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Accepted for/Published in: JMIR Mental Health

Date Submitted: Sep 12, 2021
Date Accepted: Jun 20, 2022

The final, peer-reviewed published version of this preprint can be found here:

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

Ramadurai R, Beckham E, McHugh RK, Björgvinsson T, Beard C

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

JMIR Ment Health 2022;9(8):e33545

DOI: 10.2196/33545

PMID: 35976196

PMCID: 9434389

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Optimizing and operationalizing engagement with a CBM-I smartphone app: A case series

  • Ramya Ramadurai; 
  • Erin Beckham; 
  • R. Kathryn McHugh; 
  • Throstur Björgvinsson; 
  • Courtney Beard

ABSTRACT

Background:

Engagement with mental health smartphone apps is an understudied, yet critical, construct to understand in the pursuit of more efficacious mental health apps.

Objective:

In this manuscript we examine engagement as a multidimensional construct, as well as strategies to enhance engagement for a novel app HabitWorks. HabitWorks delivers a personalized cognitive bias modification for interpretation bias intervention and was originally tested in people traversing the challenging transition from acute psychiatric care to daily life.

Methods:

Using a case series we evaluate three domains of engagement- behavioral, cognitive, and affective- for three HabitWorks participants.

Results:

This manuscript highlights various strategies to enhance engagement such as human support, personalization, self-monitoring, and privacy and security measures. Our cases illustrate the heterogeneity of engagement patterns and clinical outcomes.

Conclusions:

With rich participant-level data we emphasize the necessity of studying engagement as a multifaceted construct, and the complexity of the relationship between overall engagement and psychosocial outcomes. Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to optimize and operationalize engagement for other mHealth apps.


 Citation

Please cite as:

Ramadurai R, Beckham E, McHugh RK, Björgvinsson T, Beard C

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

JMIR Ment Health 2022;9(8):e33545

DOI: 10.2196/33545

PMID: 35976196

PMCID: 9434389

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© 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.