Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 24, 2023
Open Peer Review Period: Feb 24, 2023 - Apr 21, 2023
Date Accepted: Jul 31, 2023
(closed for review but you can still tweet)
Is Digital Phenotyping reliable for monitoring mental disorders?: A systematic review
ABSTRACT
Background:
The COVID-19 pandemic has increased the impact and spread of mental illness and made health services difficult to access, hence the need for remote, pervasive forms of mental health monitoring. Digital Phenotyping is a new approach that aims to use the measures extracted from spontaneous interactions with smartphones (e.g., screen touches or movements) or other digital devices as markers of mental status.
Objective:
This paper aimed to evaluate, through a systematic review of the scientific literature, the feasibility of using Digital Phenotyping for predicting relapse or exacerbations of symptoms in patients with mental disorders.
Methods:
Our research was carried out in 2 bibliographic databases (PubMed and Scopus), looking through articles published up to January 2023. Starting from an initial pool of 1150 scientific papers, we screened and extracted a final sample of 29 papers, by following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines.
Results:
We divided the results into four groups according to mental disorder: schizophrenia (9 out of 29), mood disorders (15 out of 29), anxiety disorders (5 out of 29), and substance use disorder (1 out of 29). Results for the first three groups showed that several features (i.e.: mobility, location, phone use, call log, heart rate, sleep, head movements, facial and vocal characteristics, sociability, social rhythms, conversations, number of steps, screen on/off status, text message logs, peripheral skin temperature, electrodermal activity, light exposure, physical activity), extracted from data collected via the smartphone and/or wearable wristbands, can be used to create digital phenotypes that could replace the gold standard assessment and could be used to predict relapse or symptom exacerbations.
Conclusions:
Thus, since the data are consistent for almost all the mental disorders considered (mood disorders, anxiety disorders, and schizophrenia), the feasibility of this approach is confirmed. In the future, a new model of health care management, through digital devices, should be integrated with the Digital Phenotyping approach and tailored mobile interventions (managing crises during relapse/exacerbation).
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Copyright
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