Citation Arifin SRM, Cheyne H, Maxwell M & Pien LS (2019) Framework analysis: A worked example from a midwifery research. Enfermería Clínica, 29 (Supplement 2), pp. 739-746. https://doi.org/10.1016/j.enfcli.2019.04.112
Framework analysis is a pragmatic approach for real-world investigations and has been commonly used in health care research. Although the theoretical part of framework analysis has been well documented, there is limited literature describing its practical use. The objective of this paper is to demonstrate systematic and explicit guidance in using framework analysis by giving an example of a study exploring women's experience of postnatal depression.
Data presented in this paper comes from semi-structured interviews of 33 women (from three different cultural backgrounds) attending for a child or postnatal care in six purposively selected maternal and child health (MCH) clinics in Kuala Lumpur.
Data were analyzed using framework analysis, which consists of three interrelated stages. In the first stage (data management), a careful selection of the data (transcripts) to be reviewed was made. The initial categories were developed based on the selected transcripts, and the initial themes were decided (known as a thematic framework). In the second stage (descriptive accounts), the thematic framework was investigated to identify any linkage and similarity between one category to another. The third stage of the analysis (explanatory accounts) involved checking exactly how the level of matching between the phenomena was distributed across the whole set of data. Using framework analysis, four themes were identified to explain the women's experience of postnatal depression namely the changes, causal explanations, dealing with postnatal depression, and perceived impacts.
The details of each stage of the analysis were explained to guide researchers through essential steps in undertaking framework analysis. Health care researchers may find a worked example addressed in this paper as useful when analyzing qualitative data.