how to ensure validity and reliability in qualitative research

Relevance of Reliability and Validity in Qualitative Research

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Traditional, quantitative concepts of validity and reliability are frequently used to critique qualitative research, often leading to criticisms of lacking scientific rigor, insufficient methodological justification, lack of transparency in analysis, and potential for researcher bias.

Alternative terminology is proposed to better capture the principles of rigor and credibility within the qualitative paradigm :

Validity in Qualitative Research

Validity focuses on the truthfulness and accuracy of findings.

Quantitative research, with its focus on objectivity and generalizability, prioritizes internal validity to establish cause-and-effect relationships between variables.

This involves carefully controlling extraneous factors to ensure the observed effects can be confidently attributed to the independent variable.

Qualitative research embraces a different epistemological framework, emphasizing subjectivity, contextual understanding, and the exploration of lived experiences.

In this paradigm, validity focuses on faithfully representing the perspectives, meanings, and interpretations of the participants.

The underlying goal remains to produce research that is rigorous, credible, and insightful, contributing meaningfully to our understanding of complex social phenomena.

This involves ensuring the research process and findings are trustworthy, authentic, and rigorous.

1. Trustworthiness

Validity in qualitative research, often referred to as trustworthiness , assesses the accuracy of findings as representations of the data, participants’ lives, cultures, and contexts.

Trustworthiness is an overarching concept that encompasses both credibility and transferability , reflecting the overall quality and integrity of the research process and findings. It signifies that the research is conducted ethically, rigorously, and transparently.

A central concept in achieving trustworthiness is methodological integrity , which emphasizes the importance of using methods and procedures that are consistent with the research question, goals, and inquiry approach.

Methodological integrity focuses on two key components: fidelity to the subject matter and utility of research contributions .

Fidelity to the Subject Matter

Fidelity to the subject matter emphasizes collecting data that capture the diversity and complexity of the phenomenon under study.

Qualitative research underscores the commitment to representing participants’ authentic perspectives and experiences faithfully and respectfully.

This goes beyond simply recording their words; it involves capturing the depth, complexity, and meaning embedded within their narratives.

Fidelity to the subject matter must demonstratee that the data is adequate to answer the research question and that the researcher’s perspectives were managed during both data collection and analysis to minimize bias.

Researchers should show that the findings are grounded in the evidence by using rich quotes and detailed descriptions of their engagement with the data. This is also referred to as thick, lush description.

Thick description involves going beyond surface-level observations to provide rich, detailed accounts of the data. This includes not just what participants say but also the context of their utterances, their emotional tone, and the nonverbal cues that contribute to meaning.

Thick description enhances authenticity by painting a vivid picture of the participants’ lived experiences, allowing readers to grasp the nuances and complexities of their perspectives.

For instance, if studying a phenomenon like “pain,” researchers should acknowledge whether they perceive it as a real, tangible experience or a socially constructed one.

This understanding shapes data collection and analysis, ensuring the findings remain true to the participants’ realities.

Utility of Research Contributions

Utility refers to the usefulness and value of the research findings.

Studies with high utility introduce new insights, expand upon existing knowledge, or offer practical applications for researchers and practitioners.

The utility of a study’s findings is evaluated in relation to its aims and tradition of inquiry. For example, studies with a critical approach should contribute to an awareness of power dynamics and oppression.

A study might have high fidelity by providing compelling descriptions of student study challenges, but if it only offers obvious or commonly known study strategies, it would have low utility.

Ideally, a study would possess both high fidelity and utility, providing a clear understanding of the phenomenon while also offering valuable contributions to the field.

Strategies to enhance trustworthiness and methodological integrity:

• Using rigorous research methods: Selecting and justifying the chosen qualitative method based on its established rigor enhances credibility and demonstrates a commitment to methodological soundness.
• Reflexivity: Critically examining personal biases, values, and experiences helps researchers identify potential influences on their interpretations and ensure that findings are not solely a product of their own perspectives.
• Promoting authentic voice: Researchers should strive to create conditions that allow participants to express themselves openly and honestly.
• Truth Value: Acknowledging the existence of multiple perspectives and ensuring that the findings accurately represent the participants’ views and experiences.
• Member checking: Involving participants in the research process by sharing findings with them to confirm the accuracy of interpretations.
• Triangulation: Utilizing multiple data sources, methods, or researchers to corroborate findings and provide a more comprehensive understanding of the phenomenon.
• Prolonged engagement: Spending sufficient time in the field to develop a deep understanding of the context and build rapport with participants, which can lead to more insightful and trustworthy data.
• Using thick, rich descriptions: Providing detailed narratives, representative quotes, and thorough descriptions of the context helps readers understand the phenomenon and assess the credibility and transferability of the findings.
• Ensuring continuous data saturation : Immersing oneself in the data, constantly refining understanding, and remaining open to gathering more data if needed ensure that the data adequately captures the complexity and diversity of the phenomenon under study.

