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

Primary Purpose

Major Depressive Disorder

Status
Unknown status
Phase
Not Applicable
Locations
United Kingdom
Study Type
Interventional
Intervention
Smartphone app in-app components
Sponsored by
King's College London
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional supportive care trial for Major Depressive Disorder

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

  • Department of Psychological Medicine, King's College LondonRecruiting

Arms of the Study

Arm 1

Arm 2

Arm Type

No Intervention

Experimental

Arm Label

RADAR-MDD Questionnaire App as Usual

RADAR-MDD Adapted Questionnaire App

Arm Description

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.

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'.

Outcomes

Primary Outcome Measures

Behavioural engagement
Data completion of active symptom tracking (PHQ-8 scale). Value of 0-12.

Secondary Outcome Measures

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.
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.
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.
Passive monitoring adherence
Fitbit device weartime

Full Information

First Posted
May 14, 2021
Last Updated
August 25, 2021
Sponsor
King's College London
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1. Study Identification

Unique Protocol Identification Number
NCT04972474
Brief Title
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

2. Study Status

Record Verification Date
May 2021
Overall Recruitment Status
Unknown status
Study Start Date
April 7, 2021 (Actual)
Primary Completion Date
August 2021 (Anticipated)
Study Completion Date
September 2021 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
King's College London

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Major Depressive Disorder

7. Study Design

Primary Purpose
Supportive Care
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
Participants will be randomised to one of two arms, the app as usual or the adapted app.
Masking
Participant
Masking Description
Participants are unaware of the changes that have been made to the app, and therefore are unaware of which arm they are randomised to.
Allocation
Randomized
Enrollment
150 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
RADAR-MDD Questionnaire App as Usual
Arm Type
No Intervention
Arm Description
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.
Arm Title
RADAR-MDD Adapted Questionnaire App
Arm Type
Experimental
Arm Description
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'.
Intervention Type
Other
Intervention Name(s)
Smartphone app in-app components
Intervention Description
Insightful notification text, data visualisation, research team contact details.
Primary Outcome Measure Information:
Title
Behavioural engagement
Description
Data completion of active symptom tracking (PHQ-8 scale). Value of 0-12.
Time Frame
Total completion at the 12-week end point
Secondary Outcome Measure Information:
Title
Experiential engagement (1)
Description
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.
Time Frame
Baseline and 12-week point
Title
Experiential engagement (2)
Description
Emotional Self-Awareness Questionnaire. 33 items, 5-point likert scale. Minimum value 0, maximum value 165. Higher value relates to increased emotional awareness.
Time Frame
Baseline and 12-week point
Title
System Usability
Description
mHealth App Usability Questionnaire. 18 items, 7-point likert scale. Minimum value 0, maximum value 126. Higher value relates to increased app usability rating.
Time Frame
Baseline and 12-week point
Title
Passive monitoring adherence
Description
Fitbit device weartime
Time Frame
Continuously across a 12-week time period

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
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
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Katie White, BSc
Phone
07850 684847
Email
katie.white@kcl.ac.uk
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Katie White, BSc
Organizational Affiliation
King's College London
Official's Role
Principal Investigator
Facility Information:
Facility Name
Department of Psychological Medicine, King's College London
City
London
ZIP/Postal Code
SE5 8AF
Country
United Kingdom
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Katie White, BSc
Phone
07850 684847
Email
katie.white@kcl.ac.uk

12. IPD Sharing Statement

Plan to Share IPD
No
Citations:
PubMed Identifier
34932005
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.
Results Reference
derived

Learn more about this trial

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

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