A cross-lagged panel network analysis of loneliness, internet use, and depression among Chinese college students

Background: Displacement theory proposes that internet use can lead to heightened feelings of loneliness and depression, whereas the stimulation theory posits the opposite pathway. However, most investigations on this topic have been cross-sectional, precluding causal inferences. Thus, we used cross-lagged network analyses to facilitate causal inferences in understanding the relations between Internet use, loneliness and depression. Methods: The participants (N = 25,249) who were recruited from 22 colleges in Guangdong province, China completed the survey in 2020 and 2021. This study examined the interactions between Internet use, loneliness and depressive symptoms (PHQ-9) among this participants. All analyses adjusted for demographics. Results: Contemporaneous networks revealed strong connections within the depression cluster and negligible associations between loneliness and internet use. Key bridging nodes were loneliness, guilt, anhedonia, and concentration problems, which linked constructs across the network. Temporal analyses did not support either the displacement or stimulation hypotheses, showing that higher loneliness predicted future depressive symptoms such as sad mood and anhedonia, as well as marginally higher internet use. Internet use exhibited mixed effects, weakly reducing suicide risk while marginally exacerbating depressive symptoms over time. Conclusions: These findings underscore the importance of loneliness as a central driver and highlight the nuanced role of internet use.