@Article{info:doi/10.2196/33545,
author="Ramadurai, Ramya
and Beckham, Erin
and McHugh, R Kathryn
and Bj{\"o}rgvinsson, Thr{\"o}stur
and Beard, Courtney",
title="Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series",
journal="JMIR Ment Health",
year="2022",
month="Aug",
day="17",
volume="9",
number="8",
pages="e33545",
keywords="engagement; mental health apps; cognitive bias modification; human support; mobile health; mHealth; mobile phone",
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. ",
issn="2368-7959",
doi="10.2196/33545",
url="https://mental.jmir.org/2022/8/e33545",
url="https://doi.org/10.2196/33545",
url="http://www.ncbi.nlm.nih.gov/pubmed/35976196"
}