examples of limitations and delimitations in qualitative research

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Research Limitations & Delimitations

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

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.

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

Delimitations in Research – Types, Examples and Writing Guide

Table of Contents

Delimitations

Delimitations in research define the boundaries and scope of a study, outlining what will and will not be addressed. They clarify the choices made by the researcher to focus on specific aspects of the topic, study area, population, or methodology. While delimitations set limits on the study’s scope, they also help improve the clarity, feasibility, and relevance of the research by narrowing down its objectives.

Definition of Delimitations

Delimitations are the intentionally established boundaries of a study that specify its scope and constraints. They outline the choices made regarding the study’s focus, sample, methodology, and timeframe, helping readers understand the study’s limitations and providing context for the findings.

Key Aspects of Delimitations:

• Define the study’s scope and boundaries.
• Explain why certain elements are included or excluded.
• Address factors that may impact generalizability.

For instance, a study on employee motivation might choose to focus only on employees within a specific industry. This choice becomes a delimitation, clarifying that findings may not apply to other sectors.

Types of Delimitations in Research

• Definition : These delimitations specify the target population for the study, such as age group, geographical area, or specific characteristics of participants.
• Example : A study on college students’ social media usage that only includes students from a specific university.
• Purpose : Population delimitations help researchers focus on a specific group, making the study more manageable and relevant.
• Definition : Conceptual delimitations define the study’s focus, including the concepts, variables, or theories the research will examine.
• Example : A study on mental health that examines only depression and anxiety, excluding other mental health disorders.
• Purpose : Conceptual delimitations clarify which aspects of a broader topic are being explored, providing a clear focus for analysis.
• Definition : These delimitations outline the methods and approaches the researcher chooses to use, including data collection techniques, sample size, or research design.
• Example : Using a survey instead of in-depth interviews in a study on job satisfaction.
• Purpose : Methodological delimitations specify the research design choices, helping readers understand the approach taken and its impact on the findings.
• Definition : Instrument delimitations refer to the specific tools, measures, or instruments used in the study.
• Example : Using a standardized questionnaire rather than a customized one to measure employee satisfaction.
• Purpose : Instrument delimitations highlight the constraints imposed by using certain tools, impacting how data is collected and interpreted.
• Definition : These delimitations specify the timeframe for data collection or the period the study covers.
• Example : A study that examines social media trends from 2019 to 2021.
• Purpose : Temporal delimitations limit the scope to a certain period, impacting the study’s relevance and potential for generalization over time.
• Definition : These delimitations confine the study to a specific location or region.
• Example : A study on urban public transportation efficiency limited to New York City.
• Purpose : Geographical delimitations set the study within a particular context, aiding in the relevance and feasibility of the research.

Examples of Delimitations in Research

• A study investigating the effect of physical activity on academic performance may choose to include only high school students from a single district. This population delimitation helps narrow the focus but may limit generalizability to students in other regions.
• Research on customer satisfaction may choose to focus only on customer service quality, excluding factors like product quality and price. This conceptual delimitation focuses on one aspect of satisfaction, simplifying the study’s scope.
• In a study exploring employee motivation, the researcher may choose to use surveys instead of interviews, as surveys allow for data collection from a larger sample. This methodological delimitation impacts the depth of data obtained but enhances the feasibility.
• A study on COVID-19 vaccination attitudes might limit its analysis to data collected between 2020 and 2022, providing a specific timeframe that contextualizes the findings.

Why Are Delimitations Important?

Delimitations are essential in research for several reasons:

• Clarity : They provide clarity on the study’s focus, allowing readers to understand its scope.
• Feasibility : By defining the scope, delimitations make the study manageable within available resources and time constraints.
• Transparency : They communicate the researcher’s choices openly, helping readers interpret the findings accurately.
• Generalizability : Delimitations help define how broadly findings can be applied, addressing potential limitations in the study’s applicability.

How to Write Delimitations in Research

• Clearly state the decisions that limit the study’s scope, such as population, location, and timeframe. Explain why these choices were made to provide context.
• Example : “This study focuses on the role of social media in shaping public opinion in the United States between 2019 and 2021. These delimitations were chosen due to data accessibility and to align with current social trends.”
• Provide a rationale for each delimitation to clarify its purpose. This justification helps readers understand why specific decisions were necessary for the study’s objectives.
• Example : “The study focuses solely on university students to maintain a consistent demographic, as previous research indicates that age can significantly impact social media usage patterns.”
• Recognize the impact of the delimitations on the study’s generalizability. Mention any limitations that readers should consider when interpreting the findings.
• Example : “While the study provides insights into social media use among university students, findings may not be generalizable to older age groups or individuals outside academic settings.”
• Avoid overly broad or vague delimitations. Keep each delimitation clear, specific, and relevant to the study’s objectives.
• Example : “The study investigates customer satisfaction among small business clients in urban areas, as rural customers may have distinct expectations due to geographic factors.”
• In a research paper, delimitations are often included in the methodology or introduction section. Ensure that they are easy to locate and appropriately placed.
• Example : Include delimitations in a subsection titled “Delimitations” within the methodology to clearly separate them from other methodological considerations.

Sample Paragraph for Delimitations

“This study explores the relationship between work-life balance and job satisfaction among employees in the tech industry within the United States. The population is limited to full-time employees aged 25-45 to maintain consistency in work hours and career stages. The study uses an online survey to collect data, as surveys allow for larger sample sizes and more efficient data collection. Additionally, the study is restricted to data collected between January and December 2023 to provide a current snapshot of the industry. While these delimitations narrow the scope of the research, they ensure a focused analysis on specific factors influencing job satisfaction in the tech sector.”

This sample paragraph highlights the study’s delimitations and provides a rationale for each, allowing readers to understand the scope and limitations.

Delimitations in research are essential for defining the boundaries of a study, guiding its focus, and helping readers interpret the findings within a specific context. By understanding and clearly stating delimitations, researchers can ensure transparency and maintain the study’s relevance and feasibility. A well-defined set of delimitations helps both the researcher and readers understand the scope, limitations, and generalizability of the research.

• Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . SAGE Publications.
• Kumar, R. (2014). Research Methodology: A Step-by-Step Guide for Beginners . SAGE Publications.
• Flick, U. (2014). An Introduction to Qualitative Research . SAGE Publications.
• Maxwell, J. A. (2013). Qualitative Research Design: An Interactive Approach . SAGE Publications.
• Patton, M. Q. (2015). Qualitative Research & Evaluation Methods: Integrating Theory and Practice . SAGE Publications.

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Researcher, Academic Writer, Web developer

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Research Limitations: Key Insights and Examples

Introduction.

Research is a fundamental component of academic and professional fields, driving innovation, informing policy, and enhancing our understanding of complex issues. However, every research endeavor comes with its own set of limitations that can impact the validity and applicability of its findings. Understanding these research limitations is crucial for researchers, practitioners, and policymakers alike, as it allows for a more nuanced interpretation of results and encourages critical thinking about the implications of the research.

In this article, we will explore the meaning of research limitations, common examples, impacts and strategies to address them, ultimately providing key insights that can enhance the quality and reliability of research outcomes.

Defining Research Limitations

Research limitations refer to the inherent weaknesses or constraints within a study that may affect its outcomes and conclusions . These limitations can arise from various factors, including the research design, methodology , sample size, and even the researcher’s biases. In essence, they represent the boundaries of the research, highlighting areas where the findings may not be fully generalizable or applicable. Understanding these limitations is crucial, as they provide context for interpreting the results and assessing the validity of the research.

In the realm of academic and scientific inquiry, research limitations can be categorized into two main types: methodological limitations and researcher-related limitations . Methodological limitations stem from the design and execution of the study, such as the choice of data collection methods , sample size, and the overall research framework .

On the other hand, researcher-related limitations may include biases , lack of experience, or insufficient resources that can influence the research process. By clearly defining these limitations, researchers can better communicate the scope and reliability of their findings , ultimately contributing to a more nuanced understanding of the research landscape.

Common Research Limitations Examples

Research limitations can manifest in various forms, impacting the overall validity and reliability of a study.

Restricted Access to Information

One common limitation is the restricted access to information, which can hinder researchers from obtaining comprehensive data necessary for thorough analysis . For instance, in studies involving sensitive topics, researchers may face challenges in gathering data due to privacy concerns or institutional restrictions. Additionally, limited access to reliable data sources can lead to a narrow scope of research, ultimately affecting the conclusions drawn from the study.

Sample Size Issues

Another prevalent limitation is the issue of sample size. A small sample may not accurately represent the larger population, leading to skewed results and reduced generalizability.

Time Constraints

Furthermore, time constraints often force researchers to rush their studies, potentially compromising the depth and quality of their findings. This is particularly evident in longitudinal studies, where the effects of time on variables are crucial for understanding trends and patterns.

Cultural Biases and Language Fluency

Lastly, cultural biases and language fluency can also pose significant challenges, as they may influence the interpretation of data and the researcher’s perspective, ultimately affecting the study’s outcomes.

Impact of Research Limitations on Findings

The importance of recognizing research limitations.

Research limitations can significantly influence the interpretation and applicability of study findings. When researchers fail to acknowledge these limitations, they risk presenting a skewed understanding of their results, which can mislead stakeholders and the broader scientific community. For instance, if a study’s sample size is too small or not representative of the target population, the conclusions drawn may not be generalizable, leading to erroneous assumptions about the wider implications of the research. Thus, recognizing and articulating these limitations is crucial for maintaining the integrity of the research process.

Enhancing Research Credibility through Transparency

Moreover, the impact of research limitations extends beyond mere interpretation; it can also affect the credibility of the research itself. Acknowledging limitations demonstrates transparency and honesty, which can enhance the trustworthiness of the findings. Conversely, neglecting to address these weaknesses may lead to skepticism among peers and reviewers, potentially undermining the study’s contributions to the field.

Strategies to Address Research Limitations

Clearly identify and articulate limitations.

One effective strategy is to clearly identify and articulate the limitations at the outset of the research. By doing so, researchers can set realistic expectations for their findings and guide readers in interpreting the results.

Using Mixed-Methods to Mitigate Research Limitations

Additionally, employing a mixed-methods approach can help mitigate certain limitations by combining qualitative and quantitative data, thus providing a more comprehensive understanding of the research question . This strategy not only enriches the data but also allows for triangulation, which can validate findings across different methodologies.

