to identifying a pattern and a relevant connection.

Lack of prior research on the subject

Citing previous research papers forms the basis of your literature review and aids in comprehending the research subject you are researching. Yet there may be little if any, past research on your issue.

The measure used to collect data

After finishing your analysis of the findings, you realize that the method you used to collect data limited your capacity to undertake a comprehensive evaluation of the findings. Recognize the flaw by mentioning that future researchers should change the specific approach for data collection.

Issues with research samples and selection

Sampling inaccuracies arise when a probability sampling method is employed to choose a sample, but that sample does not accurately represent the overall population or the relevant group. As a result, your study suffers from “sampling bias” or “selection bias.”

Limitations of the research

When your research requires polling certain persons or a specific group, you may have encountered the issue of limited access to these interviewees. Because of the limited access, you may need to reorganize or rearrange your research. In this scenario, explain why access is restricted and ensure that your findings are still trustworthy and valid despite the constraint.

Time constraints

Practical difficulties may limit the amount of time available to explore a research issue and monitor changes as they occur. If time restrictions have any detrimental influence on your research, recognize this impact by expressing the necessity for a future investigation.

Due to their cultural origins or opinions on observed events, researchers may carry biased opinions, which can influence the credibility of a research. Furthermore, researchers may exhibit biases toward data and conclusions that only support their hypotheses or arguments.

The structure of the limitations section 

The limitations of your research are usually stated at the beginning of the discussion section of your paper so that the reader is aware of and comprehends the limitations prior to actually reading the rest of your findings, or they are stated at the end of the discussion section as an acknowledgment of the need for further research.

The ideal way is to divide your limitations section into three steps: 

1. Identify the research constraints; 

2. Describe in great detail how they affect your research; 

3. Mention the opportunity for future investigations and give possibilities. 

By following this method while addressing the constraints of your research, you will be able to effectively highlight your research’s shortcomings without jeopardizing the quality and integrity of your research.

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21 Research Limitations Examples

Research limitations refer to the potential weaknesses inherent in a study. All studies have limitations of some sort, meaning declaring limitations doesn’t necessarily need to be a bad thing, so long as your declaration of limitations is well thought-out and explained.

Rarely is a study perfect. Researchers have to make trade-offs when developing their studies, which are often based upon practical considerations such as time and monetary constraints, weighing the breadth of participants against the depth of insight, and choosing one methodology or another.

In research, studies can have limitations such as limited scope, researcher subjectivity, and lack of available research tools.

Acknowledging the limitations of your study should be seen as a strength. It demonstrates your willingness for transparency, humility, and submission to the scientific method and can bolster the integrity of the study. It can also inform future research direction.

Typically, scholars will explore the limitations of their study in either their methodology section, their conclusion section, or both.

Research Limitations Examples

Qualitative and quantitative research offer different perspectives and methods in exploring phenomena, each with its own strengths and limitations. So, I’ve split the limitations examples sections into qualitative and quantitative below.

Qualitative Research Limitations

Qualitative research seeks to understand phenomena in-depth and in context. It focuses on the ‘why’ and ‘how’ questions.

It’s often used to explore new or complex issues, and it provides rich, detailed insights into participants’ experiences, behaviors, and attitudes. However, these strengths also create certain limitations, as explained below.

1. Subjectivity

Qualitative research often requires the researcher to interpret subjective data. One researcher may examine a text and identify different themes or concepts as more dominant than others.

Close qualitative readings of texts are necessarily subjective – and while this may be a limitation, qualitative researchers argue this is the best way to deeply understand everything in context.

Suggested Solution and Response: To minimize subjectivity bias, you could consider cross-checking your own readings of themes and data against other scholars’ readings and interpretations. This may involve giving the raw data to a supervisor or colleague and asking them to code the data separately, then coming together to compare and contrast results.

2. Researcher Bias

The concept of researcher bias is related to, but slightly different from, subjectivity.

Researcher bias refers to the perspectives and opinions you bring with you when doing your research.

For example, a researcher who is explicitly of a certain philosophical or political persuasion may bring that persuasion to bear when interpreting data.

In many scholarly traditions, we will attempt to minimize researcher bias through the utilization of clear procedures that are set out in advance or through the use of statistical analysis tools.

However, in other traditions, such as in postmodern feminist research , declaration of bias is expected, and acknowledgment of bias is seen as a positive because, in those traditions, it is believed that bias cannot be eliminated from research, so instead, it is a matter of integrity to present it upfront.

Suggested Solution and Response: Acknowledge the potential for researcher bias and, depending on your theoretical framework , accept this, or identify procedures you have taken to seek a closer approximation to objectivity in your coding and analysis.

3. Generalizability

If you’re struggling to find a limitation to discuss in your own qualitative research study, then this one is for you: all qualitative research, of all persuasions and perspectives, cannot be generalized.

This is a core feature that sets qualitative data and quantitative data apart.

The point of qualitative data is to select case studies and similarly small corpora and dig deep through in-depth analysis and thick description of data.

Often, this will also mean that you have a non-randomized sample size.

While this is a positive – you’re going to get some really deep, contextualized, interesting insights – it also means that the findings may not be generalizable to a larger population that may not be representative of the small group of people in your study.

Suggested Solution and Response: Suggest future studies that take a quantitative approach to the question.

4. The Hawthorne Effect

The Hawthorne effect refers to the phenomenon where research participants change their ‘observed behavior’ when they’re aware that they are being observed.

This effect was first identified by Elton Mayo who conducted studies of the effects of various factors ton workers’ productivity. He noticed that no matter what he did – turning up the lights, turning down the lights, etc. – there was an increase in worker outputs compared to prior to the study taking place.

Mayo realized that the mere act of observing the workers made them work harder – his observation was what was changing behavior.

So, if you’re looking for a potential limitation to name for your observational research study , highlight the possible impact of the Hawthorne effect (and how you could reduce your footprint or visibility in order to decrease its likelihood).

Suggested Solution and Response: Highlight ways you have attempted to reduce your footprint while in the field, and guarantee anonymity to your research participants.

5. Replicability

Quantitative research has a great benefit in that the studies are replicable – a researcher can get a similar sample size, duplicate the variables, and re-test a study. But you can’t do that in qualitative research.

Qualitative research relies heavily on context – a specific case study or specific variables that make a certain instance worthy of analysis. As a result, it’s often difficult to re-enter the same setting with the same variables and repeat the study.

Furthermore, the individual researcher’s interpretation is more influential in qualitative research, meaning even if a new researcher enters an environment and makes observations, their observations may be different because subjectivity comes into play much more. This doesn’t make the research bad necessarily (great insights can be made in qualitative research), but it certainly does demonstrate a weakness of qualitative research.

6. Limited Scope

“Limited scope” is perhaps one of the most common limitations listed by researchers – and while this is often a catch-all way of saying, “well, I’m not studying that in this study”, it’s also a valid point.

No study can explore everything related to a topic. At some point, we have to make decisions about what’s included in the study and what is excluded from the study.

So, you could say that a limitation of your study is that it doesn’t look at an extra variable or concept that’s certainly worthy of study but will have to be explored in your next project because this project has a clearly and narrowly defined goal.

Suggested Solution and Response: Be clear about what’s in and out of the study when writing your research question.

7. Time Constraints

This is also a catch-all claim you can make about your research project: that you would have included more people in the study, looked at more variables, and so on. But you’ve got to submit this thing by the end of next semester! You’ve got time constraints.

And time constraints are a recognized reality in all research.

But this means you’ll need to explain how time has limited your decisions. As with “limited scope”, this may mean that you had to study a smaller group of subjects, limit the amount of time you spent in the field, and so forth.

Suggested Solution and Response: Suggest future studies that will build on your current work, possibly as a PhD project.

8. Resource Intensiveness

Qualitative research can be expensive due to the cost of transcription, the involvement of trained researchers, and potential travel for interviews or observations.

So, resource intensiveness is similar to the time constraints concept. If you don’t have the funds, you have to make decisions about which tools to use, which statistical software to employ, and how many research assistants you can dedicate to the study.

Suggested Solution and Response: Suggest future studies that will gain more funding on the back of this ‘ exploratory study ‘.

9. Coding Difficulties

Data analysis in qualitative research often involves coding, which can be subjective and complex, especially when dealing with ambiguous or contradicting data.

After naming this as a limitation in your research, it’s important to explain how you’ve attempted to address this. Some ways to ‘limit the limitation’ include:

• Triangulation: Have 2 other researchers code the data as well and cross-check your results with theirs to identify outliers that may need to be re-examined, debated with the other researchers, or removed altogether.
• Procedure: Use a clear coding procedure to demonstrate reliability in your coding process. I personally use the thematic network analysis method outlined in this academic article by Attride-Stirling (2001).

Suggested Solution and Response: Triangulate your coding findings with colleagues, and follow a thematic network analysis procedure.

10. Risk of Non-Responsiveness

There is always a risk in research that research participants will be unwilling or uncomfortable sharing their genuine thoughts and feelings in the study.

This is particularly true when you’re conducting research on sensitive topics, politicized topics, or topics where the participant is expressing vulnerability .

This is similar to the Hawthorne effect (aka participant bias), where participants change their behaviors in your presence; but it goes a step further, where participants actively hide their true thoughts and feelings from you.

Suggested Solution and Response: One way to manage this is to try to include a wider group of people with the expectation that there will be non-responsiveness from some participants.

11. Risk of Attrition

Attrition refers to the process of losing research participants throughout the study.

This occurs most commonly in longitudinal studies , where a researcher must return to conduct their analysis over spaced periods of time, often over a period of years.

Things happen to people over time – they move overseas, their life experiences change, they get sick, change their minds, and even die. The more time that passes, the greater the risk of attrition.

Suggested Solution and Response: One way to manage this is to try to include a wider group of people with the expectation that there will be attrition over time.

12. Difficulty in Maintaining Confidentiality and Anonymity

Given the detailed nature of qualitative data , ensuring participant anonymity can be challenging.

If you have a sensitive topic in a specific case study, even anonymizing research participants sometimes isn’t enough. People might be able to induce who you’re talking about.

Sometimes, this will mean you have to exclude some interesting data that you collected from your final report. Confidentiality and anonymity come before your findings in research ethics – and this is a necessary limiting factor.

Suggested Solution and Response: Highlight the efforts you have taken to anonymize data, and accept that confidentiality and accountability place extremely important constraints on academic research.

13. Difficulty in Finding Research Participants

A study that looks at a very specific phenomenon or even a specific set of cases within a phenomenon means that the pool of potential research participants can be very low.

Compile on top of this the fact that many people you approach may choose not to participate, and you could end up with a very small corpus of subjects to explore. This may limit your ability to make complete findings, even in a quantitative sense.

You may need to therefore limit your research question and objectives to something more realistic.

Suggested Solution and Response: Highlight that this is going to limit the study’s generalizability significantly.

14. Ethical Limitations

Ethical limitations refer to the things you cannot do based on ethical concerns identified either by yourself or your institution’s ethics review board.

This might include threats to the physical or psychological well-being of your research subjects, the potential of releasing data that could harm a person’s reputation, and so on.

Furthermore, even if your study follows all expected standards of ethics, you still, as an ethical researcher, need to allow a research participant to pull out at any point in time, after which you cannot use their data, which demonstrates an overlap between ethical constraints and participant attrition.

Suggested Solution and Response: Highlight that these ethical limitations are inevitable but important to sustain the integrity of the research.

For more on Qualitative Research, Explore my Qualitative Research Guide

Quantitative Research Limitations

Quantitative research focuses on quantifiable data and statistical, mathematical, or computational techniques. It’s often used to test hypotheses, assess relationships and causality, and generalize findings across larger populations.

Quantitative research is widely respected for its ability to provide reliable, measurable, and generalizable data (if done well!). Its structured methodology has strengths over qualitative research, such as the fact it allows for replication of the study, which underpins the validity of the research.

However, this approach is not without it limitations, explained below.

1. Over-Simplification

Quantitative research is powerful because it allows you to measure and analyze data in a systematic and standardized way. However, one of its limitations is that it can sometimes simplify complex phenomena or situations.

In other words, it might miss the subtleties or nuances of the research subject.

For example, if you’re studying why people choose a particular diet, a quantitative study might identify factors like age, income, or health status. But it might miss other aspects, such as cultural influences or personal beliefs, that can also significantly impact dietary choices.

When writing about this limitation, you can say that your quantitative approach, while providing precise measurements and comparisons, may not capture the full complexity of your subjects of study.

Suggested Solution and Response: Suggest a follow-up case study using the same research participants in order to gain additional context and depth.

2. Lack of Context

Another potential issue with quantitative research is that it often focuses on numbers and statistics at the expense of context or qualitative information.

Let’s say you’re studying the effect of classroom size on student performance. You might find that students in smaller classes generally perform better. However, this doesn’t take into account other variables, like teaching style , student motivation, or family support.

When describing this limitation, you might say, “Although our research provides important insights into the relationship between class size and student performance, it does not incorporate the impact of other potentially influential variables. Future research could benefit from a mixed-methods approach that combines quantitative analysis with qualitative insights.”

3. Applicability to Real-World Settings

Oftentimes, experimental research takes place in controlled environments to limit the influence of outside factors.

This control is great for isolation and understanding the specific phenomenon but can limit the applicability or “external validity” of the research to real-world settings.

For example, if you conduct a lab experiment to see how sleep deprivation impacts cognitive performance, the sterile, controlled lab environment might not reflect real-world conditions where people are dealing with multiple stressors.

Therefore, when explaining the limitations of your quantitative study in your methodology section, you could state:

“While our findings provide valuable information about [topic], the controlled conditions of the experiment may not accurately represent real-world scenarios where extraneous variables will exist. As such, the direct applicability of our results to broader contexts may be limited.”

Suggested Solution and Response: Suggest future studies that will engage in real-world observational research, such as ethnographic research.

4. Limited Flexibility

Once a quantitative study is underway, it can be challenging to make changes to it. This is because, unlike in grounded research, you’re putting in place your study in advance, and you can’t make changes part-way through.

Your study design, data collection methods, and analysis techniques need to be decided upon before you start collecting data.

For example, if you are conducting a survey on the impact of social media on teenage mental health, and halfway through, you realize that you should have included a question about their screen time, it’s generally too late to add it.

When discussing this limitation, you could write something like, “The structured nature of our quantitative approach allows for consistent data collection and analysis but also limits our flexibility to adapt and modify the research process in response to emerging insights and ideas.”

Suggested Solution and Response: Suggest future studies that will use mixed-methods or qualitative research methods to gain additional depth of insight.

5. Risk of Survey Error

Surveys are a common tool in quantitative research, but they carry risks of error.

There can be measurement errors (if a question is misunderstood), coverage errors (if some groups aren’t adequately represented), non-response errors (if certain people don’t respond), and sampling errors (if your sample isn’t representative of the population).

For instance, if you’re surveying college students about their study habits , but only daytime students respond because you conduct the survey during the day, your results will be skewed.

In discussing this limitation, you might say, “Despite our best efforts to develop a comprehensive survey, there remains a risk of survey error, including measurement, coverage, non-response, and sampling errors. These could potentially impact the reliability and generalizability of our findings.”

Suggested Solution and Response: Suggest future studies that will use other survey tools to compare and contrast results.

6. Limited Ability to Probe Answers

With quantitative research, you typically can’t ask follow-up questions or delve deeper into participants’ responses like you could in a qualitative interview.

For instance, imagine you are surveying 500 students about study habits in a questionnaire. A respondent might indicate that they study for two hours each night. You might want to follow up by asking them to elaborate on what those study sessions involve or how effective they feel their habits are.

However, quantitative research generally disallows this in the way a qualitative semi-structured interview could.

When discussing this limitation, you might write, “Given the structured nature of our survey, our ability to probe deeper into individual responses is limited. This means we may not fully understand the context or reasoning behind the responses, potentially limiting the depth of our findings.”

Suggested Solution and Response: Suggest future studies that engage in mixed-method or qualitative methodologies to address the issue from another angle.

7. Reliance on Instruments for Data Collection

In quantitative research, the collection of data heavily relies on instruments like questionnaires, surveys, or machines.

The limitation here is that the data you get is only as good as the instrument you’re using. If the instrument isn’t designed or calibrated well, your data can be flawed.

For instance, if you’re using a questionnaire to study customer satisfaction and the questions are vague, confusing, or biased, the responses may not accurately reflect the customers’ true feelings.

When discussing this limitation, you could say, “Our study depends on the use of questionnaires for data collection. Although we have put significant effort into designing and testing the instrument, it’s possible that inaccuracies or misunderstandings could potentially affect the validity of the data collected.”

Suggested Solution and Response: Suggest future studies that will use different instruments but examine the same variables to triangulate results.

8. Time and Resource Constraints (Specific to Quantitative Research)

Quantitative research can be time-consuming and resource-intensive, especially when dealing with large samples.

It often involves systematic sampling, rigorous design, and sometimes complex statistical analysis.

If resources and time are limited, it can restrict the scale of your research, the techniques you can employ, or the extent of your data analysis.

For example, you may want to conduct a nationwide survey on public opinion about a certain policy. However, due to limited resources, you might only be able to survey people in one city.

When writing about this limitation, you could say, “Given the scope of our research and the resources available, we are limited to conducting our survey within one city, which may not fully represent the nationwide public opinion. Hence, the generalizability of the results may be limited.”

Suggested Solution and Response: Suggest future studies that will have more funding or longer timeframes.

How to Discuss Your Research Limitations

1. in your research proposal and methodology section.

In the research proposal, which will become the methodology section of your dissertation, I would recommend taking the four following steps, in order:

• Be Explicit about your Scope – If you limit the scope of your study in your research question, aims, and objectives, then you can set yourself up well later in the methodology to say that certain questions are “outside the scope of the study.” For example, you may identify the fact that the study doesn’t address a certain variable, but you can follow up by stating that the research question is specifically focused on the variable that you are examining, so this limitation would need to be looked at in future studies.
• Acknowledge the Limitation – Acknowledging the limitations of your study demonstrates reflexivity and humility and can make your research more reliable and valid. It also pre-empts questions the people grading your paper may have, so instead of them down-grading you for your limitations; they will congratulate you on explaining the limitations and how you have addressed them!
• Explain your Decisions – You may have chosen your approach (despite its limitations) for a very specific reason. This might be because your approach remains, on balance, the best one to answer your research question. Or, it might be because of time and monetary constraints that are outside of your control.
• Highlight the Strengths of your Approach – Conclude your limitations section by strongly demonstrating that, despite limitations, you’ve worked hard to minimize the effects of the limitations and that you have chosen your specific approach and methodology because it’s also got some terrific strengths. Name the strengths.

Overall, you’ll want to acknowledge your own limitations but also explain that the limitations don’t detract from the value of your study as it stands.

2. In the Conclusion Section or Chapter

In the conclusion of your study, it is generally expected that you return to a discussion of the study’s limitations. Here, I recommend the following steps:

• Acknowledge issues faced – After completing your study, you will be increasingly aware of issues you may have faced that, if you re-did the study, you may have addressed earlier in order to avoid those issues. Acknowledge these issues as limitations, and frame them as recommendations for subsequent studies.
• Suggest further research – Scholarly research aims to fill gaps in the current literature and knowledge. Having established your expertise through your study, suggest lines of inquiry for future researchers. You could state that your study had certain limitations, and “future studies” can address those limitations.
• Suggest a mixed methods approach – Qualitative and quantitative research each have pros and cons. So, note those ‘cons’ of your approach, then say the next study should approach the topic using the opposite methodology or could approach it using a mixed-methods approach that could achieve the benefits of quantitative studies with the nuanced insights of associated qualitative insights as part of an in-study case-study.

Overall, be clear about both your limitations and how those limitations can inform future studies.

In sum, each type of research method has its own strengths and limitations. Qualitative research excels in exploring depth, context, and complexity, while quantitative research excels in examining breadth, generalizability, and quantifiable measures. Despite their individual limitations, each method contributes unique and valuable insights, and researchers often use them together to provide a more comprehensive understanding of the phenomenon being studied.

Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research , 1 (3), 385-405. ( Source )

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J., & Williams, R. A. (2021).  SAGE research methods foundations . London: Sage Publications.

Clark, T., Foster, L., Bryman, A., & Sloan, L. (2021).  Bryman’s social research methods . Oxford: Oxford University Press.

Köhler, T., Smith, A., & Bhakoo, V. (2022). Templates in qualitative research methods: Origins, limitations, and new directions.  Organizational Research Methods ,  25 (2), 183-210. ( Source )

Lenger, A. (2019). The rejection of qualitative research methods in economics.  Journal of Economic Issues ,  53 (4), 946-965. ( Source )

Taherdoost, H. (2022). What are different research approaches? Comprehensive review of qualitative, quantitative, and mixed method research, their applications, types, and limitations.  Journal of Management Science & Engineering Research ,  5 (1), 53-63. ( Source )

Walliman, N. (2021).  Research methods: The basics . New York: Routledge.

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How to present limitations in research

Last updated

30 January 2024

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Limitations don’t invalidate or diminish your results, but it’s best to acknowledge them. This will enable you to address any questions your study failed to answer because of them.

In this guide, learn how to recognize, present, and overcome limitations in research.

• What is a research limitation?

Research limitations are weaknesses in your research design or execution that may have impacted outcomes and conclusions. Uncovering limitations doesn’t necessarily indicate poor research design—it just means you encountered challenges you couldn’t have anticipated that limited your research efforts.

Does basic research have limitations?

Basic research aims to provide more information about your research topic. It requires the same standard research methodology and data collection efforts as any other research type, and it can also have limitations.

• Common research limitations

Researchers encounter common limitations when embarking on a study. Limitations can occur in relation to the methods you apply or the research process you design. They could also be connected to you as the researcher.

Methodology limitations

Not having access to data or reliable information can impact the methods used to facilitate your research. A lack of data or reliability may limit the parameters of your study area and the extent of your exploration.

Your sample size may also be affected because you won’t have any direction on how big or small it should be and who or what you should include. Having too few participants won’t adequately represent the population or groups of people needed to draw meaningful conclusions.

Research process limitations

The study’s design can impose constraints on the process. For example, as you’re conducting the research, issues may arise that don’t conform to the data collection methodology you developed. You may not realize until well into the process that you should have incorporated more specific questions or comprehensive experiments to generate the data you need to have confidence in your results.

Constraints on resources can also have an impact. Being limited on participants or participation incentives may limit your sample sizes. Insufficient tools, equipment, and materials to conduct a thorough study may also be a factor.

Common researcher limitations

Here are some of the common researcher limitations you may encounter:

Time: some research areas require multi-year longitudinal approaches, but you might not be able to dedicate that much time. Imagine you want to measure how much memory a person loses as they age. This may involve conducting multiple tests on a sample of participants over 20–30 years, which may be impossible.

Bias: researchers can consciously or unconsciously apply bias to their research. Biases can contribute to relying on research sources and methodologies that will only support your beliefs about the research you’re embarking on. You might also omit relevant issues or participants from the scope of your study because of your biases.

Limited access to data : you may need to pay to access specific databases or journals that would be helpful to your research process. You might also need to gain information from certain people or organizations but have limited access to them. These cases require readjusting your process and explaining why your findings are still reliable.

• Why is it important to identify limitations?

Identifying limitations adds credibility to research and provides a deeper understanding of how you arrived at your conclusions.

Constraints may have prevented you from collecting specific data or information you hoped would prove or disprove your hypothesis or provide a more comprehensive understanding of your research topic.

However, identifying the limitations contributing to your conclusions can inspire further research efforts that help gather more substantial information and data.

• Where to put limitations in a research paper

A research paper is broken up into different sections that appear in the following order:

Introduction

Methodology

The discussion portion of your paper explores your findings and puts them in the context of the overall research. Either place research limitations at the beginning of the discussion section before the analysis of your findings or at the end of the section to indicate that further research needs to be pursued.

What not to include in the limitations section

Evidence that doesn’t support your hypothesis is not a limitation, so you shouldn’t include it in the limitation section. Don’t just list limitations and their degree of severity without further explanation.

• How to present limitations

You’ll want to present the limitations of your study in a way that doesn’t diminish the validity of your research and leave the reader wondering if your results and conclusions have been compromised.

Include only the limitations that directly relate to and impact how you addressed your research questions. Following a specific format enables the reader to develop an understanding of the weaknesses within the context of your findings without doubting the quality and integrity of your research.

Identify the limitations specific to your study

You don’t have to identify every possible limitation that might have occurred during your research process. Only identify those that may have influenced the quality of your findings and your ability to answer your research question.

Explain study limitations in detail

This explanation should be the most significant portion of your limitation section.

Link each limitation with an interpretation and appraisal of their impact on the study. You’ll have to evaluate and explain whether the error, method, or validity issues influenced the study’s outcome and how.

Propose a direction for future studies and present alternatives

In this section, suggest how researchers can avoid the pitfalls you experienced during your research process.

If an issue with methodology was a limitation, propose alternate methods that may help with a smoother and more conclusive research project. Discuss the pros and cons of your alternate recommendation.

Describe steps taken to minimize each limitation

You probably took steps to try to address or mitigate limitations when you noticed them throughout the course of your research project. Describe these steps in the limitation section.

• Limitation example

“Approaches like stem cell transplantation and vaccination in AD [Alzheimer’s disease] work on a cellular or molecular level in the laboratory. However, translation into clinical settings will remain a challenge for the next decade.”

The authors are saying that even though these methods showed promise in helping people with memory loss when conducted in the lab (in other words, using animal studies), more studies are needed. These may be controlled clinical trials, for example. 

However, the short life span of stem cells outside the lab and the vaccination’s severe inflammatory side effects are limitations. Researchers won’t be able to conduct clinical trials until these issues are overcome.

• How to overcome limitations in research

You’ve already started on the road to overcoming limitations in research by acknowledging that they exist. However, you need to ensure readers don’t mistake weaknesses for errors within your research design.

To do this, you’ll need to justify and explain your rationale for the methods, research design, and analysis tools you chose and how you noticed they may have presented limitations.

Your readers need to know that even when limitations presented themselves, you followed best practices and the ethical standards of your field. You didn’t violate any rules and regulations during your research process.

You’ll also want to reinforce the validity of your conclusions and results with multiple sources, methods, and perspectives. This prevents readers from assuming your findings were derived from a single or biased source.

• Learning and improving starts with limitations in research

Dealing with limitations with transparency and integrity helps identify areas for future improvements and developments. It’s a learning process, providing valuable insights into how you can improve methodologies, expand sample sizes, or explore alternate approaches to further support the validity of your findings.

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Writing Limitations of Research Study — 4 Reasons Why It Is Important!

It is not unusual for researchers to come across the term limitations of research during their academic paper writing. More often this is interpreted as something terrible. However, when it comes to research study, limitations can help structure the research study better. Therefore, do not underestimate significance of limitations of research study.

Allow us to take you through the context of how to evaluate the limits of your research and conclude an impactful relevance to your results.

Table of Contents

What Are the Limitations of a Research Study?

Every research has its limit and these limitations arise due to restrictions in methodology or research design.  This could impact your entire research or the research paper you wish to publish. Unfortunately, most researchers choose not to discuss their limitations of research fearing it will affect the value of their article in the eyes of readers.

However, it is very important to discuss your study limitations and show it to your target audience (other researchers, journal editors, peer reviewers etc.). It is very important that you provide an explanation of how your research limitations may affect the conclusions and opinions drawn from your research. Moreover, when as an author you state the limitations of research, it shows that you have investigated all the weaknesses of your study and have a deep understanding of the subject. Being honest could impress your readers and mark your study as a sincere effort in research.

Why and Where Should You Include the Research Limitations?

The main goal of your research is to address your research objectives. Conduct experiments, get results and explain those results, and finally justify your research question . It is best to mention the limitations of research in the discussion paragraph of your research article.

At the very beginning of this paragraph, immediately after highlighting the strengths of the research methodology, you should write down your limitations. You can discuss specific points from your research limitations as suggestions for further research in the conclusion of your thesis.

1. Common Limitations of the Researchers

Limitations that are related to the researcher must be mentioned. This will help you gain transparency with your readers. Furthermore, you could provide suggestions on decreasing these limitations in you and your future studies.

2. Limited Access to Information

Your work may involve some institutions and individuals in research, and sometimes you may have problems accessing these institutions. Therefore, you need to redesign and rewrite your work. You must explain your readers the reason for limited access.

3. Limited Time

All researchers are bound by their deadlines when it comes to completing their studies. Sometimes, time constraints can affect your research negatively. However, the best practice is to acknowledge it and mention a requirement for future study to solve the research problem in a better way.

4. Conflict over Biased Views and Personal Issues

Biased views can affect the research. In fact, researchers end up choosing only those results and data that support their main argument, keeping aside the other loose ends of the research.

Types of Limitations of Research

Before beginning your research study, know that there are certain limitations to what you are testing or possible research results. There are different types that researchers may encounter, and they all have unique characteristics, such as:

1. Research Design Limitations

Certain restrictions on your research or available procedures may affect your final results or research outputs. You may have formulated research goals and objectives too broadly. However, this can help you understand how you can narrow down the formulation of research goals and objectives, thereby increasing the focus of your study.

2. Impact Limitations

Even if your research has excellent statistics and a strong design, it can suffer from the influence of the following factors:

• Presence of increasing findings as researched
• Being population specific
• A strong regional focus.

3. Data or statistical limitations

In some cases, it is impossible to collect sufficient data for research or very difficult to get access to the data. This could lead to incomplete conclusion to your study. Moreover, this insufficiency in data could be the outcome of your study design. The unclear, shabby research outline could produce more problems in interpreting your findings.

How to Correctly Structure Your Research Limitations?

There are strict guidelines for narrowing down research questions, wherein you could justify and explain potential weaknesses of your academic paper. You could go through these basic steps to get a well-structured clarity of research limitations:

• Declare that you wish to identify your limitations of research and explain their importance,
• Provide the necessary depth, explain their nature, and justify your study choices.
• Write how you are suggesting that it is possible to overcome them in the future.

In this section, your readers will see that you are aware of the potential weaknesses in your business, understand them and offer effective solutions, and it will positively strengthen your article as you clarify all limitations of research to your target audience.

Know that you cannot be perfect and there is no individual without flaws. You could use the limitations of research as a great opportunity to take on a new challenge and improve the future of research. In a typical academic paper, research limitations may relate to:

1. Formulating your goals and objectives

If you formulate goals and objectives too broadly, your work will have some shortcomings. In this case, specify effective methods or ways to narrow down the formula of goals and aim to increase your level of study focus.

2. Application of your data collection methods in research

If you do not have experience in primary data collection, there is a risk that there will be flaws in the implementation of your methods. It is necessary to accept this, and learn and educate yourself to understand data collection methods.

3. Sample sizes

This depends on the nature of problem you choose. Sample size is of a greater importance in quantitative studies as opposed to qualitative ones. If your sample size is too small, statistical tests cannot identify significant relationships or connections within a given data set.

You could point out that other researchers should base the same study on a larger sample size to get more accurate results.

4. The absence of previous studies in the field you have chosen

Writing a literature review is an important step in any scientific study because it helps researchers determine the scope of current work in the chosen field. It is a major foundation for any researcher who must use them to achieve a set of specific goals or objectives.

However, if you are focused on the most current and evolving research problem or a very narrow research problem, there may be very little prior research on your topic. For example, if you chose to explore the role of Bitcoin as the currency of the future, you may not find tons of scientific papers addressing the research problem as Bitcoins are only a new phenomenon.

It is important that you learn to identify research limitations examples at each step. Whatever field you choose, feel free to add the shortcoming of your work. This is mainly because you do not have many years of experience writing scientific papers or completing complex work. Therefore, the depth and scope of your discussions may be compromised at different levels compared to academics with a lot of expertise. Include specific points from limitations of research. Use them as suggestions for the future.

Have you ever faced a challenge of writing the limitations of research study in your paper? How did you overcome it? What ways did you follow? Were they beneficial? Let us know in the comments below!

Frequently Asked Questions

Setting limitations in our study helps to clarify the outcomes drawn from our research and enhance understanding of the subject. Moreover, it shows that the author has investigated all the weaknesses in the study.

Scope is the range and limitations of a research project which are set to define the boundaries of a project. Limitations are the impacts on the overall study due to the constraints on the research design.

Limitation in research is an impact of a constraint on the research design in the overall study. They are the flaws or weaknesses in the study, which may influence the outcome of the research.

1. Limitations in research can be written as follows: Formulate your goals and objectives 2. Analyze the chosen data collection method and the sample sizes 3. Identify your limitations of research and explain their importance 4. Provide the necessary depth, explain their nature, and justify your study choices 5. Write how you are suggesting that it is possible to overcome them in the future

Excellent article ,,,it has helped me big

This is very helpful information. It has given me an insight on how to go about my study limitations.

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Home » Delimitations in Research – Types, Examples and Writing Guide

Delimitations in Research – Types, Examples and Writing Guide

Table of Contents

Delimitations

Definition:

Delimitations refer to the specific boundaries or limitations that are set in a research study in order to narrow its scope and focus. Delimitations may be related to a variety of factors, including the population being studied, the geographical location, the time period, the research design , and the methods or tools being used to collect data .

The Importance of Delimitations in Research Studies

Here are some reasons why delimitations are important in research studies:

• Provide focus : Delimitations help researchers focus on a specific area of interest and avoid getting sidetracked by tangential topics. By setting clear boundaries, researchers can concentrate their efforts on the most relevant and significant aspects of the research question.
• Increase validity : Delimitations ensure that the research is more valid by defining the boundaries of the study. When researchers establish clear criteria for inclusion and exclusion, they can better control for extraneous variables that might otherwise confound the results.
• Improve generalizability : Delimitations help researchers determine the extent to which their findings can be generalized to other populations or contexts. By specifying the sample size, geographic region, time frame, or other relevant factors, researchers can provide more accurate estimates of the generalizability of their results.
• Enhance feasibility : Delimitations help researchers identify the resources and time required to complete the study. By setting realistic parameters, researchers can ensure that the study is feasible and can be completed within the available time and resources.
• Clarify scope: Delimitations help readers understand the scope of the research project. By explicitly stating what is included and excluded, researchers can avoid confusion and ensure that readers understand the boundaries of the study.

Types of Delimitations in Research

Here are some types of delimitations in research and their significance:

Time Delimitations

This type of delimitation refers to the time frame in which the research will be conducted. Time delimitations are important because they help to narrow down the scope of the study and ensure that the research is feasible within the given time constraints.

Geographical Delimitations

Geographical delimitations refer to the geographic boundaries within which the research will be conducted. These delimitations are significant because they help to ensure that the research is relevant to the intended population or location.

Population Delimitations

Population delimitations refer to the specific group of people that the research will focus on. These delimitations are important because they help to ensure that the research is targeted to a specific group, which can improve the accuracy of the results.

Data Delimitations

Data delimitations refer to the specific types of data that will be used in the research. These delimitations are important because they help to ensure that the data is relevant to the research question and that the research is conducted using reliable and valid data sources.

Scope Delimitations

Scope delimitations refer to the specific aspects or dimensions of the research that will be examined. These delimitations are important because they help to ensure that the research is focused and that the findings are relevant to the research question.

How to Write Delimitations

In order to write delimitations in research, you can follow these steps:

• Identify the scope of your study : Determine the extent of your research by defining its boundaries. This will help you to identify the areas that are within the scope of your research and those that are outside of it.
• Determine the time frame : Decide on the time period that your research will cover. This could be a specific period, such as a year, or it could be a general time frame, such as the last decade.
• I dentify the population : Determine the group of people or objects that your study will focus on. This could be a specific age group, gender, profession, or geographic location.
• Establish the sample size : Determine the number of participants that your study will involve. This will help you to establish the number of people you need to recruit for your study.
• Determine the variables: Identify the variables that will be measured in your study. This could include demographic information, attitudes, behaviors, or other factors.
• Explain the limitations : Clearly state the limitations of your study. This could include limitations related to time, resources, sample size, or other factors that may impact the validity of your research.
• Justify the limitations : Explain why these limitations are necessary for your research. This will help readers understand why certain factors were excluded from the study.

When to Write Delimitations in Research

Here are some situations when you may need to write delimitations in research:

• When defining the scope of the study: Delimitations help to define the boundaries of your research by specifying what is and what is not included in your study. For instance, you may delimit your study by focusing on a specific population, geographic region, time period, or research methodology.
• When addressing limitations: Delimitations can also be used to address the limitations of your research. For example, if your data is limited to a certain timeframe or geographic area, you can include this information in your delimitations to help readers understand the limitations of your findings.
• When justifying the relevance of the study : Delimitations can also help you to justify the relevance of your research. For instance, if you are conducting a study on a specific population or region, you can explain why this group or area is important and how your research will contribute to the understanding of this topic.
• When clarifying the research question or hypothesis : Delimitations can also be used to clarify your research question or hypothesis. By specifying the boundaries of your study, you can ensure that your research question or hypothesis is focused and specific.
• When establishing the context of the study : Finally, delimitations can help you to establish the context of your research. By providing information about the scope and limitations of your study, you can help readers to understand the context in which your research was conducted and the implications of your findings.

Examples of Delimitations in Research

Examples of Delimitations in Research are as follows:

Research Title : “Impact of Artificial Intelligence on Cybersecurity Threat Detection”

Delimitations :

• The study will focus solely on the use of artificial intelligence in detecting and mitigating cybersecurity threats.
• The study will only consider the impact of AI on threat detection and not on other aspects of cybersecurity such as prevention, response, or recovery.
• The research will be limited to a specific type of cybersecurity threats, such as malware or phishing attacks, rather than all types of cyber threats.
• The study will only consider the use of AI in a specific industry, such as finance or healthcare, rather than examining its impact across all industries.
• The research will only consider AI-based threat detection tools that are currently available and widely used, rather than including experimental or theoretical AI models.

Research Title: “The Effects of Social Media on Academic Performance: A Case Study of College Students”

Delimitations:

• The study will focus only on college students enrolled in a particular university.
• The study will only consider social media platforms such as Facebook, Twitter, and Instagram.
• The study will only analyze the academic performance of students based on their GPA and course grades.
• The study will not consider the impact of other factors such as student demographics, socioeconomic status, or other factors that may affect academic performance.
• The study will only use self-reported data from students, rather than objective measures of their social media usage or academic performance.

Purpose of Delimitations

Some Purposes of Delimitations are as follows:

• Focusing the research : By defining the scope of the study, delimitations help researchers to narrow down their research questions and focus on specific aspects of the topic. This allows for a more targeted and meaningful study.
• Clarifying the research scope : Delimitations help to clarify the boundaries of the research, which helps readers to understand what is and is not included in the study.
• Avoiding scope creep : Delimitations help researchers to stay focused on their research objectives and avoid being sidetracked by tangential issues or data.
• Enhancing the validity of the study : By setting clear boundaries, delimitations help to ensure that the study is valid and reliable.
• Improving the feasibility of the study : Delimitations help researchers to ensure that their study is feasible and can be conducted within the time and resources available.

Applications of Delimitations

Here are some common applications of delimitations:

• Geographic delimitations : Researchers may limit their study to a specific geographic area, such as a particular city, state, or country. This helps to narrow the focus of the study and makes it more manageable.
• Time delimitations : Researchers may limit their study to a specific time period, such as a decade, a year, or a specific date range. This can be useful for studying trends over time or for comparing data from different time periods.
• Population delimitations : Researchers may limit their study to a specific population, such as a particular age group, gender, or ethnic group. This can help to ensure that the study is relevant to the population being studied.
• Data delimitations : Researchers may limit their study to specific types of data, such as survey responses, interviews, or archival records. This can help to ensure that the study is based on reliable and relevant data.
• Conceptual delimitations : Researchers may limit their study to specific concepts or variables, such as only studying the effects of a particular treatment on a specific outcome. This can help to ensure that the study is focused and clear.

