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构建具有代表性样本以调查加利福尼亚州无家可归人口的新方法:加利福尼亚州全州无家可归者研究

Novel methods to construct a representative sample for surveying California's unhoused population: the California Statewide Study of People Experiencing Homelessness.

作者信息

Wesson Paul, Graham-Squire Dave, Perry Eve, Assaf Ryan D, Kushel Margot

机构信息

Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States.

Benioff Homeless and Housing Initiative, University of California, San Francisco, San Francisco, CA, United States.

出版信息

Am J Epidemiol. 2025 May 7;194(5):1238-1248. doi: 10.1093/aje/kwae323.

Abstract

Existing literature on people experiencing homelessness (PEH) draws on nonrepresentative samples from service providers, populations with comorbidities, or areas with disproportionately high amounts of sheltered homelessness, leading to bias. Nearly one-third of PEH in the United States and more than half of unsheltered PEH live in California. We designed a rigorous state-representative survey of PEH to investigate the antecedents of homelessness, understand health, and inform policy solutions. The multistage design randomized at 3 levels: county, venue, and individual. Stratifying the state into 8 regions, we sampled 1 county per region to reflect statewide demographics. Within counties, sampled venues matched the expected proportion of sheltered and unsheltered residents. Within venues, interviewers randomly sampled individuals. We adjusted for nonresponse and incorporated poststratification to benchmarks. In parallel, respondent-driven sampling reached subpopulations through social networks who may otherwise have been undersampled. Our community-engaged study yielded 3200 quantitative surveys. We purposively sampled 365 participants for qualitative interviews. Demographic estimates match those found in the PIT with the added strength of statistical inference. To our knowledge, this is the first large representative study of PEH, beyond a single county, to draw inference on a large population that did not depend on service utilization. Our methods may inform future efforts to understand homelessness.

摘要

现有关于无家可归者的文献采用的是来自服务提供者、患有合并症人群或庇护性无家可归现象比例过高地区的非代表性样本,这会导致偏差。美国近三分之一的无家可归者以及超过一半的无庇护无家可归者生活在加利福尼亚州。我们设计了一项针对无家可归者的严格的全州代表性调查,以调查无家可归的成因、了解健康状况并为政策解决方案提供依据。多阶段设计在三个层面进行随机抽样:县、场所和个人。我们将该州划分为8个区域,每个区域抽取1个县以反映全州的人口特征。在各县内,抽样的场所与有庇护和无庇护居民的预期比例相匹配。在场所内,访谈员随机抽取个人。我们对无回应情况进行了调整,并纳入了后分层以达到基准。同时,通过受访者驱动抽样,通过社交网络接触到那些可能在其他情况下抽样不足的亚人群体。我们的社区参与研究获得了3200份定量调查问卷。我们有目的地抽取了365名参与者进行定性访谈。人口统计学估计与即时点数统计中的结果相符,并具有统计推断的额外优势。据我们所知,这是第一项超出单个县范围、对大量人群进行推断且不依赖服务利用情况的关于无家可归者的大型代表性研究。我们的方法可能为未来理解无家可归现象的努力提供参考。

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