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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Aug 5, 2021
Open Peer Review Period: Aug 5, 2021 - Sep 30, 2021
Date Accepted: Oct 14, 2021
(closed for review but you can still tweet)

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

Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial

White KM, Matcham F, Leightley D, Carr E, Conde P, Dawe-Lane E, Ranjan Y, Simblett S, Henderson C, Hotopf M

Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial

JMIR Res Protoc 2021;10(12):e32653

DOI: 10.2196/32653

PMID: 34932005

PMCID: 8734922

RADAR-Engage: Protocol for a two-armed randomized controlled trial exploring the effects of in-app components on engagement with a symptom tracking platform among participants with major depressive disorder

  • Katie M White; 
  • Faith Matcham; 
  • Daniel Leightley; 
  • Ewan Carr; 
  • Pauline Conde; 
  • Erin Dawe-Lane; 
  • Yatharth Ranjan; 
  • Sara Simblett; 
  • Claire Henderson; 
  • Matthew Hotopf

ABSTRACT

Background:

Multi-parametric remote measurement technologies (RMTs) comprise smartphone applications and wearable devices for both active and passive symptom tracking. They hold great potential for understanding current, and predicting future, depression status. However, the promise of using RMTs for relapse prediction is heavily dependent on user engagement, defined as both a behavioural and experiential construct. A better understanding of how to promote engagement in RMT research through various in-app components will aid in providing scalable solutions for future remote research, higher quality results and applications for implementation into clinical practice.

Objective:

To provide the rationale and protocol for a two-armed, randomized controlled trial to investigate the effect of insightful notifications, progress visualization and researcher contact details on behavioural and experiential engagement with a multi-parametric mHealth data collection platform- RADAR-Base.

Methods:

The study aims to recruit a total of 145 participants upon completion of their participation in the Remote Assessment of Disease and Relapse- Major Depressive Disorder (RADAR-MDD) study London site. Data will be collected via three weekly tasks through an active smartphone app, a passive (background) data collection app, and a Fitbit device. Participants will be randomly allocated at a 1:1 ratio to receive either (A) an adapted version of the active app that incorporates insightful notifications, progress visualization and access to researcher contact details; or (B) the active app as usual. Statistical tests will test the hypotheses that participants using the adapted app will complete a higher number of weekly tasks (behavioural engagement; primary outcome) and score higher on self-awareness measures (experiental engagement).

Results:

This study will be reported following the CONSORT (Consolidated Standards of Reporting Trials) checklist. The results of this study will be communicated via publication.

Conclusions:

This study aims to understand how best to promote engagement with RMTs in depression research. Findings will help determine the most effective techniques for implementation into both future rounds of the RADAR-MDD study and, in the longer-term, clinical practice. Clinical Trial: NCT04972474


 Citation

Please cite as:

White KM, Matcham F, Leightley D, Carr E, Conde P, Dawe-Lane E, Ranjan Y, Simblett S, Henderson C, Hotopf M

Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial

JMIR Res Protoc 2021;10(12):e32653

DOI: 10.2196/32653

PMID: 34932005

PMCID: 8734922

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