通过潜在的个人资料分析来描述患有严重COVID焦虑的人群的子组
Jacob D King1, Aisling McQuaid1, Verity C Leeson1
1Division of Psychiatry, Imperial College London, United Kingdom.
Journal of affective disorders
|October 12, 2023
概括
严重的COVID焦虑影响着各种各样的个人,与与人口统计和行为相关的不同精神病理模式. 识别子组可以改善临床评估和对这一复杂的心理健康挑战的支持.
科学领域:
- 心理学 心理学 心理学
- 公共卫生 公共卫生
- 心理健康研究 心理健康研究
背景情况:
- 严重的COVID焦虑源于压倒性的大流行体验,导致有害的行为.
- 这种焦虑是一种复杂的心理社会现象,受人口和社会因素的影响.
- 确定子组对于有针对性的临床评估和支持至关重要.
研究的目的:
- 为了确定在人口中经历严重COVID焦虑的不同小组.
- 探索已识别的子组与人口/社会因素之间的关联.
- 了解这些子组与日常功能,生活质量和保护行为之间的关系.
主要方法:
- 隐性个人资料分析被用来探索抑郁症,焦虑症,强迫症,个性和酒精使用的测量工具.
- 从英国284名患有严重COVID焦虑的个人收集了数据.
- 进一步的分析检查了与人口,社会和行为因素的关联.
主要成果:
- 一个4类模型提供了最好的合适,揭示了不同的精神病理模式.
- 这些模式与人口统计因素和COVID相关行为有着可变的关联.
- 这项研究强调了严重COVID焦虑的个体之间的异质性.
结论:
- 严重的COVID焦虑是异质的,特定的健康行为和人口统计数据与糟糕的心理健康有关.
- 通过具体干预来针对健康行为可能是一个有益的方法.
- 需要进一步的研究来了解长期和流行病特有的影响.
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