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Cited by 3,742Qualitative Research Methods and ApplicationsQualitative Research Methods and EthicsHealth Policy Implementation Science

Qualitative research in health care: Assessing quality in qualitative research

Open access
Mays, N.·2000·BMJ
DOI 10.1136/bmj.320.7226.50PMC PMC1117321
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Abstract

This is the first in a series of three articles In the past decade, qualitative methods have become more commonplace in areas such as health services research and health technology assessment, and there has been a corresponding rise in the reporting of qualitative research studies in medical and related journals.1 Interest in these methods and their wider exposure in health research has led to necessary scrutiny of qualitative research. Researchers from other traditions are increasingly concerned to understand qualitative methods and, most importantly, to examine the claims researchers make about the findings obtained from these methods. The status of all forms of research depends on the quality of the methods used. In qualitative research, concern about assessing quality has manifested itself recently in the proliferation of guidelines for doing and judging qualitative work.2–5 Users and funders of research have had an important role in developing these guidelines as they become increasingly familiar with qualitative methods, but require some means of assessing their quality and of distinguishing “good” and “poor” quality research. However, the issue of “quality” in qualitative research is part of a much larger and contested debate about the nature of the knowledge produced by qualitative research, whether its quality can legitimately be judged, and, if so, how. This paper cannot do full justice to this wider epistemological debate. Rather it outlines two views of how qualitative methods might be judged and argues that qualitative research can be assessed according to two broad criteria: validity and relevance. #### Summary points Qualitative methods are now widely used and increasingly accepted in health research, but quality in qualitative research is a mystery to many health services researchers There is considerable debate over the nature of the knowledge produced by such methods and how such research should be judged Antirealists argue …

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  • The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study.

    “The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[8,18-21].”

    From The case study approach (2011) · cites this paper as [20]

    In “Assessing the validity of qualitative research” → “Triangulation” (page not provided), the paper describes comparing multiple data sources to corroborate an interpretation and presents triangulation among ways of improving validity. It does not specifically say that this increases internal validity as defined in the citing sentence—whether the method is appropriate to the research question—and cautions that triangulation may be better viewed as promoting comprehensiveness than as a pure test of validity. (LLM, conf=0.84)

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  • Transparency throughout the research process addresses concerns about lack of scientific rigour and generalisation in case study research.

    “There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8)[8,18-21,23,26].”

    From The case study approach (2011) · cites this paper as [20]

    The sections “Clear exposition of methods of data collection and analysis” and “Relevance” say that detailed reporting lets readers assess whether interpretations are supported and whether findings apply in similar settings. This supports transparency as a response to concerns about rigour and generalisation in qualitative research, but the paper does not make the claim specifically about case study research. Page numbers are unavailable in our copy. (LLM, conf=0.85)

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  • Respondent validation addresses concerns about lack of scientific rigour and generalisation in case study research.

    “There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8)[8,18-21,23,26].”

    From The case study approach (2011) · cites this paper as [20]

    The “Respondent validation” section describes participants checking the researcher’s account and treats this as a way to improve credibility and reduce errors. The “Relevance” section discusses generalisation separately, through reporting and sampling; it does not say respondent validation addresses generalisation in case study research. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Evidence shows that researchers can influence their participants and that good qualitative research happens when the researcher is reflexive and truly understands their impact on the study and analysis.

    “Evidence shows that researchers can influence their participants and that good qualitative research happens when the researcher is reflexive and truly understands their impact on the study and analysis [64–66].”

    From Barriers to voluntary participation in sport for children: a systematic review (2018) · cites this paper as [66]

  • Results from the qualitative analysis were compared with the quantitative measures from the questionnaire, a validation strategy referred to as triangulation.

    “In addition, the results from the qualitative analysis were compared with the quantitative measures from the questionnaire; this validation strategy is also referred to as triangulation (61).”

    From Acceptance, experiences, and needs of hospitalized pregnant women toward an electronic mindfulness-based intervention: A pilot mixed-methods study (2022) · cites this paper as [61]

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Cites

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Research works printed but not linked: 4

  1. Dingwall R, Murphy E, Watson P, Greatbatch D, Parker S. Catching goldfish: quality in qualitative research. Journal of Health Services Research and Policy 1998;3:167-72.
  2. [3]Blaxter M. Criteria for evaluation of qualitative research. Medical Sociology News. 1996;22:68–71. [Google Scholar]
  3. [6]Murphy E, Dingwall R, Greatbatch D, Parker S, Watson P. Qualitative research methods in health technology assessment: a review of the literature. Health Technol Assess 1998;2. (Monograph.) [PubMed]
  4. [8]Lincoln YS, Guba EG. Naturalistic inquiry. Newbury Park, CA: Sage; 1985. [Google Scholar]

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Authors
Mays, N.
Affiliations
Treasury (NZ)
Corresponding author
Mays, N.
ORCID
Mays, N.
Venue
BMJ
Publisher
BMJ
Published
2000-01-01
Volume
320
Issue
7226
Pages
50-52
ISSN
0959-8138 (ISSN-L)
DOI
10.1136/bmj.320.7226.50
PMC
PMC1117321
OpenAlex
W2084085196
Cited by
3,742
References
12
Citations by year
2026: 91 · 2025: 108 · 2024: 153 · 2023: 147 · 2022: 180 · 2021: 166 · 2020: 209 · 2019: 206 · 2018: 220 · 2017: 216 · 2016: 199 · 2015: 208 · 2014: 220 · 2013: 208 · 2012: 185
FWCI
243.35
Type
journal article
Language
en
Open access
Locations
  • BMJ (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • HighWire Press Open Archive (submittedVersion)
Topics
  • Social Sciences › Education › Qualitative Research Methods and Applications
  • Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
Keywords
qualitative research quality, quality standards, validity, relevance, epistemology of qualitative research, anti-realism, health services research, health technology assessment, reporting guidelines
MeSH terms
Data Collection, Evaluation Studies as Topic, Quality Assurance, Health Care, Research, Guidelines as Topic

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