Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series

Abstract

Background Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy. Objective This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring. Methods We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement: consistently low, drop-off, adherent, high diary, and superuser. Results We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct. Conclusions Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps.