Background: Recent years have seen an increase in school refusal behavior among adolescents, potentially due to factors like excessive short-form video viewing, bullying, and school anxiety. Limited research has investigated how these factors contribute to school refusal behavior. This study used random forest regression, path analysis, and network analysis to identify key variables and pathways leading to school refusal behavior.

Methods: In this cross-sectional questionnaire-based study, 2,056 (996 male, 1,060 female, mean age: 14.79 ± 1.24 years) middle and senior high school students were asked to complete the School Refusal Behavior Assessment questionnaire to assess school refusal behavior features, the Excessive Short-Form Video Viewing Scale as well as self-reported viewing times during leisure days to assess excessive short-form video viewing, the SNAP-IV Rating Scale to assess the severity of inattention symptoms, and the self-administered questionnaires to assess experiences of being bullied and school anxiety.

Results: The prevalence of school refusal behavior in the surveyed adolescents was found to be 31.9% [95% confidence interval (CI): 29.8-33.9%]. In terms of significance, the severity of inattention symptoms exhibited the greatest predictive power, while excessive short-form video viewing accounted for the most variance. Path analysis revealed that excessive short-form video viewing not only directly affects school refusal behavior features but also does so indirectly through severity of inattention symptoms and school anxiety. Key bridge factors in this pathway include intense fear and anxiety associated with school attendance, manifesting as somatic symptoms and avoidance behaviors.

Conclusion: The findings indicate that not only does excessive short-form video viewing directly influence school refusal behavior features in adolescents, but it also indirectly impacts these features through mechanisms involving severity of inattention symptoms and school anxiety. The bridge factors highlight potential targets for interventions among the SRB features and predictors.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11337196PMC
http://dx.doi.org/10.3389/fpubh.2024.1450935DOI Listing

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