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Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): Recruitment, retention, and data availability in a longitudinal remote measurement study.

Research output: Contribution to journalArticlepeer-review

Faith Matcham, Daniel Leightley, Sara Siddi, Femke Lamers, Katie White, Peter Annas, Giovanni de Girolamo, Sonia Difrancesco, Josep Maria Haro, Melany Horsfall, Alina Ivan, Grace Lavelle, Qingqin Li, Federica Lombardini, David C. Mohr, Vaibhav Narayan, Carolin Oetzmann, Brenda W. Penninx, Stuart Bruce, Raluca Nica & 15 more Sara Simblett, Til Wykes, Jens Christian Brasen, Inez Myin-Germeys, Aki Rintala, Pauline Conde, Richard Dobson, Amos Folarin, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Nicholas Cummins, Nikolay V Manyakov, Srinivasan Vairavan, Matthew Hotopf

Original languageEnglish
JournalBMC Psychiatry
Accepted/In press2 Feb 2022

King's Authors

Abstract

Background
Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data.
Methods
Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse – Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months.
Results
Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had >50% data available across all data types.
Conclusions
RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

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