2. Transferability

Transferability in qualitative research is similar to external validity in quantitative research. It refers to the extent to which the findings can be applied or transferred to other contexts, settings, or groups.

While generalizability in the statistical sense is not a primary goal of qualitative research, providing sufficient details about the study context, sample, and methods can enhance the transferability of the findings.

Qualitative research prioritizes transferability over generalizability. Transferability acknowledges the context-specific nature of findings and encourages readers to consider the potential applicability of the research to other settings.

Researchers can promote transferability by providing thick descriptions of the context, the participants, and the research process.

Transferability is an external consideration, inviting readers to evaluate the potential applicability of the findings to other settings.

Promoting Transferability :

• Providing thick description: Offering detailed contextual information about the setting, participants, and findings, allowing readers to assess the potential relevance to other settings.
• Purposive sampling: Selecting participants who represent a range of perspectives and experiences relevant to the research question. This can enhance the applicability of the findings to a broader population.
• Discussing limitations: Openly acknowledging the specificities of the research context and the potential limitations of applying the findings to other settings.

Barriers to Validity in Qualitative Research

Researchers should be aware of potential threats to validity and take steps to mitigate them. Some common pitfalls include:

Researcher Bias and Perspective

Researchers’ own beliefs, values, and assumptions can influence data collection, analysis, and interpretation, potentially distorting the findings.

Acknowledging and managing these perspectives is crucial for ensuring fidelity to the subject matter.

This aligns with the concept of reflexivity in qualitative research, which encourages researchers to critically examine their own positionality and its potential impact on the research process.

Inadequate Sampling and Representation

If the sample of participants is not representative of the population of interest or if the data collected are incomplete or insufficiently detailed, the findings might lack conceptual heterogeneity and fail to capture the full range of perspectives and experiences relevant to the research question.

This emphasizes the importance of purposive sampling in qualitative research, aiming to select participants who can provide rich and diverse insights into the phenomenon under study.

Superficial Data and Lack of Thick Description

When data are presented in a cursory or overly simplistic manner, without sufficient detail and context, the validity of the findings can be questioned.

This reductionism can stem from a lack of thorough data analysis or a tendency to prioritize brevity over depth in reporting the results

Thick description , a cornerstone of qualitative research, involves providing rich, detailed accounts of the data, capturing the nuances of the participants’ experiences and the context in which they occur.

Selective Anecdotalism and Cherry-Picking

Choosing to focus on specific anecdotes or data points that support the researcher’s preconceived notions while ignoring contradictory evidence can severely undermine validity.

This selective reporting distorts the overall picture and presents a biased view of the findings.

Qualitative researchers are expected to analyze and present data comprehensively, acknowledging all relevant themes and perspectives, even those that challenge their initial assumptions.

Perceived Coercion and Power Dynamics

In qualitative research, especially when dealing with sensitive topics or vulnerable populations, power imbalances between the researcher and participants can influence the data obtained.

If participants feel pressured or coerced to provide certain answers, their responses might lack authenticity and fail to reflect their genuine perspectives.

This underscores the importance of establishing trust and rapport with participants, ensuring they feel safe and comfortable to share their experiences openly and honestly.

Attrition in Longitudinal Studies

In qualitative studies that involve multiple data collection points over time, participant attrition can threaten validity.

If participants drop out of the study for reasons related to the research topic, the remaining sample might become biased, and the findings might not accurately reflect the experiences of the original group.

Addressing attrition requires careful planning and implementation of strategies to maintain participant engagement and minimize drop-out rates.

Reliability in Qualitative Research

Traditional quantitative definition, focused on the replicability of results, is not directly applicable to qualitative inquiry.

This is because qualitative research often explores complex, context-specific phenomena that are influenced by multiple subjective interpretations.

In qualitative research, reliability refers to the consistency and stability of the research proces s and findings.

Reliability in qualitative research concerns consistency and dependability in data collection, analysis, and interpretation.

Dependability

Instead of striving for replicability, qualitative research prioritizes dependability , which focuses on the consistency and trustworthiness of the research process itself.