Proposing Future Research Directions

Another important strategy is to propose future research directions that can build upon the limitations identified in the current study. By suggesting specific areas for further investigation, researchers can encourage others to explore unresolved questions and enhance the overall body of knowledge.

Utilizing Robust Data Collection

Furthermore, utilizing robust data collection methods and ensuring a diverse sample can help reduce biases and improve the generalizability of the findings.

Strengthening Research through Peer Review and Feedback

Lastly, engaging in peer review and seeking feedback from colleagues can provide valuable insights into potential limitations that may have been overlooked, ultimately strengthening the research design.

In conclusion, understanding research limitations is crucial for both researchers and consumers of research. Acknowledging these limitations not only enhances the credibility of the study but also provides a clearer context for interpreting the findings. By recognizing the constraints under which research is conducted, stakeholders can make more informed decisions and apply the results more judiciously.

Furthermore, embracing the discussion of limitations fosters a culture of transparency and continuous improvement in research methodologies. As the landscape of research evolves, so too does the need for a nuanced understanding of its limitations. Future research endeavors should prioritize the identification and articulation of limitations, ensuring that they are not merely an afterthought but an integral part of the research narrative. By doing so, researchers can contribute to a more robust body of knowledge that acknowledges the complexities of their work, ultimately leading to more reliable and applicable findings in various fields.

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Stating the Obvious: Writing Assumptions, Limitations, and Delimitations

During the process of writing your thesis or dissertation, you might suddenly realize that your research has inherent flaws. Don’t worry! Virtually all projects contain restrictions to your research. However, being able to recognize and accurately describe these problems is the difference between a true researcher and a grade-school kid with a science-fair project. Concerns with truthful responding, access to participants, and survey instruments are just a few of examples of restrictions on your research. In the following sections, the differences among delimitations, limitations, and assumptions of a dissertation will be clarified.

Delimitations

Delimitations are the definitions you set as the boundaries of your own thesis or dissertation, so delimitations are in your control. Delimitations are set so that your goals do not become impossibly large to complete. Examples of delimitations include objectives, research questions, variables, theoretical objectives that you have adopted, and populations chosen as targets to study. When you are stating your delimitations, clearly inform readers why you chose this course of study. The answer might simply be that you were curious about the topic and/or wanted to improve standards of a professional field by revealing certain findings. In any case, you should clearly list the other options available and the reasons why you did not choose these options immediately after you list your delimitations. You might have avoided these options for reasons of practicality, interest, or relativity to the study at hand. For example, you might have only studied Hispanic mothers because they have the highest rate of obese babies. Delimitations are often strongly related to your theory and research questions. If you were researching whether there are different parenting styles between unmarried Asian, Caucasian, African American, and Hispanic women, then a delimitation of your study would be the inclusion of only participants with those demographics and the exclusion of participants from other demographics such as men, married women, and all other ethnicities of single women (inclusion and exclusion criteria). A further delimitation might be that you only included closed-ended Likert scale responses in the survey, rather than including additional open-ended responses, which might make some people more willing to take and complete your survey. Remember that delimitations are not good or bad. They are simply a detailed description of the scope of interest for your study as it relates to the research design. Don’t forget to describe the philosophical framework you used throughout your study, which also delimits your study.

Limitations

Limitations of a dissertation are potential weaknesses in your study that are mostly out of your control, given limited funding, choice of research design, statistical model constraints, or other factors. In addition, a limitation is a restriction on your study that cannot be reasonably dismissed and can affect your design and results. Do not worry about limitations because limitations affect virtually all research projects, as well as most things in life. Even when you are going to your favorite restaurant, you are limited by the menu choices. If you went to a restaurant that had a menu that you were craving, you might not receive the service, price, or location that makes you enjoy your favorite restaurant. If you studied participants’ responses to a survey, you might be limited in your abilities to gain the exact type or geographic scope of participants you wanted. The people whom you managed to get to take your survey may not truly be a random sample, which is also a limitation. If you used a common test for data findings, your results are limited by the reliability of the test. If your study was limited to a certain amount of time, your results are affected by the operations of society during that time period (e.g., economy, social trends). It is important for you to remember that limitations of a dissertation are often not something that can be solved by the researcher. Also, remember that whatever limits you also limits other researchers, whether they are the largest medical research companies or consumer habits corporations. Certain kinds of limitations are often associated with the analytical approach you take in your research, too. For example, some qualitative methods like heuristics or phenomenology do not lend themselves well to replicability. Also, most of the commonly used quantitative statistical models can only determine correlation, but not causation.

Assumptions

Assumptions are things that are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis. In other words, any scholar reading your paper will assume that certain aspects of your study is true given your population, statistical test, research design, or other delimitations. For example, if you tell your friend that your favorite restaurant is an Italian place, your friend will assume that you don’t go there for the sushi. It’s assumed that you go there to eat Italian food. Because most assumptions are not discussed in-text, assumptions that are discussed in-text are discussed in the context of the limitations of your study, which is typically in the discussion section. This is important, because both assumptions and limitations affect the inferences you can draw from your study. One of the more common assumptions made in survey research is the assumption of honesty and truthful responses. However, for certain sensitive questions this assumption may be more difficult to accept, in which case it would be described as a limitation of the study. For example, asking people to report their criminal behavior in a survey may not be as reliable as asking people to report their eating habits. It is important to remember that your limitations and assumptions should not contradict one another. For instance, if you state that generalizability is a limitation of your study given that your sample was limited to one city in the United States, then you should not claim generalizability to the United States population as an assumption of your study. Statistical models in quantitative research designs are accompanied with assumptions as well, some more strict than others. These assumptions generally refer to the characteristics of the data, such as distributions, correlational trends, and variable type, just to name a few. Violating these assumptions can lead to drastically invalid results, though this often depends on sample size and other considerations.

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Scope and Delimitations – Explained & Example

• By DiscoverPhDs
• October 2, 2020

What Is Scope and Delimitation in Research?

The scope and delimitations of a thesis, dissertation or research paper define the topic and boundaries of the research problem to be investigated.

The scope details how in-depth your study is to explore the research question and the parameters in which it will operate in relation to the population and timeframe.

The delimitations of a study are the factors and variables not to be included in the investigation. In other words, they are the boundaries the researcher sets in terms of study duration, population size and type of participants, etc.

Difference Between Delimitations and Limitations

Delimitations refer to the boundaries of the research study, based on the researcher’s decision of what to include and what to exclude. They narrow your study to make it more manageable and relevant to what you are trying to prove.

Limitations relate to the validity and reliability of the study. They are characteristics of the research design or methodology that are out of your control but influence your research findings. Because of this, they determine the internal and external validity of your study and are considered potential weaknesses.

In other words, limitations are what the researcher cannot do (elements outside of their control) and delimitations are what the researcher will not do (elements outside of the boundaries they have set). Both are important because they help to put the research findings into context, and although they explain how the study is limited, they increase the credibility and validity of a research project.

Guidelines on How to Write a Scope

A good scope statement will answer the following six questions:

• Why – the general aims and objectives (purpose) of the research.
• What – the subject to be investigated, and the included variables.
• Where – the location or setting of the study, i.e. where the data will be gathered and to which entity the data will belong.
• When – the timeframe within which the data is to be collected.
• Who – the subject matter of the study and the population from which they will be selected. This population needs to be large enough to be able to make generalisations.
• How – how the research is to be conducted, including a description of the research design (e.g. whether it is experimental research, qualitative research or a case study), methodology, research tools and analysis techniques.

To make things as clear as possible, you should also state why specific variables were omitted from the research scope, and whether this was because it was a delimitation or a limitation. You should also explain why they could not be overcome with standard research methods backed up by scientific evidence.

How to Start Writing Your Study Scope

Use the below prompts as an effective way to start writing your scope:

• This study is to focus on…
• This study covers the…
• This study aims to…

Guidelines on How to Write Delimitations

Since the delimitation parameters are within the researcher’s control, readers need to know why they were set, what alternative options were available, and why these alternatives were rejected. For example, if you are collecting data that can be derived from three different but similar experiments, the reader needs to understand how and why you decided to select the one you have.

Your reasons should always be linked back to your research question, as all delimitations should result from trying to make your study more relevant to your scope. Therefore, the scope and delimitations are usually considered together when writing a paper.

How to Start Writing Your Study Delimitations

Use the below prompts as an effective way to start writing your study delimitations:

• This study does not cover…
• This study is limited to…
• The following has been excluded from this study…

Examples of Delimitation in Research

Examples of delimitations include:

• research objectives,
• research questions,
• research variables,
• target populations,
• statistical analysis techniques .

Examples of Limitations in Research

Examples of limitations include:

• Issues with sample and selection,
• Insufficient sample size, population traits or specific participants for statistical significance,
• Lack of previous research studies on the topic which has allowed for further analysis,
• Limitations in the technology/instruments used to collect your data,
• Limited financial resources and/or funding constraints.

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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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21 Research Limitations Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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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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Scope and Delimitations in Research

Delimitations are the boundaries that the researcher sets in a research study, deciding what to include and what to exclude. They help to narrow down the study and make it more manageable and relevant to the research goal.

Updated on October 19, 2022

All scientific research has boundaries, whether or not the authors clearly explain them. Your study's scope and delimitations are the sections where you define the broader parameters and boundaries of your research.

The scope details what your study will explore, such as the target population, extent, or study duration. Delimitations are factors and variables not included in the study.

Scope and delimitations are not methodological shortcomings; they're always under your control. Discussing these is essential because doing so shows that your project is manageable and scientifically sound.

This article covers:

• What's meant by “scope” and “delimitations”
• Why these are integral components of every study
• How and where to actually write about scope and delimitations in your manuscript
• Examples of scope and delimitations from published studies

What is the scope in a research paper?

Simply put, the scope is the domain of your research. It describes the extent to which the research question will be explored in your study.

Articulating your study's scope early on helps you make your research question focused and realistic.

It also helps decide what data you need to collect (and, therefore, what data collection tools you need to design). Getting this right is vital for both academic articles and funding applications.

What are delimitations in a research paper?

Delimitations are those factors or aspects of the research area that you'll exclude from your research. The scope and delimitations of the study are intimately linked.

