Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol

BACKGROUND: There is a growing body of literature highlighting the role that wearable and mobile remote measurement technology (RMT) can play in measuring symptoms of major depressive disorder (MDD). Outcomes assessment typically relies on self-report, which can be biased by dysfunctional perception...

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Autores: Matcham, Faith, Barattieri di San Pietro, C., Bulgari, V., de Girolamo, G., Dobson, Richard J. B., Eriksson, Hans, Folarin, Amos A., Haro Abad, Josep Maria, Kerz, J., Lamers, Femke, Li, Q., Manyakov, N. V., Mohr, David C., Myin Germeys, Inez, Narayan, Vaibhav A., Bwjh, Penninx, Ranjan, Yatharth, Rashid, Zulqarnain, Rintala, Aki, Siddi, Sara, Simblett, Sara, Wykes, Til, Hotopf, Matthew, RADAR-CNS consortium
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/177073
Acceso en línea:https://hdl.handle.net/2445/177073
Access Level:acceso abierto
Palabra clave:Tecnologia mèdica
Depressió psíquica
Medical technology
Mental depression
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spelling Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocolMatcham, FaithBarattieri di San Pietro, C.Bulgari, V.de Girolamo, G.Dobson, Richard J. B.Eriksson, HansFolarin, Amos A.Haro Abad, Josep MariaKerz, J.Lamers, FemkeLi, Q.Manyakov, N. V.Mohr, David C.Myin Germeys, InezNarayan, Vaibhav A.Bwjh, PenninxRanjan, YatharthRashid, ZulqarnainRintala, AkiSiddi, SaraSimblett, SaraWykes, TilHotopf, MatthewRADAR-CNS consortiumTecnologia mèdicaDepressió psíquicaMedical technologyMental depressionBACKGROUND: There is a growing body of literature highlighting the role that wearable and mobile remote measurement technology (RMT) can play in measuring symptoms of major depressive disorder (MDD). Outcomes assessment typically relies on self-report, which can be biased by dysfunctional perceptions and current symptom severity. Predictors of depressive relapse include disrupted sleep, reduced sociability, physical activity, changes in mood, prosody and cognitive function, which are all amenable to measurement via RMT. This study aims to: 1) determine the usability, feasibility and acceptability of RMT; 2) improve and refine clinical outcome measurement using RMT to identify current clinical state; 3) determine whether RMT can provide information predictive of depressive relapse and other critical outcomes. METHODS: RADAR-MDD is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona. Participants will be asked to wear a wrist-worn activity tracker and download several apps onto their smartphones. These apps will be used to either collect data passively from existing smartphone sensors, or to deliver questionnaires, cognitive tasks, and speech assessments. The wearable device, smartphone sensors and questionnaires will collect data for up to 2-years about participants' sleep, physical activity, stress, mood, sociability, speech patterns, and cognitive function. The primary outcome of interest is MDD relapse, defined via the Inventory of Depressive Symptomatology- Self-Report questionnaire (IDS-SR) and the World Health Organisation's self-reported Composite International Diagnostic Interview (CIDI-SF). DISCUSSION: This study aims to provide insight into the early predictors of major depressive relapse, measured unobtrusively via RMT. If found to be acceptable to patients and other key stakeholders and able to provide clinically useful information predictive of future deterioration, RMT has potential to change the way in which depression and other long-term conditions are measured and managed. KEYWORDS: M-health; Major depressive disorder; Observational cohort; Outcome measurement; Passive sensing; Prospective study; Remote measurement technologyBioMed Central2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/177073Articles publicats en revistes (Medicina)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1186/s12888-019-2049-zBMC Psychiatry, 2019, vol. 19, num. 1, p. 72https://doi.org/10.1186/s12888-019-2049-zinfo:eu-repo/grantAgreement/EC/H2020/115902cc-by (c) Matcham, F. et al., 2019http://creativecommons.org/licenses/by/3.0/esinfo:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1770732026-05-27T06:46:51Z
dc.title.none.fl_str_mv Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
title Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
spellingShingle Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
Matcham, Faith
Tecnologia mèdica
Depressió psíquica
Medical technology
Mental depression
title_short Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
title_full Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
title_fullStr Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
title_full_unstemmed Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
title_sort Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol
dc.creator.none.fl_str_mv Matcham, Faith
Barattieri di San Pietro, C.