This involves demonstrating that the methods used were appropriate, that the data were collected and analyzed systematically, and that the interpretations are well-supported by the evidence.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

Strategies for promoting reliability in qualitative research:

• Standardized procedures: Establishing clear and consistent protocols for data collection, analysis, and interpretation can help ensure that the research process is systematic and replicable.
• Rigorous training for researchers in qualitative methodologies, data analysis techniques, and reflexive practices to manage their own perspectives and biases.
• Audit trails: An audit trail provides evidence of the decisions made by the researcher   regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data. This includes maintaining detailed field notes, documenting coding decisions, and preserving raw data for future reference.
• Transparency in reporting: Clearly articulating the research design, data collection methods, analytical procedures, and the researcher’s own reflexivity allows readers to assess the trustworthiness of the findings and understand the logic behind the interpretations.
• Interrater reliability (optional): While not universally employed in qualitative research, involving multiple coders to analyze the data can provide insights into the consistency of interpretations. However, it’s important to note that complete agreement might not be the goal, as differing perspectives can enrich the analysis. Discrepancies can be discussed and resolved, leading to a more comprehensive understanding of the data.

Barriers to Reliability in Qualitative Research

Subjectivity in data collection and analysis.

One of the main barriers to reliability stems from the subjective nature of qualitative data collection and analysis.

Unlike quantitative research with its standardized procedures, qualitative research often involves a deep engagement with participants and data, relying on the researcher’s interpretation and judgment.

This introduces potential for inconsistency in data coding and interpretation, especially when multiple researchers are involved.

Researchers’ personal backgrounds, experiences, and theoretical orientations can influence their interpretation of the data.

What one researcher considers significant or meaningful may differ from another researcher’s perspective.

This subjectivity can lead to variations in how data is collected, coded, and analyzed, especially when multiple researchers are involved in a study.

Lack of Detailed Documentation

Qualitative studies often involve complex and iterative processes of data collection, analysis, and interpretation. Without a clear and comprehensive record of these processes, it becomes challenging for others to assess the dependability and consistency of the findings.

Insufficient documentation of data collection methods, coding schemes, analytical decisions, and researcher reflexivity can hinder the ability to establish reliability.

A detailed audit trail, which provides a transparent account of the research process, is crucial for demonstrating the trustworthiness and credibility of qualitative findings.

Lack of detailed documentation of the research process, including data collection methods, coding schemes, and analytical decisions, can hinder reliability.

Without such documentation, it becomes difficult for other researchers to replicate the study or assess the reliability of the conclusions drawn.

Reductionism in Data Representation

Reductionism, or oversimplifying complex data by relying on short quotes and superficial descriptions, can also compromise reliability.

Such reductive practices can distort the richness and nuance of the data, leading to potentially misleading interpretations.

Qualitative research often yields rich, nuanced, and context-specific data that cannot be easily reduced to simple categories or short quotes.

However, in an effort to present findings concisely, researchers may resort to reductive practices that distort the true nature of the data.

Relying on short quotes or superficial descriptions without providing sufficient context can lead to misinterpretations and oversimplification.

Such reductive practices fail to capture the complexity and depth of the participants’ experiences and perspectives.

As a result, the reliability of the findings may be questioned, as they may not accurately represent the full range of data collected.

How to establish the validity and reliability of qualitative research?

The validity and reliability of qualitative research represent the key aspects of the quality of research. When handled meticulously, the reliability and validity parameters help differentiate between good and bad research. They also assure readers that the findings of the study are credible and trustworthy. This aspect becomes particularly vital in case studies involving primary data analysis. Here the researcher’s subjectivity can highly influence the interpretation of the data. This article clarifies how to establish the validity and reliability of qualitative research using various tools and techniques.

Establishing the validity of qualitative data

Qualitative data is as important as quantitative data , as it also helps in establishing key research points. However, since it cannot be quantified, the question of its correctness is critical. Validity relates to the appropriateness of any research value, tools and techniques, and processes, including data collection and validation (Mohamad et al., 2015). Validity also establishes the soundness of the methodology, sampling process, data analysis process, and conclusion of the study (Golafshani, 2003).

The main aspect that needs to be ensured is that the research philosophies fall in line with the research. To maintain the validity of the research, there is a need to understand the underlying needs of the research, the overarching process guidelines and the societal rules of ethical research. While establishing validity, there needs to be a consensus among the individual and the society on how to establish the correctness and accuracy of the research. If this aspect is kept in mind, the tools and techniques used are bound to be accepted by wider audiences. The main point to remember, thus, is to choose the tools wisely, which will establish how to correct the data of the research.

