Associations of Accelerometer-measured Physical Activity, Sedentary Behaviour and Different Types of Smartphone Apps Usage among University Students: A 7-day Tracking Study

Background Previous studies suggest that total screen time does not comprehensively predict health behavior. The effects on health behaviors vary by app type. This study examines the association of different app categories (social, entertainment, game, education) related to physical activity (PA) and sedentary behavior (SB) patterns among university students. Methods This study followed 345 university students aged 18–22 for 7 days. Physical activity (PA), and sedentary behavior (SB) were objectively measured using the ActiGraph GT3X-BT accelerometer. Smartphone app usage was tracked via objective daily survey logs. After the 7-day tracking period, semi-structured interviews were conducted to gather detailed information on app usage and physical activity. Data analysis was performed using SPSS 26.0 and R software. Results In 248 participants (139 males, 109 females), Males had higher daily energy expenditure and more sedentary time (ST) compared to females, who spent more time in light-intensity physical activity (LPA) but less in vigorous-intensity physical activity (VPA). Males showed a positive correlation between entertainment app usage and ST (r = 0.271, p = 0.017) and a negative correlation with sedentary interval (SI) (r = -0.266, p = 0.019). In females, social app usage correlated with increased LPA (r = 0.321, p < 0.001) and VPA was positively correlated with screen time (ST) (r = 0.195, p = 0.042). App usage also influenced SB patterns, particularly in active individuals. After controlling for confounding factors, gaming app usage in males who inactive decreased LPA (0.341 min, p = 0.036). In females, social app usage increased LPA (0.112 min, p = 0.018) but decreased VPA (0.012 min, p = 0.011) in those who inactive. ST was linked to an increase in ST and to a decrease in SI time in both genders. Conclusions Implementation of digital health interventions should be content-specific and take into account application type, gender and active status to promote sustainable active lifestyles that go beyond traditional strategies to reduce screen time.