reliability for qualitative research

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Validity, reliability, and generalizability in qualitative research

Lawrence leung.

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Address for correspondence: Prof. Lawrence Leung, Centre of Studies in Primary Care, Queen's University, 220 Bagot Street, Kingston, ON K7L 5E9, Canada. E-mail: [email protected]

This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In general practice, qualitative research contributes as significantly as quantitative research, in particular regarding psycho-social aspects of patient-care, health services provision, policy setting, and health administrations. In contrast to quantitative research, qualitative research as a whole has been constantly critiqued, if not disparaged, by the lack of consensus for assessing its quality and robustness. This article illustrates with five published studies how qualitative research can impact and reshape the discipline of primary care, spiraling out from clinic-based health screening to community-based disease monitoring, evaluation of out-of-hours triage services to provincial psychiatric care pathways model and finally, national legislation of core measures for children's healthcare insurance. Fundamental concepts of validity, reliability, and generalizability as applicable to qualitative research are then addressed with an update on the current views and controversies.

Keywords: Controversies, generalizability, primary care research, qualitative research, reliability, validity

Nature of Qualitative Research versus Quantitative Research

The essence of qualitative research is to make sense of and recognize patterns among words in order to build up a meaningful picture without compromising its richness and dimensionality. Like quantitative research, the qualitative research aims to seek answers for questions of “how, where, when who and why” with a perspective to build a theory or refute an existing theory. Unlike quantitative research which deals primarily with numerical data and their statistical interpretations under a reductionist, logical and strictly objective paradigm, qualitative research handles nonnumerical information and their phenomenological interpretation, which inextricably tie in with human senses and subjectivity. While human emotions and perspectives from both subjects and researchers are considered undesirable biases confounding results in quantitative research, the same elements are considered essential and inevitable, if not treasurable, in qualitative research as they invariable add extra dimensions and colors to enrich the corpus of findings. However, the issue of subjectivity and contextual ramifications has fueled incessant controversies regarding yardsticks for quality and trustworthiness of qualitative research results for healthcare.

Impact of Qualitative Research upon Primary Care

In many ways, qualitative research contributes significantly, if not more so than quantitative research, to the field of primary care at various levels. Five qualitative studies are chosen to illustrate how various methodologies of qualitative research helped in advancing primary healthcare, from novel monitoring of chronic obstructive pulmonary disease (COPD) via mobile-health technology,[ 1 ] informed decision for colorectal cancer screening,[ 2 ] triaging out-of-hours GP services,[ 3 ] evaluating care pathways for community psychiatry[ 4 ] and finally prioritization of healthcare initiatives for legislation purposes at national levels.[ 5 ] With the recent advances of information technology and mobile connecting device, self-monitoring and management of chronic diseases via tele-health technology may seem beneficial to both the patient and healthcare provider. Recruiting COPD patients who were given tele-health devices that monitored lung functions, Williams et al. [ 1 ] conducted phone interviews and analyzed their transcripts via a grounded theory approach, identified themes which enabled them to conclude that such mobile-health setup and application helped to engage patients with better adherence to treatment and overall improvement in mood. Such positive findings were in contrast to previous studies, which opined that elderly patients were often challenged by operating computer tablets,[ 6 ] or, conversing with the tele-health software.[ 7 ] To explore the content of recommendations for colorectal cancer screening given out by family physicians, Wackerbarth, et al. [ 2 ] conducted semi-structure interviews with subsequent content analysis and found that most physicians delivered information to enrich patient knowledge with little regard to patients’ true understanding, ideas, and preferences in the matter. These findings suggested room for improvement for family physicians to better engage their patients in recommending preventative care. Faced with various models of out-of-hours triage services for GP consultations, Egbunike et al. [ 3 ] conducted thematic analysis on semi-structured telephone interviews with patients and doctors in various urban, rural and mixed settings. They found that the efficiency of triage services remained a prime concern from both users and providers, among issues of access to doctors and unfulfilled/mismatched expectations from users, which could arouse dissatisfaction and legal implications. In UK, a care pathways model for community psychiatry had been introduced but its benefits were unclear. Khandaker et al. [ 4 ] hence conducted a qualitative study using semi-structure interviews with medical staff and other stakeholders; adopting a grounded-theory approach, major themes emerged which included improved equality of access, more focused logistics, increased work throughput and better accountability for community psychiatry provided under the care pathway model. Finally, at the US national level, Mangione-Smith et al. [ 5 ] employed a modified Delphi method to gather consensus from a panel of nominators which were recognized experts and stakeholders in their disciplines, and identified a core set of quality measures for children's healthcare under the Medicaid and Children's Health Insurance Program. These core measures were made transparent for public opinion and later passed on for full legislation, hence illustrating the impact of qualitative research upon social welfare and policy improvement.

