JMIR Hum Factors. 2025 Oct 7;12:e66536. doi: 10.2196/66536.
ABSTRACT
BACKGROUND: Adolescence is the period with the highest incidence of mental disorders, with approximately one-third, half, and two-thirds of cases emerging by ages 14, 18, and 25 years, respectively. Proactive interventions are essential, and digital phenotyping has emerged as a promising approach for timely detection and management. However, passive digital phenotyping is limited to sensor-detectable behaviors, while active phenotyping is often confined to clinical scales, missing the opportunity to capture users’ subjective perspectives and emotional nuances. Furthermore, the potential therapeutic effect of the data collection process itself on emotional disorder management remains underexplored.
OBJECTIVE: This study developed and tested a mobile app that collects passive and active digital phenotypes related to adolescents’ emotions and daily behaviors. The study aimed to assess the app’s impact on managing emotional disorders through self-monitoring and to identify daily lifestyle indicators that can predict and track the development of such disorders.
METHODS: A 4-week parallel, nonequivalent control group design was employed. The intervention group installed a digital phenotype collection tool on their mobile devices for 28 days. Passive data (location, sleep, and screen time) were continuously recorded. Active data were collected through ecological momentary assessments delivered randomly up to 8 times daily, prompting participants to report their current mood and levels of depression, anxiety, and stress. The control group received no intervention. Both groups were assessed at time points on emotional disorders, self-efficacy, and time management. Postintervention interviews were conducted with the intervention group.
RESULTS: Thirty-six Korean adolescents participated (19 control, 17 intervention). The intervention group showed significant reductions in depression (P=.04, d=0.42) and stress (P=.03, d=0.46) and improvements in self-efficacy (P=.002, d=0.50) and time management abilities (P<.001, d=0.39), with small to large effect sizes. No significant change was observed in anxiety levels (P=.11). Correlational analysis revealed weak but significant links between passive digital phenotypes and daily emotional states.
CONCLUSIONS: Integrating active and passive digital phenotypes through a mobile collection tool can help manage emotional disorders in adolescents. Use of the tool was associated with moderate reductions in depression and stress, as well as improvements in self-efficacy and time management, while anxiety levels remained unchanged, possibly due to adolescents’ differing perceptions of anxiety. Passive digital phenotypes such as location variability and phone usage showed modest correlations with daily emotional states, supporting their potential as ecological markers. These findings suggest that digital phenotype collection not only aids in monitoring but may also have therapeutic benefits by promoting self-reflection on mood and behavior. High adherence rates further support the practicality and acceptability of this approach for long-term emotional disorder management in adolescents.
PMID:41060096 | DOI:10.2196/66536
