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Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series
Ramya Ramadurai1, Erin Beckham2, R Kathryn McHugh3
1Department of Psychology, American University, Washington, DC, United States.
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.
