Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

Jussi Seppälä; Ilaria De Vita; Timo Jämsä; Jouko Miettunen; Matti Isohanni; Katya Rubinstein; Yoram Feldman; Eva Grasa; Iluminada Corripio; Jesus Berdun; Enrico D'Amico; M-RESIST Group; Maria Bulgheroni

doi:10.2196/mental.9819

Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

JMIR Ment Health. 2019 Feb 20;6(2):e9819. doi: 10.2196/mental.9819.

Authors

Jussi Seppälä^#^{1

2}, Ilaria De Vita^#³, Timo Jämsä^{4

5

6}, Jouko Miettunen^{1

5}, Matti Isohanni¹, Katya Rubinstein⁷, Yoram Feldman⁷, Eva Grasa^{8

9

10}, Iluminada Corripio^{8

9

10}, Jesus Berdun¹¹, Enrico D'Amico³; M-RESIST Group¹²; Maria Bulgheroni^#³

Affiliations

¹ Center for Life Course of Health Research, University of Oulu, Oulu, Finland.
² Department of Mental and Substance Use Services, Eksote, Lappeenranta, Finland.
³ Ab.Acus srl, Milano, Italy.
⁴ Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.
⁵ Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.
⁶ Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.
⁷ The Gertner Institute for Epidemiology and Health Policy Research, Tel Aviv, Israel.
⁸ Department of Psychiatry, Biomedical Research Institute Sant Pau (IIB-SANT PAU), Hospital Sant Pau, Barcelona, Spain.
⁹ Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.
¹⁰ CIBERSAM, Madrid, Spain.
¹¹ Fundació TIC Salut Social, Barcelona, Spain.
¹² m-RESIST, Barcelona, Spain.

^# Contributed equally.

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.

Keywords: EMA; ecological momentary assessment; m-RESIST; mobile phone; psychiatric disorder; schizophrenia; sensors.

©Jussi Seppälä, Ilaria De Vita, Timo Jämsä, Jouko Miettunen, Matti Isohanni, Katya Rubinstein, Yoram Feldman, Eva Grasa, Iluminada Corripio, Jesus Berdun, Enrico D'Amico, M-RESIST Group, Maria Bulgheroni. Originally published in JMIR Mental Health (http://mental.jmir.org), 20.02.2019.

Publication types

Review