Overall Criteria for Quality in Qualitative Research

Given the diverse genera and forms of qualitative research, there is no consensus for assessing any piece of qualitative research work. Various approaches have been suggested, the two leading schools of thoughts being the school of Dixon-Woods et al. [ 8 ] which emphasizes on methodology, and that of Lincoln et al. [ 9 ] which stresses the rigor of interpretation of results. By identifying commonalities of qualitative research, Dixon-Woods produced a checklist of questions for assessing clarity and appropriateness of the research question; the description and appropriateness for sampling, data collection and data analysis; levels of support and evidence for claims; coherence between data, interpretation and conclusions, and finally level of contribution of the paper. These criteria foster the 10 questions for the Critical Appraisal Skills Program checklist for qualitative studies.[ 10 ] However, these methodology-weighted criteria may not do justice to qualitative studies that differ in epistemological and philosophical paradigms,[ 11 , 12 ] one classic example will be positivistic versus interpretivistic.[ 13 ] Equally, without a robust methodological layout, rigorous interpretation of results advocated by Lincoln et al. [ 9 ] will not be good either. Meyrick[ 14 ] argued from a different angle and proposed fulfillment of the dual core criteria of “transparency” and “systematicity” for good quality qualitative research. In brief, every step of the research logistics (from theory formation, design of study, sampling, data acquisition and analysis to results and conclusions) has to be validated if it is transparent or systematic enough. In this manner, both the research process and results can be assured of high rigor and robustness.[ 14 ] Finally, Kitto et al. [ 15 ] epitomized six criteria for assessing overall quality of qualitative research: (i) Clarification and justification, (ii) procedural rigor, (iii) sample representativeness, (iv) interpretative rigor, (v) reflexive and evaluative rigor and (vi) transferability/generalizability, which also double as evaluative landmarks for manuscript review to the Medical Journal of Australia. Same for quantitative research, quality for qualitative research can be assessed in terms of validity, reliability, and generalizability.

Validity in qualitative research means “appropriateness” of the tools, processes, and data. Whether the research question is valid for the desired outcome, the choice of methodology is appropriate for answering the research question, the design is valid for the methodology, the sampling and data analysis is appropriate, and finally the results and conclusions are valid for the sample and context. In assessing validity of qualitative research, the challenge can start from the ontology and epistemology of the issue being studied, e.g. the concept of “individual” is seen differently between humanistic and positive psychologists due to differing philosophical perspectives:[ 16 ] Where humanistic psychologists believe “individual” is a product of existential awareness and social interaction, positive psychologists think the “individual” exists side-by-side with formation of any human being. Set off in different pathways, qualitative research regarding the individual's wellbeing will be concluded with varying validity. Choice of methodology must enable detection of findings/phenomena in the appropriate context for it to be valid, with due regard to culturally and contextually variable. For sampling, procedures and methods must be appropriate for the research paradigm and be distinctive between systematic,[ 17 ] purposeful[ 18 ] or theoretical (adaptive) sampling[ 19 , 20 ] where the systematic sampling has no a priori theory, purposeful sampling often has a certain aim or framework and theoretical sampling is molded by the ongoing process of data collection and theory in evolution. For data extraction and analysis, several methods were adopted to enhance validity, including 1 st tier triangulation (of researchers) and 2 nd tier triangulation (of resources and theories),[ 17 , 21 ] well-documented audit trail of materials and processes,[ 22 , 23 , 24 ] multidimensional analysis as concept- or case-orientated[ 25 , 26 ] and respondent verification.[ 21 , 27 ]