Advantages of Delimitations

Some Advantages of Delimitations are as follows:

• Helps to focus the study: Delimitations help to narrow down the scope of the research and identify specific areas that need to be investigated. This helps to focus the study and ensures that the research is not too broad or too narrow.
• Defines the study population: Delimitations can help to define the population that will be studied. This can include age range, gender, geographical location, or any other factors that are relevant to the research. This helps to ensure that the study is more specific and targeted.
• Provides clarity: Delimitations help to provide clarity about the research study. By identifying the boundaries and limitations of the research, it helps to avoid confusion and ensures that the research is more understandable.
• Improves validity: Delimitations can help to improve the validity of the research by ensuring that the study is more focused and specific. This can help to ensure that the research is more accurate and reliable.
• Reduces bias: Delimitations can help to reduce bias by limiting the scope of the research. This can help to ensure that the research is more objective and unbiased.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Present the Limitations of the Study Examples

What are the limitations of a study?

The limitations of a study are the elements of methodology or study design that impact the interpretation of your research results. The limitations essentially detail any flaws or shortcomings in your study. Study limitations can exist due to constraints on research design, methodology, materials, etc., and these factors may impact the findings of your study. However, researchers are often reluctant to discuss the limitations of their study in their papers, feeling that bringing up limitations may undermine its research value in the eyes of readers and reviewers.

In spite of the impact it might have (and perhaps because of it) you should clearly acknowledge any limitations in your research paper in order to show readers—whether journal editors, other researchers, or the general public—that you are aware of these limitations and to explain how they affect the conclusions that can be drawn from the research.

In this article, we provide some guidelines for writing about research limitations, show examples of some frequently seen study limitations, and recommend techniques for presenting this information. And after you have finished drafting and have received manuscript editing for your work, you still might want to follow this up with academic editing before submitting your work to your target journal.

Why do I need to include limitations of research in my paper?

Although limitations address the potential weaknesses of a study, writing about them toward the end of your paper actually strengthens your study by identifying any problems before other researchers or reviewers find them.

Furthermore, pointing out study limitations shows that you’ve considered the impact of research weakness thoroughly and have an in-depth understanding of your research topic. Since all studies face limitations, being honest and detailing these limitations will impress researchers and reviewers more than ignoring them.

Where should I put the limitations of the study in my paper?

Some limitations might be evident to researchers before the start of the study, while others might become clear while you are conducting the research. Whether these limitations are anticipated or not, and whether they are due to research design or to methodology, they should be clearly identified and discussed in the discussion section —the final section of your paper. Most journals now require you to include a discussion of potential limitations of your work, and many journals now ask you to place this “limitations section” at the very end of your article. 

Some journals ask you to also discuss the strengths of your work in this section, and some allow you to freely choose where to include that information in your discussion section—make sure to always check the author instructions of your target journal before you finalize a manuscript and submit it for peer review .

Limitations of the Study Examples

There are several reasons why limitations of research might exist. The two main categories of limitations are those that result from the methodology and those that result from issues with the researcher(s).

Common Methodological Limitations of Studies

Limitations of research due to methodological problems can be addressed by clearly and directly identifying the potential problem and suggesting ways in which this could have been addressed—and SHOULD be addressed in future studies. The following are some major potential methodological issues that can impact the conclusions researchers can draw from the research.

Issues with research samples and selection

Sampling errors occur when a probability sampling method is used to select a sample, but that sample does not reflect the general population or appropriate population concerned. This results in limitations of your study known as “sample bias” or “selection bias.”

For example, if you conducted a survey to obtain your research results, your samples (participants) were asked to respond to the survey questions. However, you might have had limited ability to gain access to the appropriate type or geographic scope of participants. In this case, the people who responded to your survey questions may not truly be a random sample.

Insufficient sample size for statistical measurements

When conducting a study, it is important to have a sufficient sample size in order to draw valid conclusions. The larger the sample, the more precise your results will be. If your sample size is too small, it will be difficult to identify significant relationships in the data.

Normally, statistical tests require a larger sample size to ensure that the sample is considered representative of a population and that the statistical result can be generalized to a larger population. It is a good idea to understand how to choose an appropriate sample size before you conduct your research by using scientific calculation tools—in fact, many journals now require such estimation to be included in every manuscript that is sent out for review.

Lack of previous research studies on the topic

Citing and referencing prior research studies constitutes the basis of the literature review for your thesis or study, and these prior studies provide the theoretical foundations for the research question you are investigating. However, depending on the scope of your research topic, prior research studies that are relevant to your thesis might be limited.

When there is very little or no prior research on a specific topic, you may need to develop an entirely new research typology. In this case, discovering a limitation can be considered an important opportunity to identify literature gaps and to present the need for further development in the area of study.

Methods/instruments/techniques used to collect the data

After you complete your analysis of the research findings (in the discussion section), you might realize that the manner in which you have collected the data or the ways in which you have measured variables has limited your ability to conduct a thorough analysis of the results.

For example, you might realize that you should have addressed your survey questions from another viable perspective, or that you were not able to include an important question in the survey. In these cases, you should acknowledge the deficiency or deficiencies by stating a need for future researchers to revise their specific methods for collecting data that includes these missing elements.

Common Limitations of the Researcher(s)

Study limitations that arise from situations relating to the researcher or researchers (whether the direct fault of the individuals or not) should also be addressed and dealt with, and remedies to decrease these limitations—both hypothetically in your study, and practically in future studies—should be proposed.

Limited access to data

If your research involved surveying certain people or organizations, you might have faced the problem of having limited access to these respondents. Due to this limited access, you might need to redesign or restructure your research in a different way. In this case, explain the reasons for limited access and be sure that your finding is still reliable and valid despite this limitation.

Time constraints

Just as students have deadlines to turn in their class papers, academic researchers might also have to meet deadlines for submitting a manuscript to a journal or face other time constraints related to their research (e.g., participants are only available during a certain period; funding runs out; collaborators move to a new institution). The time available to study a research problem and to measure change over time might be constrained by such practical issues. If time constraints negatively impacted your study in any way, acknowledge this impact by mentioning a need for a future study (e.g., a longitudinal study) to answer this research problem.

Conflicts arising from cultural bias and other personal issues

Researchers might hold biased views due to their cultural backgrounds or perspectives of certain phenomena, and this can affect a study’s legitimacy. Also, it is possible that researchers will have biases toward data and results that only support their hypotheses or arguments. In order to avoid these problems, the author(s) of a study should examine whether the way the research problem was stated and the data-gathering process was carried out appropriately.

Steps for Organizing Your Study Limitations Section

When you discuss the limitations of your study, don’t simply list and describe your limitations—explain how these limitations have influenced your research findings. There might be multiple limitations in your study, but you only need to point out and explain those that directly relate to and impact how you address your research questions.

We suggest that you divide your limitations section into three steps: (1) identify the study limitations; (2) explain how they impact your study in detail; and (3) propose a direction for future studies and present alternatives. By following this sequence when discussing your study’s limitations, you will be able to clearly demonstrate your study’s weakness without undermining the quality and integrity of your research.

Step 1. Identify the limitation(s) of the study

• This part should comprise around 10%-20% of your discussion of study limitations.

The first step is to identify the particular limitation(s) that affected your study. There are many possible limitations of research that can affect your study, but you don’t need to write a long review of all possible study limitations. A 200-500 word critique is an appropriate length for a research limitations section. In the beginning of this section, identify what limitations your study has faced and how important these limitations are.

You only need to identify limitations that had the greatest potential impact on: (1) the quality of your findings, and (2) your ability to answer your research question.

Step 2. Explain these study limitations in detail

• This part should comprise around 60-70% of your discussion of limitations.

After identifying your research limitations, it’s time to explain the nature of the limitations and how they potentially impacted your study. For example, when you conduct quantitative research, a lack of probability sampling is an important issue that you should mention. On the other hand, when you conduct qualitative research, the inability to generalize the research findings could be an issue that deserves mention.

Explain the role these limitations played on the results and implications of the research and justify the choice you made in using this “limiting” methodology or other action in your research. Also, make sure that these limitations didn’t undermine the quality of your dissertation .

Step 3. Propose a direction for future studies and present alternatives (optional)

• This part should comprise around 10-20% of your discussion of limitations.

After acknowledging the limitations of the research, you need to discuss some possible ways to overcome these limitations in future studies. One way to do this is to present alternative methodologies and ways to avoid issues with, or “fill in the gaps of” the limitations of this study you have presented.  Discuss both the pros and cons of these alternatives and clearly explain why researchers should choose these approaches.

Make sure you are current on approaches used by prior studies and the impacts they have had on their findings. Cite review articles or scientific bodies that have recommended these approaches and why. This might be evidence in support of the approach you chose, or it might be the reason you consider your choices to be included as limitations. This process can act as a justification for your approach and a defense of your decision to take it while acknowledging the feasibility of other approaches.

P hrases and Tips for Introducing Your Study Limitations in the Discussion Section

The following phrases are frequently used to introduce the limitations of the study:

• “There may be some possible limitations in this study.”
• “The findings of this study have to be seen in light of some limitations.”
•  “The first is the…The second limitation concerns the…”
•  “The empirical results reported herein should be considered in the light of some limitations.”
• “This research, however, is subject to several limitations.”
• “The primary limitation to the generalization of these results is…”
• “Nonetheless, these results must be interpreted with caution and a number of limitations should be borne in mind.”
• “As with the majority of studies, the design of the current study is subject to limitations.”
• “There are two major limitations in this study that could be addressed in future research. First, the study focused on …. Second ….”

For more articles on research writing and the journal submissions and publication process, visit Wordvice’s Academic Resources page.

And be sure to receive professional English editing and proofreading services , including paper editing services , for your journal manuscript before submitting it to journal editors.

Wordvice Resources

Proofreading & Editing Guide

Writing the Results Section for a Research Paper

How to Write a Literature Review

Research Writing Tips: How to Draft a Powerful Discussion Section

How to Captivate Journal Readers with a Strong Introduction

Tips That Will Make Your Abstract a Success!

APA In-Text Citation Guide for Research Writing

Additional Resources

• Diving Deeper into Limitations and Delimitations (PhD student)
• Organizing Your Social Sciences Research Paper: Limitations of the Study (USC Library)
• Research Limitations (Research Methodology)
• How to Present Limitations and Alternatives (UMASS)

Article References

Pearson-Stuttard, J., Kypridemos, C., Collins, B., Mozaffarian, D., Huang, Y., Bandosz, P.,…Micha, R. (2018). Estimating the health and economic effects of the proposed US Food and Drug Administration voluntary sodium reformulation: Microsimulation cost-effectiveness analysis. PLOS. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002551

Xu, W.L, Pedersen, N.L., Keller, L., Kalpouzos, G., Wang, H.X., Graff, C,. Fratiglioni, L. (2015). HHEX_23 AA Genotype Exacerbates Effect of Diabetes on Dementia and Alzheimer Disease: A Population-Based Longitudinal Study. PLOS. Retrieved from https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001853

Research Limitations & Delimitations

What they are and how they’re different (with examples)

By: Derek Jansen (MBA) | Expert Reviewed By: David Phair (PhD) | September 2022

If you’re new to the world of research, you’ve probably heard the terms “ research limitations ” and “ research delimitations ” being thrown around, often quite loosely. In this post, we’ll unpack what both of these mean, how they’re similar and how they’re different – so that you can write up these sections the right way.

Overview: Limitations vs Delimitations

• Are they the same?
• What are research limitations
• What are research delimitations
• Limitations vs delimitations

First things first…

Let’s start with the most important takeaway point of this post – research limitations and research delimitations are not the same – but they are related to each other (we’ll unpack that a little later). So, if you hear someone using these two words interchangeably, be sure to share this post with them!

Research Limitations

Research limitations are, at the simplest level, the weaknesses of the study , based on factors that are often outside of your control as the researcher. These factors could include things like time , access to funding, equipment , data or participants . For example, if you weren’t able to access a random sample of participants for your study and had to adopt a convenience sampling strategy instead, that would impact the generalizability of your findings and therefore reflect a limitation of your study.

Research limitations can also emerge from the research design itself . For example, if you were undertaking a correlational study, you wouldn’t be able to infer causality (since correlation doesn’t mean certain causation). Similarly, if you utilised online surveys to collect data from your participants, you naturally wouldn’t be able to get the same degree of rich data that you would from in-person interviews .

Simply put, research limitations reflect the shortcomings of a study , based on practical (or theoretical) constraints that the researcher faced. These shortcomings limit what you can conclude from a study, but at the same time, present a foundation for future research . Importantly, all research has limitations , so there’s no need to hide anything here – as long as you discuss how the limitations might affect your findings, it’s all good.

Research Delimitations

Alright, now that we’ve unpacked the limitations, let’s move on to the delimitations .

Research delimitations are similar to limitations in that they also “ limit ” the study, but their focus is entirely different. Specifically, the delimitations of a study refer to the scope of the research aims and research questions . In other words, delimitations reflect the choices you, as the researcher, intentionally make in terms of what you will and won’t try to achieve with your study. In other words, what your research aims and research questions will and won’t include.

As we’ve spoken about many times before, it’s important to have a tight, narrow focus for your research, so that you can dive deeply into your topic, apply your energy to one specific area and develop meaningful insights. If you have an overly broad scope or unfocused topic, your research will often pull in multiple, even opposing directions, and you’ll just land up with a muddy mess of findings .

So, the delimitations section is where you’ll clearly state what your research aims and research questions will focus on – and just as importantly, what they will exclude . For example, you might investigate a widespread phenomenon, but choose to focus your study on a specific age group, ethnicity or gender. Similarly, your study may focus exclusively on one country, city or even organization. As long as the scope is well justified (in other words, it represents a novel, valuable research topic), this is perfectly acceptable – in fact, it’s essential. Remember, focus is your friend.

Need a helping hand?

Conclusion: Limitations vs Delimitations

Ok, so let’s recap.

Research limitations and research delimitations are related in that they both refer to “limits” within a study. But, they are distinctly different. Limitations reflect the shortcomings of your study, based on practical or theoretical constraints that you faced.

Contrasted to that, delimitations reflect the choices that you made in terms of the focus and scope of your research aims and research questions. If you want to learn more about research aims and questions, you can check out this video post , where we unpack those concepts in detail.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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18 Comments

Good clarification of ideas on how a researcher ought to do during Process of choice

Thank you so much for this very simple but explicit explanation on limitation and delimitation. It has so helped me to develop my masters proposal. hope to recieve more from your site as time progresses

Thank you for this explanation – very clear.

Thanks for the explanation, really got it well.

This website is really helpful for my masters proposal

Thank you very much for helping to explain these two terms

I spent almost the whole day trying to figure out the differences

when I came across your notes everything became very clear

thanks for the clearly outlined explanation on the two terms, limitation and delimitation.

Very helpful Many thanks 🙏

Excellent it resolved my conflict .

I would like you to assist me please. If in my Research, I interviewed some participants and I submitted Questionnaires to other participants to answered to the questions, in the same organization, Is this a Qualitative methodology , a Quantitative Methodology or is it a Mixture Methodology I have used in my research? Please help me

How do I cite this article in APA format

Really so great ,finally have understood it’s difference now

Getting more clear regarding Limitations and Delimitation and concepts

I really appreciate your apt and precise explanation of the two concepts namely ; Limitations and Delimitations.

This is a good sources of research information for learners.

thank you for this, very helpful to researchers

Very good explained

Great and clear explanation, after a long confusion period on the two words, i can now explain to someone with ease.

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Research Limitations

It is for sure that your research will have some limitations and it is normal. However, it is critically important for you to be striving to minimize the range of scope of limitations throughout the research process.  Also, you need to provide the acknowledgement of your research limitations in conclusions chapter honestly.

It is always better to identify and acknowledge shortcomings of your work, rather than to leave them pointed out to your by your dissertation assessor. While discussing your research limitations, don’t just provide the list and description of shortcomings of your work. It is also important for you to explain how these limitations have impacted your research findings.

Your research may have multiple limitations, but you need to discuss only those limitations that directly relate to your research problems. For example, if conducting a meta-analysis of the secondary data has not been stated as your research objective, no need to mention it as your research limitation.

Research limitations in a typical dissertation may relate to the following points:

1. Formulation of research aims and objectives . You might have formulated research aims and objectives too broadly. You can specify in which ways the formulation of research aims and objectives could be narrowed so that the level of focus of the study could be increased.

2. Implementation of data collection method . Because you do not have an extensive experience in primary data collection (otherwise you would not be reading this book), there is a great chance that the nature of implementation of data collection method is flawed.

3. Sample size. Sample size depends on the nature of the research problem. If sample size is too small, statistical tests would not be able to identify significant relationships within data set. You can state that basing your study in larger sample size could have generated more accurate results. The importance of sample size is greater in quantitative studies compared to qualitative studies.

4. Lack of previous studies in the research area . Literature review is an important part of any research, because it helps to identify the scope of works that have been done so far in research area. Literature review findings are used as the foundation for the researcher to be built upon to achieve her research objectives.

However, there may be little, if any, prior research on your topic if you have focused on the most contemporary and evolving research problem or too narrow research problem. For example, if you have chosen to explore the role of Bitcoins as the future currency, you may not be able to find tons of scholarly paper addressing the research problem, because Bitcoins are only a recent phenomenon.

5. Scope of discussions . You can include this point as a limitation of your research regardless of the choice of the research area. Because (most likely) you don’t have many years of experience of conducing researches and producing academic papers of such a large size individually, the scope and depth of discussions in your paper is compromised in many levels compared to the works of experienced scholars.

You can discuss certain points from your research limitations as the suggestion for further research at conclusions chapter of your dissertation.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

Scientific Research and Methodology : An introduction to quantitative research and statistics

9 research design limitations.

So far, you have learnt to ask a RQ and designs studies. In this chapter , you will learn to identify:

• limitations to internally valid.
• limitations to externally valid.
• limitations to ecologically valid.

9.1 Introduction

The type of study and the research design determine how the results of the study should be interpreted. Ideally, a study would be perfectly externally and internally valid; in practice this is very difficult to achieve. Practically every study has limitations. The results of a study should be interpreted in light of these limitations. Limitations are not necessarily problems .

Limitations generally can be discussed through three components:

• Internal validity (Sect. 6.1 ): Discuss any limitations to internal validity due to the research design (such as identifying possible confounding variables). This is related to the effectiveness of the study within the sample (Sect. 9.2 ).
• External validity (Sect. 5.1 ): Discuss how well the sample represents the intended population. This is related to the generalisability of the study to the intended population (Sect. 9.3 ).
• Ecological validity : Discuss how well the study methods, materials and context approximate the real situation being studied. This is related to the practicality of the results to real life (Sect. 9.4 ).

Some of these limitations are imposed by the type of study. All these issues should be addressed when considering the study limitations.

Almost every study has limitations. Identifying potential limitations, and discussing the likely impact they have on the interpretation of the study results, is important and ethical.

Example 9.1 Delarue et al. ( 2019 ) discuss studies where subjects rate the taste of new food products. They note that taste-testing studies should (p. 78):

... allow generalizing the conclusions obtained with a consumer sample [...] to the general targeted population [i.e., external validity]... tests should be reliable in terms of accuracy and replicability [i.e., internal validity].

However, even with good internal and external validity, these studies often result in a 'high rate of failures of new launched products'. That is, the studies do not replicate the real world, and so lack ecological validity .

9.2 Limitations: internal validity

Internal validity refers to the extent to which a cause-and-effect relationship can be established in a study, eliminating other possible explanations (Sect. 6.1 ). A discussion of the limitations of internal validity should cover, as appropriate: possible confounding variables; the impact of the Hawthorne, observer, placebo and carry-over effects; the impact of any other design decisions.

If any of these issues are likely to compromise internal validity, the implications on the interpretation of the results should be discussed. For example, if the participants were not blinded, this should be clearly stated, and the conclusion should indicate that the individuals in the study may have behaved differently than usual.

Example 9.2 (Study limitations) Axmann et al. ( 2020 ) randomly allocated Ugandan farmers to receive, or not receive, hybrid maize seeds. One potential threat to internal validity was that farmers receiving the hybrid seeds could share their seeds with their neighbours.

