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The Center on Causal Data Science for Child Maltreatment Prevention (the CHAMP Center)

The Center on Causal Data Science for Child Maltreatment Prevention (the CHAMP Center)
儿童虐待预防因果数据科学中心(CHAMP 中心)
批准号:
10672629
负责人:
GLENN N SAXE
金额:
$153.93万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-05 至 2028-08-31

项目摘要

项目成果

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中文摘要
翻译
总结/摘要-总体 2019年,美国州和县儿童保护调查人员确定,有65.6万名儿童暴露于 虐待他们的照顾者。这一数字可能低估了受虐待儿童的真实人数, 相当大的差距。虐待暴露会破坏儿童的心理生物学系统, 健康和适应功能,并导致衰弱的结果,如创伤后应激,抑郁, 自我毁灭和暴力行为,冒险和滥用药物。但只有一小部分人 处于危险中的儿童受益于数十年的研究,以获得科学知识, 虐待风险及其严重后果。该提案旨在使更大规模的 通过一项旨在解决限制人口增长的中心障碍的综合科学计划, 结果规模:现有的预防性干预措施没有得到强有力的科学指导 了解虐待风险的复杂病因及其后果。 儿童和青少年虐待预防因果数据科学中心(CHAMP中心) 建议通过以下方式实现更大规模的结果:1)应用最先进的因果数据科学 方法,以几个大的,相关的,现有的数据集,以确定复杂的病因, 虐待暴露的类别(例如,性虐待、身体虐待、忽视)和与虐待有关的 结果(例如,创伤后应激障碍,抑郁,自我毁灭行为,药物滥用, 功能障碍); 2)将这些知识转化为具体的决策支持工具, 儿童服务系统,以个性化的干预措施,精确针对病因因素;和3)进行 对这种形式的决策支持进行概念验证的实地试验。通过其两个项目的综合工作, CHAMP中心将建立发现和转化科学知识的流程, 虐待及其后果的复杂病因,并传播知识和工具, 预防虐待暴露及其对高危儿童造成的毁灭性后果。
英文摘要
SUMMARY/ABSTRACT – OVERALL In 2019, US state and county child protection investigators determined that 656,000 children were exposed to maltreatment by their caregivers. This number likely underestimates the true number of maltreated children by a considerable margin. Maltreatment exposure can disrupt psychobiological systems essential for a child’s health and adaptive functioning and result in debilitating outcomes such as post-traumatic stress, depression, self-destructive and violent behavior, risk-taking, and substance abuse. Yet only a small proportion of those children at risk have benefited from decades of research to acquire the scientific knowledge to prevent maltreatment exposures and their significant consequences. This proposal seeks to enable larger-scale preventative results through an integrated scientific program designed to address the central barrier limiting the scale of results: available preventative interventions are insufficiently guided by robust scientific knowledge on the complex etiologies of maltreatment exposures and their consequential outcomes. The Center on Causal Data Science for Child and Adolescent Maltreatment Prevention (CHAMP Center) is proposed to enable the achievement of larger-scale results by: 1) applying state-of-the-art causal data science methods to several large, relevant, existing data sets to determine the complex etiologies for several categories of maltreatment exposures (e.g., sexual abuse, physical abuse, neglect) and maltreatment-related outcomes (e.g., post-traumatic stress disorder, depression, self-destructive behavior, substance abuse, functional impairments); 2) translating this knowledge into specific decision support tools for practitioners in the child services system to personalize interventions that precisely target etiological factors; and 3) conducting a proof-of-concept field trial on this form of decision support. Through the integrated work of its two projects and three cores, the CHAMP Center will establish processes to discover and translate scientific knowledge on complex etiologies of maltreatment and its consequences and disseminate knowledge and tools for large-scale prevention of maltreatment exposures and their devastating consequences in children at risk.
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Administrative Core
Computational Models for the Prediction and Prevention of Child Traumatic Stress - Resubmission - 1
Computational Models for the Prediction and Prevention of Child Traumatic Stress - Resubmission - 1
Computational Models for the Prediction and Prevention of Child Traumatic Stress - Resubmission - 1
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