Exploring Engagement With Remote Symptom Tracking for Depression (RADAR: Engage)

Major Depressive Disorder Clinical Trial

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)

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04972474
• Other study ID #: RESCM-20/21-21083
• Status: Recruiting
• Phase: N/A
• Start date: April 7, 2021
• Est. completion date: September 2021

Study information

• Verified date: May 2021
• Source: King's College London
• Contact: Katie White, BSc
• Phone: 07850 684847
• Email: katie.white[@]kcl.ac.uk
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 150
• Est. completion date: September 2021
• Est. primary completion date: August 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Depressive Disorder
• Depressive Disorder, Major
• Major Depressive Disorder

Intervention

Other:
• Smartphone app in-app components
Insightful notification text, data visualisation, research team contact details.

Locations

Country	Name	City	State
United Kingdom	Department of Psychological Medicine, King's College London	London

Sponsors (1)

Lead Sponsor	Collaborator
King's College London

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Behavioural engagement	Data completion of active symptom tracking (PHQ-8 scale). Value of 0-12.	Total completion at the 12-week end point
Secondary	Experiential engagement (1)	User Engagement Scale for mHealth Technology. 30 items, 5-point likert scale. Minimum value 0, maximum value 150. Higher value relates to increased experiential engagement.	Baseline and 12-week point
Secondary	Experiential engagement (2)	Emotional Self-Awareness Questionnaire. 33 items, 5-point likert scale. Minimum value 0, maximum value 165. Higher value relates to increased emotional awareness.	Baseline and 12-week point
Secondary	System Usability	mHealth App Usability Questionnaire. 18 items, 7-point likert scale. Minimum value 0, maximum value 126. Higher value relates to increased app usability rating.	Baseline and 12-week point
Secondary	Passive monitoring adherence	Fitbit device weartime	Continuously across a 12-week time period