TY - JOUR
T1 - Internet addiction and its association with quality of life in college students
T2 - a network perspective
AU - A, Li Ya
AU - Chen, Meng Yi
AU - Jiang, Yuan Yuan
AU - Huang, Hui Ting
AU - Liu, Shou
AU - Feng, Yuan
AU - Zhang, Xiao Li
AU - Su, Zhaohui
AU - Cheung, Teris
AU - Ng, Chee H.
AU - Xiang, Yu Tao
AU - Wang, Gang
N1 - Publisher Copyright:
Copyright © 2025 A, Chen, Jiang, Huang, Liu, Feng, Zhang, Su, Cheung, Ng, Xiang and Wang.
PY - 2025/4/2
Y1 - 2025/4/2
N2 - 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 (1, 6514) = 128.167, P < 0.001). The most central (influential) symptoms were “Academic efficiency declines” (IAT8, EI value=1.10), “Request an extension for longer time” (IAT16, EI value=1.10) and “Neglect chores to spend more time online” (IAT2, EI value=1.00) in the network model of IA symptoms. The symptom “Form new relationships with online users” (IAT4) had the strongest direct positive relationship with QoL, while “Sleep loss” (IAT14) and “Prefer the excitement online to the time with others” (IAT3) had the strongest direct negative relationship with QoL. 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.
AB - 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 (1, 6514) = 128.167, P < 0.001). The most central (influential) symptoms were “Academic efficiency declines” (IAT8, EI value=1.10), “Request an extension for longer time” (IAT16, EI value=1.10) and “Neglect chores to spend more time online” (IAT2, EI value=1.00) in the network model of IA symptoms. The symptom “Form new relationships with online users” (IAT4) had the strongest direct positive relationship with QoL, while “Sleep loss” (IAT14) and “Prefer the excitement online to the time with others” (IAT3) had the strongest direct negative relationship with QoL. 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.
KW - college students
KW - internet addiction
KW - network analysis
KW - prevalence
KW - quality of life
UR - http://www.scopus.com/inward/record.url?scp=105002655817&partnerID=8YFLogxK
U2 - 10.3389/fpsyt.2025.1555372
DO - 10.3389/fpsyt.2025.1555372
M3 - Journal article
AN - SCOPUS:105002655817
SN - 1664-0640
VL - 16
JO - Frontiers in Psychiatry
JF - Frontiers in Psychiatry
M1 - 1555372
ER -
