Mobile Phone and Wearable Sensor-Based mHealth Approach for Psychiatric Disorders and Symptoms : Systematic Review and Link to the m-RESIST Project

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M-RESIST Grp , Seppala , J , De Vita , I , Miettunen , J , Isohanni , M , Rubinstein , K , Feldman , Y , Grasa , E , Corripio , I , Berdun , J , D'Amico , E & Bulgheroni , M 2019 , ' Mobile Phone and Wearable Sensor-Based mHealth Approach for Psychiatric Disorders and Symptoms : Systematic Review and Link to the m-RESIST Project ' , Jmir mental health , vol. 6 , no. 2 , 9819 . https://doi.org/10.2196/mental.9819

Title: Mobile Phone and Wearable Sensor-Based mHealth Approach for Psychiatric Disorders and Symptoms : Systematic Review and Link to the m-RESIST Project
Author: M-RESIST Grp; Seppala, Jussi; De Vita, Ilaria; Miettunen, Jouko; Isohanni, Matti; Rubinstein, Katya; Feldman, Yoram; Grasa, Eva; Corripio, Iluminada; Berdun, Jesus; D'Amico, Enrico; Bulgheroni, Maria
Contributor organization: HYKS erva
Date: 2019-02-20
Language: eng
Number of pages: 14
Belongs to series: Jmir mental health
ISSN: 2368-7959
DOI: https://doi.org/10.2196/mental.9819
URI: http://hdl.handle.net/10138/302383
Abstract: Background: Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration. Objective: To systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy. Methods: A systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied. Results: Studies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression. Conclusions: Although the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.
Subject: sensors
mobile phone
m-RESIST
ecological momentary assessment
EMA
psychiatric disorder
schizophrenia
SERIOUS MENTAL-ILLNESS
SOCIAL RHYTHMS
HEALTH
SCHIZOPHRENIA
TECHNOLOGIES
INTERVENTION
SMARTPHONES
RECOGNITION
DEPRESSION
INPATIENTS
3124 Neurology and psychiatry
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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