Evidence map›Paper›PMID 40290629›Full record

ArticleAddictive behaviors reports2025

Latent profiles of problematic internet use and their six-month subsequent psychopathology outcomes.

Yi Wang, Brian J Hall, Yuran Chen, Chun Chen

Abstract read
In one paragraph

Article in Addictive behaviors reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yi WangSchool of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
Brian J HallCenter for Global Health Equity, New York University, Shanghai, Shanghai, China.
Yuran ChenSchool of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
Chun ChenSchool of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Problematic Internet Use (PIU) has many adverse effects on youth mental health, including heightened risks of depression and anxiety. However, few studies have systematically investigated the internal heterogeneity of PIU symptoms among rural Chinese adolescents. Data was collected from 5,271 rural Chinese adolescents from two secondary schools in Guizhou and Sichuan at two waves. This study aimed to identify PIU profiles at T1 and examine their relationships with subsequent anxiety, depression, and stress after six months at T2. Methods: A Latent Profile Analysis (LPA) was conducted to first identify PIU symptom profiles. Then, a "three-step" logistic regression mixed model was conducted to explore the association between PIU patterns and demographic correlates. Anxiety, depression, and stress symptoms collected at the second wave were compared across PIU profiles by using a Bolck-Croon-Hagenaars (BCH) approach. Results: The study found that (1) The patterns of PIU among rural adolescents could be divided into four subgroups: low PIU group (57.18%), medium PIU group (15.65%), high PIU group (9.01%), and self-blame group (18.16%), which is a uniquely identified group. (2) Being female, an ethnic minority, living off-campus, having left-behind experiences, and having fewer siblings were risk factors for high PIU group membership. (3) The order of severity for anxiety, depression, and stress was as follows: high PIU, medium PIU, self-blame, and low PIU groups. (4) The self-blame group had relatively lower anxiety, depression, and stress scores than the medium PIU group, despite the fact that the self-blame group had higher PIU scores than the medium PIU group, which further strengthens the importance of using a person-centered approach. Conclusions: Addressing the profiles of PIU is vital for rural Chinese adolescent mental health, necessitating tailored interventions.

Indexed as

AnxietyDepressionLatent profile analysisLongitudinal studyProblematic internet useRural adolescentsStress

Identifiers

PMID40290629
PMCPMC12033921

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.