Hence, the researchers contacted the \(75\) farmers allocated to receive the hybrid seeds; none of the contacted farmers reported selling or giving seeds to other farmers. This extra step increased the internal validity of the study.

Maximizing internal validity in observational studies is more difficult than in experimental studies (e.g., random allocation is not possible). The internal validity of experimental studies involving people is often compromised because people must be informed that they are participating in a study.

Example 9.3 (Internal validity) In a study of the hand-hygiene practices of paramedics ( Barr et al. 2017 ) , self -reported hand-hygiene practices were very different than what was reported by peers . That is, how people self-report their behaviours may not align with how they actually behave, which influenced the internal validity of the study.

A study evaluated using a new therapy on elderly men, and listed some limitations of their study:

... the researcher was not blinded and had prior knowledge of the research aims, disease status, and intervention. As such, these could all have influenced data recording [...] The potential of reporting bias and observer bias could be reduced by implementing blinding in future studies. --- Kabata-Piżuch et al. ( 2021 ) , p. 10

9.3 Limitations: external validity

External validity refers to the ability to generalise the findings made from the sample to the entire intended population (Sect.  5.1 ). For a study to be externally valid, it must first be internally valid: if the study of not effective in the sample studied (i.e., internally valid), the results may not apply to the intended population either.

External validity refers to how well the sample is likely to represent the intended population in the RQ.

If the population is Iowans, then the study is externally valid if the sample is representative of Iowans The results do not have to apply to people in the rest of the United States (though this can be commented on, too). The intended population is Iowans .

External validity depends on how the sample was obtained. Results from random samples (Sects.  5.5 to  5.9 ) are likely to generalise to the population and be externally valid. (The analyses in this book assume all samples are simple random samples .) Furthermore, results from approximately representative samples (Sect.  5.10 ) may generalise to the population and be externally valid if those in the study are not obviously different than those not in the study.

Example 9.4 (External validity) A New Zealand study ( Gammon et al. 2012 ) identified (for well-documented reasons) a population of interest: 'women of South Asian origin living in New Zealand' (p. 21). The women in the sample were 'women of South Asian origin [...] recruited using a convenience sample method throughout Auckland' (p. 21).

The results may not generalise to the intended population ( all women of South Asian origin living in New Zealand) because all the women in the sample came from Auckland, and the sample was not a random sample from this population anyway. The study was still useful however!

Example 9.5 (Using biochar) Farrar et al. ( 2018 ) studied growing ginger using biochar on one farm at Mt Mellum, Australia. The results may only generalise to growing ginger at Mt Mellum, but since ginger is usually grown in similar types of climates and soils, the results may apply to other ginger farms also.

9.4 Limitations: ecological validity

The likely practicality of the study results in the real world should also be discussed. This is called ecological validity .

Definition 9.1 (Ecological validity) A study is ecologically valid if the study methods, materials and context closely approximate the real situation of interest.

Studies don't need to be ecologically valid to be useful; much can be learnt under special conditions, as long as the potential limitations are understood when applying the results to the real world. The ecological validity of experimental studies may be compromised because the experimental conditions are sometimes artificially controlled (for good reason).

Example 9.6 (Ecological validity) Consider a study to determine the proportion of people that buy coffee in a reusable cup. People could be asked about their behaviour. This study may not be ecologically valid, as how people act may not align with how they say they will act.

An alternative study could watch people buy coffees at various coffee shops, and record what people do in practice. This second study is more likely to be ecologically valid , as real-world behaviour is observed.

A study observed the effect of using high-mounted rear brake lights ( Kahane and Hertz 1998 ) , which are now commonplace. The American study showed that such lights reduced rear-end collisions by about \(50\) %. However, after making these lights mandatory, rear-end collisions reduced by only \(5\) %. Why?

9.5 Limitations: study types

Experimental studies, in general, have higher internal validity than observational studies, since more of the research design in under the control of the researchers; for example, random allocation of treatments is possible to minimise confounding.

Only well-conducted experimental studies can show cause-and-effect relationships.

However, experimental studies may suffer from poor ecological validity; for instance, laboratory experiments are often conducted under controlled temperature and humidity. Many experiments also require that people be told about being in a study (due to ethics), and so internal validity may be comprised (the Hawthorne effect).

Example 9.7 (Retrofitting) giandomenico2022systematic studied retro-fitting houses with energy-saving devices, and found large discrepancies in savings for observational studies ( \(12.2\) %) and experimental studies ( \(6.2\) %). The authors say that 'this finding reinforces the importance of using study designs with high internal validity to evaluate program savings' (p. 692).

9.6 Chapter summary

The limitations in a study need to be identified, and may be related to:

• internal validity (effectiveness): how well the study is conducted within the sample, isolating the relationship of interest.
• external validity (generalisability): how well the sample results are likely to apply to the intended population.
• ecological validity (practicality): how well the results may apply to the real-world situation.

Many of the limitations are a results of the type of study.

9.7 Quick review questions

Are the following statements true or false ?

• When interpreting the results of a study, the steps taken to maximize internal validity should be evaluated TRUE FALSE
• If studies are not externally valid, then they are not useful. TRUE FALSE
• When interpreting the results of a study, the steps taken to maximize external validity do not need to be evaluated TRUE FALSE
• When interpreting the results of a study, ecological validity is about the impact of the study on the environment. TRUE FALSE

9.8 Exercises

Answers to odd-numbered exercises are available in App.  E .

Exercise 9.1 A research study examined how people can save energy through lighting choices ( Gentile 2022 ) . The study states (p. 9) that the results 'are limited to the specific study and cannot be easily projected to other similar settings'.

What type of validity is being discussed here?

Exercise 9.2 Fill the blanks with the correct word: internal , external or ecological .

When interpreting the results of studies, we consider the practicality ( internal external ecological validity), the generalizability ( internal external ecological validity) and the effectiveness ( internal external ecological validity).

Exercise 9.3 A student project asked if 'the percentage of word retention higher in male students than female students?' When discussing external validity , the students stated:

We cannot say whether or not the general public have better or worse word retention compared to the students that we will be studying.

Why is the statement not relevant in a discussion of external validity?

Exercise 9.4 Yeh et al. ( 2018 ) conducted an experimental study to 'determine if using a parachute prevents death or major traumatic injury when jumping from an aircraft'.

The researchers randomised \(23\) volunteers into one of two groups: wearing a parachute, or wearing an empty backpack. The response variable was a measurement of death or major traumatic injury upon landing. From the study, death or major injury was the same in both groups (0% for each group). However, the study used 'small stationary aircraft on the ground, suggesting cautious extrapolation to high altitude jumps' (p. 1).

Comment on the internal, external and ecological validity.

Exercise 9.5 A study examined how well hospital patients sleep at night ( Delaney et al. 2018 ) . The researchers state that 'convenience sampling was used to recruit patients' (p. 2). Later, the researchers state (p. 7):

... while most healthy individuals sleep primarily or exclusively at night, it is important to consider that patients requiring hospitalization will likely require some daytime nap periods. This study looks at sleep only in the night-time period \(22\) : \(00\) -- \(07\) : \(00\) h, without the context of daytime sleep considered.

Discuss these issues using the language introduced in this chapter.

Exercise 9.6 Botelho et al. ( 2019 ) examined the food choices made when subjects were asked to shop for ingredients to make a last-minute meal. Half were told to prepare a 'healthy meal', and the other half told just to prepare a 'meal'. The authors stated (p. 436):

Another limitation is that results report findings from a simulated purchase. As participants did not have to pay for their selection, actual choices could be different. Participants may also have not behaved in their usual manner since they were taking part in a research study, a situation known as the Hawthorne effect.

What type of limitation is being discussed?

Exercise 9.7 Johnson et al. ( 2018 ) studied the use of over-the-counter menthol cough-drops in people with a cough. One conclusion from the observational study of \(548\) people was that, taking 'too many cough drops [...] may actually make coughs more severe', as one author explained in an interview about the study Critique this statement.

Limited by our limitations

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• Volume 8 , pages 261–264, ( 2019 )

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Study limitations represent weaknesses within a research design that may influence outcomes and conclusions of the research. Researchers have an obligation to the academic community to present complete and honest limitations of a presented study. Too often, authors use generic descriptions to describe study limitations. Including redundant or irrelevant limitations is an ineffective use of the already limited word count. A meaningful presentation of study limitations should describe the potential limitation, explain the implication of the limitation, provide possible alternative approaches, and describe steps taken to mitigate the limitation. This includes placing research findings within their proper context to ensure readers do not overemphasize or minimize findings. A more complete presentation will enrich the readers’ understanding of the study’s limitations and support future investigation.

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Writing Quantitative Research Studies

The Specific Aims

Avoid common mistakes on your manuscript.

Introduction

Regardless of the format scholarship assumes, from qualitative research to clinical trials, all studies have limitations. Limitations represent weaknesses within the study that may influence outcomes and conclusions of the research. The goal of presenting limitations is to provide meaningful information to the reader; however, too often, limitations in medical education articles are overlooked or reduced to simplistic and minimally relevant themes (e.g., single institution study, use of self-reported data, or small sample size) [ 1 ]. This issue is prominent in other fields of inquiry in medicine as well. For example, despite the clinical implications, medical studies often fail to discuss how limitations could have affected the study findings and interpretations [ 2 ]. Further, observational research often fails to remind readers of the fundamental limitation inherent in the study design, which is the inability to attribute causation [ 3 ]. By reporting generic limitations or omitting them altogether, researchers miss opportunities to fully communicate the relevance of their work, illustrate how their work advances a larger field under study, and suggest potential areas for further investigation.

Goals of presenting limitations

Medical education scholarship should provide empirical evidence that deepens our knowledge and understanding of education [ 4 , 5 ], informs educational practice and process, [ 6 , 7 ] and serves as a forum for educating other researchers [ 8 ]. Providing study limitations is indeed an important part of this scholarly process. Without them, research consumers are pressed to fully grasp the potential exclusion areas or other biases that may affect the results and conclusions provided [ 9 ]. Study limitations should leave the reader thinking about opportunities to engage in prospective improvements [ 9 , 10 , 11 ] by presenting gaps in the current research and extant literature, thereby cultivating other researchers’ curiosity and interest in expanding the line of scholarly inquiry [ 9 ].

Presenting study limitations is also an ethical element of scientific inquiry [ 12 ]. It ensures transparency of both the research and the researchers [ 10 , 13 , 14 ], as well as provides transferability [ 15 ] and reproducibility of methods. Presenting limitations also supports proper interpretation and validity of the findings [ 16 ]. A study’s limitations should place research findings within their proper context to ensure readers are fully able to discern the credibility of a study’s conclusion, and can generalize findings appropriately [ 16 ].

Why some authors may fail to present limitations

As Price and Murnan [ 8 ] note, there may be overriding reasons why researchers do not sufficiently report the limitations of their study. For example, authors may not fully understand the importance and implications of their study’s limitations or assume that not discussing them may increase the likelihood of publication. Word limits imposed by journals may also prevent authors from providing thorough descriptions of their study’s limitations [ 17 ]. Still another possible reason for excluding limitations is a diffusion of responsibility in which some authors may incorrectly assume that the journal editor is responsible for identifying limitations. Regardless of reason or intent, researchers have an obligation to the academic community to present complete and honest study limitations.

A guide to presenting limitations

The presentation of limitations should describe the potential limitations, explain the implication of the limitations, provide possible alternative approaches, and describe steps taken to mitigate the limitations. Too often, authors only list the potential limitations, without including these other important elements.

Describe the limitations

When describing limitations authors should identify the limitation type to clearly introduce the limitation and specify the origin of the limitation. This helps to ensure readers are able to interpret and generalize findings appropriately. Here we outline various limitation types that can occur at different stages of the research process.

Study design

Some study limitations originate from conscious choices made by the researcher (also known as delimitations) to narrow the scope of the study [ 1 , 8 , 18 ]. For example, the researcher may have designed the study for a particular age group, sex, race, ethnicity, geographically defined region, or some other attribute that would limit to whom the findings can be generalized. Such delimitations involve conscious exclusionary and inclusionary decisions made during the development of the study plan, which may represent a systematic bias intentionally introduced into the study design or instrument by the researcher [ 8 ]. The clear description and delineation of delimitations and limitations will assist editors and reviewers in understanding any methodological issues.

Data collection

Study limitations can also be introduced during data collection. An unintentional consequence of human subjects research is the potential of the researcher to influence how participants respond to their questions. Even when appropriate methods for sampling have been employed, some studies remain limited by the use of data collected only from participants who decided to enrol in the study (self-selection bias) [ 11 , 19 ]. In some cases, participants may provide biased input by responding to questions they believe are favourable to the researcher rather than their authentic response (social desirability bias) [ 20 , 21 , 22 ]. Participants may influence the data collected by changing their behaviour when they are knowingly being observed (Hawthorne effect) [ 23 ]. Researchers—in their role as an observer—may also bias the data they collect by allowing a first impression of the participant to be influenced by a single characteristic or impression of another characteristic either unfavourably (horns effect) or favourably (halo effort) [ 24 ].

Data analysis

Study limitations may arise as a consequence of the type of statistical analysis performed. Some studies may not follow the basic tenets of inferential statistical analyses when they use convenience sampling (i.e. non-probability sampling) rather than employing probability sampling from a target population [ 19 ]. Another limitation that can arise during statistical analyses occurs when studies employ unplanned post-hoc data analyses that were not specified before the initial analysis [ 25 ]. Unplanned post-hoc analysis may lead to statistical relationships that suggest associations but are no more than coincidental findings [ 23 ]. Therefore, when unplanned post-hoc analyses are conducted, this should be clearly stated to allow the reader to make proper interpretation and conclusions—especially when only a subset of the original sample is investigated [ 23 ].

Study results

The limitations of any research study will be rooted in the validity of its results—specifically threats to internal or external validity [ 8 ]. Internal validity refers to reliability or accuracy of the study results [ 26 ], while external validity pertains to the generalizability of results from the study’s sample to the larger, target population [ 8 ].

Examples of threats to internal validity include: effects of events external to the study (history), changes in participants due to time instead of the studied effect (maturation), systematic reduction in participants related to a feature of the study (attrition), changes in participant responses due to repeatedly measuring participants (testing effect), modifications to the instrument (instrumentality) and selecting participants based on extreme scores that will regress towards the mean in repeat tests (regression to the mean) [ 27 ].

Threats to external validity include factors that might inhibit generalizability of results from the study’s sample to the larger, target population [ 8 , 27 ]. External validity is challenged when results from a study cannot be generalized to its larger population or to similar populations in terms of the context, setting, participants and time [ 18 ]. Therefore, limitations should be made transparent in the results to inform research consumers of any known or potentially hidden biases that may have affected the study and prevent generalization beyond the study parameters.

Explain the implication(s) of each limitation

Authors should include the potential impact of the limitations (e.g., likelihood, magnitude) [ 13 ] as well as address specific validity implications of the results and subsequent conclusions [ 16 , 28 ]. For example, self-reported data may lead to inaccuracies (e.g. due to social desirability bias) which threatens internal validity [ 19 ]. Even a researcher’s inappropriate attribution to a characteristic or outcome (e.g., stereotyping) can overemphasize (either positively or negatively) unrelated characteristics or outcomes (halo or horns effect) and impact the internal validity [ 24 ]. Participants’ awareness that they are part of a research study can also influence outcomes (Hawthorne effect) and limit external validity of findings [ 23 ]. External validity may also be threatened should the respondents’ propensity for participation be correlated with the substantive topic of study, as data will be biased and not represent the population of interest (self-selection bias) [ 29 ]. Having this explanation helps readers interpret the results and generalize the applicability of the results for their own setting.

Provide potential alternative approaches and explanations

Often, researchers use other studies’ limitations as the first step in formulating new research questions and shaping the next phase of research. Therefore, it is important for readers to understand why potential alternative approaches (e.g. approaches taken by others exploring similar topics) were not taken. In addition to alternative approaches, authors can also present alternative explanations for their own study’s findings [ 13 ]. This information is valuable coming from the researcher because of the direct, relevant experience and insight gained as they conducted the study. The presentation of alternative approaches represents a major contribution to the scholarly community.

Describe steps taken to minimize each limitation

No research design is perfect and free from explicit and implicit biases; however various methods can be employed to minimize the impact of study limitations. Some suggested steps to mitigate or minimize the limitations mentioned above include using neutral questions, randomized response technique, force choice items, or self-administered questionnaires to reduce respondents’ discomfort when answering sensitive questions (social desirability bias) [ 21 ]; using unobtrusive data collection measures (e.g., use of secondary data) that do not require the researcher to be present (Hawthorne effect) [ 11 , 30 ]; using standardized rubrics and objective assessment forms with clearly defined scoring instructions to minimize researcher bias, or making rater adjustments to assessment scores to account for rater tendencies (halo or horns effect) [ 24 ]; or using existing data or control groups (self-selection bias) [ 11 , 30 ]. When appropriate, researchers should provide sufficient evidence that demonstrates the steps taken to mitigate limitations as part of their study design [ 13 ].

In conclusion, authors may be limiting the impact of their research by neglecting or providing abbreviated and generic limitations. We present several examples of limitations to consider; however, this should not be considered an exhaustive list nor should these examples be added to the growing list of generic and overused limitations. Instead, careful thought should go into presenting limitations after research has concluded and the major findings have been described. Limitations help focus the reader on key findings, therefore it is important to only address the most salient limitations of the study [ 17 , 28 ] related to the specific research problem, not general limitations of most studies [ 1 ]. It is important not to minimize the limitations of study design or results. Rather, results, including their limitations, must help readers draw connections between current research and the extant literature.

The quality and rigor of our research is largely defined by our limitations [ 31 ]. In fact, one of the top reasons reviewers report recommending acceptance of medical education research manuscripts involves limitations—specifically how the study’s interpretation accounts for its limitations [ 32 ]. Therefore, it is not only best for authors to acknowledge their study’s limitations rather than to have them identified by an editor or reviewer, but proper framing and presentation of limitations can actually increase the likelihood of acceptance. Perhaps, these issues could be ameliorated if academic and research organizations adopted policies and/or expectations to guide authors in proper description of limitations.

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• Definition/Introduction

Conducting research from planning to publication can be a very rewarding process. However, multiple preventable setbacks can occur within each stage of research. While these inefficiencies are an inevitable part of the research process, understanding common pitfalls can limit those hindrances. Many issues can present themselves throughout the research process. It has been said about academics that “the politics are so harsh because the stakes are so low.” Beyond interpersonal and political / funding concerns, prospective authors may encounter some disenchantment with the publish or perish culture. With a metric of (any) publication, the motivation to contribute meaningfully to science can be overshadowed by a compulsive drive to publish. [1]  We believe in quality over quantity and highlight the importance of channeling creativity when pursuing scholarly work.

When considering embarking on a medical research project, one must begin with detailed planning. Do not underestimate the amount of time a project can take, often spanning years from conception to manuscript preparation. Will you conduct a retrospective chart review, a prospective study, or a true clinical trial with randomization and blinding? Will you systematically seek out and remove sources of bias from the study design and interpretation of results? Will you ensure the study is powered properly to justify conclusions? Will you eliminate or explain any conflicts of interest occurring among your author group? Will you fall victim to the temptation of frivolous subgroup analyses, or will you stick with the original plan? Will your study have a realistic chance at publication in a journal within your specialty, or perhaps another subfield? The study results may prove the null hypothesis, a ‘negative study,’ and therefore be difficult to publish. [2]  Additionally, the intervention you find beneficial may subsequently be proven unhelpful or even dangerous, leading to prudent medical reversal. [3]

These considerations and more necessitate meticulous planning and vigilant adherence to a sound protocol. Along the way, you will encounter obstacles, pitfalls, some of which are presented in this article. But remain persistent, and your efforts will be rewarded with publication and contribution to science. This review covers common pitfalls researchers encounter and suggested strategies to avoid them.

