Digital biomarkers from geolocation data in bipolar disorder and schizophrenia: a systematic review.


Journal

Journal of the American Medical Informatics Association : JAMIA
ISSN: 1527-974X
Titre abrégé: J Am Med Inform Assoc
Pays: England
ID NLM: 9430800

Informations de publication

Date de publication:
01 11 2019
Historique:
received: 20 12 2018
revised: 11 03 2019
accepted: 27 03 2019
pubmed: 2 7 2019
medline: 30 1 2021
entrez: 2 7 2019
Statut: ppublish

Résumé

The study sought to explore to what extent geolocation data has been used to study serious mental illness (SMI). SMIs such as bipolar disorder and schizophrenia are characterized by fluctuating symptoms and sudden relapse. Currently, monitoring of people with an SMI is largely done through face-to-face visits. Smartphone-based geolocation sensors create opportunities for continuous monitoring and early intervention. We searched MEDLINE, PsycINFO, and Scopus by combining terms related to geolocation and smartphones with SMI concepts. Study selection and data extraction were done in duplicate. Eighteen publications describing 16 studies were included in our review. Eleven studies focused on bipolar disorder. Common geolocation-derived digital biomarkers were number of locations visited (n = 8), distance traveled (n = 8), time spent at prespecified locations (n = 7), and number of changes in GSM (Global System for Mobile communications) cell (n = 4). Twelve of 14 publications evaluating clinical aspects found an association between geolocation-derived digital biomarker and SMI concepts, especially mood. Geolocation-derived digital biomarkers were more strongly associated with SMI concepts than other information (eg, accelerometer data, smartphone activity, self-reported symptoms). However, small sample sizes and short follow-up warrant cautious interpretation of these findings: of all included studies, 7 had a sample of fewer than 10 patients and 11 had a duration shorter than 12 weeks. The growing body of evidence for the association between SMI concepts and geolocation-derived digital biomarkers shows potential for this instrument to be used for continuous monitoring of patients in their everyday lives, but there is a need for larger studies with longer follow-up times.

Identifiants

pubmed: 31260049
pii: 5480567
doi: 10.1093/jamia/ocz043
pmc: PMC6798569
doi:

Substances chimiques

Biomarkers 0

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

1412-1420

Subventions

Organisme : Medical Research Council
ID : MC_PC_13042
Pays : United Kingdom

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association.

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Auteurs

Paolo Fraccaro (P)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, United Kingdom.
Hartree Centre STFC Laboratory, IBM Research UK, Warrington, United Kingdom.

Anna Beukenhorst (A)

Centre for Epidemiology, Division of Musculoskeletal & Dermatological Sciences, University of Manchester, Manchester, United Kingdom.

Matthew Sperrin (M)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, United Kingdom.

Simon Harper (S)

School of Computer Science, University of Manchester, Manchester, United Kingdom.

Jasper Palmier-Claus (J)

Division of Psychology & Mental Health, University of Manchester, Manchester, United Kingdom.
Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.

Shôn Lewis (S)

Division of Psychology & Mental Health, University of Manchester, Manchester, United Kingdom.

Sabine N Van der Veer (SN)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, United Kingdom.
Centre for Epidemiology, Division of Musculoskeletal & Dermatological Sciences, University of Manchester, Manchester, United Kingdom.
National Institute of Health Research Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, United Kingdom.

Niels Peek (N)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, United Kingdom.
National Institute of Health Research Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, United Kingdom.
National Institute of Health Research Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom.

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