Sheard, Laura orcid.org/0000-0002-9241-8361 and Marsh, Claire (2019) How to analyse longitudinal data from multiple sources in qualitative health research:the pen portrait analytic technique. BMC Medical Research Methodology. 169. ISSN 1471-2288
Abstract
BACKGROUND: Longitudinal qualitative research is starting to be used in applied health research, having been popular in social research for several decades. There is potential for a large volume of complex data to be captured, over a span of months or years across several different methods. How to analyse this volume of data - with its inherent complexity - represents a problem for health researchers. There is a previous dearth of methodological literature which describes an appropriate analytic process which can be readily employed. METHODS: We document a worked example of the Pen Portrait analytic process, using the qualitative dataset for which the process was originally developed. RESULTS: Pen Portraits are recommended as a way in which longitudinal health research data can be concentrated into a focused account. The four stages of undertaking a pen portrait are: 1) understand and define what to focus on 2) design a basic structure 3) populate the content 4) interpretation. Instructive commentary and guidance is given throughout with consistent reference to the original study for which Pen Portraits were devised. The Pen Portrait analytic process was developed by the authors, borne out of a need to effectively integrate multiple qualitative methods collected over time. Pen Portraits are intended to be adaptable and flexible, in order to meet the differing analytic needs of qualitative longitudinal health studies. CONCLUSIONS: The Pen Portrait analytic process provides a useful framework to enable researchers to conduct a robust analysis of multiple sources of qualitative data collected over time.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © The Author(s) 2019 |
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Health Sciences (York) |
Depositing User: | Pure (York) |
Date Deposited: | 23 Apr 2020 12:50 |
Last Modified: | 16 Oct 2024 16:33 |
Published Version: | https://doi.org/10.1186/s12874-019-0810-0 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1186/s12874-019-0810-0 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159841 |