Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder

F Matcham; E Carr; K M White; D Leightley; F Lamers; S Siddi; P Annas; G de Girolamo; J M Haro; M Horsfall; A Ivan; G Lavelle; Q Li; F Lombardini; D C Mohr; V A Narayan; B W H J Penninx; C Oetzmann; M Coromina; S K Simblett; J Weyer; T Wykes; S Zorbas; J C Brasen; I Myin-Germeys; P Conde; R J B Dobson; A A Folarin; Y Ranjan; Z Rashid; N Cummins; J Dineley; S Vairavan; M Hotopf; RADAR-CNS consortium

doi:10.1016/j.jad.2022.05.005

Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder

J Affect Disord. 2022 Aug 1:310:106-115. doi: 10.1016/j.jad.2022.05.005. Epub 2022 May 5.

Authors

F Matcham¹, E Carr², K M White³, D Leightley³, F Lamers⁴, S Siddi⁵, P Annas⁶, G de Girolamo⁷, J M Haro⁵, M Horsfall⁴, A Ivan³, G Lavelle³, Q Li⁸, F Lombardini⁵, D C Mohr⁹, V A Narayan⁸, B W H J Penninx⁴, C Oetzmann³, M Coromina¹⁰, S K Simblett¹¹, J Weyer¹², T Wykes¹³, S Zorbas¹², J C Brasen⁶, I Myin-Germeys¹⁴, P Conde², R J B Dobson², A A Folarin², Y Ranjan², Z Rashid², N Cummins², J Dineley¹⁵, S Vairavan⁸, M Hotopf¹⁶; RADAR-CNS consortium¹⁷

Affiliations

¹ Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK. Electronic address: faith.matcham@kcl.ac.uk.
² Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
³ Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
⁴ Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands.
⁵ Parc Sanitari Sant Joan de Déu, Fundació San Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.
⁶ H. Lundbeck A/S, Valby, Denmark.
⁷ IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
⁸ Janssen Research and Development, LLC, Titusville, NJ, USA.
⁹ Center for Behavioral Intervention Technologies, Department of Preventative Medicine, Northwestern University, Chicago, IL, USA.
¹⁰ Parc Sanitari Joan de Déu, Barcelona, Spain.
¹¹ Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
¹² RADAR-CNS Patient Advisory Board.
¹³ Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, London, UK.
¹⁴ Department for Neurosciences, Center for Contextual Psychiatry, KU Leuven, Leuven, Belgium.
¹⁵ Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; EIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Augsburg, Germany.
¹⁶ Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, London, UK.
¹⁷ www.radar-cns.org, UK.

PMID: 35525507
DOI: 10.1016/j.jad.2022.05.005

Abstract

Background: Remote sensing for the measurement and management of long-term conditions such as Major Depressive Disorder (MDD) is becoming more prevalent. User-engagement is essential to yield any benefits. We tested three hypotheses examining associations between clinical characteristics, perceptions of remote sensing, and objective user engagement metrics.

Methods: The Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) study is a multicentre longitudinal observational cohort study in people with recurrent MDD. Participants wore a FitBit and completed app-based assessments every two weeks for a median of 18 months. Multivariable random effects regression models pooling data across timepoints were used to examine associations between variables.

Results: A total of 547 participants (87.8% of the total sample) were included in the current analysis. Higher levels of anxiety were associated with lower levels of perceived technology ease of use; increased functional disability was associated with small differences in perceptions of technology usefulness and usability. Participants who reported higher system ease of use, usefulness, and acceptability subsequently completed more app-based questionnaires and tended to wear their FitBit activity tracker for longer. All effect sizes were small and unlikely to be of practical significance.

Limitations: Symptoms of depression, anxiety, functional disability, and perceptions of system usability are measured at the same time. These therefore represent cross-sectional associations rather than predictions of future perceptions.

Conclusions: These findings suggest that perceived usability and actual use of remote measurement technologies in people with MDD are robust across differences in severity of depression, anxiety, and functional impairment.

Keywords: Cohort study; Engagement; Major Depressive Disorder; Predictors; Remote sensing.

Publication types

Observational Study
Research Support, Non-U.S. Gov't

MeSH terms

Anxiety Disorders
Cross-Sectional Studies
Depressive Disorder, Major* / diagnosis
Humans
Recurrence
Remote Sensing Technology