University of Michigan, School of Social Work, 1080 S. University Avenue, Ann Arbor, MI 48109, United States of America.
Wayne State University, School of Social Work, 5447 Woodward Avenue, Detroit, MI 48202, United States of America.
Child Abuse Negl. 2022 Sep;131:105688. doi: 10.1016/j.chiabu.2022.105688. Epub 2022 Jun 7.
The public health significance of the opioid epidemic is well-established. However, few states collect data on opioid problems among families involved in child welfare services. The absence of data creates significant barriers to understanding the impact of opioids on the service system and the needs of families being served.
This study sought to validate binary and count-based indicators of opioid-related maltreatment risk based on mentions of opioid use in written child welfare summaries.
We developed a comprehensive list of terms referring to opioid street drugs and pharmaceuticals. This terminology list was used to scan and flag investigator summaries from an extensive collection of investigations (N = 362,754) obtained from a state-based child welfare system in the United States. Associations between mentions of opioid use and investigators' decisions to substantiate maltreatment and remove a child from home were tested within a framework of a priori hypotheses.
Approximately 6.3% of all investigations contained one or more opioid use mentions. Opioid mentions exhibited practically signficant associations with investigator decisions. One in ten summaries that were substantiated had an opioid mention. One in five investigations that led to the out-of-home placement of a child contained an opioid mention.
This study demonstrates the feasibility of using simple text mining procedures to extract information from unstructured text documents. These methods provide novel opportunities to build insights into opioid-related problems among families involved in a child welfare system when structured data are not available.
阿片类药物泛滥对公共健康的影响已得到充分证实。然而，很少有州收集涉及儿童福利服务家庭的阿片类药物问题数据。由于缺乏数据，人们难以了解阿片类药物对服务系统的影响以及接受服务的家庭的需求。
本研究旨在验证基于提及阿片类药物使用的二进制和计数型阿片类相关虐待风险指标，这些提及出现在儿童福利摘要中。
我们开发了一个全面的术语列表，用于指代阿片类街头毒品和药物。该术语列表用于扫描和标记来自美国一个州的儿童福利系统中广泛收集的调查（N=362754）中的调查员摘要。在预先设定的假设框架内，检验了提及阿片类药物使用与调查员决定证实虐待行为和将儿童从家中带走之间的关联。
大约 6.3%的调查包含一个或多个阿片类药物使用提及。阿片类药物的提及与调查员的决策具有实际显著的关联。在被证实的摘要中，每十份中有一份提及阿片类药物。在导致儿童离家安置的调查中，每五份中有一份提及阿片类药物。
本研究证明了使用简单的文本挖掘程序从非结构化文本文件中提取信息的可行性。当没有结构化数据时，这些方法为深入了解参与儿童福利系统的家庭中的阿片类相关问题提供了新的机会。
