开发和验证护士前月经综合征风险预测模型:基于护士的TARGET队列研究结果
Li Li1,2, Xiaoyan Lv1,2, Yuxin Li3
1Department of Nursing, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Frontiers in public health
|October 19, 2023
概括
这项研究确定了护士患有月经前综合征 (PMS) 的关键风险因素,开发了一个准确的预测模型. 该模型可以帮助识别有风险的个体,以便进行早期干预和改善福祉.
科学领域:
- 妇科健康 妇科健康
- 职业健康 职业健康 职业健康
- 预测建模预测建模
背景情况:
- 月经前综合征 (PMS) 显著影响生育年龄的女性.
- 对于PMS的风险因素仍然不完全理解,特别是在职业队列中.
- 护士面临着独特的压力因素,可能会影响PMS的发展.
研究的目的:
- 在护理人口中识别与PMS相关的风险因素.
- 开发和验证用于评估PMS风险的预测模型.
- 为患有PMS的护士提供早期识别和干预的工具.
主要方法:
- 通过在线调查,对18,645名护士进行了多中心,横截面的研究.
- 收集了月经前综合征量表 (PMSS) 和各种生理,社会,心理,职业和行为变量.
- 逐步多变量逻辑回归和LASSO与10倍交叉验证被用来构建预测模型.
主要成果:
- 孕前综合征的关键预测因素包括茶/咖啡消费,睡眠质量,月经的规律性,经障,工作场所的欺凌,应对方式,焦虑,抑郁和感知到的压力.
- 预测模型表现出强大的歧视力 (AUC 0.765训练,0.769测试).
- 校准曲线证实了模型在预测观察结果方面的高准确性.
结论:
- 一个经过验证的预测模型准确地识别了患PMS风险的护士.
- 这种工具可以促进早期检测和针对护士健康的有针对性的支持.
- 通过积极的PMS管理来改善护士的福祉至关重要.
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