Most previous studies focused on the associations of depression and anxiety with Internet addiction (IA) have used variable-centered approaches. This study aims to explore the distinct developmental trajectories of depression and anxiety, and their association with IA based on person-centered approaches.
A total of 437 Chinese high school freshmen at the baseline were followed across one year. Latent class growth analysis (LCGA) and growth mixture modeling (GMM) were used to identify the heterogeneity of individual trajectories of depression and anxiety.
For depression, there were three distinct trajectories identified, namely, the escalating group (n=60, 13.7%), recovery group (n=31, 7.1%), and the low-stable group (n=346, 79.2%). For anxiety, the subgroups consisted of the escalating group (n=50, 11.4%), the recovery group (n=34, 7.8%), and the low-stable group (n=353, 80.8%). The probability of IA in the depression low-stable group was significantly smaller compared to those in either the recovery group (χ=10.794, P=0.001) or the escalating group (χ=19.314, P<0.001). The probability of IA in the anxiety low-stable group was found to be significantly smaller than that in the recovery group (χ=17.359, P<0.001) and the escalating group (χ=7.752, P=0.005).
The sample was limited to students from one specific high school and had a one-year follow-up.
The findings of the study suggest the necessity of early prevention and intervention strategies for those students with depression and anxiety, which are at elevated risk of developing IA.

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