Essentially, delimitations form a more detailed and narrowed-down formulation of the scope in terms of exclusion. The delimitations explain what was (intentionally) not considered within the given piece of research.

Scope and delimitations examples

Use the following examples provided by our expert PhD editors as a reference when coming up with your own scope and delimitations.

Scope example

Your research question is, “What is the impact of bullying on the mental health of adolescents?” This topic, on its own, doesn't say much about what's being investigated.

The scope, for example, could encompass:

• Variables: “bullying” (dependent variable), “mental health” (independent variable), and ways of defining or measuring them
• Bullying type: Both face-to-face and cyberbullying
• Target population: Adolescents aged 12–17
• Geographical coverage: France or only one specific town in France

Delimitations example

Look back at the previous example.

Exploring the adverse effects of bullying on adolescents' mental health is a preliminary delimitation. This one was chosen from among many possible research questions (e.g., the impact of bullying on suicide rates, or children or adults).

Delimiting factors could include:

• Research design : Mixed-methods research, including thematic analysis of semi-structured interviews and statistical analysis of a survey
• Timeframe : Data collection to run for 3 months
• Population size : 100 survey participants; 15 interviewees
• Recruitment of participants : Quota sampling (aiming for specific portions of men, women, ethnic minority students etc.)

We can see that every choice you make in planning and conducting your research inevitably excludes other possible options.

What's the difference between limitations and delimitations?

Delimitations and limitations are entirely different, although they often get mixed up. These are the main differences:

This chart explains the difference between delimitations and limitations. Delimitations are the boundaries of the study while the limitations are the characteristics of the research design or methodology.

Delimitations encompass the elements outside of the boundaries you've set and depends on your decision of what yo include and exclude. On the flip side, limitations are the elements outside of your control, such as:

• limited financial resources
• unplanned work or expenses
• unexpected events (for example, the COVID-19 pandemic)
• time constraints
• lack of technology/instruments
• unavailable evidence or previous research on the topic

Delimitations involve narrowing your study to make it more manageable and relevant to what you're trying to prove. Limitations influence the validity and reliability of your research findings. Limitations are seen as potential weaknesses in your research.

Example of the differences

To clarify these differences, go back to the limitations of the earlier example.

Limitations could comprise:

• Sample size : Not large enough to provide generalizable conclusions.
• Sampling approach : Non-probability sampling has increased bias risk. For instance, the researchers might not manage to capture the experiences of ethnic minority students.
• Methodological pitfalls : Research participants from an urban area (Paris) are likely to be more advantaged than students in rural areas. A study exploring the latter's experiences will probably yield very different findings.

Where do you write the scope and delimitations, and why?

It can be surprisingly empowering to realize you're restricted when conducting scholarly research. But this realization also makes writing up your research easier to grasp and makes it easier to see its limits and the expectations placed on it. Properly revealing this information serves your field and the greater scientific community.

Openly (but briefly) acknowledge the scope and delimitations of your study early on. The Abstract and Introduction sections are good places to set the parameters of your paper.

Next, discuss the scope and delimitations in greater detail in the Methods section. You'll need to do this to justify your methodological approach and data collection instruments, as well as analyses

At this point, spell out why these delimitations were set. What alternative options did you consider? Why did you reject alternatives? What could your study not address?

Let's say you're gathering data that can be derived from different but related experiments. You must convince the reader that the one you selected best suits your research question.

Finally, a solid paper will return to the scope and delimitations in the Findings or Discussion section. Doing so helps readers contextualize and interpret findings because the study's scope and methods influence the results.

For instance, agricultural field experiments carried out under irrigated conditions yield different results from experiments carried out without irrigation.

Being transparent about the scope and any outstanding issues increases your research's credibility and objectivity. It helps other researchers replicate your study and advance scientific understanding of the same topic (e.g., by adopting a different approach).

How do you write the scope and delimitations?

Define the scope and delimitations of your study before collecting data. This is critical. This step should be part of your research project planning.

Answering the following questions will help you address your scope and delimitations clearly and convincingly.

• What are your study's aims and objectives?
• Why did you carry out the study?
• What was the exact topic under investigation?
• Which factors and variables were included? And state why specific variables were omitted from the research scope.
• Who or what did the study explore? What was the target population?
• What was the study's location (geographical area) or setting (e.g., laboratory)?
• What was the timeframe within which you collected your data ?
• Consider a study exploring the differences between identical twins who were raised together versus identical twins who weren't. The data collection might span 5, 10, or more years.
• A study exploring a new immigration policy will cover the period since the policy came into effect and the present moment.
• How was the research conducted (research design)?
• Experimental research, qualitative, quantitative, or mixed-methods research, literature review, etc.
• What data collection tools and analysis techniques were used? e.g., If you chose quantitative methods, which statistical analysis techniques and software did you use?
• What did you find?
• What did you conclude?

Useful vocabulary for scope and delimitations

When explaining both the scope and delimitations, it's important to use the proper language to clearly state each.

For the scope , use the following language:

• This study focuses on/considers/investigates/covers the following:
• This study aims to . . . / Here, we aim to show . . . / In this study, we . . .
• The overall objective of the research is . . . / Our objective is to . . .

When stating the delimitations, use the following language:

• This [ . . . ] will not be the focus, for it has been frequently and exhaustively discusses in earlier studies.
• To review the [ . . . ] is a task that lies outside the scope of this study.
• The following [ . . . ] has been excluded from this study . . .
• This study does not provide a complete literature review of [ . . . ]. Instead, it draws on selected pertinent studies [ . . . ]

Analysis of a published scope

In one example, Simione and Gnagnarella (2020) compared the psychological and behavioral impact of COVID-19 on Italy's health workers and general population.

Here's a breakdown of the study's scope into smaller chunks and discussion of what works and why.

Also notable is that this study's delimitations include references to:

• Recruitment of participants: Convenience sampling
• Demographic characteristics of study participants: Age, sex, etc.
• Measurements methods: E.g., the death anxiety scale of the Existential Concerns Questionnaire (ECQ; van Bruggen et al., 2017) etc.
• Data analysis tool: The statistical software R

Analysis of published scope and delimitations

Scope of the study : Johnsson et al. (2019) explored the effect of in-hospital physiotherapy on postoperative physical capacity, physical activity, and lung function in patients who underwent lung cancer surgery.

The delimitations narrowed down the scope as follows:

Refine your scope, delimitations, and scientific English

English ability shouldn't limit how clear and impactful your research can be. Expert AJE editors are available to assess your science and polish your academic writing. See AJE services here .

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What Is Delimitation in Research? Examples of Scope & Delimitation

When you’re planning the launch of a study or report, you’ll need to make some important decisions to limit the people you’re researching and the ways you’ll conduct your study. Every credible research study has restrictions and limits in what it covers, and these boundaries are articulated through a research assignment’s delimitations and scope.

Delimitation is the process of drawing boundaries for or fixing the limits of something. Researchers identify and articulate delimitations to explain what their studies will and won’t cover while also defining the methodologies and approaches they’ll use to carry out their studies.

Delimitations help inform the overall scope, which is how deeply a paper, dissertation or study delves into a research question. A scope is the extent of the area or subject matter that something deals with. Often, a well-defined scope addresses the following standard questions:

• Why: What is the point of this research?
• What: What topic is being investigated?
• Where: Where is this research occurring and why?
• When: What is the timeline of this research?
• Who: What are the demographics of the study’s subjects?
• How: What is the methodology of this research (for example, qualitative versus quantitative, which we’ll get into in a bit)?

The key is to explore and clearly define boundaries and barriers on the front end, which will formally become your research study’s delimitations and overall scope. We’ll walk you through how you can identify your study’s delimitations and provide an overview of the important role they play in shaping the overall scope of your research.

Differences Between Limitations and Delimitations

Limitations and delimitations in research both clearly define the boundaries of the research problem that you’re studying. The primary difference between limitations and delimitations comes down to whether the researcher sets the boundaries or those boundaries come from unforeseen factors outside of the researcher’s control.

Delimitations involve a researcher establishing boundaries, whereas limitations are about identifying weaknesses in or barriers to carrying out the study as the researcher originally intended. Limitations disclose what a researcher cannot do (factors outside their control), and delimitations disclose what a researcher won’t do (factors that they chose not to focus on within the scope of the study).

For example, in a study about the impact of arts integration on proficiency levels within an elementary school classroom of 30 students, a limitation may be that the researcher only received parental consent for 25 students to participate. Additional examples of limitations are a lack of previous research on the subject to analyze and work from, a lack of access to the right tools and technology to collect data, and a lack of financial resources to sustain the research. Unlike researcher-defined delimitations, these limitations are initially unforeseen and outside of the researcher’s control.

An example of a delimitation, on the other hand, would be if the researcher opted to focus on third graders and exclude students without special needs from the study. A delimitation tells readers whom the study will cover. In this example, that’s third graders who utilize special education accommodations. The delimitations can also explain how a study is done, which might be through conducting student interviews and an analysis of test results before and after the integration of the arts into the special needs curriculum. Lastly, delimitations provide a picture of where a researcher conducts the study. In the case of this example, the delimitations could include the state, school district and specific school participating in the study.

Examples of Delimitations in Research

Research delimitations can shape and inform a study’s research objectives, methodology, variables and target populations. They can potentially prevent certain outcomes by focusing on sample sizes or population demographics, or they can help in achieving statistical significance. Setting these boundaries helps narrow a researcher’s focus area while increasing the relevance and specificity of the study.

In the example above, the delimitation that narrows the study only to third graders who use special education services ends up removing some potential variables that could impact the outcome of the research. It makes the scope more specific and more relevant. It also opens the door to future research on whether the results are the same for all third graders. Clear delimitations serve research practitioners by defining clear boundaries for what readers and reviewers can expect to find out about in key areas of the study, including where, how and with whom the study is carried out.

Scope and Delimitation in Quantitative Research

Qualitative research involves collecting and analyzing data that aren’t easily reduced to numbers, such as the study of human behaviors or perceptions within specific social environments. Quantitative research, meanwhile, involves collecting numerical data. These data can be helpful in measuring patterns and averages and in testing theories.

