Evidence map›Paper›PMID 40242181›Full record

ArticleFrontiers in psychiatry2025

Internet addiction and its association with quality of life in college students: a network perspective.

Li-Ya A, Meng-Yi Chen, Yuan-Yuan Jiang, Hui-Ting Huang, Shou Liu, Yuan Feng, Xiao-Li Zhang, Zhaohui Su, Teris Cheung, Chee H Ng and 2 more

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Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Li-Ya A *Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.
Meng-Yi Chen *Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.
Yuan-Yuan Jiang *Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.
Hui-Ting Huang *Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.
Shou Liu *Department of Public Health, Medical College, Qinghai University, Xining, Qinghai, China.
Yuan FengBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Xiao-Li ZhangUnit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.
Zhaohui SuSchool of Public Health, Southeast University, Nanjing, China.
Teris CheungSchool of Nursing, Hong Kong Polytechnic University, Hong Kong, Hong Kong, SAR, China.
Chee H NgDepartment of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond VIC, Australia.
Yu-Tao XiangUnit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao SAR, China.
Gang WangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Internet addiction (IA), especially in young people, has gained increasing attention in recent years. This study examined the prevalence of IA and its associated factors, relationship with quality of life (QoL) and network structure among college students. Methods: A cross-sectional study was conducted between September and December 2023 in China. Internet addiction symptoms were assessed using the Internet Addiction Test (IAT). Univariate and multivariate analyses were performed to explore the correlates of IA. The relationship between IA and QoL was examined using analysis of covariance (ANCOVA). The Expected Influence (EI) centrality index was used in the network model to characterize the structure of IA symptoms. Results: A total of 6,514 college students were included. The prevalence of IA was 27.9% [95% confidence interval (CI): 26.8%-29.0%]. A binary logistic regression analysis indicated that living in urban areas (OR=1.135, P=0.032), being in senior grade (OR=1.396, P=0.017), and having current drinking (OR=1.431, P<0.001) were associated with increased risk of IA, while having a major in health (OR=0.796, P<0.001), good health status (OR=0.516, P<0.001), good economic status (OR=0.607, P<0.001), and regular physical exercise (OR=0.727, P<0.001) were associated with reduced risk of IA. ANCOVA revealed that college students with IA had lower QoL score (F Conclusion: Internet addiction was common among Chinese college students. Interventions targeting the most central symptoms and those closely associated with QoL should be developed to address IA in college students and improve the QoL of those with IA in this population.

Indexed as

college studentsinternet addictionnetwork analysisprevalencequality of life

Identifiers

PMID40242181
PMCPMC12000118

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