One of the major techniques that can be used for establishing the validity of qualitative data includes choosing a skilled moderator. Employing a moderator will help overcome personal bias. Thus, the researcher or the organisation can employ moderators to ensure that the data is genuine and is not influenced by “what the researcher wants to see or hear”.

Another way to promote the validity of research is by employing the strategy of triangulation. This basically involves that the research will be conducted from different or multiple perspectives. For example, this can take the form of using several moderators, in different locations or it could be multiple individuals who are analysing the same data. Basically, any technique through which the researcher can analyse the data from different angles.

Furthermore, the validity of qualitative research can also be established using a technique known as respondent validation. This basically involves testing the initial results with the participants in order to see if the results still ring true.

Establishing the reliability of qualitative data

Quantitative research includes reliability measures where the researcher must prove that the process and the results have replicable outcomes. On the other hand, reliability in qualitative research includes very diverse paradigms, where the aspect itself is epistemologically counter-intuitive along with having a very difficult definition (Russell, 2014). Thus, what needs to be done to maintain and establish reliability in qualitative research is to be consistent.

Reliability tests for qualitative research can be established by techniques like:

• refutational analysis,
• use of comprehensive data,
• constant testing and comparison of data,
• use of tables to record data,
• as well as the use of inclusive deviant cases.

These techniques can help support the data sourcing, data validation and data presentation process of the research, as well as support the claim of reliability in terms of form and context.

Triangulation is another aspect which becomes very important in establishing reliability in the research. Also, as an additional note, it is very important for qualitative research to include a reference to a quantitative aspect. The use of a simple quantitative aspect in otherwise completely qualitative research creates a very positive attitude towards the overall concept of the research and helps to establish reliability in a much easier form. Also, the inclusion of at least two reliability tests, as per the type of research outcomes of a research, is a dependable way of establishing that the research process and results are reliable.

Dos of validity and reliability of qualitative data

• While establishing validity and reliability, it is very important to decide the tools and techniques to be used in the research, before conducting the actual research. This helps in establishing the parameters for obtaining reliable and valid results from the beginning and does not impair the results of the research at the end of the process.
• To conduct efficient reliability and validity measures, an effective assessment of the literature must be done to understand which processes will work. Irrelevant approaches that compromise the reliability and validity of research should not be pursued.
• Reliability and validity processes should be conducted in tandem with the research processes being carried out to confirm the research objective, which provides another additional layer of authenticity to the research work.

Don’ts’ of validity and reliability of qualitative data

• Reliability and validity should not be taken as an extra element of the research. If they do not add value to research, they result in insecurity regarding the accuracy of the results.
• To be able to establish reliability and validity, researchers should not include excessive measures to support their research claims. This may add to unauthenticated results, as adding too many measures will overcomplicate the research.

An example statement of validity

The validity of this research was established using two measures, the data blinding and the inclusion of different sampling groups in the plan. The research included an assessment of the knowledge of traditional cuisine among the present population of a city. Where the sample was divided into two groups- to reduce biases. The sample included young adults, who have been mostly raised in an urban environment, along with middle-aged and elderly population who have had a partial upbringing in the rural area of India. The inclusion of greater diversity and a large number of sample respondents led the research to reduce its biasness towards only one type of outcome, creating a base for valid results. The other technique used was to restrict the amount of information shared with the respondents to make sure that the research was not biased with preconceived notions of the respondents. These steps helped to establish the validity of the results gained, proving the accurateness of the qualitative research. Further, the validity of the questionnaire was established using a panel of experts that reviewed the questionnaire. And hence the statements that did not go well with the subject of the study were removed.

An example statement of reliability

In terms of establishing reliability, the researcher conducted two processes. The first included recording the data in a table to provide an overall assessment of the data collection process and the updated assessment of the results, as they come. The use of the table for recording data provided the researcher with a chance to quickly interpret the results as per the record of every individual respondent and realize the progress of the research.

The table also helped in the concise construction of the conclusion of the research parameters. The reliability was also assessed through data triangulation. Among the various model of data triangulation such as methodological triangulation, data triangulation, investigator triangulation and theoretical triangulation. The study adopted theoretical triangulation, wherein other research works in the same arena were analysed and presented as a literature review to support the results claims of the data collection and analysis process. Moreover, the reliability measures relating to the triangulation of data provided an extensive understanding of the research objectives, which provided an additional layer of reliable stamping to the research.