In the previous example of a study that reviews arts integration within a classroom, say the scope shifted from measuring changes in average student proficiency levels to measuring student perception of the overall learning experience. This would shift the study from quantitative to qualitative.

Defining the research approach, or the way in which the researcher conducts the study, is a delimitation. In a qualitative research study within an academic environment, a researcher may choose to administer a survey or conduct interviews for data collection around the students’ perceptions of the learning experience. If the study was intended to collect quantitative data as opposed to qualitative, the data-collection approach might instead involve measuring the numeric change in student test scores.

Quantitative research still uses delimitations to explain what the data will reveal and what they won’t. This gives others a reasonable expectation of what your data will explain, how you’ve analyzed it and how accurate your measurements were.

Guidelines in Writing About Scope and Delimitation

You should include a discussion of delimitations in the introduction to your research study, thesis or dissertation. Delimitations, limitations and overall scope are often made through statements like:

• This study covers…
• This study does not cover…
• This study is limited to…
• This study focuses on…
• The following has been excluded from this study…

Once you explicitly state what your delimitations are, you should also clearly list the other options available and the reasons why you did not pursue those alternative approaches. All reasoning should connect back to your research study, outlining the relevance of the study and explaining how and why you narrowed your focus. There’s nothing inherently moral about delimitations; they’re not good or bad, so your tone in writing them should reflect that. This is about being objective and about transparently and explicitly sharing what readers can expect from your research study.

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• Triangulation in Qualitative Research: Methods and Benefits

Discover key triangulation methods in qualitative research and how they strengthen data reliability and insights.

Making sense of heaps of research can sometimes feel like torture. Not even the research enthusiasts find it thrilling to squint at data for hours, thinking, “ Wait… am I truly seeing the full picture? ”

Luckily, triangulation in qualitative research can save you from the agony. Read on to learn how it cross-checks your research from multiple angles, making it more precise and reliable.

And if you’re more into the “how” than the “why,” our AI-powered research assistant can help you out. Marvin easily stores, analyzes, and connects the dots across all your customer research. Try Marvin free and see for yourself.

What is Triangulation in Qualitative Research?

Triangulation sounds fancy. But in reality, it’s just about not putting all your research eggs in one basket. Instead of relying on one method (which could miss the mark), you use different approaches to get a more reliable result:

• Collect data from various users
• Try multiple research methods
• Ask fellow researchers to weigh in

Human behavior is messy, and qualitative research dives right into it. That’s why you need more than one angle to understand what’s going on.

When it comes to qualitative research, triangulation takes different routes to see if they all lead to the same destination. The goal is to confirm that your findings are well-rounded and reliable.

What is the Purpose of Triangulation in Qualitative Research?

Customer analysis is critical when designing a product. You need to know what your users truly think, feel, and experience. And no one wants shaky, one-sided conclusions. That’s where triangulation comes in — to:

• Reduce the risk of bias or misunderstandings
• Strengthen your findings by viewing them from different perspectives

Example of Triangulation in Qualitative Research

Let’s say you’re conducting user research for a new app feature. Triangulation could involve a combination of:

• Method 1: Interview users
• Method 2: Observe their behavior using screen recordings
• Method 3: Analyze feedback from your support team about common complaints

In the end, you get a more complete, reliable picture of your users’ needs. And that brings you much closer to building something that truly solves their problems.

Types of Triangulation in Research

The example above is methodological triangulation in action. But that’s just one of the four types of triangulation.

Let’s break them down to help you pick the right one for your next research project.

1. Methodological Triangulation

Here, you mix up different methods to investigate the same research question. Maybe you combine user interviews with usability testing. You can also conduct focus groups and online surveys.

The goal of this triangulation research method is to cross-check your results from different angles. One method might highlight user frustration. But when you combine it with another one that reveals their behavior patterns, you get the full story.

2. Data Triangulation

This one’s all about variety. Data triangulation in qualitative research involves gathering feedback from different times, places, or people. It makes you less likely to miss important details.

For example, if you’re running a study, you can collect feedback from three groups: early adopters, casual users, and support teams. Each group gives you a different perspective on the same product or service.

3. Investigator Triangulation

Investigator or researcher triangulation brings in multiple researchers. They analyze the data from their perspectives. You compare their interpretations. In short, you add extra eyes to your work and end up with fewer blind spots.

This method can eliminate personal bias and give a more objective view of the findings. (Plus, collaboration is always more fun, right?)

4. Theory Triangulation

Picture this one as if trying on glasses with different theoretical lenses. Let’s say you’re researching user behavior. One lens might be behavioral psychology; another might be design thinking. Each view lets you see your data from a new angle.

By using different theories, you avoid squeezing your data into one box. It keeps your mind open — and who knows? You might stumble on insights you didn’t expect.

Advantages of Qualitative Research Triangulation

Triangulation adds depth and confidence to your research. It helps you feel less overwhelmed by data and more assured in the insights you pull. Here’s why:

• More reliable insights: Triangulation prevents feedback from getting all twisted up by the end. No more “ Did I get this right? ” vibes — just solid, trustworthy results.
• Reduced researcher bias: When using triangulation, you’re less likely to let your assumptions color the results. You get a more balanced and objective view.
• Richer, deeper data: Different methods or perspectives give you more context. Instead of a surface-level understanding of what users do, you grasp why they do it.
• Stronger findings: You’re hard to argue with when your conclusions rely on multiple methods or sources. This makes it easier to win over stakeholders.
• Flexible research design: You can mix and match methods to fit your project’s needs, gaining more control over your research process.

How to Implement Triangulation in Qualitative Research

With triangulation, you want to cover every angle and leave no stone unturned. Follow these steps to triangulate your way to deeper insights.

1. Define Your Research Objective

Get crystal clear on your research question. What are you trying to learn about your users? This will help you pick the best combination of methods and sources to answer your question from all angles.

2. Choose Your Triangulation Strategy and Methods

Which type of triangulation do you want to use? You might pick just one or a combination of a few, depending on your research question.

For example, if you’re using methodological triangulation, you can combine qualitative methods (interviews or focus groups) with quantitative methods (surveys). If you’ve chosen data triangulation, sources can be different user types, time periods, or locations.

No matter what methods or sources you use, they should serve your research objective and cross-verify your findings to uncover deeper insights.

3. Collect and Analyze the Data

Start by collecting data from each method or source you’ve chosen. 

As you analyze, ensure each method addresses the same research question — this will let you spot patterns or discrepancies across sources and make the next step easier.

4. Compare and Cross-Check Your Findings

The actual comparison is the essence of triangulation. Are there any contradictions? Are you seeing the same patterns across the board and getting well-rounded, reliable insights?

Contradictions can reveal nuances you might have missed or point to areas where different user groups or methods provide unique perspectives.

5. Collaborate With Other Researchers

If you choose investigator triangulation, you can now bring other researchers to interpret the data. 

Multiple minds can spot biases or assumptions one person might miss, making your research even more objective.

6. Draw and Communicate Conclusions

Finally, your insights are stronger and more credible because they’ve been validated from different angles. When presenting your findings, highlight how triangulation strengthened the results.

Now that you’ve learned how triangulation can consolidate your research findings, why not make it easier with Marvin? Our AI-powered research repository takes the heavy lifting out of cross-checking data.

Need to pull insights from different sources and analyze them in one place without missing a beat? Create a free account to see how Marvin helps you get the most out of your qualitative research.

Limitations and Challenges of Implementing Triangulation

Despite its benefits, triangulation isn’t all rainbows and perfectly cross-checked data. Watch out for the following challenges you might face when implementing it:

• Takes more time and resources: Triangulation is no small task. You’ll need to budget more time and resources to pull it off. Watch out for extended deadlines and bigger research teams!
• Limitations come into play: Each method might have limitations or quirks, making it tough to line up the results. Sometimes, when your interview data contradicts your survey results, it’s challenging to piece it all together without pulling your hair out.
• Consistency is hard to achieve: One researcher might interpret the data differently than another. Or maybe the way you phrased questions in a survey doesn’t quite match the interview format. Consistency becomes slippery when using different methods or collaborating with multiple researchers.
• Information overload may creep in: More data isn’t always better, leaving you feeling like drowning in a sea of insights. Getting lost in the details is easy, but sticking to the plan will help avoid analysis paralysis.

Best Practices for Triangulation in Research

Like with any good strategy, there are ways to do triangulation right to get the full benefits without the headaches:

1. Focus on Complementary Methods or Data Sources

The goal is to cover different dimensions of the same issue, not duplicate efforts. Therefore, pick the most suitable methods instead of using as many as possible.

For instance, pairing user interviews with usability testing works because interviews reveal user opinions, while usability testing shows how they actually behave.

2. Prioritize Quality Over Quantity

Two or three well-chosen methods that give you rich, reliable insights will often be more effective than spreading yourself thin with too many.

Instead of going wide, go deep. Focus on gathering high-quality data that truly addresses your research question.

3. Maintain a Balance Between Consistency and Flexibility

Triangulation’s strength is the ability to adapt. Balance consistency with flexibility to tweak your approach when necessary.

Don’t be afraid to pivot if one approach isn’t delivering the expected insights or new information suggests a better path.

4. Don’t Ignore Contradictions—Explore Them

Contradictory results can often point to deeper insights. They may reveal nuances or hidden factors you hadn’t considered.

Dig deeper into those contradictions instead of trying to reconcile everything neatly—they might tell you something valuable.

Frequently Asked Questions (FAQs)

Ready to jump head-first into triangulation? Check out these FAQs first:

Can Triangulation be Used in All Qualitative Research Studies?

You can use triangulation in most qualitative research studies, but it’s not always necessary. With complex research or ambiguous user behavior, it makes sense to use multiple methods or data sources. However, it may not be worth the extra work for smaller, more focused studies.

What Are the Ethical Considerations When Using Triangulation in Qualitative Research?

You need to be sure that you’re transparent with participants about how their data will be used across these methods. Also, keep privacy in mind. If you’re pulling data from multiple sources, be clear on how you’re storing and handling that data securely.

How Do You Ensure Consistency When Using Multiple Methods?

Consistency doesn’t mean everything has to be exactly the same. Still,  your methods should be comparable enough to draw meaningful insights when cross-checking the results. The key is to set up a clear framework from the start. Your questions, protocols, and data collection techniques should align even if they spread across different methods.

