Clinical trial NCT04972474: Exploring Engagement With Remote Symptom Tracking for Depression (RADAR: Engage)
Official title: A Two-Armed Trial Exploring the Effects of In-App Components on User Engagement With a Symptom-Tracking System for Depression (RADAR: Engage)
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Major Depressive Disorder
Lead sponsor: King's College London
Sponsor class: OTHER
First posted: 2021-07-22
Enrollment: 150
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Participants will be randomised to one of two arms, the app as usual or the adapted app.
Primary purpose: SUPPORTIVE_CARE

Brief summary: The aim of this study is to understand how best to promote engagement with remote measurement technology (RMT) research in major depressive disorder, using the RADAR-MDD infrastructure as a case study. An adapted questionnaire app with insightful notifications and progress visualization will be compared against the app as usual, in terms of behavioural and experiential engagement.

Detailed description: Remote measurement technologies (RMTs) provide an opportunity for real-time, longitudinal health tracking through a combination of smartphone apps for symptom reporting (active RMT; aRMT) and mobile/wearable sensors for passive data collection (passive RMT; pRMT). The use of RMTs to track relapse and remission of symptoms in major depressive disorder (MDD) is thought to be more reflective of patient daily experience, in comparison to retrospective recall during clinic visits. The Remote Assessment of Disease and Relapse- Major Depressive Disorder (RADAR-MDD) study uses RMTs to identify predictors of MDD relapse. It collects multiparametric RMT data through the RADAR-base system over a two year follow-up period; aRMT data is collected via mood-tracking questionnaires in the active app, and pRMT data is collected via a fitness watch, the Fitbit Charge device. The promise of RADAR-MDD depends heavily on user engagement with the app. Currently, engagement with aRMT symptom tracking in the field is hugely heterogeneous and preliminary estimates of the RADAR-MDD study suggest around 50% completion of fortnightly questionnaires. There are several, in-app methods available to promote engagement with mHealth tools. Notifications with theoretically informed content can provide a trigger to perform a behaviour, and data visualisation of progress can prompt continued data input. It is unclear which combination of in-app features can promote engagement with the RADAR-base system, while minimising participant burden.

This study therefore aims to understand how best to promote engagement with RMT research, using the RADAR-MDD project as a case study. This protocol will outline a mixed-methods approach to exploring the impact of additional, in-app components on engagement with symptom tracking via the RADAR-Base infrastructure. First, a two-armed randomized controlled trial will compare the RADAR-MDD questionnaire app as usual with an adapted app with insightful notifications and progress visualization, aimed at promoting behavioural and experiential engagement. Engagement will be measured as a) provision of symptom tracking scores over the 12-week study period, and b) the degree to which participants feel experientially engaged with symptom tracking via the system. Second, qualitative interviews will reveal participant experiences of the techniques used.

The study has three main objectives:

To examine the impact of an adapted smartphone app on behavioural engagement with RMT symptom tracking, in comparison with the RADAR-MDD app as usual;

To examine the impact of an adapted smartphone app on experiential engagement with RMT symptom tracking, in comparison with the RADAR-MDD app as usual;

Qualitatively explore the views of participants on the use of an adapted smartphone app to increase engagement with the RADAR-Base system.

Findings in this field would go some way to providing scalable solutions for engagement in RMT studies, higher quality results and applications for implementation into clinical practice.

Eligibility criteria: Inclusion Criteria:

* Participation in the RADAR-MDD London site study
* Consent for future research contact given during participation in the RADAR-MDD study
* Willing and able to continue using an Android smartphone
* Willing and able to continue using a Fitbit device
* Capacity to give informed consent

Exclusion Criteria:

* Development of a comorbid psychiatric disorder since participation in the RADAR-MDD study

Primary outcomes:
measure: Behavioural engagement
timeFrame: Total completion at the 12-week end point
Secondary outcomes:
measure: Experiential engagement (1)
timeFrame: Baseline and 12-week point
measure: Experiential engagement (2)
timeFrame: Baseline and 12-week point
measure: System Usability
timeFrame: Baseline and 12-week point
measure: Passive monitoring adherence
timeFrame: Continuously across a 12-week time period
Other outcomes:
Locations:
city: London
country: United Kingdom
facility: Department of Psychological Medicine, King's College London
Study officials:
affiliation: King's College London
name: Katie White, BSc
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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 Dec 21;10(12):e32653. doi: 10.2196/32653.