Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Sep 20, 2019
Date Accepted: Apr 3, 2020
Optimizing Smartphone Cognitive Behavioral Therapy for Body Dysmorphic Disorder Using Passive Smartphone Data: Initial Insights from a Pilot Trial
ABSTRACT
Background:
Smartphone-delivered cognitive behavioral therapy (CBT) is becoming more common, but its research remains in its infancy. Little is known about how people typically engage with smartphone CBT, or which engagement and mobility patterns may optimize treatment. Passive smartphone data offers a unique opportunity for gaining insights into these knowledge gaps.
Objective:
This study examines passive smartphone data across a pilot course of smartphone CBT for body dysmorphic disorder (BDD), to inform hypothesis generation and the design of subsequent, larger trials.
Methods:
Ten adults with primary diagnoses of BDD were recruited nationally and completed telehealth clinician assessments with a reliable evaluator. In a 12-week open pilot trial of smartphone CBT, we initially characterized natural patterns of engagement with the treatment, and we initially tested how engagement and mobility patterns across treatment corresponded with treatment response.
Results:
Most participants interacted briefly and frequently with the smartphone treatment. More frequent app usage (r = -0.57), as opposed to greater usage duration (r = -0.084), correlated strongly with response. GPS-detected time at home, a potential digital marker of avoidance, decreased across treatment and correlated moderately with BDD severity (r = 0.49).
Conclusions:
The sample was small in this pilot study; thus, results should be used to inform hypotheses and design of subsequent trials. Results provide initial evidence that frequent (even if brief) practice of CBT skills may optimize response to smartphone CBT, and that mobility patterns may serve as useful passive markers of symptom severity. This is one of the first studies to examine the value that passively-collected sensor data may contribute to understanding and optimizing response to smartphone CBT. With further validation, results can inform how to enhance smartphone CBT design. Clinical Trial: ClinicalTrials.gov Identifier: NCT03221738
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.