Directional Relations Between Symptoms of Adolescent Smartphone Addiction, Academic Burnout, and Psychological Distress: A Cross-Lagged Panel Network Analysis

Wei Yao,1, Mengjian Hu,1,2, Hanchao Hou,1,3 Peng Yang,4 Shiguang Ni1 1Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, People’s Republic of China; 2School of Psychology, South China Normal University, Guangzhou, Guangdong, People’s Republic of China; 3The Centre for Wellbeing Science, University of Melbourne, Melbourne, Australia; 4Faculty of Data Science and Information Technology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, People’s Republic of ChinaThese authors contributed equally to this workCorrespondence: Shiguang Ni, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, People’s Republic of China, Email ni.shiguang@sz.tsinghua.edu.cnBackground: Previous research has identified a high risk of smartphone addiction and its association with general and school-contextual mental health problems (ie, psychological distress and academic burnout) among Chinese adolescents. Nonetheless, the directional and symptom-level relationships among these problems remain underexamined, hindering understanding of the mechanisms underlying their co-occurrence. Based on the I-PACE (Interaction of Person-Affect-Cognition-Execution) model, this study addressed these gaps by performing a cross-lagged panel network (CLPN) analysis.Methods: Data were obtained from a survey of 589 adolescents in secondary schools in China at two time points, with a five-month interval. Using a CLPN approach, this study examined the directional relationships among smartphone addiction, academic burnout, and psychological distress at the symptom level.Results: The depression and anxiety symptoms of psychological distress, as well as the withdrawal symptom of smartphone addiction, emerged as strong bridging symptoms. Moreover, three mechanisms linking the three problems were identified. First, depression predicted cyberspace-oriented relationships and smartphone overuse, and anxiety predicted daily-life disturbances. Second, withdrawal predicted anxiety. Third, depression predicted exhaustion from studying, and withdrawal predicted cynical attitudes towards studying.Conclusion: The results support the predisposing factors–smartphone addiction cycle described in the I-PACE model, aligning with the vulnerability, predisposition entrenchment, and intensification mechanisms proposed by the model. Psychological distress symptoms, as predisposing factors, playing key roles in the cycle. However, the results indicate that school situational factors such as academic burnout may function as distal outcomes rather than triggers in the cycle. The key linking mechanisms identified in this study are informative for generating hypotheses for future research and developing practical intervention strategies.Keywords: smartphone addiction, academic burnout, psychological distress, cross-lagged panel network