Reliability

In quantitative research, reliability refers to exact replicability of the processes and the results. In qualitative research with diverse paradigms, such definition of reliability is challenging and epistemologically counter-intuitive. Hence, the essence of reliability for qualitative research lies with consistency.[ 24 , 28 ] A margin of variability for results is tolerated in qualitative research provided the methodology and epistemological logistics consistently yield data that are ontologically similar but may differ in richness and ambience within similar dimensions. Silverman[ 29 ] proposed five approaches in enhancing the reliability of process and results: Refutational analysis, constant data comparison, comprehensive data use, inclusive of the deviant case and use of tables. As data were extracted from the original sources, researchers must verify their accuracy in terms of form and context with constant comparison,[ 27 ] either alone or with peers (a form of triangulation).[ 30 ] The scope and analysis of data included should be as comprehensive and inclusive with reference to quantitative aspects if possible.[ 30 ] Adopting the Popperian dictum of falsifiability as essence of truth and science, attempted to refute the qualitative data and analytes should be performed to assess reliability.[ 31 ]

Generalizability

Most qualitative research studies, if not all, are meant to study a specific issue or phenomenon in a certain population or ethnic group, of a focused locality in a particular context, hence generalizability of qualitative research findings is usually not an expected attribute. However, with rising trend of knowledge synthesis from qualitative research via meta-synthesis, meta-narrative or meta-ethnography, evaluation of generalizability becomes pertinent. A pragmatic approach to assessing generalizability for qualitative studies is to adopt same criteria for validity: That is, use of systematic sampling, triangulation and constant comparison, proper audit and documentation, and multi-dimensional theory.[ 17 ] However, some researchers espouse the approach of analytical generalization[ 32 ] where one judges the extent to which the findings in one study can be generalized to another under similar theoretical, and the proximal similarity model, where generalizability of one study to another is judged by similarities between the time, place, people and other social contexts.[ 33 ] Thus said, Zimmer[ 34 ] questioned the suitability of meta-synthesis in view of the basic tenets of grounded theory,[ 35 ] phenomenology[ 36 ] and ethnography.[ 37 ] He concluded that any valid meta-synthesis must retain the other two goals of theory development and higher-level abstraction while in search of generalizability, and must be executed as a third level interpretation using Gadamer's concepts of the hermeneutic circle,[ 38 , 39 ] dialogic process[ 38 ] and fusion of horizons.[ 39 ] Finally, Toye et al. [ 40 ] reported the practicality of using “conceptual clarity” and “interpretative rigor” as intuitive criteria for assessing quality in meta-ethnography, which somehow echoed Rolfe's controversial aesthetic theory of research reports.[ 41 ]

Food for Thought

Despite various measures to enhance or ensure quality of qualitative studies, some researchers opined from a purist ontological and epistemological angle that qualitative research is not a unified, but ipso facto diverse field,[ 8 ] hence any attempt to synthesize or appraise different studies under one system is impossible and conceptually wrong. Barbour argued from a philosophical angle that these special measures or “technical fixes” (like purposive sampling, multiple-coding, triangulation, and respondent validation) can never confer the rigor as conceived.[ 11 ] In extremis, Rolfe et al. opined from the field of nursing research, that any set of formal criteria used to judge the quality of qualitative research are futile and without validity, and suggested that any qualitative report should be judged by the form it is written (aesthetic) and not by the contents (epistemic).[ 41 ] Rolfe's novel view is rebutted by Porter,[ 42 ] who argued via logical premises that two of Rolfe's fundamental statements were flawed: (i) “The content of research report is determined by their forms” may not be a fact, and (ii) that research appraisal being “subject to individual judgment based on insight and experience” will mean those without sufficient experience of performing research will be unable to judge adequately – hence an elitist's principle. From a realism standpoint, Porter then proposes multiple and open approaches for validity in qualitative research that incorporate parallel perspectives[ 43 , 44 ] and diversification of meanings.[ 44 ] Any work of qualitative research, when read by the readers, is always a two-way interactive process, such that validity and quality has to be judged by the receiving end too and not by the researcher end alone.

In summary, the three gold criteria of validity, reliability and generalizability apply in principle to assess quality for both quantitative and qualitative research, what differs will be the nature and type of processes that ontologically and epistemologically distinguish between the two.

Source of Support: Nil.

Conflict of Interest: None declared.

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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.

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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.

• View inline

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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