Linking multiple risk exposure profiles with adolescent Internet addiction: Insights from the person-centered approach

Published on Oct 1, 2017in Computers in Human Behavior4.306
· DOI :10.1016/j.chb.2017.04.063
Dongping Li8
Estimated H-index: 8
(CCNU: Central China Normal University),
Xian Li7
Estimated H-index: 7
(University at Albany, SUNY)
+ 3 AuthorsYanhui Wang8
Estimated H-index: 8
(Jiaying University)
Abstract Accumulating evidence suggests that multiple environmental and individual risk factors are involved in the development of adolescent Internet addiction. However, previous research has primarily relied on variable-centered approaches to examine how each risk factor functions to predict Internet addiction in isolation, ignoring the possibility that there are subgroups of adolescents who may differ in their combined exposure to multiple risk factors. Using a cross-sectional design, we sampled 14 risk factors across multiple socio-ecological levels and used a person-centered approach to identify subgroups of multiple risk exposure and to relate these subgroups to adolescent Internet addiction. A total of 998 Chinese adolescents ( M age  = 15.15 years, SD  = 1.57) participated in this study by filling out questionnaires regarding 14 family, school, peer, and individual risk factors and Internet addiction. Latent profile analysis identified 4 profiles that evidenced distinct patterns of risk factors: low risk (37%), moderate risk (44%), high risk (15%) and peer risk (4%). The high risk and moderate risk profiles showed higher risk for Internet addiction than the low risk profile. The peer risk profile had higher risk for Internet addiction than the high risk, moderate risk, and low risk profiles. These findings suggest that considerable heterogeneity exists in multiple risk exposure and the multiple risk exposure profiles are differentially associated with adolescent Internet addiction. Results from this study can inform the development of tailored intervention and prevention strategies to reduce adolescent Internet addiction.
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