The mediating role of internet use in the relationship between working hours and depressive symptoms: an analysis based on cross-lagged models.

Background: Amidst the rapid development of the digital economy, prolonged working hours linked to mental health have become a global concern. Objective: To examine the longitudinal interplay between working hours and depression, and the mediating role of internet use. Methods: Utilizing a two-wave longitudinal dataset from the China Family Panel Studies (CFPS) spanning 2016 to 2018, we constructed a dynamic analysis sample of 4,900 workers aged 18-70. We employed cross-lagged panel models and semi-longitudinal mediation models to systematically investigate the bidirectional mechanisms between working hours and depressive symptoms. A key focus was to elucidate the mediating pathways of internet use and its heterogeneity across different groups. Results: The cross-lagged model revealed that working hours, internet use, and depressive symptoms showed dynamic interplay. Working hours, internet use, and depressive symptoms in 2016 positively predicted their respective outcomes in 2018. 2016 working hours positively predicted 2018 internet use (β = 0.045, p < 0.001) and 2018 depressive symptoms (β = 0.027, p < 0.05). Crucially, 2016 internet use negatively predicted 2018 depressive symptoms (β = -0.032, p < 0.01). The semi-longitudinal mediation model demonstrated that internet use mediated the working hours-depression symptoms link (effect = -0.0013, p < 0.05), meaning more work led to more internet use, which then reduced depression. This mediation was significant for women, married women, older adults, and stably employed groups. Furthermore, both online entertainment and online social interaction can significantly reduce the risk of depression, but this effect requires a usage frequency of at least 1-2 times per week. Conclusion: Excessive work harms mental health. Internet use mediates this effect, effectively buffering the psychological harm of overwork.