Bulgari, V.
de Girolamo, G.
Dobson, Richard J. B.
Eriksson, Hans
Folarin, Amos A.
Haro Abad, Josep Maria
Kerz, J.
Lamers, Femke
Li, Q.
Manyakov, N. V.
Mohr, David C.
Myin Germeys, Inez
Narayan, Vaibhav A.
Bwjh, Penninx
Ranjan, Yatharth
Rashid, Zulqarnain
Rintala, Aki
Siddi, Sara
Simblett, Sara
Wykes, Til
Hotopf, Matthew
RADAR-CNS consortium
author Matcham, Faith
author_facet Matcham, Faith
Barattieri di San Pietro, C.
Bulgari, V.
de Girolamo, G.
Dobson, Richard J. B.
Eriksson, Hans
Folarin, Amos A.
Haro Abad, Josep Maria
Kerz, J.
Lamers, Femke
Li, Q.
Manyakov, N. V.
Mohr, David C.
Myin Germeys, Inez
Narayan, Vaibhav A.
Bwjh, Penninx
Ranjan, Yatharth
Rashid, Zulqarnain
Rintala, Aki
Siddi, Sara
Simblett, Sara
Wykes, Til
Hotopf, Matthew
RADAR-CNS consortium
author_role author
author2 Barattieri di San Pietro, C.
Bulgari, V.
de Girolamo, G.
Dobson, Richard J. B.
Eriksson, Hans
Folarin, Amos A.
Haro Abad, Josep Maria
Kerz, J.
Lamers, Femke
Li, Q.
Manyakov, N. V.
Mohr, David C.
Myin Germeys, Inez
Narayan, Vaibhav A.
Bwjh, Penninx
Ranjan, Yatharth
Rashid, Zulqarnain
Rintala, Aki
Siddi, Sara
Simblett, Sara
Wykes, Til
Hotopf, Matthew
RADAR-CNS consortium
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Tecnologia mèdica
Depressió psíquica
Medical technology
Mental depression
topic Tecnologia mèdica
Depressió psíquica
Medical technology
Mental depression
description BACKGROUND: There is a growing body of literature highlighting the role that wearable and mobile remote measurement technology (RMT) can play in measuring symptoms of major depressive disorder (MDD). Outcomes assessment typically relies on self-report, which can be biased by dysfunctional perceptions and current symptom severity. Predictors of depressive relapse include disrupted sleep, reduced sociability, physical activity, changes in mood, prosody and cognitive function, which are all amenable to measurement via RMT. This study aims to: 1) determine the usability, feasibility and acceptability of RMT; 2) improve and refine clinical outcome measurement using RMT to identify current clinical state; 3) determine whether RMT can provide information predictive of depressive relapse and other critical outcomes. METHODS: RADAR-MDD is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona. Participants will be asked to wear a wrist-worn activity tracker and download several apps onto their smartphones. These apps will be used to either collect data passively from existing smartphone sensors, or to deliver questionnaires, cognitive tasks, and speech assessments. The wearable device, smartphone sensors and questionnaires will collect data for up to 2-years about participants' sleep, physical activity, stress, mood, sociability, speech patterns, and cognitive function. The primary outcome of interest is MDD relapse, defined via the Inventory of Depressive Symptomatology- Self-Report questionnaire (IDS-SR) and the World Health Organisation's self-reported Composite International Diagnostic Interview (CIDI-SF). DISCUSSION: This study aims to provide insight into the early predictors of major depressive relapse, measured unobtrusively via RMT. If found to be acceptable to patients and other key stakeholders and able to provide clinically useful information predictive of future deterioration, RMT has potential to change the way in which depression and other long-term conditions are measured and managed. KEYWORDS: M-health; Major depressive disorder; Observational cohort; Outcome measurement; Passive sensing; Prospective study; Remote measurement technology
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/177073
url https://hdl.handle.net/2445/177073
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1186/s12888-019-2049-z
BMC Psychiatry, 2019, vol. 19, num. 1, p. 72
https://doi.org/10.1186/s12888-019-2049-z
info:eu-repo/grantAgreement/EC/H2020/115902
dc.rights.none.fl_str_mv cc-by (c) Matcham, F. et al., 2019
http://creativecommons.org/licenses/by/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Matcham, F. et al., 2019
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv Articles publicats en revistes (Medicina)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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