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Updated: Jun 12, 2025

Psychophysiological Assessment of the Effectiveness of Emotion Regulation Strategies in Childhood
Published on: February 11, 2017
The longitudinal relationships between problematic mobile phone use symptoms and negative emotions: a cross-lagged
Guanghui Shen1, Guoyong Huang2, Mengting Wang3
1Wenzhou Seventh People's Hospital, Wenzhou 325006, China; School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China.
Background:
The association between problematic mobile phone use (PMPU) and negative emotions in university students is not well understood in terms of causality and directionality. This study aims to clarify whether negative emotions trigger PMPU or whether the PMPU itself leads to increased negative emotions over time.
Methods:
A two-wave longitudinal study was conducted involving 5568 Chinese freshmen who were surveyed at baseline and followed up after one academic year. PMPU, social media use, online game use, fear of missing out, loneliness, social anxiety, and academic burnout were measured. Cross-sectional and longitudinal connections between these variables were examined using network analysis techniques.
Results:
The variable with the strongest influence in both contemporaneous networks was "Productivity loss" of MAPI. Moreover, "Academic burnout" at baseline significantly predicted higher levels of problematic smartphone use and negative emotions at follow-up, suggesting that it may serve as a catalyst for addictive tendencies. Furthermore, we observed bidirectional relationships between "Escapism" and "Social anxiety", as well as between "Social anxiety" and "Inability to control craving", suggesting a potential self-perpetuating cycle.
Conclusion:
These findings highlight the role of academic burnout in initiating cycles of PMPU and negative emotions. In order to effectively tackle PMPU, it is crucial to consider the underlying drivers such as academic burnout and emotional states. This is important due to the complex and reciprocal associations uncovered through our longitudinal network analysis.
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