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Accepted for/Published in: JMIR Mental Health

Date Submitted: Jan 11, 2018
Open Peer Review Period: Jan 18, 2018 - Jul 26, 2018
Date Accepted: Dec 15, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

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

Seppälä J, De Vita I, Jämsä T, Miettunen J, Isohanni M, Rubinstein K, Feldman Y, Grasa E, Corripio I, Berdún J, D'Amico E, Bulgheroni M, M-RESIST Group

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

JMIR Ment Health 2019;6(2):e9819

DOI: 10.2196/mental.9819

PMID: 30785404

PMCID: 6401668

Smartphone and wearable sensors-based m-Health approach for psychiatric disorders and symptoms – a systematic review and link to m-RESIST project

  • Jussi Seppälä; 
  • Ilaria De Vita; 
  • Timo Jämsä; 
  • Jouko Miettunen; 
  • Matti Isohanni; 
  • Katia Rubinstein; 
  • Yoram Feldman; 
  • Eva Grasa; 
  • Illuminada Corripio; 
  • Jesús Berdún; 
  • Enrico D'Amico; 
  • Maria Bulgheroni; 
  • M-RESIST Group

ABSTRACT

Background:

m-RESIST (Mobile Therapeutic Attention for Patients with Treatment Resistant Schizophrenia) is an EU H2020 funded project aimed at designing and validating an innovative therapeutic programme for treatment-resistant schizophrenia exploiting information from smartphone and wearable sensors for behavioural tracking to support intervention administration.

Objective:

To systematically review original studies on sensor-based m-Health applications aimed at pointing out associations between sensor data and symptoms of psychiatric disorders to support the m-RESIST approach to assess effectiveness of behavioural monitoring in therapy.

Methods:

A systematic review of the English language literature, according to PRISMA guidelines, was performed through Scopus, PubMed, Web of Science and Cochrane Central Register of Controlled Trials databases in the time frame between 1st September 2009 and 30th September 2018. Search terms included mental health, mental disorders, depression, anxiety, schizophrenia, bipolar, insomnia, stress, mobile, smartphone, monitoring, sensor, sensing.

Results:

Only studies reporting quantitative information from the mobile use and/or wearable sensors data collection and associating this information with clinical outcomes were included. Two independent experts evaluated the selected articles. 35 studies were identified, most of them investigating bipolar disorders and depression, depression symptoms, stress and symptoms of stress while only few addressed persons with schizophrenia.

Conclusions:

Data from sensors demonstrate an association with the symptoms of schizophrenia, bipolar disorder and depression while usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.


 Citation

Please cite as:

Seppälä J, De Vita I, Jämsä T, Miettunen J, Isohanni M, Rubinstein K, Feldman Y, Grasa E, Corripio I, Berdún J, D'Amico E, Bulgheroni M, M-RESIST Group

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

JMIR Ment Health 2019;6(2):e9819

DOI: 10.2196/mental.9819

PMID: 30785404

PMCID: 6401668

Per the author's request the PDF is not available.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.