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Cited by 522

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

A Critical Overview of Interpretative Phenomenological Analysis: A Contemporary Qualitative Research Approach

Open access
Tuffour, Isaac·2017·Journal of Healthcare Communications

Abstract

Context: Interpretative Phenomenological Analysis (IPA) has become a dominant qualitative research methodology in many academic disciplines.The desire to understand the theoretical underpinnings of this research approach is evident.Objective: This paper is aimed at providing an overview and limitations of IPA.This paper will hopefully equip researchers when deciding on the appropriate research methodology to their research topic.Methods: A range of literature on qualitative research approach and phenomenology is reviewed.The relevant literatures on the theoretical underpinnings of IPA are examined.Results: The article illuminates that IPA represents a highly useful methodology in providing a rich and nuance insight into the experiences of research participants.Conclusion: IPA is a forward-looking research approach that adopts a flexible and versatile design to understand people's experiences.

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Metadata

Authors
Tuffour, I.
Venue
Journal of Healthcare Communications
Published
2017
Volume
02
Issue
04
ISSN
2472-1654 (ISSN-L)
OpenAlex
W2765304963
Cited by
522
References
19
FWCI
55.91
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A Critical Overview of Interpretative Phenomenological Analysis: A Contemporary Qualitative Research Approach. https://app.cochat.ai/papers/10.4172/2472-1654.100093
The paper
Tuffour, I. (2017). A Critical Overview of Interpretative Phenomenological Analysis: A Contemporary Qualitative Research Approach. Journal of Healthcare Communications. https://doi.org/10.4172/2472-1654.100093

Data sources

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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.