ABSTRACT
Interpretation bias is a transdiagnostic mechanism underlying anxiety. Theoretical models highlight the role of parental interpretation bias in predicting and maintaining child anxiety. However, very few studies have examined parent interpretation bias as a treatment target. The current pilot study tested the feasibility and acceptability of an interpretation bias intervention delivered by a smartphone app, called HabitWorks, in parents of anxious children who self-reported at least mild symptoms of anxiety and negative interpretation bias. Parents of anxious youth (ages 8 to 16) were recruited from the waitlists of three child anxiety clinics. They were asked to complete interpretation modification exercises via the HabitWorks app 3 times per week for 1 month. Participants completed assessments at pre- and post-intervention and 1-month follow-up to assess changes in interpretation bias, anxiety symptoms, and overall perceptions of HabitWorks. Participants (N=14) (Mage=44.36; 14.29% men, 85.71% women) completed an average of 13.29 exercises out of the 12 prescribed. Acceptability ratings were high. Interpretation bias, as measured by an assessment version of the intervention exercise, significantly improved from pre- to posttreatment, and these improvements were maintained at the 1-month follow-up. Anxiety symptoms significantly improved from the "mild" severity range to the "none to minimal" range. In this pilot feasibility study in parents of anxious youth, HabitWorks was a feasible and acceptable low-intensity intervention. These preliminary results support a future controlled trial of HabitWorks for parents. Future studies are also needed to test whether targeting interpretation bias in parents has downstream effects on maladaptive parent behaviors and ultimately, child interpretation bias and anxiety.
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.