• Golafshani, N. (2003) ‘Understanding Reliability and Validity in Qualitative Research’, The Qualitative Report , 8(4), pp. 597–607.
• Mohamad, M. M. et al. (2015) ‘Measuring the Validity and Reliability of Research Instruments’, Procedia – Social and Behavioral Sciences . Elsevier, 204, pp. 164–171. doi: 10.1016/j.sbspro.2015.08.129.
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• Volume 18, Issue 2
• Issues of validity and reliability in qualitative research
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• Helen Noble 1 ,
• Joanna Smith 2
• 1 School of Nursing and Midwifery, Queens's University Belfast , Belfast , UK
• 2 School of Human and Health Sciences, University of Huddersfield , Huddersfield , UK
• Correspondence to Dr Helen Noble School of Nursing and Midwifery, Queens's University Belfast, Medical Biology Centre, 97 Lisburn Rd, Belfast BT9 7BL, UK; helen.noble{at}qub.ac.uk

https://doi.org/10.1136/eb-2015-102054

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Evaluating the quality of research is essential if findings are to be utilised in practice and incorporated into care delivery. In a previous article we explored ‘bias’ across research designs and outlined strategies to minimise bias. 1 The aim of this article is to further outline rigour, or the integrity in which a study is conducted, and ensure the credibility of findings in relation to qualitative research. Concepts such as reliability, validity and generalisability typically associated with quantitative research and alternative terminology will be compared in relation to their application to qualitative research. In addition, some of the strategies adopted by qualitative researchers to enhance the credibility of their research are outlined.

Are the terms reliability and validity relevant to ensuring credibility in qualitative research?

Although the tests and measures used to establish the validity and reliability of quantitative research cannot be applied to qualitative research, there are ongoing debates about whether terms such as validity, reliability and generalisability are appropriate to evaluate qualitative research. 2–4 In the broadest context these terms are applicable, with validity referring to the integrity and application of the methods undertaken and the precision in which the findings accurately reflect the data, while reliability describes consistency within the employed analytical procedures. 4 However, if qualitative methods are inherently different from quantitative methods in terms of philosophical positions and purpose, then alterative frameworks for establishing rigour are appropriate. 3 Lincoln and Guba 5 offer alternative criteria for demonstrating rigour within qualitative research namely truth value, consistency and neutrality and applicability. Table 1 outlines the differences in terminology and criteria used to evaluate qualitative research.

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Terminology and criteria used to evaluate the credibility of research findings

What strategies can qualitative researchers adopt to ensure the credibility of the study findings?

Unlike quantitative researchers, who apply statistical methods for establishing validity and reliability of research findings, qualitative researchers aim to design and incorporate methodological strategies to ensure the ‘trustworthiness’ of the findings. Such strategies include:

Accounting for personal biases which may have influenced findings; 6

Acknowledging biases in sampling and ongoing critical reflection of methods to ensure sufficient depth and relevance of data collection and analysis; 3

Meticulous record keeping, demonstrating a clear decision trail and ensuring interpretations of data are consistent and transparent; 3 , 4

Establishing a comparison case/seeking out similarities and differences across accounts to ensure different perspectives are represented; 6 , 7

Including rich and thick verbatim descriptions of participants’ accounts to support findings; 7

Demonstrating clarity in terms of thought processes during data analysis and subsequent interpretations 3 ;

Engaging with other researchers to reduce research bias; 3

Respondent validation: includes inviting participants to comment on the interview transcript and whether the final themes and concepts created adequately reflect the phenomena being investigated; 4

Data triangulation, 3 , 4 whereby different methods and perspectives help produce a more comprehensive set of findings. 8 , 9

Table 2 provides some specific examples of how some of these strategies were utilised to ensure rigour in a study that explored the impact of being a family carer to patients with stage 5 chronic kidney disease managed without dialysis. 10

Strategies for enhancing the credibility of qualitative research

In summary, it is imperative that all qualitative researchers incorporate strategies to enhance the credibility of a study during research design and implementation. Although there is no universally accepted terminology and criteria used to evaluate qualitative research, we have briefly outlined some of the strategies that can enhance the credibility of study findings.

• Sandelowski M
• Lincoln YS ,
• Barrett M ,
• Mayan M , et al
• Greenhalgh T
• Lingard L ,

Twitter Follow Joanna Smith at @josmith175 and Helen Noble at @helnoble

Competing interests None.

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