There you have it — triangulation in all its multi-angled glory. You can mix methods, gather data from different sources, or team up with other researchers. However you do it, it’s the ace up your sleeve for uncovering deeper insights and minimizing bias.

Before you go forth and triangulate, remember that covering all those angles doesn’t have to be a pain. Marvin helps with triangulation in qualitative data analysis through:

• Centralized data: Store interviews, surveys, support tickets, and sales calls in one place.
• AI-powered insights: Automatically connect the dots between multiple data sources.
• Effortless comparisons: Easily cross-check findings from different methods.

Book a demo today and see how Marvin supports your research by simplifying data collection, organization, and analysis. Bring all your insights in one place to focus on what actually matters — cross-checking your data and getting deeper insights through more efficient triangulation.

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Research Findings Guide: Examples, Types, and Structuring Tips

• November 7, 2024

Dr. Marvin L. Smith

Research findings are the core insights derived from a study, summarizing key results and answering the research question . They reveal patterns, relationships, or trends, whether through qualitative insights or quantitative data. 

Understanding how to write findings in research is crucial—it provides clarity, supports claims, and often determines the study’s impact. 

This article explores types of research findings , examples, and methods to present them effectively. 

Whether you’re looking to learn about research findings, explore examples of different types of research findings, or need guidance on structuring findings in a paper, this guide has you covered.

What Are Research Findings?

Research findings are the key results or discoveries from a study. 

They directly address the research question, revealing insights that support or challenge the hypothesis. These findings can be qualitative, like observations or themes, or quantitative, like statistics or patterns. 

Clear and accurate findings ensure readers understand the study’s outcome.

Importance of Research Findings

Research findings are the cornerstone of any study, offering critical evidence to support the researcher’s conclusions . They serve as the basis for establishing facts, verifying hypotheses, and validating the study’s objectives. 

Findings not only demonstrate that a study has met its intended goals but also underscore its relevance and reliability within a field.

In academic and professional circles, strong research findings enhance the credibility of a paper. They demonstrate that the study is grounded in rigorous data analysis, increasing the likelihood of acceptance by peers and recognition in the wider community. 

When findings are presented clearly and backed by sound evidence, they provide a solid foundation for future research, inspiring new questions and guiding subsequent studies.

Additionally, well-structured findings are invaluable for decision-making across sectors. 

In healthcare , they inform treatment protocols and health policies; in business , they shape product development and strategic planning; in education , they enhance teaching methods and learning outcomes. 

Without concrete findings, research would lack direction and impact, making these insights essential for applying knowledge to real-world problems and advancing knowledge in meaningful ways.

Types of Research Findings

Research findings can be categorized based on both the data’s nature and its origin, giving readers insight into the study’s methods and the type of evidence presented. 

This classification—into qualitative vs. quantitative findings and primary vs. secondary findings—helps researchers structure their findings more effectively and ensures readers can follow the study’s approach.

Qualitative vs. Quantitative Findings

Qualitative findings focus on understanding experiences, motivations, and perceptions by capturing themes, patterns, and meanings through methods like interviews, focus groups, and observations. They address the “how” and “why” behind phenomena.

For instance, in a study exploring customer satisfaction, qualitative findings might reveal that customers feel valued when employees remember their names—an insight drawn from direct interview responses. 

These findings provide rich, contextual insights that add depth and human perspectives.

Quantitative findings , on the other hand, are based on numerical data derived from methods like surveys, experiments, and statistical analysis. These findings answer “what,” “how much,” or “how many,” offering a measurable view of trends or relationships.

In the same customer satisfaction study, quantitative findings could show that 78% of surveyed customers rate their satisfaction as “high.” 

This data-driven approach offers clear, objective metrics that validate or challenge hypotheses and allow comparisons across variables.

Using both qualitative and quantitative findings often provides a balanced perspective, combining numerical rigor with contextual understanding—a method known as mixed-methods research.

Primary vs. Secondary Findings

Primary findings emerge directly from the researcher’s own data collection. These are original insights obtained through firsthand research, such as an experiment, survey, or field study. 

For example, a study measuring the effects of a new medication on blood pressure would yield primary findings about its effectiveness based on the data collected during clinical trials. 

These findings introduce new knowledge to the field, making them highly valuable and directly tied to the study’s objectives.

Secondary findings are drawn from data or insights that others have previously collected. They often support or add context to primary findings without introducing new information. 

For instance, in a study on the effectiveness of teaching methods, secondary findings might include statistics from government reports on educational outcomes. 

These findings help frame the research within a broader context, showing how it aligns with or diverges from existing studies. By combining primary and secondary findings, researchers can enhance the credibility of their work and provide a fuller understanding of the topic.

Each type of research finding serves a unique purpose. 

Qualitative and quantitative findings provide different perspectives on data, while primary and secondary findings strengthen the depth and breadth of research, making it more impactful and informative.

Interpreting Research Findings

Interpreting research findings involves reviewing data to uncover meaningful insights. This process not only highlights key results but also strengthens the study’s credibility by ensuring clarity and accuracy in presenting findings.

Analyzing Data and Recognizing Patterns

Data analysis helps identify trends, correlations, or differences within the dataset. By recognizing these patterns, researchers draw conclusions that directly address the research question. Effective analysis reveals underlying insights and shows how findings connect to the study’s objectives.

Ensuring Validity and Accuracy

Ensuring validity and accuracy is essential in interpreting findings. Validity confirms that the findings genuinely reflect the data and align with the research question, while accuracy ensures consistent, error-free analysis. Together, they reinforce the study’s reliability, making its conclusions trustworthy and impactful.

Presenting Research Findings

Presenting research findings effectively is crucial for helping readers understand and engage with the study’s outcomes. A well-structured presentation and the use of visuals ensure clarity, while accessible language makes findings understandable to a wider audience.

Structuring a Clear Presentation

Organize findings in a logical order that directly addresses the research question, starting with the most significant results. Use headings, subheadings, and bullet points to break down information, making it easier for readers to follow. Concise and clear language keeps the focus on key insights without overwhelming details.

Using Visuals for Emphasis

Visuals, like charts, graphs, and tables, highlight key data points and make complex information easier to grasp.

For example, a bar chart can show survey results by comparing response percentages across different groups, while a line graph can track changes over time, such as monthly sales trends or patient recovery rates. 

Tables are also effective for presenting detailed numerical data, allowing readers to compare figures side by side.

These visual aids help readers quickly identify patterns and comparisons, enhancing the impact of findings and overall comprehension. A well-placed chart or table can make a difference by translating raw data into a clear, engaging visual summary .

Communicating Findings to Non-Experts

To reach non-experts, simplify technical terms and avoid jargon. Use clear, everyday language and provide brief explanations when needed. Presenting findings in an accessible way ensures broader understanding and maximizes the research’s reach and influence.

Challenges in Reporting Research Findings

Reporting research findings can be challenging, as it requires accuracy and objectivity to avoid misleading readers. Identifying and addressing these challenges is essential to maintain credibility and transparency.

Misinterpretation and Bias

Misinterpretation happens when findings are presented in a way that leads readers to incorrect conclusions. To avoid this, use precise language and clarify key points. Bias, whether intentional or unintentional, can distort findings by emphasizing certain outcomes. Being aware of potential biases and reporting objectively ensures a fair representation of the data.

Addressing Limitations

Every study has limitations—factors that may affect the results or the generalizability of findings. Clearly acknowledging these limitations shows honesty and helps readers understand the scope of the research. Addressing limitations also guides future studies by highlighting areas for improvement or further investigation.

Applications of Research Findings

Research findings have broad applications across various fields, guiding decisions, influencing policies, and informing future research. 

In healthcare, findings can lead to new treatments, improve patient care, or shape public health guidelines. 

In business, research insights drive product development, marketing strategies, and customer experience enhancements. 

In education, findings inform teaching methods and curriculum design, ultimately improving learning outcomes.

Moreover, research findings often serve as a foundation for further studies, allowing other researchers to build on existing knowledge. Whether applied to solve real-world problems or deepen understanding within a field, these findings contribute significantly to progress and innovation.

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CRO Guide   >  Chapter 3.1

Qualitative Research Methods: Examples, Limitations & Analysis

Qualitative research is a method focused on understanding human behavior and experiences through non-numerical data. Qualitative research methods include:

• One-on-one interviews,
• Focus groups, Ethnographic research,
• Case studies,
• Record keeping,
• Qualitative observations

In this article, we’ll provide tips and tricks on how to use qualitative research to better understand your audience through real world examples and improve your ROI. We’ll also learn the difference between qualitative and quantitative data.

Table of Contents

Marketers often seek to understand their customers deeply. Qualitative research methods such as face-to-face interviews, focus groups, and qualitative observations can provide valuable insights into your products, your market, and your customers’ opinions and motivations. Understanding these nuances can significantly enhance marketing strategies and overall customer satisfaction.

What is Qualitative Research

Qualitative research is a market research method that focuses on obtaining data through open-ended and conversational communication. This method focuses on the “why” rather than the “what” people think about you. Thus, qualitative research seeks to uncover the underlying motivations, attitudes, and beliefs that drive people’s actions. 

Let’s say you have an online shop catering to a general audience. You do a demographic analysis and you find out that most of your customers are male. Naturally, you will want to find out why women are not buying from you. And that’s what qualitative research will help you find out.

In the case of your online shop, qualitative research would involve reaching out to female non-customers through methods such as in-depth interviews or focus groups. These interactions provide a platform for women to express their thoughts, feelings, and concerns regarding your products or brand. Through qualitative analysis, you can uncover valuable insights into factors such as product preferences, user experience, brand perception, and barriers to purchase.

Types of Qualitative Research Methods

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience regarding a particular topic.

The most frequently used qualitative analysis methods are one-on-one interviews, focus groups, ethnographic research, case study research, record keeping, and qualitative observation.

1. One-on-one interviews

Conducting one-on-one interviews is one of the most common qualitative research methods. One of the advantages of this method is that it provides a great opportunity to gather precise data about what people think and their motivations.

Spending time talking to customers not only helps marketers understand who their clients are, but also helps with customer care: clients love hearing from brands. This strengthens the relationship between a brand and its clients and paves the way for customer testimonials.

• A company might conduct interviews to understand why a product failed to meet sales expectations.
• A researcher might use interviews to gather personal stories about experiences with healthcare.

These interviews can be performed face-to-face or on the phone and usually last between half an hour to over two hours. 

When a one-on-one interview is conducted face-to-face, it also gives the marketer the opportunity to read the body language of the respondent and match the responses.

2. Focus groups

Focus groups gather a small number of people to discuss and provide feedback on a particular subject. The ideal size of a focus group is usually between five and eight participants. The size of focus groups should reflect the participants’ familiarity with the topic. For less important topics or when participants have little experience, a group of 10 can be effective. For more critical topics or when participants are more knowledgeable, a smaller group of five to six is preferable for deeper discussions.

The main goal of a focus group is to find answers to the “why”, “what”, and “how” questions. This method is highly effective in exploring people’s feelings and ideas in a social setting, where group dynamics can bring out insights that might not emerge in one-on-one situations.

• A focus group could be used to test reactions to a new product concept.
• Marketers might use focus groups to see how different demographic groups react to an advertising campaign.

One advantage that focus groups have is that the marketer doesn’t necessarily have to interact with the group in person. Nowadays focus groups can be sent as online qualitative surveys on various devices.

Focus groups are an expensive option compared to the other qualitative research methods, which is why they are typically used to explain complex processes.

3. Ethnographic research

Ethnographic research is the most in-depth observational method that studies individuals in their naturally occurring environment.

This method aims at understanding the cultures, challenges, motivations, and settings that occur.

• A study of workplace culture within a tech startup.
• Observational research in a remote village to understand local traditions.

Ethnographic research requires the marketer to adapt to the target audiences’ environments (a different organization, a different city, or even a remote location), which is why geographical constraints can be an issue while collecting data.

This type of research can last from a few days to a few years. It’s challenging and time-consuming and solely depends on the expertise of the marketer to be able to analyze, observe, and infer the data.

4. Case study research

The case study method has grown into a valuable qualitative research method. This type of research method is usually used in education or social sciences. It involves a comprehensive examination of a single instance or event, providing detailed insights into complex issues in real-life contexts.  

• Analyzing a single school’s innovative teaching method.
• A detailed study of a patient’s medical treatment over several years.

Case study research may seem difficult to operate, but it’s actually one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

Record keeping is similar to going to the library: you go over books or any other reference material to collect relevant data. This method uses already existing reliable documents and similar sources of information as a data source.

• Historical research using old newspapers and letters.
• A study on policy changes over the years by examining government records.

This method is useful for constructing a historical context around a research topic or verifying other findings with documented evidence.

6. Qualitative observation

Qualitative observation is a method that uses subjective methodologies to gather systematic information or data. This method deals with the five major sensory organs and their functioning, sight, smell, touch, taste, and hearing.

• Sight : Observing the way customers visually interact with product displays in a store to understand their browsing behaviors and preferences.
• Smell : Noting reactions of consumers to different scents in a fragrance shop to study the impact of olfactory elements on product preference.
• Touch : Watching how individuals interact with different materials in a clothing store to assess the importance of texture in fabric selection.
• Taste : Evaluating reactions of participants in a taste test to identify flavor profiles that appeal to different demographic groups.
• Hearing : Documenting responses to changes in background music within a retail environment to determine its effect on shopping behavior and mood.

Below we are also providing real-life examples of qualitative research that demonstrate practical applications across various contexts:

Qualitative Research Real World Examples

Let’s explore some examples of how qualitative research can be applied in different contexts.

1. Online grocery shop with a predominantly male audience

Method used: one-on-one interviews.

Let’s go back to one of the previous examples. You have an online grocery shop. By nature, it addresses a general audience, but after you do a demographic analysis you find out that most of your customers are male.

One good method to determine why women are not buying from you is to hold one-on-one interviews with potential customers in the category.

Interviewing a sample of potential female customers should reveal why they don’t find your store appealing. The reasons could range from not stocking enough products for women to perhaps the store’s emphasis on heavy-duty tools and automotive products, for example. These insights can guide adjustments in inventory and marketing strategies.

2. Software company launching a new product

Method used: focus groups.

Focus groups are great for establishing product-market fit.

Let’s assume you are a software company that wants to launch a new product and you hold a focus group with 12 people. Although getting their feedback regarding users’ experience with the product is a good thing, this sample is too small to define how the entire market will react to your product.

So what you can do instead is holding multiple focus groups in 20 different geographic regions. Each region should be hosting a group of 12 for each market segment; you can even segment your audience based on age. This would be a better way to establish credibility in the feedback you receive.

3. Alan Pushkin’s “God’s Choice: The Total World of a Fundamentalist Christian School”

Method used: ethnographic research.

Moving from a fictional example to a real-life one, let’s analyze Alan Peshkin’s 1986 book “God’s Choice: The Total World of a Fundamentalist Christian School”.

Peshkin studied the culture of Bethany Baptist Academy by interviewing the students, parents, teachers, and members of the community alike, and spending eighteen months observing them to provide a comprehensive and in-depth analysis of Christian schooling as an alternative to public education.

The study highlights the school’s unified purpose, rigorous academic environment, and strong community support while also pointing out its lack of cultural diversity and openness to differing viewpoints. These insights are crucial for understanding how such educational settings operate and what they offer to students.

Even after discovering all this, Peshkin still presented the school in a positive light and stated that public schools have much to learn from such schools.

Peshkin’s in-depth research represents a qualitative study that uses observations and unstructured interviews, without any assumptions or hypotheses. He utilizes descriptive or non-quantifiable data on Bethany Baptist Academy specifically, without attempting to generalize the findings to other Christian schools.

4. Understanding buyers’ trends

Method used: record keeping.

Another way marketers can use quality research is to understand buyers’ trends. To do this, marketers need to look at historical data for both their company and their industry and identify where buyers are purchasing items in higher volumes.

For example, electronics distributors know that the holiday season is a peak market for sales while life insurance agents find that spring and summer wedding months are good seasons for targeting new clients.

5. Determining products/services missing from the market

Conducting your own research isn’t always necessary. If there are significant breakthroughs in your industry, you can use industry data and adapt it to your marketing needs.

The influx of hacking and hijacking of cloud-based information has made Internet security a topic of many industry reports lately. A software company could use these reports to better understand the problems its clients are facing.

As a result, the company can provide solutions prospects already know they need.

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Qualitative Research Approaches

Once the marketer has decided that their research questions will provide data that is qualitative in nature, the next step is to choose the appropriate qualitative approach.

The approach chosen will take into account the purpose of the research, the role of the researcher, the data collected, the method of data analysis , and how the results will be presented. The most common approaches include:

• Narrative : This method focuses on individual life stories to understand personal experiences and journeys. It examines how people structure their stories and the themes within them to explore human existence. For example, a narrative study might look at cancer survivors to understand their resilience and coping strategies.
• Phenomenology : attempts to understand or explain life experiences or phenomena; It aims to reveal the depth of human consciousness and perception, such as by studying the daily lives of those with chronic illnesses.
• Grounded theory : investigates the process, action, or interaction with the goal of developing a theory “grounded” in observations and empirical data. 
• Ethnography : describes and interprets an ethnic, cultural, or social group;
• Case study : examines episodic events in a definable framework, develops in-depth analyses of single or multiple cases, and generally explains “how”. An example might be studying a community health program to evaluate its success and impact.

How to Analyze Qualitative Data

Analyzing qualitative data involves interpreting non-numerical data to uncover patterns, themes, and deeper insights. This process is typically more subjective and requires a systematic approach to ensure reliability and validity. 

1. Data Collection

Ensure that your data collection methods (e.g., interviews, focus groups, observations) are well-documented and comprehensive. This step is crucial because the quality and depth of the data collected will significantly influence the analysis.

2. Data Preparation

Once collected, the data needs to be organized. Transcribe audio and video recordings, and gather all notes and documents. Ensure that all data is anonymized to protect participant confidentiality where necessary.

3. Familiarization

Immerse yourself in the data by reading through the materials multiple times. This helps you get a general sense of the information and begin identifying patterns or recurring themes.

Develop a coding system to tag data with labels that summarize and account for each piece of information. Codes can be words, phrases, or acronyms that represent how these segments relate to your research questions.

• Descriptive Coding : Summarize the primary topic of the data.
• In Vivo Coding : Use language and terms used by the participants themselves.
• Process Coding : Use gerunds (“-ing” words) to label the processes at play.
• Emotion Coding : Identify and record the emotions conveyed or experienced.

5. Thematic Development

Group codes into themes that represent larger patterns in the data. These themes should relate directly to the research questions and form a coherent narrative about the findings.

6. Interpreting the Data

Interpret the data by constructing a logical narrative. This involves piecing together the themes to explain larger insights about the data. Link the results back to your research objectives and existing literature to bolster your interpretations.

7. Validation

Check the reliability and validity of your findings by reviewing if the interpretations are supported by the data. This may involve revisiting the data multiple times or discussing the findings with colleagues or participants for validation.

8. Reporting

Finally, present the findings in a clear and organized manner. Use direct quotes and detailed descriptions to illustrate the themes and insights. The report should communicate the narrative you’ve built from your data, clearly linking your findings to your research questions.

Limitations of qualitative research

The disadvantages of qualitative research are quite unique. The techniques of the data collector and their own unique observations can alter the information in subtle ways. That being said, these are the qualitative research’s limitations:

1. It’s a time-consuming process

The main drawback of qualitative study is that the process is time-consuming. Another problem is that the interpretations are limited. Personal experience and knowledge influence observations and conclusions.

Thus, qualitative research might take several weeks or months. Also, since this process delves into personal interaction for data collection, discussions often tend to deviate from the main issue to be studied.

2. You can’t verify the results of qualitative research

Because qualitative research is open-ended, participants have more control over the content of the data collected. So the marketer is not able to verify the results objectively against the scenarios stated by the respondents. For example, in a focus group discussing a new product, participants might express their feelings about the design and functionality. However, these opinions are influenced by individual tastes and experiences, making it difficult to ascertain a universally applicable conclusion from these discussions.

3. It’s a labor-intensive approach

Qualitative research requires a labor-intensive analysis process such as categorization, recording, etc. Similarly, qualitative research requires well-experienced marketers to obtain the needed data from a group of respondents.

