Accepted for/Published in: JMIR Mental Health
Date Submitted: Apr 22, 2022
Open Peer Review Period: Apr 22, 2022 - Jun 17, 2022
Date Accepted: Jun 13, 2022
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited.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.
Clinical Targets and Attitudes towards Implementing Digital Health Tools for Remote Measurement in Treatment for Depression: A Qualitative Study
ABSTRACT
Background:
Remote measurement technologies (RMTs) such as smartphones and wearable devices could improve treatment outcomes for depression through enhanced illness characterisation and monitoring. However, little is known about which digital outcomes are clinically meaningful to patients and clinicians. Moreover, if these technologies are to be successfully implemented within treatment, stakeholders’ views on barriers to, and facilitators of, their implementation in treatment need to be considered.
Objective:
This study aimed to (1) identify clinically meaningful targets for digital health research in depression, and (2) explore attitudes towards their implementation in psychological services.
Methods:
A grounded theory approach was employed on qualitative data from three focus groups on patients with a current diagnosis of depression and clinicians with over 6 months' experience delivering psychotherapy (n = 22).
Results:
Emerging themes on clinical targets fell into two main categories: ‘promoters’ and ‘markers’ of change. The former are behaviours participants engage in to promote mental health; the latter are behaviors that signal a change in mood. These themes were further subdivided into external (changes in behaviours), or internal (changes in thoughts or feelings) and mapped with potential digital sensors. Six implementation acceptability themes emerged: (1) technology-related factors, (2) information and data management, (3) emotional support, (4) cognitive support, (5) increased self-awareness, and (6) clinical utility.
Conclusions:
The ‘promoters’ vs ‘markers’ of change differentiation has implications for a causal model of digital phenotyping in depression, which this paper presents. Internal vs external subdivisions are helpful in determining which factors are more susceptible to being measured with active vs passive methods. The implications for implementation within psychotherapy are discussed with regards to treatment effectiveness, service provision, and patient and clinician experience.
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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.