JMIR Publications

ABSTRACT

Background:

The increasing prevalence of problematic smartphone use (PSU) among university students is raising concerns, particularly as excessive smartphone engagement is linked to negative outcomes such as mental health issues, academic underperformance, and sleep disruption. Despite the severity of PSU, its association with behaviors such as physical activity, mobility, and sociability has received limited research attention. Ecological momentary assessment (EMA), including passive data collection through digital phenotyping indicators, offers an objective approach to explore these behavioral patterns.

Objective:

This study aimed to examine associations between self-reported psychosocial measures, app-based EMA data—including daily behavioral indicators from global positioning system (GPS) location tracking—and PSU in university students during the exam period.

Methods:

A 6-week observational study was conducted with 243 university students, using app-based EMA on personal smartphones to collect data on daily behaviors and psychosocial factors related to smartphone overuse. Smartphone addiction was assessed using the Korean Smartphone Addiction Proneness Scale. Data collected from the Big4+ app, including self-reports on mood, sleep, and appetite, as well as passive sensor data (GPS location, acceleration, and steps), were used to evaluate overall health. Logistic regression analysis was conducted to identify factors that significantly influenced smartphone overuse, providing insights into daily behavior and mental health patterns.

Results:

Of the students, 23% (56/243) exhibited smartphone addiction. The regression analysis revealed significant positive associations between PSU and several factors, including depression (Patient Health Questionnaire-9; odds ratio [OR] 8.48; 95% confidence interval [CI] 1.95-36.87; P = .004), social interaction anxiety (Social Interaction Anxiety Scale; OR=4.40; 95%; CI=1.59-12.15; P = .004), sleep disturbances (General Sleep Disturbance Scale; OR 3.44; 95% CI 1.15-10.30; P = .028), and longer sleep duration (OR=3.11; 95% CI=1.14-8.48; P = .027). Conversely, a significant negative association was found between PSU and time spent at home (OR 0.35; 95% CI 0.13-0.94; P = .037).

Conclusions:

This study suggests that negative self-perceptions of mood and sleep, along with patterns of increased mobility identified through GPS data, elevate the risk of PSU, particularly under academic stress. Combining psychosocial assessments with EMA data offers valuable insights for managing PSU during high-stress periods, such as exams, and provides new directions for future research.