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

August 25, 2021 updated by: King's College London

A Two-Armed Trial Exploring the Effects of In-App Components on User Engagement With a Symptom-Tracking System for Depression (RADAR: Engage)

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.

Study Overview

Status

Recruiting

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.

Study Type

Interventional

Enrollment (Anticipated)

150

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

      • London, United Kingdom, SE5 8AF
        • Recruiting
        • Department of Psychological Medicine, King's College London
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Supportive Care
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: RADAR-MDD Questionnaire App as Usual
The RADAR-MDD questionnaire app as usual asks participants to complete 3x active tasks per week, with one reminder notification at 9am on a day that a questionnaire is due. The notification reads 'Questionnaire Time. Won't usually take longer than 3 minutes'. The participant is not able to view any data progress, aside from through the Fitbit app, which was present in the original RADAR-MDD study.
Experimental: RADAR-MDD Adapted Questionnaire App

The following components are also present:

Notifications: The notification will alternate between the phrases 'Questionnaire Time. Symptom tracking might increase self-awareness of your emotions (Bakker & Rickard, 2018)', 'Questionnaire Time. Symptom tracking is a technique often used in treatment to increase insight into your symptoms (Kramer et al., 2014)', and 'Questionnaire Time. Tracking your symptoms through a smartphone and Fitbit might help research to better understand health conditions'.

Progress visualisation: Participants will be able to view their questionnaire completion progress as a visualisation through the app, in the form of a graph.

Additional components: An additional text on the home screen of the active app will read 'You can contact your research team between 9am-5pm Mon-Fri if you have questions, onradar-engage@kcl.ac.uk'.

Insightful notification text, data visualisation, research team contact details.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Behavioural engagement
Time Frame: Total completion at the 12-week end point
Data completion of active symptom tracking (PHQ-8 scale). Value of 0-12.
Total completion at the 12-week end point

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Experiential engagement (1)
Time Frame: Baseline and 12-week point
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
Experiential engagement (2)
Time Frame: Baseline and 12-week point
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
System Usability
Time Frame: Baseline and 12-week point
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
Passive monitoring adherence
Time Frame: Continuously across a 12-week time period
Fitbit device weartime
Continuously across a 12-week time period

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Katie White, BSc, King's College London

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 7, 2021

Primary Completion (Anticipated)

August 1, 2021

Study Completion (Anticipated)

September 1, 2021

Study Registration Dates

First Submitted

May 14, 2021

First Submitted That Met QC Criteria

July 19, 2021

First Posted (Actual)

July 22, 2021

Study Record Updates

Last Update Posted (Actual)

August 26, 2021

Last Update Submitted That Met QC Criteria

August 25, 2021

Last Verified

May 1, 2021

More Information

Terms related to this study

Other Study ID Numbers

  • RESCM-20/21-21083

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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