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Capturing Intervention Effects Over Time: Reanalysis of a Critical Time Intervention for Homeless Mentally Ill Men

机译:随时间推移获取干预效果:对无家可归的精神病患者的关键时间干预的重新分析

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摘要

Objectives. We analyzed whether a method for identifying latent trajectories—latent class growth analysis (LCGA)—was useful for understanding outcomes for individuals subject to an intervention.Methods. We used LCGA to reanalyze data from a published study of mentally ill homeless men in a critical time intervention (CTI) program. In that study, 96 men leaving a shelter’s onsite psychiatric program were randomly assigned to experimental and control groups. The former received CTI services and the latter usual services. Each individual’s housing circumstances were observed for 18 months after program initiation. Our outcome measure was monthly homelessness: a person was considered homeless in a month if he was homeless for even 1 night that month.Results. Four latent classes were found among the control group, but just 3 among the experimental group. Control, but not experimental, group individuals showed a small class of chronically homeless men. The size of the never-homeless class was 19 percentage points larger for the experimental than for the control group. J- and inverted-U-shaped patterns were also found among both groups, but with important differences in timing of patterns.Conclusions. Our results reveal effects not apparent in the original analysis, suggesting that latent class growth models improve intervention evaluation.
机译:目标。我们分析了一种识别潜在轨迹的方法(潜在类增长分析(LCGA))是否有助于理解受干预个体的结局。我们使用LCGA重新分析了危重时间干预(CTI)计划中一项有关精神病无家可归者的已发表研究的数据。在该研究中,将离开收容所现场精神病学计划的96名男性随机分配到实验组和对照组。前者获得CTI服务,后者获得常规服务。在计划启动后的18个月内,观察每个人的住房状况。我们的结局指标是每月无家可归:如果一个人在当月甚至一个晚上都无家可归,则该人在一个月内被视为无家可归。对照组中发现了四个潜在类别,而实验组中只有三个潜在类别。对照组(但不是实验组)显示了一小类长期无家可归的男人。实验组的无家可归者人数比对照组大19个百分点。两组之间也发现了J型和倒U形图案,但是图案的时间差异很大。我们的结果揭示了在原始分析中不明显的影响,表明潜在的阶级增长模型可以改善干预评估。

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