Using behavioral insights to design implementation strategies in public mental health settings: a qualitative study of clinical decision-making

Abstract

Background: Trauma-focused cognitive behavioral therapy (TF-CBT) is an evidence-based intervention for youth with posttraumatic stress disorder. An important component of TF-CBT is the trauma narrative (TN), a phase in the intervention in which youth are guided to process the memories, thoughts, and feelings associated with their traumatic experience(s). Previous work has shown that TF-CBT clinicians complete TNs with only half of their clients, yet little is known about what determines TF-CBT clinicians’ use of TNs. The behavioral insights literature—an interdisciplinary field studying judgment and decision-making—offers theoretical and empirical tools to conceptualize what drives complex human behaviors and decisions. Drawing from the behavioral insights literature, the present study seeks to understand what determines clinician use of TNs and to generate strategies that target these determinants. Methods: Through semi-structured qualitative interviews, we sought the perspectives of trained TF-CBT clinicians working in public mental health settings across the city of Philadelphia (N = 17) to understand their decisions to use TNs with clients. We analyzed the qualitative data using a coding approach informed by the behavioral insights literature. We used an iterative process of structured hypothesis generation, aided by a behavioral insights guide, and rapid validation informed by behavioral insights to uncover the determinants of TN use. We then generated implementation strategies that targeted these determinants using the “Easy Attractive Social Timely” framework, a behavioral insights design approach. Results: We generated and validated three broad themes about what determines clinician implementation of TNs: decision complexity, clinician affective experience, and agency norms. We hypothesized behavioral insights that underlie these implementation determinants and designed a list of nine corresponding behavioral insights strategies that may facilitate TN implementation. Conclusions: Our study investigated why an effective component of an evidence-based intervention is difficult to implement. We leveraged robust scientific theories and empirical regularities from the behavioral insights literature to understand clinician perspectives on TN implementation. These factors were theoretically linked to implementation strategies. Our work revealed the potential for using behavioral insights in the diagnosis of evidence-based intervention determinants and the design of implementation strategies.