Investigating the mechanisms of internet gaming disorder and developing intelligent monitoring models using artificial intelligence technologies: protocol of a prospective cohort

Huang, Yeen1; Wu, Ruipeng2,3; Huang, Yuanyuan4; Xiang, Yingping5; Zhou, Wei5

2024-09-18

10.1186/s12889-024-20028-4

BMC PUBLIC HEALTH   影响因子和分区

1471-2458

Background Internet gaming disorder (IGD), recognized by the World Health Organization (WHO), significantly impacts adolescent mental and physical health. With a global prevalence of 3.05%, rates are higher in Asia, especially among adolescents and males. The COVID-19 pandemic has exacerbated IGD due to increased gaming time from isolation and anxiety. Vulnerable groups include adolescents with poor academic performance, introverted personalities, and comorbid mental disorders. IGD mechanisms remain unclear, lacking prospective research. Based on Skinner's reinforcement theory, the purpose of this study is to explore the mechanisms of IGD from individual and environmental perspectives, incorporating age-related changes and game features, and to develop intelligent monitoring models for early intervention in high-risk adolescents. Methods This prospective cohort study will investigate IGD mechanisms in middle and high school students in Shenzhen, China. Data will be collected via online surveys and Python-based web scraping, with a 3-year follow-up and assessments every 6 months. Unstructured data obtained through Python-based web scraping will be structured using natural language processing techniques. Collected data will include personal characteristics, gaming usage, academic experiences, and psycho-behavioral-social factors. Baseline data will train and test predictive models, while follow-up data will validate them. Data preprocessing, normalization, and analysis will be performed. Predictive models, including Cox proportional hazards and Weibull regression, will be evaluated through cross-validation, confusion matrix, receiver operating characteristic (ROC) curve, area under the curve (AUC), and root mean square error (RMSE). Discussion The study aims to understand the interplay between individual and environmental factors in IGD, incorporating age-related changes and game features. Active monitoring and early intervention are critical for preventing IGD. Despite limitations in geographic scope and biological data collection, the study's innovative design and methodologies offer valuable contributions to public health, promoting effective interventions for high-risk individuals.

Internet Game Mechanisms Monitoring models Artificial intelligence Prospective cohort

SCI

英语

第一 ; 通讯

Public, Environmental & Occupational Health

Public, Environmental & Occupational Health

WOS:001315757300011

BMC

Web of Science

1.Southern Univ Sci & Technol, Sch Publ Hlth & Emergency Management, Shenzhen, Peoples R China
2.Xizang Minzu Univ, Sch Med, Xianyang, Peoples R China
3.Southeast Univ, Sch Publ Hlth, Nanjing, Peoples R China
4.Shenzhen Ctr Dis Control & Prevent, Div Immunizat Planning, Shenzhen, Peoples R China
5.Shenzhen Prevent & Treatment Ctr Occupat Dis, Occupat Hazard Assessment Inst, Shenzhen, Peoples R China

Huang, Yeen,Wu, Ruipeng,Huang, Yuanyuan,et al. Investigating the mechanisms of internet gaming disorder and developing intelligent monitoring models using artificial intelligence technologies: protocol of a prospective cohort[J]. BMC PUBLIC HEALTH,2024,24(1).

Huang, Yeen,Wu, Ruipeng,Huang, Yuanyuan,Xiang, Yingping,&Zhou, Wei.(2024).Investigating the mechanisms of internet gaming disorder and developing intelligent monitoring models using artificial intelligence technologies: protocol of a prospective cohort.BMC PUBLIC HEALTH,24(1).

Huang, Yeen,et al."Investigating the mechanisms of internet gaming disorder and developing intelligent monitoring models using artificial intelligence technologies: protocol of a prospective cohort".BMC PUBLIC HEALTH 24.1(2024).