Algorithmic and sensor-based research on Chinese children’s and adolescents’ screen use behavior and light environment - Wang, Jifang; Shen, Yang; Zhao, Jing; Wang, Xiaoying; Chen, Zhi; Han, Tian; Huang, Yangyi; Wang, Yuliang; Zhao, Wuxiao; Wen, Wen; Zhou, Xingtao; Xu, Ye (Frontiers in Public Health, 2024)
Background Myopia poses a global health concern and is influenced by both genetic and environmental factors. The incidence of myopia tends to increase during infectious outbreaks, such as the COVID-19 pandemic. This study examined the screen-time behaviors among Chinese children and adolescents and investigated the efficacy of artificial intelligence (AI)-based alerts in modifying screen-time practices. Methods A cross-sectional analysis was performed using data from 6,716 children and adolescents with AI-enhanced tablets that monitored and recorded their behavior and environmental light during screen time. Results The median daily screen time of all participants was 58.82 min. Among all age groups, elementary-school students had the longest median daily screen time, which was 87.25 min and exceeded 4 h per week. Children younger than 2 years engaged with tablets for a median of 41.84 min per day. Learning accounted for 54.88% of participants’ screen time, and 51.03% (3,390/6,643) of the participants used tablets for 1 h at an average distance <50 cm. The distance and posture alarms were triggered 807,355 and 509,199 times, respectively. In the study, 70.65% of the participants used the tablet under an illuminance of <300 lux during the day and 61.11% under an illuminance of <100 lux at night. The ambient light of 85.19% of the participants exceeded 4,000 K color temperature during night. Most incorrect viewing habits (65.49% in viewing distance; 86.48% in viewing posture) were rectified swiftly following AI notifications (all p < 0.05). Conclusion Young children are increasingly using digital screens, with school-age children and adolescents showing longer screen time than preschoolers. The study highlighted inadequate lighting conditions during screen use. AI alerts proved effective in prompting users to correct their screen-related behavior promptly.