Abstract

BackgroundMulti-parametric remote measurement technologies (RMTs) comprise smartphone apps and wearable devices for both active and passive symptom tracking. They hold potential for understanding current depression status and predicting future depression status. However, the promise of using RMTs for relapse prediction is heavily dependent on user engagement, which is defined as both a behavioral 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 in clinical practice.ObjectiveThe aim of this study is to provide the rationale and protocol for a 2-armed randomized controlled trial to investigate the effect of insightful notifications, progress visualization, and researcher contact details on behavioral and experiential engagement with a multi-parametric mobile health data collection platform, Remote Assessment of Disease and Relapse (RADAR)–base.MethodsWe aim to recruit 140 participants upon completion of their participation in the RADAR Major Depressive Disorder study in the London site. Data will be collected using 3 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 an adapted version of the active app that incorporates insightful notifications, progress visualization, and access to researcher contact details or the active app as usual. Statistical tests will be used to assess the hypotheses that participants using the adapted app will complete a higher percentage of weekly tasks (behavioral engagement: primary outcome) and score higher on self-awareness measures (experiential engagement).ResultsRecruitment commenced in April 2021. Data collection was completed in September 2021. The results of this study will be communicated via publication in 2022.ConclusionsThis study aims to understand how best to promote engagement with RMTs in depression research. The findings will help determine the most effective techniques for implementation in both future rounds of the RADAR Major Depressive Disorder study and, in the long term, clinical practice.Trial RegistrationClinicalTrials.gov NCT04972474; http://clinicaltrials.gov/ct2/show/NCT04972474International Registered Report Identifier (IRRID)DERR1-10.2196/32653

Highlights

  • BackgroundThe last decade has seen a significant increase in the use of mobile technology in health care research and clinical practice [1]

  • One such application of mHealth is the use of remote measurement technologies (RMTs), which provide real-time, longitudinal health tracking using a combination of smartphone apps for active symptom reporting tasks and mobile or wearable sensors for passive data collection [2]

  • This study aims to test the effect of in-app components in a multi-parametric RMT platform on engagement with active and passive symptom tracking in Major depressive disorder (MDD)

Read more

Summary

Objective

The aim of this study is to provide the rationale and protocol for a 2-armed randomized controlled trial to investigate the effect of insightful notifications, progress visualization, and researcher contact details on behavioral and experiential engagement with a multi-parametric mobile health data collection platform, Remote Assessment of Disease and Relapse (RADAR)–base

Methods
Conclusions
Background
Study Design
Principal Findings
Strengths and Limitations
Conflicts of Interest
12. RADAR-CNS
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call