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. 2025 May 15;15(1):16853.
doi: 10.1038/s41598-025-96671-7.

Relationship between adolescent gaming addiction and myopia, ocular surface condition, and health status: a questionnaire based cohort study

Xiao-Yu Wang #  1 , Jin-Yu Hu #  2   1 , Qian-Ming Ge #  1 , Cheng Chen  1 , San-Hua Xu  1 , Qian Ling  1 , Yan-Mei Zeng  1 , Wan-Ting Yao  1 , Hong Wei  1 , Jie Zou  1 , Liang-Qi He  1 , Yan Lou  3 , Yi Shao  4   5
Affiliations

Relationship between adolescent gaming addiction and myopia, ocular surface condition, and health status: a questionnaire based cohort study

Xiao-Yu Wang et al. Sci Rep. .

Abstract

This study explores the relationship between gaming addiction among Chinese adolescents and their myopia, ocular surface conditions, and overall health. A cross-sectional questionnaire-based cohort study included 835 participants aged 13-17, selected from 3300. Tools included the Hospital Anxiety and Depression Scale (HADS), Van Dream Anxiety Scale (VDAS), 36-Item Short-Form Health Survey (SF-36), Ocular Surface Disease Index (OSDI), Internet Addiction Test (IAT), and Internet Gaming Disorder Scale-20 (IGD-20). Linear regression, Pearson correlation, and unpaired t-tests were used. Gaming addiction correlated with worsened physical and mental health. Older age and longer gaming duration were linked to higher myopia rates. Males scored higher on HADS, VDAS, IAT, and IGD-20 but lower on SF-36 than females. Myopic gamers had longer gaming durations and higher IAT scores. IGD-20 scores for gamers playing 5-6+ hours daily showed stronger correlations with HADS, VDAS, and OSDI. Online gaming significantly impacts vision, physical and mental health, and ocular surface conditions. Score differences between groups underscore the need for interventions, including mental health support, cognitive-behavioral correction, and preventive eye care.

Keywords: Adolescents; Internet game addiction; Myopia; Ocular surface; Physical health; Psychological health.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Ethical approval and consent to participate: The study methods and protocols were approved by the Medical Ethics Committee of the First Affiliated Hospital of Nanchang University (Nanchang, China) and followed the principles of the Declaration of Helsinki. The guardians of the adolescent participants have given informed consent for their participating in the questionnaire survey.

Figures

Fig. 1
Fig. 1
Inclusion procedure.
Fig. 2
Fig. 2
The population proportion of enrolled participants. The population composition of participants by age, gender, myopia condition, degree of dry eye and region.
Fig. 3
Fig. 3
Comparative analysis of differences in multiple health indicators between groups. This figure presents a comprehensive comparison of health indicators between the two groups, including Hospital Anxiety and Depression Scale (HADS), Van Dream Anxiety Scale (VDAS), 36-item Short-Form Health Survey (SF-36), Ocular Surface Disease Index (OSDI), Internet Addiction Test (IAT) and Internet Gaming Disorder Scale-20 (IGD-20). Significant mean differences between groups are symbolized by asterisks. ****P < 0.0001.
Fig. 4
Fig. 4
Linear regression analysis assessing the association of HAS and HDS, PCS and MCS between groups. This figure presents the results of linear regression analyses investigating the relationships between the Hospital Anxiety Scale (HAS) and the Hospital Depression Scale (HDS), the Mental Component Summary (MCS) and the Physical Component Summary (PCS) between groups. The analyses were conducted separately for (A,C) non-game group and (B,D) game group.
Fig. 5
Fig. 5
Pearson correlation coefficient matrix of various indicators in the game group. This figure shows the results of Pearson correlation analysis between various indicators in the game group, investigating the relationship between gender, age, myopia condition, game duration, sleep duration, Hospital Anxiety and Depression Scale (HADS), Van Dream Anxiety Scale (VDAS), 36-item Short-Form Health Survey (SF-36), Ocular Surface Disease Index (OSDI), Internet Addiction Test (IAT) and Internet Gaming Disorder Scale-20 (IGD-20).
Fig. 6
Fig. 6
Comparative analysis of demographic variations in multifaceted indicators. This figure presents a comprehensive comparison of indicators across different demographic groups, focusing on gender and regional characteristics. The analyses assess the impact of demographic variations on game duration, sleep duration, Hospital Anxiety and Depression Scale (HADS), Van Dream Anxiety Scale (VDAS), 36-item Short-Form Health Survey (SF-36), Ocular Surface Disease Index (OSDI), Internet Addiction Test (IAT) and Internet Gaming Disorder Scale-20 (IGD-20). (A) Comparative analysis of gender variations in multifaceted indicators. (B) Comparative analysis of myopia condition variations in multifaceted indicators. (C) Comparative analysis of region variations in multifaceted indicators. Significant mean differences between groups are symbolized by asterisks. *P < 0.0001.
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