4. It’s difficult to investigate causality

Qualitative research requires thoughtful planning to ensure the obtained results are accurate. There is no way to analyze qualitative data mathematically. This type of research is based more on opinion and judgment rather than results. Because all qualitative studies are unique they are difficult to replicate.

5. Qualitative research is not statistically representative

Because qualitative research is a perspective-based method of research, the responses given are not measured.

Comparisons can be made and this can lead toward duplication, but for the most part, quantitative data is required for circumstances that need statistical representation and that is not part of the qualitative research process.

While doing a qualitative study, it’s important to cross-reference the data obtained with the quantitative data. By continuously surveying prospects and customers marketers can build a stronger database of useful information.

Quantitative vs. Qualitative Research

Image source

Quantitative and qualitative research are two distinct methodologies used in the field of market research, each offering unique insights and approaches to understanding consumer behavior and preferences.

As we already defined, qualitative analysis seeks to explore the deeper meanings, perceptions, and motivations behind human behavior through non-numerical data. On the other hand, quantitative research focuses on collecting and analyzing numerical data to identify patterns, trends, and statistical relationships.  

Let’s explore their key differences: 

Nature of Data:

• Quantitative research : Involves numerical data that can be measured and analyzed statistically.
• Qualitative research : Focuses on non-numerical data, such as words, images, and observations, to capture subjective experiences and meanings.

Research Questions:

• Quantitative research : Typically addresses questions related to “how many,” “how much,” or “to what extent,” aiming to quantify relationships and patterns.
• Qualitative research: Explores questions related to “why” and “how,” aiming to understand the underlying motivations, beliefs, and perceptions of individuals.

Data Collection Methods:

• Quantitative research : Relies on structured surveys, experiments, or observations with predefined variables and measures.
• Qualitative research : Utilizes open-ended interviews, focus groups, participant observations, and textual analysis to gather rich, contextually nuanced data.

Analysis Techniques:

• Quantitative research: Involves statistical analysis to identify correlations, associations, or differences between variables.
• Qualitative research: Employs thematic analysis, coding, and interpretation to uncover patterns, themes, and insights within qualitative data.

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Setting Limits and Focusing Your Study: Exploring scope and delimitation

As a researcher, it can be easy to get lost in the vast expanse of information and data available. Thus, when starting a research project, one of the most important things to consider is the scope and delimitation of the study. Setting limits and focusing your study is essential to ensure that the research project is manageable, relevant, and able to produce useful results. In this article, we will explore the importance of setting limits and focusing your study through an in-depth analysis of scope and delimitation.

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Table of Contents

Scope and Delimitation – Definition and difference

Scope refers to the range of the research project and the study limitations set in place to define the boundaries of the project and delimitation refers to the specific aspects of the research project that the study will focus on.

In simpler words, scope is the breadth of your study, while delimitation is the depth of your study.

Scope and delimitation are both essential components of a research project, and they are often confused with one another. The scope defines the parameters of the study, while delimitation sets the boundaries within those parameters. The scope and delimitation of a study are usually established early on in the research process and guide the rest of the project.

Types of Scope and Delimitation

Significance of Scope and Delimitation

Setting limits and focusing your study through scope and delimitation is crucial for the following reasons:

• It allows researchers to define the research project’s boundaries, enabling them to focus on specific aspects of the project. This focus makes it easier to gather relevant data and avoid unnecessary information that might complicate the study’s results.
• Setting limits and focusing your study through scope and delimitation enables the researcher to stay within the parameters of the project’s resources.
• A well-defined scope and delimitation ensure that the research project can be completed within the available resources, such as time and budget, while still achieving the project’s objectives.

5 Steps to Setting Limits and Defining the Scope and Delimitation of Your Study

There are a few steps that you can take to set limits and focus your study.

1. Identify your research question or topic

The first step is to identify what you are interested in learning about. The research question should be specific, measurable, achievable, relevant, and time-bound (SMART). Once you have a research question or topic, you can start to narrow your focus.

2. Consider the key terms or concepts related to your topic

What are the important terms or concepts that you need to understand in order to answer your research question? Consider all available resources, such as time, budget, and data availability, when setting scope and delimitation.

The scope and delimitation should be established within the parameters of the available resources. Once you have identified the key terms or concepts, you can start to develop a glossary or list of definitions.

3. Consider the different perspectives on your topic

There are often different perspectives on any given topic. Get feedback on the proposed scope and delimitation. Advisors can provide guidance on the feasibility of the study and offer suggestions for improvement.

It is important to consider all of the different perspectives in order to get a well-rounded understanding of your topic.

4. Narrow your focus

Be specific and concise when setting scope and delimitation. The parameters of the study should be clearly defined to avoid ambiguity and ensure that the study is focused on relevant aspects of the research question.

This means deciding which aspects of your topic you will focus on and which aspects you will eliminate.

5. Develop the final research plan

Revisit and revise the scope and delimitation as needed. As the research project progresses, the scope and delimitation may need to be adjusted to ensure that the study remains focused on the research question and can produce useful results. This plan should include your research goals, methods, and timeline.

Examples of Scope and Delimitation

To better understand scope and delimitation, let us consider two examples of research questions and how scope and delimitation would apply to them.

Research question: What are the effects of social media on mental health?

Scope: The scope of the study will focus on the impact of social media on the mental health of young adults aged 18-24 in the United States.

Delimitation: The study will specifically examine the following aspects of social media: frequency of use, types of social media platforms used, and the impact of social media on self-esteem and body image.

Research question: What are the factors that influence employee job satisfaction in the healthcare industry?

Scope: The scope of the study will focus on employee job satisfaction in the healthcare industry in the United States.

Delimitation: The study will specifically examine the following factors that influence employee job satisfaction: salary, work-life balance, job security, and opportunities for career growth.

Setting limits and defining the scope and delimitation of a research study is essential to conducting effective research. By doing so, researchers can ensure that their study is focused, manageable, and feasible within the given time frame and resources. It can also help to identify areas that require further study, providing a foundation for future research.

So, the next time you embark on a research project, don’t forget to set clear limits and define the scope and delimitation of your study. It may seem like a tedious task, but it can ultimately lead to more meaningful and impactful research. And if you still can’t find a solution, reach out to Enago Academy using #AskEnago and tag @EnagoAcademy on Twitter , Facebook , and Quora .

Frequently Asked Questions

The scope in research refers to the boundaries and extent of a study, defining its specific objectives, target population, variables, methods, and limitations, which helps researchers focus and provide a clear understanding of what will be investigated.

Delimitation in research defines the specific boundaries and limitations of a study, such as geographical, temporal, or conceptual constraints, outlining what will be excluded or not within the scope of investigation, providing clarity and ensuring the study remains focused and manageable.

To write a scope; 1. Clearly define research objectives. 2. Identify specific research questions. 3. Determine the target population for the study. 4. Outline the variables to be investigated. 5. Establish limitations and constraints. 6. Set boundaries and extent of the investigation. 7. Ensure focus, clarity, and manageability. 8. Provide context for the research project.

To write delimitations; 1. Identify geographical boundaries or constraints. 2. Define the specific time period or timeframe of the study. 3. Specify the sample size or selection criteria. 4. Clarify any demographic limitations (e.g., age, gender, occupation). 5. Address any limitations related to data collection methods. 6. Consider limitations regarding the availability of resources or data. 7. Exclude specific variables or factors from the scope of the study. 8. Clearly state any conceptual boundaries or theoretical frameworks. 9. Acknowledge any potential biases or constraints in the research design. 10. Ensure that the delimitations provide a clear focus and scope for the study.

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Open Access

Study Protocol

Frequency of limitations statements in original research articles of United States leading medical journals: A meta-research protocol

Contributed equally to this work with: Nin-Chieh Hsu, Hung-Bin Tsai, Chia-Hao Hsu

Roles Conceptualization, Formal analysis, Funding acquisition, Writing – original draft

Affiliations Division of Hospital Medicine, Department of Internal Medicine, Taipei City Hospital Zhongxing Branch, Taipei, Taiwan, Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan

Roles Investigation, Resources

Roles Formal analysis, Investigation

Affiliations Department of Orthopedics, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

Roles Methodology

Affiliation Division of Hospital Medicine, Department of Internal Medicine, Taipei City Hospital Zhongxing Branch, Taipei, Taiwan

Roles Writing – review & editing

Affiliation Department of Internal Medicine, Stanford University, School of Medicine, Stanford, California, United States of America

Roles Conceptualization, Supervision, Writing – review & editing

* E-mail: [email protected]

Affiliations Muribushi Okinawa Clinical Training Center, Urasoe City, Okinawa, Japan, Tokyo Foundation for Policy Research, Roppongi, Minato-ku, Tokyo, Japan

• Nin-Chieh Hsu, 
• Hung-Bin Tsai, 
• Chia-Hao Hsu, 
• Ming-Yan Tsai, 
• Charles Liao, 
• Yasuharu Tokuda

• Published: November 1, 2024
• https://doi.org/10.1371/journal.pone.0305970
• Reader Comments

Limitation declarations are commonly deemed essential to uphold intellectual humility for scientific research, but little has been reported about the limitation statements in published original research articles. This meta-research study aims to investigate the trends of limitation statements among three leading general medical journals in the US.

This cross-sectional study will compile a data set of full-length original research articles published in the New England Journal of Medicine, Journal of the American Medical Association, and Annals of Internal Medicine between 2002 and 2022. Limitation statement will be recognized by two investigators, and a predefined set of sensitive keywords is used for sensitivity analysis. Frequency of limitation statements within the main text of research articles and trends for different study designs, including their association with the corresponding reporting guidelines, are the main measurements. We employ the Cochran-Armitage test for trend analysis.

The findings of this study will provide an overview of the limitation statements in leading general medical journals in the US. The results may contribute to future research to identify factors that are associated with the presence of limitation statements.

Citation: Hsu N-C, Tsai H-B, Hsu C-H, Tsai M-Y, Liao C, Tokuda Y (2024) Frequency of limitations statements in original research articles of United States leading medical journals: A meta-research protocol. PLoS ONE 19(11): e0305970. https://doi.org/10.1371/journal.pone.0305970

Editor: Mickael Essouma, Universal Scientific Education and Research Network, UNITED KINGDOM

Received: May 13, 2024; Accepted: June 5, 2024; Published: November 1, 2024

Copyright: © 2024 Hsu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data cannot be shared publicly because of the study protocol.