• Issues of Concern

There are five phases of research: planning phase, data collection/analysis phase, writing phase, journal submission phase, and rejections/revisions/acceptance phase.

Phase I Pitfalls: Planning a Study

The highest yield preempting of pitfalls in the research process occurs in the planning phase. This is when a researcher can set the stage for an optimal research process. Below are pitfalls that can occur during the planning phase.

Pitfall: Underestimating what committing to a research project requires

Conducting a research study and achieving publication sounds fulfilling, right?

Consider the many steps: conducting a literature search, writing an IRB proposal, planning and having research meetings, long and cumbersome data collection processes, working with statisticians or analyzing complex data, having unexpected research setbacks (e.g., subjects drop out, newly published papers on same topic, etc.), the possibility that after data collection you have no statistically (or clinically) significant findings, conducting an updated literature search, writing introduction, methods, results, and discussion sections of a paper, going through the many journal options to determine best fit while aiming for high impact factors, adhering to journal guidelines/fixing drafts, writing cover letters stating importance of the topic to respective journals, creating journal portal accounts, possibly being rejected numerous times, waiting months for journal decisions, working on numerous revisions and being informed by numerous individuals about all of the flaws in your writing and research.

Does it sound, maybe less fulfilling ?

Conducting a research project from inception to publication can be a rewarding experience. Research requires significant time. Setbacks are normal. To produce an important and sought-after research product, an individual must understand the magnitude of commitment required.

Pitfall: Choosing the wrong research pursuit/topic lacks precision

Consider an investigator interested in substance use research. The first challenge is the immense amount of research already published on this topic. Fortunately, there is still a massive amount of uncharted territory in substance use research.

It is important to understand what has been done and what is still undiscovered in your area of research. Do not simply study a topic because you find it interesting; passion is advantageous, but you should ensure that your study will contribute to some field/specialty or research in a significant way.

How does your research differ from what has been done?

How will it impact practice in a way that no previous study has?

Consider these questions when choosing a topic for research. Otherwise, you may struggle to get the work published. It can be demoralizing if you have already written your paper and realize that your paper is not going to get accepted by a reputable journal due to the presence of other papers already describing the same concepts you have.

As always, the first step is a thorough literature search.

Pitfall: Not considering research bias

A common theme noted in literature is that bias can, unfortunately, lead to failure to reproduce results, raising concerns regarding the integrity of science. [4]  Bias can be considered various (inadvertent) poor strategies related to data design, analysis, and results reporting that produce spurious results and papers that perhaps should not be published. [5]

While one cannot completely eliminate bias from the research process, researchers should take steps to understand research bias in study endeavors and determine how to minimize bias during the planning phase of the study.  

Pitfall: Not focusing on which variables to collect

Researchers often want to collect as much data as possible but should not build a list of variables that includes every single detail about subjects if the variables collected are unlikely to yield insight into the topic of research. The longer the data collection instrument, the higher likelihood of (human) errors (if manually data entry) and the longer duration of the data collection phase. Instead of taking time to build a database with many variables, consider cutting irrelevant variables and use that time to increase the sample size. Determine, based on your own clinical knowledge and published empirical works, which variables are most crucial. 

Pitfall: Worrying about the statistics after the data has been collected

A vital part of the research process is ensuring you have a rigorous statistical approach. Involve your statistician very early in the project, preferably in the planning stages. They will have insight into the types of variables to collect and help shape the research methods. Statistical power is an important concept to consider before data collection to avoid false-negative results (Zlowodzki et al., 2006). Furthermore, other concepts, such as covariates, need to be part of the planning phase. Do not wait until after the data collection phase to give data to the statistician who cannot transform the data you have into outputs you want.

Pitfall: Not setting defined author roles

It is important to define who will be declared authors at the beginning of the research process to avoid conflict. Do most people want to be an author? Sure. Does everybody do the work worthy of authorship? No. While placing general comments in a shared document's margin may make the paper slightly better, it probably should not qualify for authorship. Review authorship criteria to determine what constitutes authorship. Clear expectations can ensure that everyone is on the same page and that everyone feels the process is fair, especially for individuals who plan to invest significant time in the project. Clear expectations for each author should occur before any writing begins, including deadlines and specific contributions. [6] [7] [6]

Pitfall: Not considering limitations of work before the paper is written

Avoid this pitfall by reviewing recent manuscripts and reading the limitations sections of these papers. Many of these limitations sections will make notions about generalizability to other populations. Some will discuss low power. Even the best papers in the top journals have many limitations. The best way to avoid or mitigate your work's limitations is to consider them during the planning phase.

How can you set up your project to limit your limitations section?

What (types of) samples should you include in your study?

Were you originally thinking of retrospective design, but it could be prospective?

What steps can you utilize to control baseline characteristics between groups?

Consider all limitations and think about how you can control these before data collection.

Phase II Pitfalls: Data Collection and Analysis

After the planning has occurred, typically after institutional review board (IRB) approval, the data collection and analysis phase can transpire. The entire team should typically stay involved throughout these phases. Below are pitfalls to avoid.

Pitfall: Not being involved in the data collection phase

It is important to be involved with the data collection phase, even if you do not personally collect data. Train the individuals who collect data to ensure all are on the same page and provide periodic oversight to ensure accuracy and quality of the data over time. [8]  Do not assume the data collection phase is going smoothly – you may find yourself with a huge dataset riddled with inconsistencies or errors. Schedule periodic meetings to review data.

Pitfall: Not being involved with the statistical analysis phase

If you are not conducting the statistical analysis, do not assume that the person who is analyzing the data is 100% on the same page. Have meetings about the data, how to interpret the data, and the limitations of the data. Ask what other ways the data could be analyzed and how reviewers might negatively critique the data itself or the statistical methods.

The person conducting the analysis will not have the same familiarity with the topic. You are not going to be as familiar with the outputs. By understanding each other, you will a) have clearer, more robust methods and results in sections of the paper, b) limit critiques regarding the statistical approach/data outcomes, c) understand your research better for any presentations, discussion, or future work, and d) develop a positive collaboration for future work.

Phase III Pitfalls: The Writing Phase

The next phase is the writing phase. While this section covers pitfalls during the writing phase, for recommendations on conducting a literature search, writing, and publishing research, see StatPearls Evidence-Base Medicine Chapter: How to Write and Publish a Scientific Manuscript. [9]  Below are pitfalls that can occur during the writing phase. 

Pitfall: Poor or outdated references

When writing your paper, perform multiple literature searches to ensure all recent, salient references are covered—claims about recent similar work or research that frames your study if the references are outdated. Journals may even ask reviewers to comment on the presence or absence of up-to-date/suitable references. Conduct a literature search prior to data collection and stay on top of references throughout the research process as new papers become available.

Pitfall: No clearly defined purpose of the paper

Many aspects of manuscripts can get overlooked. Lack of a clear purpose statement can doom a paper to futility. Remind the readers of the goal of the project. You do not want consumers of your research to read the results section and forget what the goals/main outcomes are. The purpose statement should be located at the end of the introduction section.  

Pitfall: Unclear methods making research hard to reproduce

A common concern in science is the lack of transparency in methods for reproducibility. The methods section should allow a reader to understand exactly what was done and conduct the study. Consider examining the S treng T hening the R eporting of OB servational studies in E pidemiology (STROBE) checklist for the methods (as well as other paper sections) to ensure best reporting practices for reproducibility. [10]

Pitfall: The tables and narratives are the same

Reviewers prefer you not to state findings in narratives that are in tables. Tables focus readers on the most important results and are not redundant with the written content. Make call-outs to the table in the paper's narrative sections, but do not state information found in tables.  

Pitfall: Not reporting all data/outcomes

Some authors will state the main outcome of interest or have a statement such as “there were no other statistically significant findings between other groups.” Authors must report all outcomes and statistical analyses for reproducibility of the research. While this may be difficult to do with a broad approach, utilize tables and appendices to report all outcomes to show transparency and limit researcher bias.

Pitfall: Repeating results in discussion

Do not simply restate in the discussion what you already have in the results section. Utilize this section of the paper to link other references to your work and reflect on other empirical investigations' similarities or differences. Explain why your research provides an impactful contribution to the topic.  

Pitfall: Making conclusions that do not align with your work

Authors sometimes note in their conclusions how the work impacts a topic due to X reason when X may be too broad a claim and the work doesn’t really support or prove that notion. Researchers should align their conclusions to their own results and highlight the significance of their findings.

Pitfall: Thinking the title is not a big deal

A strong title will help with the impact/readership of your paper. Consider keeping a short title that provides the main takeaway. Papers with more concise titles and present the study conclusion result in a bigger impact/receive more citations. [11]

Pitfall: Completing the abstract last minute

Similar to the title, do not underestimate an abstract. Journal and conference reviewers (and the general audience) may only read your abstract. The abstract must have the key results and contributions of the study and be well-written.

Phase IV Pitfalls: Submitting to a Journal

After the paper has been written, it is time to choose the journal. This phase also has numerous pitfalls. Below are pitfalls that can occur during this phase.  

Pitfall: Choosing the wrong journal

Choosing the journal for your work can be overwhelming due to the number of options. Always look at the aims and scope of prospective journals. Look through the author guidelines to ensure that your manuscript adheres. This will save time. Review your reference list for any journals that appear more than once; if so, consider submitting to that journal. You do not want to submit your paper, wait two weeks, and then get a desk rejection because the editors state the paper is not aligned to the journal's aims and scope.

Additionally, researchers can aim too high and spend months (and numerous hours in journal submission portals) trying to publish a manuscript in a journal with a very large impact factor. Though admirable, if the research design and results lacking “gold standard” reporting, authors should consider a journal that is more likely to accept. Find a balance between the quality of your paper and the quality of the journal. Seek feedback from the other authors and/or senior colleagues who can provide honest feedback.

Pitfall: Poor cover letter on journal submission

Do not submit work with a flawed cover letter (errors or lack of clarity in how your work contributes to the body of literature). Spend time writing a detailed cover letter once, have it edited by someone else, and utilize that for all future projects. You can highlight the differences (e.g., the purpose of this work, our results showed) with each project. Use the cover letter to highlight the significance of the study while adhering to the disclosure guidelines (e.g., conflicts of interests, authors contributions, data releases, etc.), which will help the editorial board determine not only the suitability of the paper for the journal but also streamline the review process. [12]

Pitfall: Assuming that after the paper has been submitted to a journal, the work is done             

The paper has been submitted! You think you are finished…but, unfortunately, the publishing game may still be far from over. Researchers often do not recognize the amount of time going into the submission/rejection/revisions phases. Revisions can sometimes be total overhauls, more work than writing a whole new paper. Be prepared to continue working.

Phase V Pitfalls: The Rejections, Revisions, and Acceptance Phase

Finally, perhaps the most unpredictable phase, the rejections, revisions, and acceptance phase, has unique pitfalls and other obstacles.

Pitfall: Mourning rejections too long/ “sitting on” a rejected paper             

Did you get a desk to reject (i.e., the manuscript was not even sent for blind review)? That is unfortunate but common. You do not have time to sulk. Get that paper submitted somewhere else. The older the data, the less desirable your paper becomes. If the paper went in for a full review and was rejected, that may be even tougher than a desk reject because more time has elapsed. The good news is that (hopefully) you received feedback to incorporate in a revision. Do not spend too much time grieving rejections.

Pitfall: Not laying to rest rejected papers when it is indeed their time to go

Did you write a paper a couple of years ago, and you’ve submitted it to 20 different journals? The data is getting old. The topic wasn’t focused on. The sample size was small. Perhaps the project is not worth pursuing any longer. Do not give in to the sunk cost fallacy. If, however, you are proud of the work and stand by the paper, do not give up. If you believe after the numerous rejections that the topic/project is flawed, you can use this failure as a personal learning/growth opportunity. Do not repeat controllable mistakes on future projects.

Pitfall: Not addressing all of reviewer feedback

Did you get a revise and resubmit? Great news! The reviewers and editors will likely ask you to respond to each comment when you resubmit. Address all of the reviewer feedback. Take your time reading through the feedback, digest it, and re-read it. Carefully respond and decide how to revise your manuscript based on the feedback. Share the reviews and the duties of revision with coauthors. In your response to reviewers, stay professional and address each statement, even if you disagree with what is stated. If you do not respond to each statement, the reviewers often highlight the concern(s) again.

Pitfall: Thinking you know what the reviewers are going to say

Research reviewers are like a box of chocolates. You never know what you are going to get. You may be worried about a section of your paper/research approach, and the reviewers do not mention it at all in their review; instead, they criticize a section of your manuscript that you are most proud of.

In some reviews, you may get feedback like the following:

Reviewer #1

Please change lines 104-108 as I believe they are irrelevant to your study.

Reviewer #2

Please build on lines 104-108, as I believe they are the foundation of your study.

Sometimes, after multiple revisions, there are new concerns presented by the reviewers. This can be disheartening. Should some regulations restrict reviewers from bringing up new ideas/concerns during revision #7? Perhaps. Does any current rule prevent them from doing this? No.

During the review process, we must have faith that the reviewers are knowledgeable and provide fair, insightful, and constructive feedback. While the review process can be arbitrary or frustrating in some cases, peer review remains the gold standard in a scientific publication. Stay positive and persistent. Stay professional in responses to the reviewers. Remember that the review process can be very beneficial as it often leads to feedback that truly elevates your work and makes the product (and you) look better. [13]

Pitfall: Not rewarding yourself for a published paper

You did it! Celebrate your accomplishment. Reflect on the merit of your effort before you move on to other work or re-enter the cycle of IRBs, data coding, journal submissions, etc. Remember and appreciate how remarkable it is that you just contributed knowledge to the world.

• Clinical Significance

Many pitfalls can occur throughout the research process. Researchers should understand these pitfalls and utilize strategies to avoid them to produce high-quality, sought-after research results that are useful for basic science and clinical practice.

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Disclosure: Jacob Shreffler declares no relevant financial relationships with ineligible companies.

Disclosure: Martin Huecker 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 Shreffler J, Huecker MR. Common Pitfalls In The Research Process. [Updated 2023 Mar 6]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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Researchers review findings and clinical messages from the Women’s Health Initiative 30 years after launch

Data from influential study underscore the importance of personalized and shared decision-making to support the health of postmenopausal women

WHAT: A new review in JAMA highlights key findings and clinical messages from the Women’s Health Initiative (WHI), the largest women’s health study in the United States. The WHI is supported by the National Institutes of Health’s National Heart, Lung, and Blood Institute (NHLBI), and was created to study factors that may reduce risks for cardiovascular disease, cancer, hip fractures, and other conditions in postmenopausal women. More than 68,000 women enrolled in clinical trials between 1993 and 1998 and were followed for up to 20 years.

After reviewing these long-term data, the researchers explain the primary findings:

Hormone therapy and menopause. The WHI study found that estrogen or a combination of estrogen and progestin, two types of hormone replacement therapies, had varying outcomes with chronic conditions, and the evidence does not support the use of these therapies to reduce risks for chronic diseases, such as heart disease, stroke, cancer, and dementia. The study was not designed to assess the effects of FDA-approved hormone therapies for treating menopausal symptoms, the benefits of which had been established before the WHI study began.

The authors reinforce the importance of women making shared decisions with physicians about the benefits or risks of taking hormone therapy during menopause. For example, women younger than age 60 with low-to-average risk for cardiovascular disease and breast cancer who want to take hormone therapy may experience greater health benefits than risks during early menopause to treat moderate-to-severe symptoms, such as bothersome hot flashes or night sweats.

Calcium and vitamin D supplements and bone fractures. A combined calcium and vitamin D supplement was not associated with reduced risks for hip fractures among postmenopausal women at average risk for osteoporosis, according to the study. However, the authors note that supplements can help fill nutrient gaps among women who do not meet the daily recommended intake for these nutrients . Therefore, women with questions about adequate intake and levels should consult with their healthcare provider.

Low-fat diets and cancer. A low-fat dietary pattern with at least five daily servings of fruits and vegetables and increased grains did not reduce the risk of breast or colorectal cancer. However, upon subsequent analyses during the follow-up period, researchers found that this type of eating pattern was associated with a reduced risk of death from breast cancer.

Findings from the clinical trials and study observations can vary based on multiple factors, such as age and underlying cardiovascular disease risks, so women ages 50 and older should work with their clinicians to make individualized and shared medical decisions, the researchers noted.

STUDY: Manson, JE, Crandall CJ, Rossouw JE, et al. The Women’s Health Initiative randomized trials and clinical practice: A review. JAMA ; 2024. Doi: 10.1001/jama.2024.6542.

WHO: Candice A. Price, Ph.D., program director of the epidemiology branch, located within the Division of Cardiovascular Sciences at NHLBI, is available to discuss this review.

About the National Heart, Lung, and Blood Institute (NHLBI):  NHLBI is the global leader in conducting and supporting research in heart, lung, and blood diseases and sleep disorders that advances scientific knowledge, improves public health, and saves lives. For more information, visit  www.nhlbi.nih.gov .

About the National Institutes of Health (NIH):  NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit  www.nih.gov .

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Review article, strategies in product engineering of mesenchymal stem cell-derived exosomes: unveiling the mechanisms underpinning the promotive effects of mesenchymal stem cell-derived exosomes.

• 1 Orthopedics Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
• 2 Orthopedics Department, Longgang District People’s Hospital of Shenzhen and the Second Affiliated Hospital, The Chinese University of Hong Kong, Shenzhen, China
• 3 Orthopedics Department, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China
• 4 Central Laboratory, Longgang District People’s Hospital of Shenzhen and the Second Affiliated Hospital, The Chinese University of Hong Kong, Shenzhen, China
• 5 The Biomechanics Group, Department of Mechanical Engineering, Imperial College London, London, United Kingdom
• 6 Department of Engineering, Faculty of Environment, Science and Economy, University of Exeter, Exeter, United Kingdom

Articular cartilage injuries present a significant global challenge, particularly in the aging population. These injuries not only restrict movement due to primary damage but also exacerbate elderly degenerative lesions, leading to secondary cartilage injury and osteoarthritis. Addressing osteoarthritis and cartilage damage involves overcoming several technical challenges in biological treatment. The use of induced mesenchymal stem cells (iMSCs) with functional gene modifications emerges as a solution, providing a more stable and controllable source of Mesenchymal Stem Cells (MSCs) with reduced heterogeneity. Furthermore, In addition, this review encompasses strategies aimed at enhancing exosome efficacy, comprising the cultivation of MSCs in three-dimensional matrices, augmentation of functional constituents within MSC-derived exosomes, and modification of their surface characteristics. Finally, we delve into the mechanisms through which MSC-exosomes, sourced from diverse tissues, thwart osteoarthritis (OA) progression and facilitate cartilage repair. This review lays a foundational framework for engineering iMSC-exosomes treatment of patients suffering from osteoarthritis and articular cartilage injuries, highlighting cutting-edge research and potential therapeutic pathways.

1 Introduction

Cartilage damage, a consequence of factors such as exercise, trauma, inflammation, and degeneration, represents the most prevalent joint disease globally and is a principal precursor to osteoarthritis (OA) ( Berenbaum and Walker, 2020 ; Quicke et al., 2022 ). The limited regenerative and repair capabilities of articular cartilage, a consensus among scholars, pose significant challenges; once damaged, its self-repair ability is notably compromised. This progressive deterioration of articular cartilage, both through damage and disease, leads to OA ( Coryell et al., 2021 ). The pathological foundation of OA includes cell inflammation-mediated chondrocyte hypertrophy, degeneration, apoptosis, extracellular matrix (ECM) degradation, and articular cartilage and subchondral bone reactive hyperplasia. Its clinical manifestations, such as pain, joint swelling, stiffness, and deformity, profoundly impact patients’ quality of life, underscoring the urgency of effective articular cartilage repair strategies before OA onset.

