使用机器学习方法预测与健康相关的生活质量差的儿童和青少年
Chang Xiong1, Lili Zhang2, Zhijuan Li1
1The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi, 214023, China.
Health and quality of life outcomes
|August 27, 2025
概括
一个新的名图可以预测年轻人的健康相关生活质量 (HRQoL). 主要因素包括自我伤害,学业疲劳,家长虐待,压力,欺凌,饮食和睡眠, 提供了有价值的预测工具.
科学领域:
- 儿童健康
- 生活质量研究
- 预测模型
背景情况:
- 儿童和青少年的与健康相关的生活质量 (HRQoL) 受许多因素的影响.
- 有限的研究已经探索了HRQoL的多维预测因素,包括个体特征,健康风险行为和负面生活事件.
研究的目的:
- 开发一个用于预测儿童和青少年HRQoL的指数表.
- 确定该人群中HRQoL的重要多维因素.
主要方法:
- 研究人员对12145名儿童和青少年进行了调查.
- 后勤回归,拉索回归和随机森林模型确定了关键预测因素.
- 使用多变量逻辑回归构建了一个名图,并进行了内部验证.
主要成果:
- HRQoL的重要预测因素包括非自杀性自伤,学术倦怠,父母虐待,压力,欺凌受害者,健康饮食和睡眠.
- 诺米图显示出良好的预测准确性,曲线下的面积 (AUC) 为0. 765 (训练) 和0. 775 (验证).
- 决策曲线分析表明,该名录具有良好的临床效用.
结论:
- 一种新型的诺米图模型有效地预测儿童和青少年的HRQoL.
- 这个工具可以作为医疗保健专业人员和研究人员的宝贵参考.
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