The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Qualitative Data Analysis for Health Services Research: Developing Taxonomy, Themes, and Theory
Open accessAbstract
Objective. To provide practical strategies for conducting and evaluating analyses of qualitative data applicable for health services researchers. Data Sources and Design. We draw on extant qualitative methodological literature to describe practical approaches to qualitative data analysis. Approaches to data analysis vary by discipline and analytic tradition; however, we focus on qualitative data analysis that has as a goal the generation of taxonomy, themes, and theory germane to health services research. Principle Findings. We describe an approach to qualitative data analysis that applies the principles of inductive reasoning while also employing predetermined code types to guide data analysis and interpretation. These code types (conceptual, relationship, perspective, participant characteristics, and setting codes) define a structure that is appropriate for generation of taxonomy, themes, and theory. Conceptual codes and subcodes facilitate the development of taxonomies. Relationship and perspective codes facilitate the development of themes and theory. Intersectional analyses with data coded for participant characteristics and setting codes can facilitate comparative analyses. Conclusions. Qualitative inquiry can improve the description and explanation of complex, real‐world phenomena pertinent to health services research. Greater understanding of the processes of qualitative data analysis can be helpful for health services researchers as they use these methods themselves or collaborate with qualitative researchers from a wide range of disciplines.
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“As per recommendations on team approaches [43], our team’s mix of researchers from psychology, psychiatry, and sociology perspectives helped us explore differences in interpretation and reduced the influence of theoretical or personal preconceptions.”
From Support Needs and Experiences of People Bereaved by Suicide: Qualitative Findings from a Cross-Sectional British Study of Bereaved Young Adults (2018) · cites this paper as [43]
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“Intercoder reliability was encouraged by ensuring at least two members of the research team coded each of the transcripts independently and agreed upon the final coding used46.”
From The complexity of mental health care for people with COPD: a qualitative study of clinicians’ perspectives (2021) · cites this paper as [46]
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“Selected anonymised interview excerpts were drawn out to ensure the individual ‘stories’ were not lost and to explore how themes interrelated [29].”
Metadata
- Authors
- Bradley, E. H., Curry, L. A., & Devers, K. J.
- Affiliations
- Yale University (US)
- UConn Health (US)
- Virginia Commonwealth University (US)
- Venue
- Health Services Research
- Publisher
- Wiley
- Published
- 2007-01-24
- Volume
- 42
- Issue
- 4
- Pages
- 1758-1772
- ISSN
- 0017-9124 (ISSN-L)
- 1475-6773
- PMC
- PMC1955280
- OpenAlex
- W1987614881
- Semantic Scholar
- 681b6891fca9fab4b6c968ebe6b889fd5d60db7c
- Cited by
- 3,437
- References
- 66
- Citations by year
- 2026: 140 · 2025: 209 · 2024: 261 · 2023: 265 · 2022: 334 · 2021: 304 · 2020: 295 · 2019: 238 · 2018: 237 · 2017: 235 · 2016: 189 · 2015: 196 · 2014: 145 · 2013: 118 · 2012: 93
- FWCI
- 149.24
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Health Services Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Keywords
- qualitative data analysis, taxonomy development, theme development, theory development, inductive reasoning, participant characteristics, intersectional analysis, interdisciplinary collaboration
- MeSH terms
- Health Services Research, Humans, Statistics as Topic, Qualitative Research
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