JMIR Publications

ABSTRACT

Background:

Adolescence is the period with the highest incidence of mental disorders, half of which begin before age 18. Mental health issues during this stage of life can have extended effects into adulthood, highlighting the need for proactive interventions. Advances in technology have introduced digital phenotypes as a way to diagnose and treatment of emotional disorders early. Despite their potential, concerns have been raised about the technical limitations of passive digital phenotypes and the limited uses of active digital phenotypes. Moreover, the effect of data collection on managing emotional disorders remains unexplored.

Objective:

This study developed a service that collects and tracks digital phenotypes related to the emotions and daily lives of adolescents and determined whether it positively affected emotional disorder management through self-monitoring. Additionally, this study identified everyday life indicators that can be used to predict and track the development of emotional disorders.

Methods:

A four-week parallel, non-equivalent control group design was employed. The intervention group was instructed to install a digital phenotype collection service on their mobile devices for 28 days. The control group was not required to engage in any specific task. Both groups were assessed at multiple points for emotional disorders, namely depression, anxiety, and stress; self-efficacy; and time management abilities. Following the intervention, the intervention group participated in semi-structured interviews to discuss their experiences.

Results:

Total of 36 adolescents participated in the study. The digital phenotype collection system significantly reduced adolescents’ depression (P = .044) and stress (P = .034) and significantly increased their self-efficacy (P = .002) and time management abilities (P < .001). However, it did not result in significant changes in anxiety levels (P = .113). The correlational analysis revealed weak but statistically significant relationships between passive digital phenotypes and daily levels of depression, anxiety, and stress.

Conclusions:

The findings suggest that the digital phenotype collection service can be used to understand and manage emotional disorders in adolescents. This study was empirically significant because it showed that the service positively affected depression, stress, self-efficacy, and time management, all of which are crucial aspects of adolescent life. Furthermore, the study’s high level of participant adherence, despite the extensive engagement required, underscores the potential for using digital phenotyping in adolescent mental health care. The study contributes to a growing body of evidence supporting the use of digital phenotyping as a means of diagnosing and managing emotional disorders in adolescents.