From Description and Reduction of Manifest Content to Latent Interpretation: Integration of Content and Thematic Analyses for Large Qualitative Survey Datasets
Technological changes offer immense opportunity for qualitative data collection in health research, in both standalone qualitative surveys and mixed-method designs. However, not all qualitative analysis is suitable for the large qualitative datasets that can be obtained from surveys with numerous open-ended questions. This paper aimed to (1) consider the appropriateness of common qualitative approaches for analysing textual responses in survey data, (2) extend conceptual and practical considerations for a novel integration of content and thematic analysis for qualitative survey data, and (3) demonstrate the application through a worked example. Content analysis can be well suited for individual open-ended questions of a survey, identifying codes and categories. However, where multiple open-ended survey questions are included in a survey, an interpretative process may be needed to facilitate the identification of latent themes across numerous qualitative survey questions. To address the need for hybrid, descriptive and interpretative methods, this perspective paper extends the sequential integration of content and thematic analysis to facilitate analysis of large qualitative datasets. This iterative and recursive analytic process is presented as a tool for researchers to sequentially reduce and describe large volumes of textual responses with content analysis, and an interpretative thematic process to integrate data across numerous questions. The point of analytic transition is described, and an integrated framework is illustrated and demonstrated with a worked example. This flexible integration can be employed with any variation of content analysis and thematic analysis and may be applied with qualitative data generated in mixed-method surveys or purely qualitative surveys. This integration provides a practical framework for analysing data from numerous qualitative questions in a survey and may have utility for researchers analysing qualitative survey data across all disciplines.
Authors
- Maja Nedeljkovic (ORCID: https://orcid.org/0000-0003-0963-0335)
- Kylie Rice (ORCID: https://orcid.org/0000-0002-7072-5619)
- Glen William Bates (ORCID: https://orcid.org/0000-0001-5435-1269)
Institutions
- Swinburne University of Technology (AU)
- University of New England (AU)
Publication Details
- Journal
- International Journal of Mental Health Nursing
- Published
- 2026-11-11
- DOI
- https://doi.org/10.1111/inm.70380
- Primary Topic
- Qualitative Research Methods and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00