Mobile phone and wearable sensor-based mHealth approaches for psychiatric disorders and symptoms: systematic review
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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.
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Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors
Jacobson, N. C., Summers, B., & Wilhelm, S. (2020) · Journal of Medical Internet Research · doi:10.2196/16875 · Cited by 162 · see citing works
Opoku Asare, K., Terhorst, Y., Vega, J., Peltonen, E., Lagerspetz, E., & Ferreira, D. (2021) · JMIR mHealth and uHealth · doi:10.2196/26540 · Cited by 145 · see citing works
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A control theoretic approach to evaluate and inform ecological momentary interventions
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- Authors
- Seppälä, J., De Vita, I., Jämsä, T., Miettunen, J., Isohanni, M., Rubinstein, K., Feldman, Y., Grasa, E., Corripio, I., Berdun, J., D'Amico, E., M-RESIST Group, & Bulgheroni, M.
- Affiliations
- South Karelia Central Hospital (FI)
- Oulu University Hospital (FI)
- University of Oulu (FI)
- Universitat Autònoma de Barcelona (ES)
- Ab.Acus (Italy) (IT)
- Corresponding author
- M-RESIST Group
- ORCID
- Venue
- JMIR Mental Health
- Publisher
- JMIR Publications Inc.
- Published
- 2019-02-20
- Volume
- 6
- Issue
- 2
- Pages
- e9819
- ISSN
- 2368-7959 (ISSN-L)
- PMC
- PMC6401668
- OpenAlex
- W2955308548
- Cited by
- 148
- References
- 79
- Citations by year
- 2026: 8 · 2025: 19 · 2024: 27 · 2023: 20 · 2022: 19 · 2021: 24 · 2020: 23 · 2019: 8
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Mental Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- Työväentutkimus Vuosikirja (submittedVersion)
- Funders
- Centres de Recerca de Catalunya
- European Commission (HORIZON2020, 643552)
- Generalitat de Catalunya
- Horizon 2020 Framework Programme (643552)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- mobile health, wearable sensors, mental illness, treatment-resistant schizophrenia, bipolar disorder, depression, stress, behavioral monitoring, smartphone use
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