Using machine‐assisted topic analysis to expedite thematic analysis of free‐text data: Exemplar investigation of factors influencing health behaviours and wellbeing during the <scp>COVID</scp> ‐19 pandemic
MATA shows promise as a resource-saving method for thematic analysis of large qualitative datasets whilst maintaining researcher control and insight. Findings show the interconnection between health behaviours, physical health and wellbeing over the pandemic, and the influence of control and reflective processes.
Authors
- Trisevgeni Papakonstantinou (ORCID: https://orcid.org/0000-0001-5116-1531)
- Ben Ainsworth (ORCID: https://orcid.org/0000-0002-5098-1092)
- Pippa Belderson (ORCID: https://orcid.org/0000-0003-2065-6878)
- Paulina Bondaronek (ORCID: https://orcid.org/0000-0003-0096-1234)
- Sarah Hanson (ORCID: https://orcid.org/0000-0003-4751-8248)
- Caitlin Notley (ORCID: https://orcid.org/0000-0003-0876-3304)
- Felix Naughton (ORCID: https://orcid.org/0000-0001-9790-2796)
- Emma Ward (ORCID: https://orcid.org/0000-0002-7579-3215)
Institutions
- University of East Anglia (GB)
- NIHR Southampton Biomedical Research Centre (GB)
- University of Southampton (GB)
- University College London (GB)
Publication Details
- Journal
- British Journal of Health Psychology
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1111/bjhp.70017
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00