Daily estimates of clinical severity of symptoms in bipolar disorder from smartphone-based self-assessments.
Journal
Translational psychiatry
ISSN: 2158-3188
Titre abrégé: Transl Psychiatry
Pays: United States
ID NLM: 101562664
Informations de publication
Date de publication:
18 06 2020
18 06 2020
Historique:
received:
04
11
2019
accepted:
29
04
2020
revised:
18
04
2020
entrez:
20
6
2020
pubmed:
20
6
2020
medline:
22
6
2021
Statut:
epublish
Résumé
Currently, the golden standard for assessing the severity of depressive and manic symptoms in patients with bipolar disorder (BD) is clinical evaluations using validated rating scales such as the Hamilton Depression Rating Scale 17-items (HDRS) and the Young Mania Rating Scale (YMRS). Frequent automatic estimation of symptom severity could potentially help support monitoring of illness activity and allow for early treatment intervention between outpatient visits. The present study aimed (1) to assess the feasibility of producing daily estimates of clinical rating scores based on smartphone-based self-assessments of symptoms collected from a group of patients with BD; (2) to demonstrate how these estimates can be utilized to compute individual daily risk of relapse scores. Based on a total of 280 clinical ratings collected from 84 patients with BD along with daily smartphone-based self-assessments, we applied a hierarchical Bayesian modelling approach capable of providing individual estimates while learning characteristics of the patient population. The proposed method was compared to common baseline methods. The model concerning depression severity achieved a mean predicted R
Identifiants
pubmed: 32555144
doi: 10.1038/s41398-020-00867-6
pii: 10.1038/s41398-020-00867-6
pmc: PMC7303106
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
194Subventions
Organisme : Innovationsfonden (Innovation Fund Denmark)
ID : 5164-00001B
Pays : International
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