Chor Ka Ho Brian, McClelland Gary M, Weiner Dana A, Jordan Neil, Lyons John S
Mental Health Services and Policy Program, Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, 710 North Lake Shore Drive, Suite 1200, Chicago, IL 60611, USA.
Child Abuse Negl. 2013 Oct;37(10):871-82. doi: 10.1016/j.chiabu.2013.04.016. Epub 2013 Jun 12.
Out-of-home placement decision-making in child welfare is founded on the best interest of the child in the least restrictive setting. After a child is removed from home, however, little is known about the mechanism of placement decision-making. This study aims to systematically examine the patterns of out-of-home placement decisions made in a state's child welfare system by comparing two models of placement decision-making: a multidisciplinary team decision-making model and a clinically based decision support algorithm. Based on records of 7816 placement decisions representing 6096 children over a 4-year period, hierarchical log-linear modeling characterized concordance or agreement, and discordance or disagreement when comparing the two models and accounting for age-appropriate placement options. Children aged below 16 had an overall concordance rate of 55.7%, most apparent in the least restrictive (20.4%) and the most restrictive placement (18.4%). Older youth showed greater discordant distributions (62.9%). Log-linear analysis confirmed the overall robustness of concordance (odd ratios [ORs] range: 2.9-442.0), though discordance was most evident from small deviations from the decision support algorithm, such as one-level under-placement in group home (OR=5.3) and one-level over-placement in residential treatment center (OR=4.8). Concordance should be further explored using child-level clinical and placement stability outcomes. Discordance might be explained by dynamic factors such as availability of placements, caregiver preferences, or policy changes and could be justified by positive child-level outcomes. Empirical placement decision-making is critical to a child's journey in child welfare and should be continuously improved to effect positive child welfare outcomes.
儿童福利中的家庭外安置决策是基于儿童在限制最少的环境中的最大利益做出的。然而，在儿童被带离家庭后，关于安置决策的机制却知之甚少。本研究旨在通过比较两种安置决策模型：多学科团队决策模型和基于临床的决策支持算法，系统地研究一个州儿童福利系统中家庭外安置决策的模式。基于四年期间代表6096名儿童的7816次安置决策记录，分层对数线性模型刻画了两种模型之间的一致性或一致性，以及不一致性或分歧，并考虑了适合年龄的安置选择。16岁以下儿童的总体一致性率为55.7%，在限制最少的安置（20.4%）和限制最大的安置（18.4%）中最为明显。年龄较大的青少年表现出更大的不一致分布（62.9%）。对数线性分析证实了一致性的总体稳健性（优势比[OR]范围：2.9 - 442.0），尽管不一致性在与决策支持算法的小偏差中最为明显，例如在集体家庭中一级安置不足（OR = 5.3）和在住院治疗中心一级安置过度（OR = 4.8）。应使用儿童层面的临床和安置稳定性结果进一步探讨一致性。不一致性可能由安置的可用性、照顾者偏好或政策变化等动态因素来解释，并可能因积极的儿童层面结果而合理。实证安置决策对于儿童在儿童福利中的历程至关重要，应不断改进以实现积极的儿童福利结果。