Cartilage, a specialized connective tissue, is distinguished by its avascular, aneural, and alymphatic nature, characterized by a dense ECM and chondrocytes embedded in a matrix rich in collagen fibers and proteoglycans ( Vahedi et al., 2021 ). Its histological and biochemical properties, coupled with the low metabolic and proliferative states of chondrocytes, restrict their hyperplasia and migration to damaged areas. This limitation impedes cartilage tissue’s self-repair and regeneration, failing to halt disease progression ( Schenker et al., 2017 ). Current clinical approaches to osteoarthritis and osteochondral injury encompass conventional medication for early-stage articular cartilage damage, which alleviates swelling and pain but fails to fundamentally address lesion progression. Surgical interventions, including subchondral microfractures, autografts, allogeneic cartilage grafts, and periosteal and perichondrial transplantation, face challenges such as tissue degeneration, donor scarcity, and limited repair scopes. Hence, timely and effective treatment of articular cartilage damage remains crucial in preventing OA development.

Tissue engineering and regenerative medicine have recently gained prominence in addressing articular cartilage damage and osteoarthritis. This field leverages bioengineering technologies to repair and regenerate human tissues and organs, combining materials science, medicine, biology, and engineering theories. Techniques include using biological materials as scaffolds for cell and tissue regeneration, employing pluripotent stem cells, and inducing stem cell differentiation with biological activity signal factors to engineer new tissues ( Huang et al., 2012 ; Stanco et al., 2020 ; Zhao R. et al., 2021 ). Stem cell-based therapy primarily utilizes human pluripotent stem cells and multipotent (MSCs for regenerative medicine ( Hoang et al., 2022 ). The pioneering stem cell transplantation was performed by the French oncologist George Mathé in 1958 ( Jansen, 2005 ). Over subsequent decades, MSC-based research and therapy have witnessed significant achievements, attributed to MSCs’ unique properties, such as their ability to evade the immune response, availability from various tissue sources, straightforward isolation, rapid proliferative capacity, and suitability for cryopreservation. Recently, the focus has increasingly shifted towards exosomes derived from MSCs, prompted by concerns over the medical safety and the yet-to-be-fully-ascertained efficacy of MSC-based therapies ( Hoang et al., 2022 ).

Compared to cell-based therapies, exosome application offers numerous advantages, including high physicochemical stability, inherent biocompatibility, minimal toxicity, and reduced immunogenicity ( Hade et al., 2022 ; Nan et al., 2022 ). Furthermore, exosomes exhibit unique biological functions mirroring those of their parent cells ( Zhou A. K. et al., 2023 ). Notably, exosomes serve as promising drug delivery vehicles, attributed to their prolonged circulation half-life, favorable biodistribution, specific cellular interactions, and the feasibility of direct modification ( Kimiz-Gebologlu and Oncel, 2022 ; Nan et al., 2022 ). Extracellular vesicles (EVs), particularly exosomes, have been identified as key mediators of MSC paracrine function, playing a vital role in intercellular signaling ( Chen et al., 2019 ). Exosomes, derived from transcytosed endosomes and released into the extracellular fluid, are lipid bilayer membrane-enclosed structures containing various bioactive molecules. They function as intercellular communication pathways, facilitating material exchange and signal transmission between cells ( Patil and Rhee, 2019 ; Skotland et al., 2019 ). In stem cell biological therapy, exosomes mimic parental stem cell functions while avoiding issues like abnormal differentiation and immune rejection.Futhermore, it is easier to preserve and transport them ( Atlasi and Stunnenberg, 2017 ; Zhou C. et al., 2023 ). The application of exosomes in OA prevention and treatment has shown promising results, such as their role in the formation of neohyaline cartilagein rat knee cartilage defect models, effectively promoting cartilage matrix synthesis and delaying articular cartilage degeneration ( Zhang et al., 2015 ; Zhu et al., 2017 ).

In this review, we consolidate the benefits and manufacturing techniques associated with engineering exosomes. Additionally, we delve into recent research that elucidates the mechanisms underpinning the therapeutic effects of MSC-derived exosomes on OA.

2 The advantage and challenge of induced mesenchymal stem cells (iMSCs)-exosomes

In comparison to MSCs isolated from homologous adult tissues, iMSCs exhibit a more stable molecular phenotype, enhanced proliferative differentiation capabilities, and superior regenerative repair capacities in animal disease models ( Sabapathy and Kumar, 2016 ; Lee et al., 2023 ; Gultian et al., 2022 ). Consequently, iMSCs, surpassing iPSCs in quality, present broader application prospects. They inherit the advantages of iPSCs, including the ability to reprogram diverse adult cells such as those from peripheral blood, skin biopsies, and detached body surface cells (; Dupuis and Oltra, 2021 ; Wang Q. et al., 2023 ; Wu et al., 2018 ; Zhou C. et al., 2023 ). Given the potentially infinite replicative capacity of iPSCs, the source for iMSCs can be considered similarly inexhaustible. While iPSCs themselves display heterogeneity, a single iPSC clone exhibits low internal heterogeneity ( Devito et al., 2019 ). Thus, deriving iMSCs from single iPSC cells or clonal differentiation minimizes MSC heterogeneity, facilitating the acquisition of functionally stable and defined MSC products, including exosomes. iMSCs can be efficiently prepared on a large scale, yielding stable and controllable final products, including exosomes, suitable for diverse clinical applications downstream ( Obara et al., 2016 )

Furthermore, the monoclonal stage of iPSCs is conducive to genetic modifications, influencing all downstream iMSC products, including exosomes ( Hollmann et al., 2020 ). This capability opens avenues for developing new generations of biotherapeutic technologies leveraging specific gene functions.The efficacy of exosome-based biotherapies is intricately linked to the source of the parental stem cells. Advances in cell reprogramming technology, particularly in the study of induced pluripotent stem cells (iPSCs), have not only deepened our understanding of stem cell pluripotency and its molecular regulatory mechanisms but have also provided a source of totipotent stem cells capable of extensive proliferation ( Gallegos et al., 2013 ; Aboul-Soud et al., 2021 ).

However, the research and development of iMSC-exosomes face several technical challenges, including (; Zhang et al., 2023 ; Wang X. et al., 2023 ; Chen et al., 2021 ; Sadeghi et al., 2023 ; Gurung et al., 2021 ; Hade et al., 2021 ; Tang et al., 2023 ): 1) Identifying the core efficacy components and mechanisms of action of iMSC-exosomes for specific diseases. 2) Enhancing the enrichment and efficacy of specific components within iMSC-140 exosomes. 3) Ensuring mass production, quality stability, and efficient storage and transportation processes for iMSC-exosomes. 4) Optimizing the effective delivery and functionality of iMSC-exosomes in specific tissue contexts.

3 Strategies to improve exosome performance

To augment the yield and quality of exosomes, as well as to enhance their targeting precision, biostability, and therapeutic efficacy, numerous studies have been conducted. These accomplishments are comprehensively summarized in Figure 1 .

Figure 1 . Strategies for Enhancing Exosome Efficacy This figure presents three key strategies for boosting the performance of MSC-derived exosomes: 1) three-dimensional culture of MSCs to enhance exosome production and quality, 2) improving exosomal functional components through targeted pathways, and 3) surface modification of exosomes for better targeting and delivery. Additionally, it illustrates methods to increase the concentration of effective molecules (effectors) within the exosomes.

3.1 Three-dimensional culture of MSCs

The conventional method of culturing mesenchymal stem cells (MSCs) involves a two-dimensional (2D) monolayer setup. However, this approach has limitations, particularly in terms of proliferation efficiency, falling short of meeting the clinical demand for high doses of MSCs. Furthermore, the development and functionality of MSCs are significantly influenced by molecular interactions within their environment. Traditional 2D cultures fail to replicate the spatial distribution, nutrient transfer, cell migration, and mechanical stimulation characteristics of a three-dimensional (3D) extracellular matrix (ECM) microenvironment. This discrepancy can lead to variations in gene expression, signaling, and morphology of MSCs from their natural state ( Li et al., 2015 ), potentially impacting the biological function of exosomes.

Recognizing these limitations, the 3D culture and amplification of MSCs using 3D printed scaffolds have gained widespread acceptance. Microcarriers (MCs), consisting of hydrogel microparticles made from materials like gelatin, hyaluronic acid, collagen, or natural biological macromolecules such as chitosan, sodium alginate, and their derivatives combined with polyethylene glycol, offer a promising solution ( Figure 2 ) ( Tavassoli et al., 2018 ). These MCs present several advantages, including facilitating large-scale cell culture and expansion, mimicking in vivo 3D microenvironments, establishing cell-cell and cell-ECM interactions, and promoting gene expression and secretion activities akin to in vivo conditions (; Tseng et al., 2016 ; Shekaran, et al., 2016 ).

Figure 2 . MCs of different shapes Spherical MCs like (A) Cytodex 1 and (B) Cytopore. (C) 2D microhex is an example of hexagon shape carriers produced by Nunc™. (D) Fibra-cel ® is a product of New Brunswick™ that has a disc shape. (E) Lens-shape MCs like Cytoline 1 and Cytoline 2 (F) are produced via GE Healthcare. (G) and (H) shows DE-52 and DE-53 as available cylindrical MCs in the market which are produced by Whatman™. In panel G, i and ii shows attachment of L-929, a corn-type fibroblastic and MDCK, a canine kidney cell line, Epithelial cells, respectively to DE-52. In panel H, i and ii shows attachment of the baby hamster kidney cell line (BHK, Fibroblastic type) and Primary chick embryo fibroblast, respectively to DE-53. (I) Morphology of human ESCs on (i) DE-53 (large aggregates), (ii) Cytodex-1 (thin aggregate layers) and (iii) Tosoh 65 PR (compact aggregates). Images adapted from Ref (Niet al., 2020).

3.2 The approaches to improve the functional components in exosomes

The extraction of exosomes typically involves techniques such as overspeed centrifugation, ultrafiltration, immunoaffinity capture, charge-neutralization-based polymer precipitation, size exclusion chromatography, and microfluidic separation ( Wu J. et al., 2019 ). These methods yield exosomes with varying levels of purity, yield, size, surface potential, and inclusion composition, and currently, there is no standardized extraction protocol ( Yang et al., 2019 ). The identification of exosomes is predominantly based on their morphological characteristics under electron microscope, particle size specific protein markers ( Zhao X. et al., 2021 ). However, the efficacy of these identification methods can be influenced by the quality of the kits used and other external factors ( Momen-Heravi F. 2017 ).

To enhance tissue regeneration efficiency, further enrichment of functional components in exosomes is crucial ( Sun et al., 2021 ). The enrichment of exosomes with functional components is primarily achieved through either the overexpression of these components in parental cells or direct delivery to the exosomes (Pegtel and Gould, 2019). The former approach, involving genetic expression of functional components by parental cells and their subsequent secretion into exosomes, faces challenges in specifically regulating functional components and often results in low yields of exosomes enriched with targeted components ( Sun et al., 2021 ). In contrast, physical and chemical methods such as incubation, electroporation, heat shock, ultrasound, freeze-thaw cycles, extrusion, gradient pH regulation, and transient penetration of phospholipid bilayers have proven more efficient and feasible ( Colombo et al., 2014 ; Kalluri and LeBleu, 2020 ; Mondal et al., 2023 ). These methods enhance the interaction of target functional components with the exosomes’ surface.

3.3 Surface modification of the iMSC-exosomes

The lipid bilayers of exosomes play a crucial role in shielding internal functional components from external environmental damage. However, their thermodynamic instability during storage makes them susceptible to alterations in the medium, temperature, time, and physical and chemical properties. Such changes can result in the loss of internal functional components, formation of multilayer vesicle structures, and aggregation. Repeated freeze-thaw cycles can also alter the lipid bilayer’s marker characteristics and composition ( Maroto et al., 2017 ).

When administered subcutaneously, intravenously, or intraperitoneally, exosomes are known to accumulate in organs like the liver, spleen, lungs, and gastrointestinal tract within 2 h and are rapidly cleared by macrophages ( Takahashi et al., 2013 ). The incorporation of exosomes into hydrogels for sustained release can mitigate the low tissue retention observed with direct injections. However, this passive diffusion release mechanism is difficult to control due to the influence of hydrogel porosity and degradation rate. Moreover, the negative charge on both exosome and cell membranes creates electrostatic barriers that reduce the bio-utilization efficiency of exosomes ( Feng et al., 2021 ).

Surface modification of exosomes can enhance their physicochemical properties. Sushil et al. utilized cholesterol-modified DNA strands for complementary pairing and embedding a polymer onto the exosome membrane surface, improving stability and therapeutic efficacy without altering in vivo distribution or specific targeting. However, this method’s chemical synthesis complexity and the temperature-sensitive annealing of DNA chain segments may impact exosome activity. In contrast, Feng et al. (2021) demonstrated the incubation of exosomes with polylysine (ε PL)-PEG-distearoyl phosphatidylethanolamine (DSPE) (PPD), integrating the DSPE segment into the exosome membrane while reversing the ε PL segment from electronegative to electropositive. This modification increased exosome uptake, penetration, and retention in cartilage, thereby enhancing OA treatment effects ( Lathwal et al., 2021 ). While this approach is simpler and does not affect the structure and content of exosomes, it results in increased exosome size and reduced cartilage absorption rate.

4 Molecular and cellular mechanisms of MSCs-exosomes in the treatment of OA and articular cartilage

Given the vast array of sources for MSCs, including bone marrow, synovium, umbilical cord, urine, infrapatellar fat pad, and adipose tissues, exosomes derived from these cells hold considerable potential for OA therapy. The exploration of the mechanisms through which MSC-exosomes prevent OA represents a critical pathway towards their clinical application. MSC-derived exosomes contribute to cartilage repair and OA prevention through various mechanisms, such as inhibiting ECM degradation and chondrocyte apoptosis, promoting ECM secretion and autophagy, and enhancing chondrocyte proliferation and migration (refer to Figure 3 and Table 1 ).

Figure 3 . Mechanisms of MSC-Exosome Action in Cartilage Homeostasis and Osteoarthritis Treatment This figure illustrates how MSC-exosomes, derived from different tissues, influence cartilage homeostasis and address osteoarthritis through multiple mechanisms: ① Delivery of miRNA, LncRNA, or proteins to chondrocytes suppresses NF-κB, mTOR, and pro-inflammatory factor release. While some MSC-exosomes may activate the Wnt/β-catenin signaling pathway, overexpression of certain miRNAs redirects these exosomes to inhibit this pathway; ②The suppression of MMP13, MMP3, RUNX2, and ADAMTS5 expression through various signaling pathways prevents ECM degradation; ③ Enhancement of COL2A1, Collagen II, aggrecan, and SOX9 expression via diverse signaling routes increases ECM synthesis; ④ Cartilage homeostasis is maintained by activating autophagy through multiple pathways; ⑤ Cartilage regeneration is promoted by stimulating chondrocyte proliferation and migration and reducing apoptosis via varied signaling mechanisms.

Table 1 . Summary sheet about the sources of MSCs, experimental animal model, methods to enrich exosomes, and key activator molecules in studies about the mechanism of MSCs-exosomes to treat OA.

4.1 Exosomes derived from bone marrow MSCs

Exosomes derived from bone marrow MSCs play a crucial role in mitigating chondrocyte injury in OA induced by IL-1β, with miR-3960 emerging as a principal effector. In chondrocytes, the increase in PHLDA2 expression activates the Wnt/β-catenin pathway through the upregulation of SDC1 expression, leading to the degradation of the cartilage extracellular matrix due to elevated levels of MMP-13 and ADAMTS5, alongside reduced levels of collagen II and aggrecan. However, miR-3960, enriched in the exosomes secreted by MSCs, can be delivered to chondrocyte cells, subsequently degrading PHLDA2 mRNA. Moreover, the expression profiles of miR-3960, PHLDA2, SDC1, and β-catenin in cartilage tissues from OA patients align with findings from their prospective study ( Ye et al., 2022 ).Xia Qingqing et al. identified a negative correlation between miR-125a-5p and E2F2 in the cartilage of traumatic osteoarthritis patients and in a corresponding mouse model. The exosomes derived from bone marrow MSCs, which are taken up by chondrocytes in mice, contain miR-125a-5p that suppresses E2F2 expression. This downregulation leads to decreased MMP-13 levels and increased levels of collagen II, aggrecan, and SOX9, thereby facilitating chondrocyte migration and alleviating extracellular matrix degradation ( Xia et al., 2021 ).Through miRNA microarray analysis, Mao Guping et al. found that miR-92a-3p levels in MSC exosomes were upregulated following chondrogenic induction in bone marrow MSCs, but downregulated in OA chondrocyte-secreted exosomes compared to normal cartilage. MiR-92a-3p suppresses MMP-13 and RUNX2 expression while enhancing aggrecan, COL2A1, and SOX9 expression, thereby inhibiting cartilage degradation—a process regulated by reduced WNT5A expression in chondrocytes ( Mao et al., 2018 ).Sun Hao et al. demonstrated that miR-320c, enriched in exosomes secreted by bone marrow MSCs undergoing chondrogenic differentiation, promotes osteoarthritis chondrocyte proliferation, enhances SOX9 expression, and inhibits MMP-13 expression. This contributes to chondrogenesis induction and inflammation suppression in chondrocytes ( Sun et al., 2019 ).Chen Xue et al. observed higher ELF3 levels and lower miR-136-5p levels in traumatic OA cartilage tissues compared to healthy cartilage. Exosomes secreted by bone marrow MSCs, rich in miR-136-5p, are internalized by chondrocytes, leading to downregulated ELF3 expression, which in turn alleviates cartilage degeneration and enhances chondrocyte migration through the upregulation of collagen II, aggrecan, and SOX9, and the downregulation of MMP-13 expression ( Chen et al., 2020 ).DDX20, identified as a key regulator in chondrocyte damage induced by IL-1β, activates the NF-κB signaling pathway, promoting chondrocyte damage through increased expression of MMP-3 and MMP-13. Exosomes derived from bone marrow MSCs can counteract this effect by downregulating DDX20 levels, thanks to the enrichment of miR-361-5p within them ( Tao et al., 2021 ).Liu Yubao et al. demonstrated that in a mouse OA model, MSC-exosomes promoted chondrocyte proliferation, inhibited apoptosis, and maintained cartilage homeostasis. This was achieved through the upregulation of COL2A1 and aggrecan and the downregulation of MMP-13 and RUNX2, mediated by the lncRNA-KLF3-AS1/miR-206/GIT1 axis ( Liu et al., 2018 ).

4.2 Exosomes derived from synovial MSCs

Exosomes derived from synovial MSCs have demonstrated a capacity to foster chondrocyte regeneration, although they did not show benefits for ECM synthesis. These exosomes aid in OA prevention by encouraging chondrocyte proliferation and migration and by reducing apoptosis, yet they do not affect ECM secretion. However, exosomes overexpressing miR-155-5p were found to enhance ECM secretion in OA chondrocytes through the degradation of Runx2 ( Wang et al., 2021 ). In a similar vein, Tao Shicong et al. reported that exosomes from synovial MSCs could activate YAP through the delivery of wnt5a and wnt5b, key activators of the Wnt signaling pathway. This activation leads to increased chondrocyte proliferation and migration, albeit at the expense of ECM secretion. Nonetheless, this limitation could be addressed by miR-140-5p, which elevates the levels of SOX9, aggrecan, and collagen II by inhibiting RalA ( Tao et al., 2017 ). Further, Qiu Min et al. observed a reduced expression of miR-129-5p in the cartilage tissues of OA patients and in chondrocytes induced by IL-1β, while HMGB1 was more highly expressed compared to healthy tissue. Exosomes from human synovial MSCs, rich in miR-129-5p, were able to elevate its levels in chondrocytes, subsequently downregulating HMGB1. Consequently, there was a reduction in the inflammatory response and apoptosis of chondrocytes ( Qiu et al., 2021 ).

