Applying qualitative comparative analysis in a systematic review: Lessons learned

Evidence synthesis of primary studies assessing complex interventions poses challenges due to the heterogeneity of study populations, interventions, outcomes, or study designs. Qualitative comparative analysis (QCA) aims to identify conditions or combinations of conditions that lead to a specific outcome and may be an appropriate instrument to deal with heterogeneity and complexity.

We aimed to describe the lessons learned when applying QCA in a systematic review on technology-based counselling interventions in dementia.

The lessons learned were generated through research team reflection and discussion of the challenges and problems encountered in the process of applying the initial steps of the QCA. As the QCA remained incomplete, a brief account of aspects to be considered when using QCA methodology for data synthesis within a systematic review is presented.

The lessons learned comprise the importance of clear eligibility criteria representing the core elements of interventions and the need for a consistent dataset based on sufficient reporting and suitable publication types. We also recommend adoption of a multi-perspective view by integrating theoretical and practical knowledge.

QCA may increase knowledge gain in systematic reviews by capturing the complexity of interventions and contexts. An adequate dataset is needed to enable systematic comparison. To achieve this, adherence to frameworks guiding the development, implementation, and evaluation of complex interventions as well as to reporting guidelines is essential.