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

Overview

Journal J Med Internet Res

Publisher JMIR Publications

Specialty Medical Informatics

Date 2020 Jan 16

PMID 31939746

Citations 18

Authors

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

Affiliations

Soon will be listed here.

Abstract

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.

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