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

BMC Psychiatry

David C. Mohr¹  Inez Myin-Germeys²  Aki Rintala³  Zulqarnain Rashid⁴  Callum Stewart⁴  Richard J. B. Dobson⁴  Pauline Conde⁴  Amos A. Folarin⁴  Yatharth Ranjan⁴  Nick Cummins⁵  Femke Lamers⁶  Brenda W. J. H. Penninx⁶  Melany Horsfall⁶  Sonia Difrancesco⁶  Peter Annas⁷  Jens Christian Brasen⁷  Giovanni de Girolamo⁸  Sara K. Simblett⁹  Til Wykes⁹  Carolin Oetzmann⁹  Grace Lavelle⁹  Alina Ivan⁹  Katie M. White⁹  Daniel Leightley⁹  Faith Matcham⁹  Matthew Hotopf^1,10  Nikolay V. Manyakov^1,11  Qingqin Li^1,12  Srinivasan Vairavan^1,12  Vaibhav A. Narayan^1,12  Federica Lombardini^1,13  Sara Siddi^1,13  Josep Maria Haro^1,13  Raluca Nica^1,14  Stuart Bruce^1,14 

[1] Center for Behavioral Intervention Technologies, Department of Preventative Medicine, Northwestern University, Chicago, IL, USA;Department for Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium;Department for Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium;Faculty of Social and Health Care, LAB University of Applied Sciences, Lahti, Finland;Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK;Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK;Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany;Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands;H. Lundbeck A/S, Valby, Denmark;IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy;Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK;Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK;South London and Maudsley NHS Foundation Trust, London, UK;Janssen Pharmaceutica NV, Beerse, Belgium;Janssen Research and Development, LLC, Titusville, NJ, USA;Parc Sanitari Sant Joan de Déu, Fundació Sant Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain;RADAR-CNS Patient Advisory Board, King’s College London, London, UK;

关键词: Major depressive disorder;    Remote measurement technologies;    Longitudinal;    Multicentre;    Cohort study;   

DOI  :  10.1186/s12888-022-03753-1

来源: Springer

【 摘 要 】

BackgroundMajor 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.MethodsRemote 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.ResultsIndividuals 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.ConclusionsRADAR-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.

【 授权许可】

CC BY