Peer-reviewed article
The use of Qualitative Comparative Analysis (QCA) in child well-being research: a scoping review of research on child well-being research and interventions
Aye Thiri Kyaw, Meghna Ranganathan, Cathy Zimmerman, Isabelle Pearson, Emily Warren et al. ·
Summary
Written by AI, not yet AICS's view · claude-sonnet-5-5This scoping review looks at how Qualitative Comparative Analysis (QCA), a method for finding the different combinations of conditions that lead to an outcome, has been used in child well-being research. The authors searched eight databases for English-language peer-reviewed studies up to 2023 and included 28 of 626 papers. Most studies focused on mental health or socio-emotional health, and most were in high income countries. The authors report that QCA can show several pathways to the same outcome and handle combinations of conditions, but it has limits on generalisability and on how many conditions can be tested. They conclude QCA is promising when used alongside traditional analyses and that researchers should follow good-practice guidelines.
Key points
- 626 papers were found and 28 met the inclusion criteria.
- Most studies (n = 23) were mainly in high income countries.
- Only two studies explicitly used well-being concepts (subjective well-being and psychological well-being).
- Commonly reported strengths of QCA were describing multiple pathways to the same outcome (equifinality) and examining combinations of conditions (causal complexity).
- Reported weaknesses were generalisability of the data and the limited number of causal conditions that can be included.
Limitations
The abstract does not name the countries covered, and the review only includes English-language peer-reviewed studies; systematic reviews and meta-analyses using QCA were excluded. It describes how QCA is used rather than testing whether any specific intervention improves child well-being.
Abstract
Abstract Background Qualitative Comparative Analysis (QCA) is a method for examining configurational causality by identifying pathways that lead to an outcome of interest. There is a growing body of literature that uses QCA to measure child well-being due to its ability to generate evidence of causality for complex social phenomena. This scoping review examines how QCA studies are being employed to investigate child well-being and assesses the potential of QCA as a method to produce intervention-focused evidence and to contribute to future methodological development to address the complexity of child well-being. Method We systematically searched Embase, PsyINFO, MEDLINE, Social Policy and Practice, Global Health, Econlit, Scopus and Web of Science for peer-reviewed studies that had used QCA methods in child well-being studies. We searched studies published in English up until 2023. Systematic reviews and meta-analyses using QCA were excluded due to insufficient methodological detail for inclusion in our analysis. We followed the PRISMA-ScR flowchart and guidelines for study screening to ensure a systematic selection process. Data extraction was undertaken to capture information of most relevance to QCA best practice. Data were analysed using a basic qualitative content analysis approach. Results The search identified 626 papers, of which 28 met our inclusion criteria. Dimensions of well-being included: psychological/mental health (n = 9); physical health (n = 2); language development under education (n = 1); socio-emotional health (n = 7); physical and psychological/mental health (n = 3), psychological/mental health and education (n = 1); and multi-dimensional health (n = 3). Two studies stated explicitly that they used well-being concepts—subjective well-being and psychological well-being. Most studies (n = 23) were predominantly in high income countries (HIC). Commonly reported strengths of QCA were the capacity to a) describe various pathways or combinations of pathways to the same outcome (equifinality); and b) examine conjunctural causation (combination of absent/present conditions), known as ‘causal complexity’. Weaknesses related to a) generalisability of the data; and b) the number of causal conditions that can be included in the analysis. Our findings suggest that QCA can be effectively used alongside traditional analyses to provide a more nuanced understanding. Conclusion QCA is a promising method with potential to address complexity when assessing the different dimensions of child well-being. More comprehensive guidelines are now available that offer good practices to enhance the quality of the QCA research. To build greater confidence using this method, scholars are recommended to adhere to these good practices to establish the highest levels of transparency of the analysis.