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Developing and Validating a Predictive Risk Model for Youth Placement in Residential Care to Support Decision-Making under the Family First Prevention Services Act
Residential Treatment for Children & Youth Pub Date : 2022-08-17 , DOI: 10.1080/0886571x.2022.2111018
Ka Ho Brian Chor 1 , Richard A. Epstein 2 , Zhidi Luo 2
Affiliation  

ABSTRACT

Under the Family First Prevention Services Act, federal Title IV-E claiming requirements for youth who are placed in Qualified Residential Treatment Programs (QRTPs) are more stringent than previous criteria for residential care. Independent Qualified Individuals are required to assess the appropriateness of QRTP placements and judicial reviews must formally approve these placements. Child welfare agencies can use administrative data and empirical methods to adapt to these changes from a prevention standpoint. The current study detailed an approach for developing and validating a Cox proportional-hazards model predicting time-to-first placement in residential care among 43,770 legal spells for youth under the care of one large Midwest child welfare agency. Internal validation using 200 bootstrap resamples yielded stable predictors consistent with those in the literature, strong discriminative ability, and high prediction accuracy. External validation applied the model to examine the risk of residential care placement in the first 90 days of youth’s legal spells. This proactive risk prediction encapsulates a preventive approach preceding the 90-day timeline of QRTP assessment and court review. Results suggest that robust prediction of existing practice of residential care placement has the potential to inform caseworker-level service and placement planning, and build system-level capacity for residential and community-based care.



中文翻译:

开发和验证青少年安置护理的预测风险模型,以支持《家庭优先预防服务法》下的决策

摘要

根据《家庭优先预防服务法》,联邦第四章 E 款对被安置在合格寄宿治疗计划 (QRTP) 中的青少年的索赔要求比以前的寄宿护理标准更为严格。独立的合格个人需要评估 QRTP 安置的适当性,并且司法审查必须正式批准这些安置。儿童福利机构可以利用行政数据和经验方法从预防的角度来适应这些变化。当前的研究详细介绍了一种开发和验证 Cox 比例风险模型的方法,该模型预测中西部一家大型儿童福利机构照顾的 43,770 名青少年的首次寄宿护理时间。使用200次bootstrap重采样进行内部验证,得到了与文献一致的稳定预测值,判别能力强,预测精度高。外部验证应用该模型来检查青少年在法定期限的前 90 天内接受寄宿护理安置的风险。这种主动风险预测概括了在 QRTP 评估和法庭审查的 90 天时间表之前的预防方法。结果表明,对现有寄宿护理安置实践的稳健预测有可能为个案工作者级别的服务和安置规划提供信息,并建立寄宿和社区护理的系统级能力。外部验证应用该模型来检查青少年在法定期限的前 90 天内接受寄宿护理安置的风险。这种主动风险预测概括了在 QRTP 评估和法庭审查的 90 天时间表之前的预防方法。结果表明,对现有寄宿护理安置实践的稳健预测有可能为个案工作者级别的服务和安置规划提供信息,并建立寄宿和社区护理的系统级能力。外部验证应用该模型来检查青少年在法定期限的前 90 天内接受寄宿护理安置的风险。这种主动风险预测概括了在 QRTP 评估和法庭审查的 90 天时间表之前的预防方法。结果表明,对现有寄宿护理安置实践的稳健预测有可能为个案工作者级别的服务和安置规划提供信息,并建立寄宿和社区护理的系统级能力。

更新日期:2022-08-17
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