In JMIR mental health
The COVID-19 pandemic has required transitioning many clinical addiction treatment programs to telephonic or virtual visits. Novel solutions are needed to enhance substance use treatment during a time when many patients are disconnected from clinical care and social supports. Digital phenotyping, which leverages the unique functionality of smartphones sensors (GPS, social behavior, and typing patterns), can buttress clinical treatment in a remote, scalable fashion. Specifically, digital phenotyping has the potential to improve relapse prediction and intervention, relapse detection, and overdose intervention. Digital phenotyping may enhance relapse prediction through coupling machine learning algorithms with the enormous wealth of collected behavioral data. Activity based analysis in real time potentially can be used to prevent relapse by warning substance users when they approach locational triggers such as bars or liquor stores. Wearable devices detect when someone has relapsed to substances through measuring physiological changes such as electrodermal activity and locomotion. Despite its initial promise, privacy, security and barriers to access are important issues to address.
Hsu Michael, Ahern David K, Suzuki Joji