The Application of Qualitative Comparative Analysis in Implementation Research: When and How to Use It

Introduction: While the development of prevention programs to address behavioral health issues in the U.S. has grown substantially in recent years, efforts to implement these best practices in community settings are not well understood. Nuanced details from multi-dimensional perspectives, e.g. aspects of an organization, characteristics of individuals involved, and intervention components, converge to produce outcomes. There is a high need to understand how these factors behave as configurations in large, multi-dimensional systems of care. The aim of this session is to present prevention researchers with an innovative methodological tool that can be used to understand the successful translation of research to practice in community settings: Qualitative Comparative Analysis (QCA). Because QCA does not rely on a variable-based approach, rather integrates case-based knowledge, this technique is valuable in assessing complex social systems. With the growing use of QCA in Dissemination and Implementation Science, it is imperative to transparently discuss application of this method and demonstrate the complexity of steps involved to successfully conduct this analysis. By illustrating and presenting findings from two completed implementation studies, this session will focus on demonstrating the use of QCA, including how to complete analyses, interpret findings, and how to approach the subjective nature of this particular methodology. Additionally, this presentation will review the mechanisms allowing for causal complexities using QCA.

Methods: QCA is based on a set-theoretic approach and uses Boolean logic to determine conditions that are necessary for the outcome to occur, and configurational combinations of conditions that are sufficient for an outcome to occur. This method entails a 10-step process including the selection and calibration of conditions, dialogue with the data throughout an iterative evaluation process, and procedures to resolve counterfactual contradictions that may appear during analysis. Causal pathways are determined using a reductionist approach.

Results: Results of two studies will be presented. A quantitative study designed to identify pathways associated with the sustainment of EBPs across diverse SAMHSA-funded programs, and a mixed-methods study identifying necessary conditions and sufficient pathways to fidelity of cognitive-based therapies across publicly-funded mental health programs in an inner-city context.

Conclusions: We demonstrate the application of QCA in Implementation Science, including the mechanisms of causality using this methodology. We also discuss the advantages of this mixed-methods approach when studying the implementation of evidence-based prevention programs across a variety of community settings.