4.3 Exosomes derived from umbilical cord MSCs

Yan Litao et al. demonstrated that mechanical stimulation during cell culture could amplify the secretion of exosomes by umbilical cord mesenchymal stem cells. These exosomes proved advantageous for repairing cartilage defects, a benefit attributed to the encapsulation of LncRNA H19 ( Yan et al., 2020 ). Zhou Hao et al. further revealed that exosomes derived from umbilical cord mesenchymal stem cells exerted a protective effect on OA, as evidenced in a mouse OA model created by surgical destabilization of the medial meniscus. The protective mechanism was attributed to exosomal miR-1208, which reduced the m6A modification level of NLRP3 mRNA by targeting METTL3 mRNA, leading to a decrease in pro-inflammatory factor levels. Consequently, chondrocyte regeneration was enhanced due to increased proliferation and migration and reduced apoptosis. Additionally, ECM degradation was curtailed through the upregulation of COL2A1 and aggrecan and the downregulation of ADAMTS5 and MMP-13 ( Zhou et al., 2022 ).

4.4 Exosomes derived from urine MSCs

Exosomes secreted by urine-derived stem cells cultured under hypoxic conditions were found to be enriched in miR-26a-5p, which effectively inhibits PTEN expression in chondrocytes, thereby promoting their proliferation and migration ( Wan et al., 2022 ). Moreover, exosomes from human urine-derived stem cells were shown to enhance the proliferation and migration of chondrocytes induced by IL-1β, while concurrently inhibiting apoptosis, albeit with a reduction in ECM secretion. Intriguingly, when overexpressed with miR-140-5p, these exosomes facilitated the upregulation of collagen II and aggrecan. Mechanistically, miR-140-5p was found to decrease VEGFA levels in cartilage and synovial fluid samples obtained from patients with knee osteoarthritis or from a rat model of the disease ( Liu et al., 2022 ).

4.5 Exosomes derived from remaining MSCs

In vitro studies reveal that exosomes derived from adipose stem cells effectively downregulate the expression of prostaglandin E2, IL-6, IL-1β, and TNF-α in the murine chondroprogenitor cell line ADTC5. The encapsulated miR-338-3p within these exosomes is delivered to interleukin-1β-induced ADTC5 cells, promoting the degradation of RUNX2 mRNA. Consequently, this results in the inhibition of cell degradation and apoptosis, alongside the promotion of cell proliferation ( Li et al., 2022 ).Wu Jiangyi et al. demonstrated that exosomes secreted by infrapatellar fat pad MSCs can maintain cartilage homeostasis by enhancing autophagy levels, attributed to the inhibition of mTOR. The encapsulated miR-100-5p within these exosomes can bind to the 3′-untranslated region (3′UTR) of mTOR, promoting its degradation. The exosomes ameliorated OA severity in vivo and inhibited cell apoptosis, enhanced matrix synthesis, and reduced the expression of catabolic factors in vitro . Given the relative ease of harvesting infrapatellar fat pad MSCs from OA patients, this study may guide future clinical therapies for OA ( Wu X. et al., 2019 ).

5 Discussion and perspectives

This review underscores the transformative potential ofiMSC-exosomes in treating OA and repairing articular cartilage. The advanced bioengineering of iMSCs, rooted in iPSC technology, presents a paradigm shift in regenerative medicine. Their enhanced stability, proliferative capabilities, and regenerative repair capacities herald a new era in tissue engineering. However, the journey from laboratory to clinic is fraught with challenges, notably in identifying and enhancing key efficacy components of iMSC-exosomes, ensuring their mass production and stability, and optimizing delivery mechanisms.

The shift from two-dimensional to three-dimensional culture systems using MCsmarks a significant advancement in MSC culture, more accurately mimicking in vivo conditions and enhancing exosome functionality. The challenges, such as inefficient cell apposition and particle residue, represent crucial areas for future research. Additionally, the refinement of exosome extraction and enrichment techniques, alongside innovative strategies for surface modification, could exponentially enhance their therapeutic potential.

The intricate molecular and cellular mechanisms by which MSC-exosomes influence cartilage repair and OA treatment, including modulation of inflammatory responses and promotion of chondrocyte proliferation and migration and ECM secretion, inhibition of apoptosis and ECM degradation, are at the forefront of current research.

While certain studies have highlighted the adverse effects of MSC-derived exosomes on the ECM, modifications such as overexpressing specific effectors in MSC-exosomes have demonstrated the potential to counteract these drawbacks. Specifically, the Wnt signaling pathway, which can be activated by certain MSC-exosomes, may be subdued through the overexpression of particular effectors ( Tao et al., 2017 ; Wang et al., 2021 ; Liu et al., 2022 ). Consequently, engineered MSC-exosomes, enriched with tailored effector molecules, present a more promising approach for OA prevention compared to their unmodified counterparts. This suggests that strategic modifications can enhance the therapeutic utility of MSC-exosomes, making them a more suitable option for OA intervention. Translating these mechanisms into effective clinical interventions remains a pivotal challenge. Future research must focus on elucidating and harnessing these mechanisms more effectively, potentially through targeted gene editing and advanced bioengineering techniques.

Looking forward, the field must prioritize the development of standardized protocols for iMSC-exosome production and application, addressing issues of heterogeneity and scalability. Clinical trials are imperative to translate these cellular and molecular insights into real-world therapies. Furthermore, exploring the immunomodulatory potential of MSC-exosomes could open new avenues for treating inflammatory aspects of OA.

The potential of iMSC-exosomes in OA treatment and cartilage repair is immense. The intersection of cellular biology, molecular engineering, and bioinformatics stands to revolutionize our approach to regenerative medicine. As we advance, a collaborative, interdisciplinary effort encompassing researchers, clinicians, and regulatory bodies will be essential in overcoming existing barriers and realizing the full therapeutic potential of iMSC-exosomes.

6 Conclusion

To enhance the biological treatment of OA and articular cartilage injury, several technical challenges must be addressed. Here we proposed solutions include using functionally genetically modified iMSCs combined with 3D printed scaffolds for 3D culture, enriching functional miRNA, and modifying the membrane surface of iMSC-exosomes to augment their function. We also summarized the mechanisms of iMSC-exosomes on chondrocyte proliferation, apoptosis, autophagy, ECM synthesis, and inflammatory repair at molecular and subcellular levels. The content that discussed in this review offers insights for treating OA and articular cartilage damage.

Author contributions

YJ: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing–original draft, Writing–review and editing. HL: Writing–original draft, Writing–review and editing. FS: Writing–review and editing. LF: Writing–review and editing. HZ: Writing–review and editing. YH: Writing–review and editing. JL: Writing–review and editing. DW: Writing–review and editing. HP: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing–original draft, Writing–review and editing. JY: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing–original draft, Writing–review and editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was granted by the Shenzhen Municipal Natural Science Foundation of China (JCYJ20220530162206012).

Acknowledgments

Our special thanks go to Guangqian Zhou PhD and Liangge He PhD for their help in suggesting the general direction of this manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbreviations

MSCs, mesenchymal stem cells; miRNA, microRNA; lncRNA, long non-coding RNA; NF-κB, nuclear factor kappa B; mTOR, mechanistic target of rapamycin; MMP-13, matrix metallopeptidase-13; MMP-3, matrix metalloproteinase-3; RUNX2,runt-related transcription factor 2; ADAMTS5, a disintegrin and metalloproteinase with thrombospondin motifs 5; COL2A1, collagen type II alpha 1; SOX9, (sex determining region Y)-box 9; ECM, extracellular matrix.

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Keywords: engineering, osteoarthritis, cartilage damage, induced mesenchymal stem cells, exosomes, 3D printed stent

Citation: Jiang Y, Lv H, Shen F, Fan L, Zhang H, Huang Y, Liu J, Wang D, Pan H and Yang J (2024) Strategies in product engineering of mesenchymal stem cell-derived exosomes: unveiling the mechanisms underpinning the promotive effects of mesenchymal stem cell-derived exosomes. Front. Bioeng. Biotechnol. 12:1363780. doi: 10.3389/fbioe.2024.1363780

Received: 31 December 2023; Accepted: 08 April 2024; Published: 02 May 2024.

Reviewed by:

Copyright © 2024 Jiang, Lv, Shen, Fan, Zhang, Huang, Liu, Wang, Pan and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Haile Pan, [email protected] ; Jianhua Yang, [email protected]

† These authors have contributed equally to this work and share first authorship

This article is part of the Research Topic

Tissue Engineering and Regenerative Medicine: Advances, Controversies, and Future Directions

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Do good lessons promote students' attention and behavior?

by Anke Wilde, Leibniz-Institut für Bildungsforschung und Bildungsinformation

Students are better able to regulate themselves in lessons that they consider to be particularly well implemented. This is the conclusion drawn from a study by the DIPF | Leibniz Institute for Research and Information in Education, published in the journal Learning and Instruction .

The link between teaching quality and self-regulation tends to be particularly true for pupils who have problems controlling their behavior and following lessons, for example due to ADHD symptoms.

Good teaching is characterized by the teacher leading the class through the lesson without disruption, encouraging the students to think, taking an interest in them and supporting them individually. The better the teacher is at this, the better the students will be able to regulate their behavior, for example by paying attention, cooperating and adhering to the class rules.

As a result, they learn better. This link, which has already been established in research, has now been examined in more detail in this daily diary study and evaluated with the help of multilevel analyses.

It became clear that the quality of teaching has an impact not only on self-regulation overall, but also in each individual lesson, as Dr. Friederike Blume, lead author of the now published study, summarizes the results.

"When teachers are particularly good at classroom management and providing student support in a lesson, students are better able to regulate their behavior. When these two characteristics of good teaching are not working well in a lesson, students also reported that they were less able to concentrate and engage."

Cognitive activation, the third characteristic of good teaching, was hardly relevant for self-regulation. Therefore, the personal relationship between teacher and student is particularly important, emphasizes Dr. Blume.

This is especially true for students who have difficulties with self-regulation, such as those with attention deficit hyperactivity disorder (ADHD).

"Many teachers find it difficult to establish a positive relationship with children with ADHD symptoms," says the educational researcher. "However, our study showed that in lessons where children with self-regulation difficulties felt particularly supported by their teacher, they were more likely to report being able to concentrate better and follow class rules.

"It is therefore worth taking a positive approach to these children in the classroom and showing a genuine interest in them, as this can reduce the pressure on teachers in the long term and bring more calm to the classroom."

The DIPF researcher also recommends that teachers ask their students for feedback on their teaching from time to time. Although this is still a taboo for many, it can provide valuable information on how to better tailor their teaching to the needs of individual students.

A total of 64 pupils in years 5 and 6 took part in the study. They did not necessarily belong to the same school or class, but were recruited through an email appeal to music schools, sports and leisure centers, for example.

At the start of the study, the children completed a questionnaire about general information such as their grade level and type of school, as well as how they rated their self-regulation skills. Over the next three school weeks, the children answered daily questions about the last lesson of each day.

The questions related to the quality of teaching (e.g., support from the teacher, disruptions in lessons, stimulation of reflection), as well as their ability to regulate themselves in that lesson (e.g., attention, impulse control, motor activity).

The links between the individual lessons and the corresponding daily entries were evaluated using multilevel analysis. Among other things, the results were analyzed on an intrapersonal level, which allows conclusions to be drawn at the level of the individual child. In addition, interpersonal associations were examined, which allows conclusions to be drawn about all participants together.

Limitations of the study

Studies with such an elaborate design, involving daily diaries, always aim to collect data in as short time as possible. As a result, teaching quality was only measured here on the basis of only few statements, which certainly do not cover all the characteristics of good teaching.

Future studies should therefore take a closer look at classroom interaction processes to explore which features of teaching are particularly beneficial, especially for children with stronger ADHD symptoms.

Furthermore, future studies must show whether the results found here apply to all subjects or only to certain subjects, and the role of different teaching methods.

Journal information: Learning and Instruction

Provided by Leibniz-Institut für Bildungsforschung und Bildungsinformation

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Preventable Premature Deaths from the Five Leading Causes of Death in Nonmetropolitan and Metropolitan Counties, United States, 2010–2022

Surveillance Summaries / May 2, 2024 / 73(2);1–11

Macarena C. García, DrPH 1 ; Lauren M. Rossen, PhD 2 ; Kevin Matthews, PhD 3 ; Gery Guy, PhD 4 ; Katrina F. Trivers, PhD 5 ; Cheryll C. Thomas, MSPH 5 ; Linda Schieb, MSPH 5 ; Michael F. Iademarco, MD 1 ( View author affiliations )

Introduction

Limitations, future directions, acknowledgments.

• Article PDF
• Rural reinvestment: A path forward to addressing geographic health inequities

Problem/Condition: A 2019 report quantified the higher percentage of potentially excess (preventable) deaths in U.S. nonmetropolitan areas compared with metropolitan areas during 2010–2017. In that report, CDC compared national, regional, and state estimates of preventable premature deaths from the five leading causes of death in nonmetropolitan and metropolitan counties during 2010–2017. This report provides estimates of preventable premature deaths for additional years (2010–2022).

Period Covered: 2010–2022.

Description of System: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate preventable premature deaths from the five leading causes of death among persons aged <80 years. CDC’s National Center for Health Statistics urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent’s county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Preventable premature deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Preventable premature deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and the District of Columbia.

Results: During 2010–2022, the percentage of preventable premature deaths among persons aged <80 years in the United States increased for unintentional injury (e.g., unintentional poisoning including drug overdose, unintentional motor vehicle traffic crash, unintentional drowning, and unintentional fall) and stroke, decreased for cancer and chronic lower respiratory disease (CLRD), and remained stable for heart disease. The percentages of preventable premature deaths from the five leading causes of death were higher in rural counties in all years during 2010–2022. When assessed by the six urban-rural county classifications, percentages of preventable premature deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan and fringe metropolitan) for the five leading causes of death during the study period.

During 2010–2022, preventable premature deaths from heart disease increased most in noncore (+9.5%) and micropolitan counties (+9.1%) and decreased most in large central metropolitan counties (−10.2%). Preventable premature deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan and large fringe metropolitan counties (−100.0%; benchmark achieved in both county categories in 2019). In all county categories, preventable premature deaths from unintentional injury increased, with the largest increases occurring in large central metropolitan (+147.5%) and large fringe metropolitan (+97.5%) counties. Preventable premature deaths from CLRD decreased most in large central metropolitan counties where the benchmark was achieved in 2019 and increased slightly in noncore counties (+0.8%). In all county categories, preventable premature deaths from stroke decreased from 2010 to 2013, remained constant from 2013 to 2019, and then increased in 2020 at the start of the COVID-19 pandemic. Percentages of preventable premature deaths varied across states by urban-rural county classification during 2010–2022.

Interpretation: During 2010–2022, nonmetropolitan counties had higher percentages of preventable premature deaths from the five leading causes of death than did metropolitan counties nationwide, across public health regions, and in most states. The gap between the most rural and most urban counties for preventable premature deaths increased during 2010–2022 for four causes of death (cancer, heart disease, CLRD, and stroke) and decreased for unintentional injury. Urban and suburban counties (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in preventable premature deaths from unintentional injury during 2010–2022, leading to a narrower gap between the already high (approximately 69% in 2022) percentage of preventable premature deaths in noncore and micropolitan counties. Sharp increases in preventable premature deaths from unintentional injury, heart disease, and stroke were observed in 2020, whereas preventable premature deaths from CLRD and cancer continued to decline. CLRD deaths decreased during 2017–2020 but increased in 2022. An increase in the percentage of preventable premature deaths for multiple leading causes of death was observed in 2020 and was likely associated with COVID-19–related conditions that contributed to increased mortality from heart disease and stroke.

Public Health Action: Routine tracking of preventable premature deaths based on urban-rural county classification might enable public health departments to identify and monitor geographic disparities in health outcomes. These disparities might be related to different levels of access to health care, social determinants of health, and other risk factors. Identifying areas with a high prevalence of potentially preventable mortality might be informative for interventions.

Premature deaths, all-cause mortality, and poor health outcomes are greater among residents of rural counties than of urban counties in the United States ( 1 ). In 2021, the all-cause age-adjusted death rate in the United States was 841.6 per 100,000 population. The gap in all-cause mortality between rural (nonmetropolitan) and urban (metropolitan) areas of the United States continues to widen. In 1999, the death rate in rural areas was 7% higher than in urban areas; by 2019, it was 20% higher ( 2 ). Describing premature mortality rates from the five leading causes of death (cancer, unintentional injury [e.g., unintentional poisoning including drug overdose, unintentional motor vehicle traffic crash, unintentional drowning, and unintentional fall], heart disease, stroke, and chronic lower respiratory disease [CLRD]) and related rural disparities might help guide public health messaging and interventions.

The risk for premature death is associated with modifiable factors that vary by disease ( 3 ). Four of the five leading risk factors for premature death are more prevalent in rural areas of the United States: using tobacco, obesity, physical inactivity, and drinking alcohol or drinking in excess ( 4 , 5 ). Extensive literature on social determinants of health has established the importance of community context in shaping all aspects of health ( 6 ). Structural factors (e.g., lower socioeconomic status, limited access to health care professionals, and limited job opportunities) increase the risk for premature death among rural residents ( 7 ).

Multiple factors influence the rural-urban gap in preventable premature deaths. Because each of the five leading causes of death is age related, these conditions are more prevalent in rural areas of the United States where residents typically are older than their urban counterparts. Working-age adults might leave rural areas to seek better economic opportunities elsewhere ( 8 ), and older persons might be more likely to retire in rural areas ( 9 ). However, the population’s age structure alone does not explain the disparity in mortality. Instead, differences in social circumstances, socioeconomic characteristics, health-related behaviors, and access to health care services affect mortality and potentially contribute to approximately half of all preventable premature deaths ( 10 ). County-level disparities in all-cause premature deaths by rurality, race, and ethnicity have been documented ( 11 ). Data on cause-specific preventable premature deaths from the leading causes of death by rurality, sex, race, and ethnicity are limited, and direct comparisons accounted for by these factors will be reported in subsequent analyses.

Rural public health needs and sociodemographic characteristics of rural populations are changing ( 12 ). Although the proportion of the U.S. population that lives in rural areas is gradually declining, any rural population growth can be attributed to in-migration, which might require sensitivity to cultural differences ( 13 , 14 ). With gradual declines in population, the wealth and tax bases of rural counties also are decreasing, resulting in reduced funding for social and health services ( 15 ).

In this analysis, mortality data were used to estimate the number and percentage of deaths from each of the five leading causes of death that could have been prevented if all states had similarly low death rates. Disparities in premature mortality from the five leading causes of death in rural areas in the United States during 2010–2022 also were estimated. The results of this analysis are intended to serve as a critical resource for policymakers, public health officials, and researchers striving to understand and address the root causes of preventable premature deaths.

This analysis used mortality data for U.S. residents from the National Vital Statistics System ( https://www.cdc.gov/nchs/index.htm ) to calculate preventable premature deaths by urban-rural county classification from the five leading causes of death during 2010–2022 (heart disease, cancer, unintentional injury, CLRD, and stroke). Deaths from COVID-19 were excluded to maintain consistency and facilitate the assessment of trends over time. Data for 2022 are provisional counts from January through June and were annualized for comparability with previous years.

The number of preventable premature deaths for a specific cause (also described as potentially preventable premature or excess deaths) is equal to the difference in the number of observed deaths among persons aged <80 years and the number of deaths expected if the mortality rate in all states were equivalent to the average rate of the three states with the lowest mortality. Rates in the three states define the benchmarks. The benchmark for each cause of death is derived from a unique set of three states.

Rural and urban categories were identified using the National Center for Health Statistics 2013 urban-rural classification scheme for counties ( 16 ). County of residence of the decedent was used to determine urban-rural county classification. The categories are 1: large central metropolitan (most urban), 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore (most rural).

Preventable premature deaths were calculated individually for the two nonmetropolitan categories (micropolitan and noncore) and the four metropolitan categories (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) as well as for the broader categories of metropolitan and nonmetropolitan. Analyses were restricted to deaths with an underlying cause of death from the five leading causes of death based on the International Classification of Diseases, 10th Revision (ICD-10): heart disease (I00–I09, I11, I13, and I20–I51), cancer (C00–C97), unintentional injury (V01–X59 and Y85–Y86), CLRD (J40–J47), and stroke (I60–I69). The analysis of preventable premature deaths during 2010–2022 was restricted to persons aged <80 years at the time of death. The age restriction is consistent with the average life expectancy for the U.S. population in 2010, which was approximately 79 years ( 17 ).

