The True Colours Remote Symptom Monitoring System: A Decade of Evolution.

digital health ecological momentary assessment mood disorders signs and symptoms symptom assessment

Journal

Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882

Informations de publication

Date de publication:
15 01 2020
Historique:
received: 15 07 2019
accepted: 22 10 2019
revised: 25 09 2019
entrez: 16 1 2020
pubmed: 16 1 2020
medline: 6 8 2020
Statut: epublish

Résumé

The True Colours remote mood monitoring system was developed over a decade ago by researchers, psychiatrists, and software engineers at the University of Oxford to allow patients to report on a range of symptoms via text messages, Web interfaces, or mobile phone apps. The system has evolved to encompass a wide range of measures, including psychiatric symptoms, quality of life, and medication. Patients are prompted to provide data according to an agreed personal schedule: weekly, daily, or at specific times during the day. The system has been applied across a number of different populations, for the reporting of mood, anxiety, substance use, eating and personality disorders, psychosis, self-harm, and inflammatory bowel disease, and it has shown good compliance. Over the past decade, there have been over 36,000 registered True Colours patients and participants in the United Kingdom, with more than 20 deployments of the system supporting clinical service and research delivery. The system has been adopted for routine clinical care in mental health services, supporting more than 3000 adult patients in secondary care, and 27,263 adolescent patients are currently registered within Oxfordshire and Buckinghamshire. The system has also proven to be an invaluable scientific resource as a platform for research into mood instability and as an electronic outcome measure in randomized controlled trials. This paper aimed to report on the existing applications of the system, setting out lessons learned, and to discuss the implications for tailored symptom monitoring, as well as the barriers to implementation at a larger scale.

Identifiants

pubmed: 31939746
pii: v22i1e15188
doi: 10.2196/15188
pmc: PMC6996723
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e15188

Subventions

Organisme : Medical Research Council
ID : MR/L023784/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_17215
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/M024962/1
Pays : United Kingdom
Organisme : Parkinson's UK
ID : J-0901
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_EX_MR/N50192X/1
Pays : United Kingdom

Informations de copyright

©Sarah M Goodday, Lauren Atkinson, Guy Goodwin, Kate Saunders, Matthew South, Clare Mackay, Mike Denis, Chris Hinds, Mary-Jane Attenburrow, Jim Davies, James Welch, William Stevens, Karen Mansfield, Juulia Suvilehto, John Geddes. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.01.2020.

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Auteurs

Sarah M Goodday (SM)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
4YouandMe, Seattle, WA, United States.

Lauren Atkinson (L)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Oxford Center for Human Brain Activity, University of Oxford, Oxford, United Kingdom.

Guy Goodwin (G)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

Kate Saunders (K)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

Matthew South (M)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

Clare Mackay (C)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

Mike Denis (M)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

Chris Hinds (C)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Big Data Institute, University of Oxford, Oxford, United Kingdom.

Mary-Jane Attenburrow (MJ)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

Jim Davies (J)

Big Data Institute, University of Oxford, Oxford, United Kingdom.
Department of Computer Science, University of Oxford, Oxford, United Kingdom.

James Welch (J)

Big Data Institute, University of Oxford, Oxford, United Kingdom.
NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.

William Stevens (W)

Department of Computer Science, University of Oxford, Oxford, United Kingdom.

Karen Mansfield (K)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

Juulia Suvilehto (J)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

John Geddes (J)

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

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