在自我报告和健康行政数据中识别情绪障碍
Irène Dohouin1,2, Maude Laberge3,4,5, Anaïs Lacasse6
1School of public health, University of Montreal, Montreal, Quebec, Canada.
Brain and behavior
|November 7, 2024
概括
情绪障碍 (MD) 的患病率在调查和健康数据之间存在差异,重叠程度较低. 每个数据源都捕捉到不同的患者群体,需要仔细解释研究结果.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
背景情况:
- 准确识别患有情绪障碍 (MDs) 的人对于了解患病率至关重要.
- 通过比较卫生行政数据和基于人口的调查,可以发现不一致性和方法限制.
研究的目的:
- 通过结合数据源来估计情绪障碍的流行率.
- 评估调查和行政数据之间的情绪障碍模式的一致性.
- 在数据源之间调查个体特征的差异.
主要方法:
- 利用护理轨迹丰富数据 (TorSaDE) 队列,将加拿大社区健康调查 (CCHS) 波与北克卫生行政数据合并.
- 包括CCHS参与和最近使用医疗服务的个人.
- 基于自报与行政数据中的MD存在/不存在的四个组的比较特征.
主要成果:
- 在96,079人的队列中,整体MD患病率为10.8%.
- 自我报告的患病率为6.03%,而行政数据显示为7.79%.
- 数据来源之间的一致性较低 (27.4%);只在一个来源中识别的个人表现出不同的社会经济和健康状况.
结论:
- 每个数据源都识别出具有情绪障碍的独特亚群.
- 来自个别来源的流行率估计应谨慎解释,因为种群捕获不同.
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