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The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Interpretative Phenomenological Analysis (IPA): A Qualitative Methodology of Choice in Healthcare Research

Biggerstaff, Deborah, Thompson, Andrew R.·2008·Qualitative Research in Psychology

Abstract

This paper focuses on the teaching of the qualitative method, Interpretative Phenomenological Analysis (IPA), to healthcare professionals (HCPs). It introduces briefly the philosophical background of IPA and how it has been used within healthcare research, and then discusses the teaching of IPA to HCPs within received educational theory. Lastly, the paper describes how IPA has been taught to students/trainees in some specific healthcare professions (clinical psychology, medicine, nursing and related disciplines). In doing this, the paper demonstrates the essential simplicity, paradoxical complexity, and methodological rigour that IPA can offer as a research tool in understanding healthcare and illness from the patient or service user perspective.

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Metadata

Authors
Biggerstaff, D., & Thompson, A. R.
Venue
Qualitative Research in Psychology
Published
2008-09-20
Volume
5
Issue
3
Pages
214-224
ISSN
  • 1478-0887 (ISSN-L)
  • 1478-0895
OpenAlex
W2115780895
Cited by
722
References
46
FWCI
25.76
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Interpretative Phenomenological Analysis (IPA): A Qualitative Methodology of Choice in Healthcare Research. https://app.cochat.ai/papers/10.1080/14780880802314304
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Biggerstaff, D., & Thompson, A. R. (2008). Interpretative Phenomenological Analysis (IPA): A Qualitative Methodology of Choice in Healthcare Research. Qualitative Research in Psychology. https://doi.org/10.1080/14780880802314304

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.