韩国青少年对智能手机的过度依赖:对概念上信息化的AI/ML建模的位置分层评估
Andrew H Kim1, Uibin Lee2, Yohan Cho3
1School of Social Work, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA.
International journal of environmental research and public health
|October 29, 2025
概括
这项研究开发了一种人工智能驱动的查工具,以检测韩国青少年对智能手机过度依赖. 该工具提供针对性的公共卫生见解和政策建议,以应对使用的区域差异.
科学领域:
- 公共卫生 公共卫生
- 人工智能的人工智能
- 青少年心理学 青少年心理学
背景情况:
- 近40%的韩国青少年表现出智能手机过度依赖,这是一个重大的公共卫生问题.
- 使用模式和相关风险在不同的区域背景下有很大差异.
- 现有的监测工具缺乏准确性来解决这个问题的细微,心理上知情的性质.
研究的目的:
- 开发一种高性能,低风险的查工具,用于使用AI/ML监测青少年对智能手机过度依赖.
- 探索与智能手机过度依赖相关的有意义的心理构造.
- 为公共卫生干预提供基于地方的政策建议.
主要方法:
- 利用了1873名韩国青少年 (2023年智能手机过度依赖调查) 的数据.
- 使用嵌套建模方法与概念上知情的AI/ML模型,从131.1.中选择了59个特征.
- 进行了地方分层分析,以检查区域差异.
主要成果:
- 开发了一种具有强大预测准确度 (AUC = 81.5%) 的选工具,确定智能手机使用案例为关键贡献者.
- 构建特定模型强调了数字能力,风险感知和后果的重要性 (AUC范围:80.6-89.1%).
- 显示了模型性能 (AUC范围:71.4-91.1%) 和当地特征重要性的实质性区域差异.
结论:
- 将概念框架与AI/ML集成,可以有效地检测青少年对智能手机的过度依赖.
- 这项研究提供了新的方法来监测疾病负担,并推进构造层面的洞察力.
- 这些发现支持针对韩国的针对性,基于地点的公共卫生政策建议.
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