从跨部门的角度分析非自愿入院的风险因素:潜伏类分析
Jona Carlet1, Florian Hotzy1, Anke Maatz1
1Department of Adult Psychiatry and Psychotherapy, Psychiatric University Clinic Zurich and University of Zurich, Switzerland.
International journal of law and psychiatry
|January 24, 2026
概括
具有多重边缘化身份的个人面临非自愿入院 (IA) 的风险更高. 这突显了获得及时和自愿治疗的潜在障碍,需要进一步调查.
科学领域:
- 心理健康服务研究 心理健康服务研究
- 卫生社会学 卫生社会学
- 公共卫生政策 公共卫生政策
背景情况:
- 非自愿入院 (IA) 是一个关键但有争议的精神卫生保健实践,只允许防止伤害.
- 现有的研究往往侧重于个体社会人口统计学因素,可能会忽视复杂的社会身份和健康不平等.
- 交叉性理论认为,重叠的社会身份创造了独特的边缘化经验,影响健康结果.
研究的目的:
- 应用一个跨界框架来识别面临非自愿入境风险较高的社会人口学子组.
- 调查交叉的边缘化身份如何与非自愿入学风险相关.
主要方法:
- 隐性类分析 (LCA) 用于识别不同的社会人口统计学子组.
- 分析了苏黎世精神病学大学诊所 (2017-2020) 的16024例病例数据.
- 社会人口统计学变量包括性别,年龄,国籍,居住地,教育,就业和语言能力,类与IA等临床因素进行验证.
主要成果:
- 确定了四个不同的社会人口统计类别.
- 与非自愿入境最相关的阶级是失业,社会福利依赖,非欧洲公民身份,临时居留/难民身份和低教育程度.
- 相反,拥有瑞士国籍,永久居留权和就业的班级显示,非自愿入学的风险明显较低.
结论:
- 一个交叉的方法显示,多个边缘化身份的个体面临的非自愿入院的风险较高.
- 这些发现表明,弱势群体在获得自愿和早期心理健康护理方面存在潜在障碍.
- 进一步的研究至关重要,以了解和拆除这些障碍,公平的护理.
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