Digital phenotyping for mental disorders monitoring: a systematic review (Preprint)

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 systematically review the scientific literature related to the use of Digital Phenotyping for predicting relapse or exacerbations of symptoms in patients with mental disorders. METHODS From an initial pool of 1150 scientific papers, we selected a final sample of 29 that we divided into four groups based on the mental disorder. RESULTS The results showed that Digital Phenotyping could replace the gold standard assessment and can 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).