Funding: National Science and Technology Council (Taiwan) (NSTC 112-2410-H-002-174-MY2 and NSTC 112-2410-H-002-172-MY2) on the article processing charges. The authors declare no conflict of interest. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The concept of intellectual humility is gaining considerable recognition, celebrated as an integral aspect of wisdom, a facilitator of self-improvement, and a catalyst for more constructive dialogue [ 1 ]. Acknowledgement of limitation is an attitude of humility warranted in the scientific research. Reducing potential confounding through meticulous study design is a task assigned to researchers [ 2 , 3 ]; however, biases remain unavoidable [ 4 , 5 ]. In accordance with journal author guidelines, providing a statement of limitations is typically obligatory in original research. Nevertheless, the prevalence and pattern of such limitations declarations in published works have not been reported.

The reporting guidelines for pertinent publication types were established approximately 15 years ago [ 6 , 7 ]. The Consolidated Standards of Reporting Trials (CONSORT) guidelines for randomized control trials (RCT) mandate limitations, generalizability interpretation in the discussion or comment section [ 6 , 8 ]. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement for observational studies mandate key results, limitations, interpretation, generalizability in the discussion section [ 9 ]. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for reporting systematic reviews and meta-analyses of studies, consists of a 27-item checklist. also mandate an item to include discussions of limitations at study, outcome, and review level [ 10 ].

Despite the explicit requirement for a limitation statement outlined in the respective checklists of these reporting guidelines, adherence to such guidelines is seldom reported. A review of the first 50 articles from each of the six most-cited research journals and two leading open-access journals published in 2005 found that only 67 articles (17%) of the 400 articles mentioned any limitations in their scientific work [ 11 ]. However, most of these reports were completed before the implementation of reporting guidelines. Including journals with different editorial policies may introduce bias. Furthermore, previous studies did not examine any trends in the inclusion of limitation statements in articles.

This study aims to assess the frequency of limitation statements in original articles within three leading general medical journals in the United States. It seeks to explore trends from 2002 to 2022, both before and after the publication of relevant reporting guidelines for the respective publication types. Based on personal observations, we hypothesize that there is an increasing trend in the inclusion of limitation statements, particularly after the publication of reporting guidelines.

Methods and analysis

So far, there is no formal reporting guideline for meta-analysis. We will use the reporting guideline proposed by Murad et al. [ 12 ], which provided a framework for reporting meta-epidemiological studies.

Eligibility criteria

The eligible criteria are original articles published in the New England Journal of Medicine (NEJM), Journal of American Medical Association (JAMA) and Annals of Internal Medicine (Ann Intern Med). These three journals are selected because they were rated the top three general medical journals in the US.

Study selection

NEJM, JAMA and Ann Intern Med adapt different kinds of columns, consisting of a variety of article types. Therefore, we only enroll articles which were published in the original article section of NEJM, the original contribution and original research section of JAMA, and original research section of Ann Intern Med. Articles categorized in other sections, such as preliminary communication or special communication, regardless of publication types, are not enrolled. A model of flow diagram that will be used to describe for the study selection process is depicted in S1 Fig in the supplement file.

Data collection process

We systematically acquired, through hand-searching, all the full text of original articles published between the first issue in January 2002 to the last issue in December 2022 from the website of the NEJM, JAMA and Ann Intern Med.

We only exclude original articles, by hand-searching, which have been labelled as retracted, regardless of the reason and availability on the journal website. Examples are Mehra’s and Gander’s articles in NEJM and JAMA, respectively [ 13 , 14 ].

The Japan-US-Taiwan meta-research group gathers researchers who have published a few commentaries in both NEJM [ 15 ], JAMA [ 16 ] and other leading journals [ 17 ]. In this study, two reviewers (Hsu NC and Hsu CH) will conduct the investigations independently for each article to determine whether a limitation statement exists. Discrepancies will be resolved by consultation with the corresponding author (Tokuda Y). We identify limitations exclusively within the discussion section, as we observe that articles often discussed methods for minimizing bias or controlling for confounding in the methodology section. Some authors may subjectively characterize these approaches as strengths of the study, while others acknowledge them as limitations. Consequently, our focus is specifically on determining whether these statements are presented in the discussion section.

Variables in this study include the study design and the temporal relationship with the respective reporting guidelines. The study designs are classified into three categories. A randomized controlled trial (RCT) is defined as a comparative study reporting a random assignment of participants anywhere in the report. A clinical trial without random assignment is identified as a non-randomized trial. A meta-analysis study is defined as a quantitative research synthesis method that statistically combines the results of multiple independent studies, typically indicated in the title of a report [ 18 ].

The CONSORT statement was first published in 1996 [ 6 ], with subsequent revision in 2001 [ 7 ], and 2010 [ 8 ]. We investigate publication between 2002 and 2022 and chose the year 2010 as a reference point to assess the pre-post changes in limitation statements of randomized trials. The STROBE guideline for observational studies, initially published in 2007 without subsequent revisions [ 10 ], serves as the reference point for pre-post changes in limitation statements for non-randomized trials.

The main measure of our study is the existence of limitation statements in eligible articles. Before investigation, the authors have convened a consensus meeting regarding the definition of the limitation statement. The forms of the limitation statement are categorized and exemplified in S1 Table . After a random review of original articles published in these three journals, there are ten primary forms of limitation statements commonly found in the discussion section of academic papers, which include: (1) a subheading entitled “limitations”; (2) a subheading entitled “strengths and limitations”; (3) a subheading entitled “methodological considerations”; (4) a single paragraph discussing limitations without a subheading; (5) multiple paragraphs discussing limitations without a subheading; (6) statements of limitations or weaknesses alongside strengths within the same paragraph; (7) discussions of “bias” without mentioning limitations; (8) discussions of “weakness” without mentioning limitations; (9) reasons for interpreting the results cautiously, without directly mentioning limitations; and (10) acknowledgments of areas where the study may fall short, without using the terms “limitations,” “weakness,” or “bias.” ( S1 Table )

Synthesis of results

The main result of interest is the frequency of limitation statement in the discussion section of eligible original research articles, and the trend of annual publications from 2002 to 2022 counted on a yearly basis.

To avoid missing limitation statements in articles not reporting limitations in any of the ten forms mentioned above, we will conduct a sensitivity analysis. Three reviewers (Hsu NC, Hsu CH, and Tsai HB) have convened a consensus meeting to identify additional words that will be used during the sensitivity analysis: "limited", "confound", and "caution". Combined with “limitation”, “weakness”, and “bias”, which we have already employed in the primary form, the sensitivity analysis will contain six words. We have done a pilot testing of the sensitivity analysis using the original articles published in the first three months of 2012, 2014, 2016, 2018, 2020 and 2022 in NEJM and JAMA. With the gold standard of limitation statements recognized independently by two reviewers (Hsu NC and Hsu CH), the absence of all six limitation-pertinent words predicted no limitation statement with 100% accuracy. The occurrence of at least two of the six words resulted in a 100% accuracy in predicting the existence of limitation statements. Based on this pilot test, articles lacking any of the six limitation-pertinent words will be categorized as having no limitation statements in this study. On the websites of these journals, we will use these limitation-pertinent words to manually screen the full text of each article in electronic form as a sensitivity analysis.

We use the Chi-square test to depict frequency distributions for descriptive categorical variables, such as the frequency of limitation statements within a specific journal or a research design. Trends between journals, research designs, and pre-post change are analyzed by the Cochran Armitage test with a P value. Analyses will be conducted using R (R Project for Statistical Computing version 4.1.2) and SPSS version 24. A P value of 0.05 or less will be used to define the statistical significance of a test result.

We do not seek approval from the research ethics committee or institutional review board because the study does not involve human subjects, and the data are publicly available.

The fourth edition of the "Uniform Requirements for Manuscripts Submitted to Biomedical Journals," initially published in NEJM in 1991, served as a coordinating document developed by the International Committee of Medical Journal Editors (ICMJE) in North America [ 19 ]. In this document, it suggested the article should “include in the Discussion section the implications of the findings and their limitations, including implications for future research”. Because the limitations of a study can be discussed in various ways, it becomes challenging to audit their presence or absence.

From the introduction of the first CONSORT statement in 1996, statements of specific interpretation of study findings, including sources of bias and imprecision (internal validity) and discussion of external validity, including appropriate quantitative measures are necessary in the comment section among the five structured subheadings of RCT [ 6 ]. However, the submission process of an original research for some leading medical journals does not mandate an inclusion of any formal reporting guideline.

Our study aims to analyze the inclusion of limitation statements in the reports of original research published by three leading general medical journals in the United States. We hypothesize that the inclusion of limitation statements has been increasing, particularly following the publication of reporting guidelines. This investigation may contribute to the audit of reporting quality in trials, compatible with the goal and mission of a meta-research study. A previous review in psychology critically examined diverse approaches to defining and measuring intellectual humility and identified the common element: a meta-cognitive ability to recognize the limitations of one’s beliefs and knowledge [ 1 ]. Therefore, limitation statements in a research report are crucial and go beyond merely adhering to reporting guidelines.

Limitations

Potential limitations of our study encompass exclusive focus on three medical journals in the US, challenges in recognizing limitation statements, variations in author writing styles, confounding by the peer review process, and absence of a comprehensive analysis of the content and quality of the limitation statements. NEJM doesn’t require the inclusion of a subsection on limitations in the discussion. While JAMA suggested a subsection of limitation since 2017, we emphasize that our study refrains from drawing direct comparisons between the journals in this context.

The findings of this study may provide an overview of the limitation statements in leading general medical journals in the US, including the frequency and trends. As this is an inaugural investigation, the results may provide a foundation for future research aimed at identifying factors such as article types, research topics, and journal author guidelines that are associated with the presence of limitation statements.

Supporting information

S1 fig. a modified prisma flow diagram for meta-research analysis..

https://doi.org/10.1371/journal.pone.0305970.s001

S1 Table. Forms of limitation statement in the discussion section of original research articles.

https://doi.org/10.1371/journal.pone.0305970.s002

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