Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 4,040

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Interpretative Phenomenological Analysis

·2020·SAGE Research Methods Foundations

Abstract

The aim of interpretative phenomenological analysis (IPA) is to explore in detail how participants are making sense of their personal and social world, and the main currency for an IPA study is the meanings particular experiences, events, states hold for participants. The approach is phenomenological (see Chapter 3) in that it involves detailed examination of the participant’s lifeworld; it attempts to explore personal experience and is concerned with an individual’s personal perception or account of an object or event, as opposed to an attempt to produce an objective statement of the object or event itself. At the same time, IPA also emphasizes that the research exercise is a dynamic process with an active role for the researcher in that process. One is trying to get close to the participant’s personal world, to take, in Conrad’s (1987) words, an ‘insider’s perspective’, but one cannot do this directly or completely. Access depends on, and is complicated by, the researcher’s own conceptions; indeed, these are required in order to make sense of that other personal world through a process of interpretative activity. Thus, a two-stage interpretation process, or a double hermeneutic, is involved. The participants are trying to make sense of their world; the researcher is trying to make sense of the participants trying to make sense of their world. IPA is therefore intellectually connected to hermeneutics and theories of interpretation (Packer and Addison, 1989; Palmer, 1969; Smith, in press; see also Chapter 2 this volume). Different interpretative stances are possible, and IPA combines an empathic hermeneutics with a questioning hermeneutics. Thus, consistent with its phenomenological origins, IPA is concerned with trying to understand what it is like, from the point of view of the participants, to take their side. At the same time, a detailed IPA analysis can also involve asking critical questions of the texts from participants, such as the following: What is the person trying to achieve here? Is something leaking out here that wasn’t intended? Do I have a sense of something going on here that maybe the participants themselves are less aware of?

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.4135/9781526421036813346

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Metadata

Venue
SAGE Research Methods Foundations
Published
2020
OpenAlex
W1938990613
Cited by
4,040
References
3
Type
reference entry
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Interpretative Phenomenological Analysis. https://app.cochat.ai/papers/10.4135/9781526421036813346
The paper
Interpretative Phenomenological Analysis. (2020). SAGE Research Methods Foundations. https://doi.org/10.4135/9781526421036813346

Data sources

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.