[基于LASSO回归分析的大学生非-自杀自我-伤害行为的风险预测模型]
Shijiao Tang1, Chuhan Yan2, Chenxi Lin2
1Department of Maternal and Child Health, Xiangya School of Public Health, Central South University, Changsha 410013, China. 726414590@qq.com.
概括
使用LASSO回归的预测模型确定了大学生非自杀自伤 (NSSI) 的关键风险因素. 该工具有助于早期识别和干预NSSI风险的学生.
科学领域:
- 精神病学和心理健康 精神病学和心理健康
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 非自杀性自伤 (NSSI) 是大学生日益关注的公共卫生问题.
- 有效的早期识别工具对于干预至关重要.
研究的目的:
- 在大学生中开发NSSI的预测模型.
- 使用LASSO回归分析来识别重要的预测因素.
主要方法:
- 在6个省份的4121名大学生中进行了在线问卷调查.
- 收集了社会人口统计数据,并使用了NSSI,抑郁,愤怒,暴力,创伤和精神经历的验证尺度.
- 应用LASSO回归来识别预测因素并构建一个预测模型,通过校准和ROC曲线进行验证.
主要成果:
- 该研究发现参与者中NSSI的患病率为15.8%.
- 拉索回归确定了五个关键预测因素:童年欺凌,酒精使用史,抑郁症状,愤怒反和精神病类经历.
- 预测模型的AUC为0.782 (训练) 和0.769 (测试),这表明预测准确度很好.
结论:
- 在大学生中使用LASSO回归开发了一个强大的NSSI预测模型.
- 该模型通过名图可视化,可以有效评估NSSI风险.
- 这个工具可以帮助临床医生和教育工作者识别有风险的学生,以便及时进行干预.
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