Age-specific mortality rates for each of the five leading causes of death were used to derive the number of preventable premature deaths using methods described elsewhere ( 18 ). Age groupings varied by cause of death. (Most were 10-year age groups; however, the size of the youngest age group ranged from 0 to 9 years for unintentional injury to 0 to 49 years for CLRD and cerebrovascular disease because deaths from those causes are rare among younger persons.) For each age group and cause of death, the death rates of the three states with the lowest rates during 2008–2010 (benchmark states) were averaged to produce benchmark rates ( 18 ) ( https://stacks.cdc.gov/view/cdc/42342 ). These benchmarks were chosen to represent the lowest death rates achievable by states at the beginning of the study period and did not vary by year to allow for the examination of trends over time. Although using time-varying benchmarks would better account for potential improvements over time in the benchmark rates, time-varying benchmarks also would make temporal and geographic comparisons more difficult. The same benchmarks were applied to both nonmetropolitan and metropolitan counties, and benchmarks were not adjusted for other characteristics that might affect death rates (e.g., race, ethnicity, socioeconomic status, and urbanicity). Deaths attributed to COVID-19 from 2020 through June 2022 were excluded from this study.

The numbers of preventable premature deaths for each cause of death were assumed to follow a Poisson distribution. SEs were calculated using standard formulas that incorporated the variance around both the observed and the expected counts ( 18 ), and pairwise z-tests were performed to determine whether the differences during 2010–2022 were statistically significant (p<0.05). All differences during 2010–2022 are statistically significant unless otherwise noted. The percentage of preventable premature deaths was calculated by dividing the number of preventable premature deaths by the total observed number of premature deaths.

The percentage of preventable premature deaths from cancer decreased from 2010 through June 2022 (from 21% to 0.3%) ( Figure 1 ). Regardless of urban-rural classification, all county categories experienced decreases ( Figure 2 ). However, the decreases in urban counties were larger than those in rural counties, which widened the rural-urban disparities in preventable premature deaths from cancer (Figure 2) ( Table ). The percentage of preventable premature deaths from cancer in noncore counties in 2022 (18.1%) was similar to the percentage in large central metropolitan counties in 2010 (17.9%).

The percentage of preventable premature deaths from heart disease decreased from 2010 through 2019 (from 33.5% to 28.8%), followed by a steep increase to 33.6% from 2020 through June 2022 (Figure 1). Increases from 2020 through June 2022 occurred across all rural-urban categories except for large central metropolitan counties, which experienced a decrease from 32.9% in 2020 to 30.1% in 2021 (Figure 2) (Table). Rural counties had the highest percentage of preventable premature deaths from heart disease in 2022 (45.8% in micropolitan counties and 49.4% in noncore counties) (Figure 2) (Table). Most states experienced an increase in preventable early deaths from heart disease and stroke (96% and 88% of states, respectively) from 2019 through June 2022 (Supplementary Table, https://stacks.cdc.gov/view/cdc/147842 ).

The percentage of preventable premature deaths from unintentional injury increased from 2010 to 2019 (from 38.8% to 53.8%), followed by a steep increase from 2019 to 2021 and a slight decrease through June 2022 to 63.5% (Figure 1). Increases in preventable premature deaths from unintentional injury during 2010–2022 were statistically significant for all metropolitan categories except micropolitan. Rural percentages were higher than in urban areas, but the gap narrowed (Figure 2). The percentages increased in all states except Wyoming, but the increase varied widely at the state level (Supplementary Table, https://stacks.cdc.gov/view/cdc/147842 ).

The percentage of preventable premature deaths from CLRD decreased from 2010 through 2022 (from 38.6% to 25.5%) (Figure 1). The percentage of preventable premature deaths varied widely when stratified by rural-urban county category, but all county categories except for noncore counties experienced decreases. Rural-urban disparities widened when large central metropolitan percentages decreased from 23.4% in 2010 to 0% in 2022, whereas the rural percentages hovered between 50.7% and 54.8% in 2022 (Figure 2) (Table).

The percentage of preventable premature deaths from stroke decreased slightly from 2010 through 2019 (32.4% to 26.4%), followed by an increase to 33.9% through June 2022 (Figure 1). Each rural-urban category experienced steep increases from 2019 to June 2022, except for noncore counties that experienced a slight decrease from 2021 to June 2022; rural counties had the highest percentages from January to June 2022 (42.0% in micropolitan counties and 40.9% in noncore counties) (Figure 2) (Table). The highest percentages of preventable premature deaths from stroke in 2022 were in southern states (Supplementary Table, https://stacks.cdc.gov/view/cdc/147842 ).

Rural residents, particularly those in noncore counties, experienced high percentages of preventable premature deaths during the study period. The rural-urban disparities in premature deaths varied by cause of death. However, disparities were not limited to place of residence. Disparities in all-cause premature deaths also were associated with other demographic factors (e.g., sex, race, and ethnicity) ( 11 ). For example, the highest rates of premature deaths were observed in rural counties where a majority of the population was Black, African American, American Indian, or Alaska Native ( 11 ). To address disparities in preventable premature deaths across rural and urban counties, data on disparities in cause-specific premature deaths from the five leading causes by rural-urban county category, race, and ethnicity are needed to inform interventions and health care policies for specific racial and ethnic groups. A follow-up of this analysis stratified by race and ethnicity will be published in subsequent reports, further contributing evidence to guide existing and new programs and policies.

Overall, the decrease in preventable premature deaths from cancer was substantial and was greatest in urban counties where access to preventive services, treatment, survivor care, and specialty care is much higher than in rural counties ( 19 ). Large central metropolitan and fringe metropolitan areas achieved the benchmark rates in 2019. This is consistent with overall declines in cancer mortality, which decreased 27% between 2001 and 2020 ( 20 ). The decrease in preventable premature deaths likely reflects multiple factors. Increases in recommended screening for the leading causes of deaths from cancer (e.g., lung, colon, cervical, and female breast) have led to earlier detection, when treatment is more effective, and prevention by detecting cellular changes before they turn into cancer, as in the case of colorectal cancer ( 21 ). Increases in vaccination rates for cancer-causing viruses and decreases in prevalence of risk factors (e.g., combustible tobacco use) also have driven cancer mortality downward ( 22 ). Access to these cancer prevention and early detection strategies was increased with the expansion of Medicaid ( 23 ). New cancer treatments and therapies, specifically for lung cancer and melanoma, also have led to longer survival for those with a cancer diagnosis ( 24 ). CDC conducted a demonstration project on how to best provide care for persons living in rural areas who had cancer diagnosed ( 25 ). Although cancer is categorized as a single disease group in this analysis, each cancer site has different risk factors, has varying treatment methods, and can manifest itself in different ways among groups by sex, age, race, and ethnicity. Preventable premature death might vary depending on the cancer site and might not have decreased for cancers with increasing prevalence of risk factors (e.g., obesity), no recommended screening modalities, or therapies that have not changed. Lung cancer, the leading cause of cancer mortality, accounted for 23% of all cancer deaths in 2020 ( 20 ). Geographic differences in combustible tobacco use and use of lung cancer screening likely partially drive differences in lung cancer mortality. Access to lung cancer screening facilities is more limited in rural counties than in urban counties ( 26 ). Despite overall reductions in preventable premature deaths from cancer, premature deaths surpass the national average in micropolitan and noncore counties, highlighting the need in rural areas to reduce cancer-related premature deaths. Because more urban areas surpassed the 2010 benchmarks for cancer death rates in 2019, future updates to the cancer-specific benchmarks using more recent years of data might better reflect the lowest achievable death rates.

Unintentional Injury

The worsening and expanding drug overdose epidemic, increases in motor vehicle traffic fatalities, and falls drive the growth in preventable premature deaths from unintentional injury ( 27 ). Narrowing rural-urban disparities in the percentage of preventable premature deaths from unintentional injury were driven by worsening rates of preventable mortality in more urban areas, with the percentage more than doubling in large central metropolitan areas over the study period. For drug overdoses, access to medications for opioid use disorder continues to be more limited in rural counties, as evidenced by low buprenorphine dispensing rates and reduced treatment capacity ( 28 ). For motor vehicle traffic crashes, rural residents have an increased risk for death and are less likely than urban residents to wear seat belts ( 29 ). Evidence-based interventions reduce rural-urban disparities in seat belt use and motor vehicle death rates ( 30 ). Many fall risk factors are modifiable, implying that many falls can be prevented ( 31 ).

Heart Disease and Stroke

Disparities in preventable premature deaths from heart disease and stroke between rural and urban areas existed across the study period. These gaps increased from 2019 to June 2022, except in large central metropolitan counties where a decrease of three percentage points was observed from 2020 to 2021. Increases in preventable premature deaths from heart disease and stroke in 2020 and 2021 were likely associated with COVID-19–related conditions that contributed to risk-associated increased mortality from heart disease and stroke ( 32 ). Increases in systolic and diastolic blood pressure, a leading risk factor for heart disease and stroke, were observed among all age groups when comparing 2020 with 2019 ( 33 ). Inequities in control of hypertension (i.e., systolic blood pressure values of ≥130 mm Hg, diastolic blood pressure of >80 mm Hg, or both) were observed during the COVID-19 pandemic and are related to insufficient health care access, medication adherence, and monitoring ( 34 ). Patients might have delayed or avoided seeking emergency care when experiencing a life-threatening event during the height of the COVID-19 pandemic ( 35 ). Emergency department visits for heart attack and stroke decreased by 20% during the weeks after the declaration of COVID-19 as a national emergency on March 13, 2020, and hospital admissions for heart attack and stroke decreased during the pandemic ( 35 ). In addition, COVID-19 was associated with an increased risk for stroke and heart disease ( 36 , 37 ).

Chronic Lower Respiratory Disease

Despite the overall decrease during 2010–2020 (because of decreases observed in larger urban areas), the percentage of preventable premature deaths from CLRD was relatively stable in medium and small urban counties and rural counties during 2010–2015. During 2010–2022, the sharpest decline in preventable premature death from CLRD in urban areas occurred from 2019 through 2021 and could be the result of deaths from COVID-19 that otherwise would have been attributable to CLRD. Persons with CLRD (e.g., chronic obstructive pulmonary disease) are at increased risk for death from COVID-19 ( 38 ).

The findings in this report are subject to at least six limitations. First, applying benchmarks (e.g., the three states with the lowest rates) to all urban-rural county categories facilitates comparisons but might not represent the lowest death rates achievable by certain subgroups. For example, large metropolitan areas met the benchmarks for cancer in 2019 and, therefore, had negative estimates of preventable premature deaths during 2019–2022. In these instances, negative estimates were truncated at zero to indicate that the 2010 benchmarks had been achieved. Using urban-rural–specific benchmarks would likely result in larger numbers of preventable premature deaths in certain categories and larger rural-urban disparities in certain cases. However, using benchmarks specific to state, age, cause, and subgroup (e.g., urban-rural, sex, race, and ethnicity) also could lead to less stable estimates because of smaller numbers of deaths when stratifying by multiple demographic and geographic dimensions. Second, the differences cannot be attributed solely to population size and geographic location because risk factors do not occur randomly in populations and are related to well-known social, demographic, environmental, economic, and geographic attributes of the neighborhoods in which persons live and work ( 39 ). Third, estimates of preventable premature deaths using historical benchmarks (e.g., 2008–2010) might not reflect improvements in mortality that could have occurred in a later year. For example, the 2010 benchmarks for cancer are higher than if benchmarks were based on 2022 data because of decreases in cancer deaths during 2010–2022. Fourth, the numbers of preventable premature deaths by cause are not necessarily independent, and the numbers of potentially excess deaths from the five causes cannot be combined to generate a total. For example, the number of preventable premature deaths from cancer might be lower because persons with cancer died from another cause (e.g., heart disease). Fifth, deaths from certain causes might have increased partly because of COVID-19 and the pandemic. Specifically, misclassification of deaths from COVID-19 that were attributed to other causes (because of lack of testing or reporting on the death certificate) could have contributed to a greater number of deaths across other causes and by rural and urban areas. In addition, certain causes of death might have increased because of indirect pandemic-related effects (e.g., reduced access to emergency care or life-saving treatments). Finally, data for 2022 were based on provisional data from the first half of the year, and results might differ when the final data for the full year are available.

The findings in this report demonstrate the value of analyzing preventable premature deaths according to the six National Center for Health Statistics 2013 urban-rural county classifications. Reporting trends in preventable premature deaths over a 12-year period highlights differences over time and might aid in understanding underlying structural, environmental, and social risk factors. Because of increasing percentages of preventable premature deaths in recent years for specific causes of death and certain demographic groups, these data might augment traditional rate comparisons and help guide focused public health interventions. Comparing the findings in this report with data from tools such as the CDC Interactive Atlas of Heart Disease and Stroke ( https://www.cdc.gov/dhdsp/maps/atlas/index.htm ) might help identify social determinants of health, health care infrastructure, and public policies that could be related to increases or decreases in preventable premature deaths in specific nonmetropolitan areas. Detailed community-based evaluations might clarify how various risk factors and social determinants of health relate to premature mortality and related rural-urban disparities. In addition, other methods for developing benchmark rates might be helpful, including using benchmarks based on the nonmetropolitan areas with the lowest death rates, or updating benchmarks based on more recent data, especially for causes of death (e.g., cancer) that have decreased substantially over time. In addition, more detailed analyses by race, ethnicity, and age, along with examining preventable deaths among persons aged >80 years, and preventable premature deaths from other causes (especially causes that are more prevalent in rural counties) might be informative.

Defining preventable premature deaths within the context of the five leading causes of death does not capture the full spectrum of preventable mortality. The degree to which these deaths could be prevented is related to various factors, including distinct prevention strategies, varying risk factors, and the availability of effective interventions, all of which vary by cause. Not all premature deaths are equally preventable among the leading causes or even within each specific leading cause category, as exemplified by certain types of cancer ( 40 ).

Routine tracking of preventable premature deaths by urban-rural county classification might facilitate the identification of areas with high prevalence of preventable premature mortality along with related geographic and urban-rural disparities in health outcomes. These disparities might be related to different levels of access to health care, social determinants of health, and other risk factors. Findings might help guide more focused interventions to reduce premature death from the five leading causes of death and reduce disparities by rural-urban residence and geographic region.

Health care professionals, medical examiners, coroners, vital registrars, and vital statistics offices across the United States.

Corresponding author: Macarena C. García, Office of Science and Medicine, Office of the Assistant Secretary of Health, U.S. Department of Health and Human Services, Washington, DC. Telephone: 678-770-6220; Email: [email protected] .

1 Office of Science and Medicine, Office of the Assistant Secretary of Health, U.S. Department of Health and Human Services, Washington, DC; 2 National Center for Health Statistics, CDC, Hyattsville, Maryland; 3 National Center for State, Tribal, Local, and Territorial Public Health Infrastructure and Workforce, CDC, Atlanta, Georgia; 4 National Center for Injury Prevention and Control, CDC, Atlanta, Georgia; 5 National Center for Chronic Disease Prevention and Health Promotion, CDC, Atlanta, Georgia

Conflicts of Interest

All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

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FIGURE 1 . Percentages of preventable premature deaths* among persons aged <80 years from the five leading causes of death, by year — National Vital Statistics System, United States, 2010–2022 †

* Preventable premature deaths are defined as deaths among persons aged <80 years in excess of the number that would be expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates).

† Data for 2022 are provisional counts from January through June and were annualized for comparability with previous years.

FIGURE 2 . Percentages of preventable premature deaths* among persons aged <80 years from the five leading causes of death, by rural-urban county classification and year — National Vital Statistics System, United States, 2010–2022 †

* Preventable premature deaths are defined as deaths among persons aged <80 years in excess of the number that would be expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Estimates of potentially excess deaths that were negative were set to zero. These negative excess estimates occurred in cases where deaths were fewer than expected (i.e., mortality was lower than benchmark rates). † Data for 2022 are provisional counts from January through June and were annualized for comparability with previous years. § Includes unintentional poisoning (e.g., drug overdose), unintentional motor vehicle traffic crash, unintentional drowning, and unintentional fall ( https://www.cdc.gov/injury/wisqars/animated-leading-causes.html ).

Suggested citation for this article: García MC, Rossen LM, Matthews K, et al. Preventable Premature Deaths from the Five Leading Causes of Death in Nonmetropolitan and Metropolitan Counties, United States, 2010–2022. MMWR Surveill Summ 2024;73(No. SS-2):1–11. DOI: http://dx.doi.org/10.15585/mmwr.ss7302a1 .

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Advancing Neurological Research

Neuroscience has long been challenged by the limitations of existing imaging technologies, especially in the fields of neurology, oncology and psychiatry. SIGNA MAGNUS aims to change that narrative by offering unprecedented clarity and detail in imaging procedures using the latest deep-learning algorithms. By focusing solely on the head, this MR scanner can delve deep into the brain's microstructure, microvasculature and function, providing researchers with a clearer picture of neurological diseases and disorders.

SIGNA MAGNUS boasts GE HealthCare's most advanced 3.0T MR imaging technology, tailored specifically for head-only imaging. Equipped with HyperG gradient technology, featuring 300 mT/m and 750 T/m/s, the system enables the detection of finer details that were previously unattainable. Its superior gradient performance allows for advanced anatomical, diffusion and functional techniques, supported by cutting-edge deep-learning algorithms.

Potential Application

Currently, only a fraction of the world's population suffering from neurological disorders can be diagnosed using MRI. SIGNA MAGNUS represents a significant leap forward in expanding the clinical applications of MRI, particularly in the realm of neurology. By offering superior gradient performance and advanced imaging techniques, SIGNA MAGNUS can help researchers explore new parameters and biomarkers, ultimately enhancing the ability to diagnose, understand and treat complex neurological conditions.

With SIGNA MAGNUS, GE HealthCare is setting new benchmarks in medical research and clinical patient care. This system reflects GE HealthCare's commitment to research and development, as well as its dedication to pushing the boundaries of MR imaging. The potential impact of SIGNA MAGNUS on patient outcomes and our understanding of the human brain is profound, paving the way for new discoveries in neuroscience.

GE HealthCare's collaboration with leading research institutions, such as Brigham and Women's Hospital, demonstrates its commitment to fostering innovation and collaboration in the field of medical imaging. By working closely with researchers and clinicians, GE HealthCare ensures that every scientific advancement translates into meaningful health outcomes for patients worldwide.

GE HealthCare Technologies Inc. Price

GE HealthCare Technologies Inc. price | GE HealthCare Technologies Inc. Quote

Zacks Rank & Stocks to Consider

GE Healthcare currently carries a Zacks Rank #3 (Hold).

Some better-ranked stocks in the broader medical space that have announced quarterly results are  Align Technology, Inc.  ALGN,  Ecolab  ECL and  Boston Scientific Corporation  BSX.

Align Technology, carrying a Zacks Rank of 2 (Buy) at present, reported first-quarter 2024 adjusted earnings per share (EPS) of $2.14, which beat the Zacks Consensus Estimate by 8.1%. You can see  the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

Revenues of $997.4 million outpaced the consensus mark by 2.6%.

Align Technology has a long-term estimated growth rate of 6.9%. Its earnings surpassed estimates in three of the trailing four quarters and missed once, delivering an average surprise of  5.9%.

Ecolab, carrying a Zacks Rank of 2 at present, has an estimated long-term growth rate of 13.3%. Its earnings surpassed estimates in each of the trailing four quarters, delivering an average surprise of 1.7%.

Ecolab’s shares have risen 33.8% against the industry’s 9.3% decline in the past year.

Boston Scientific reported first-quarter 2024 adjusted EPS of 56 cents, which beat the Zacks Consensus Estimate by 9.8%. Revenues of $3.86 billion surpassed the Zacks Consensus Estimate by 4.9%. The company currently carries a Zacks Rank #2.

BSX has a long-term estimated growth rate of 12.5%. Its earnings surpassed estimates in each of the trailing four quarters, delivering an average surprise of 7.5%.

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