1 Åbo Akademi University, Turku, Finland.
2 University of Helsinki, Finland.
Sex Abuse. 2019 Jun;31(4):374-396. doi: 10.1177/1079063217732791. Epub 2017 Sep 21.
In assessments of child sexual abuse (CSA) allegations, informative background information is often overlooked or not used properly. We therefore created and tested an instrument that uses accessible background information to calculate the probability of a child being a CSA victim that can be used as a starting point in the following investigation. Studying 903 demographic and socioeconomic variables from over 11,000 Finnish children, we identified 42 features related to CSA. Using Bayesian logic to calculate the probability of abuse, our instrument-the Finnish Investigative Instrument of Child Sexual Abuse (FICSA)-has two separate profiles for boys and girls. A cross-validation procedure suggested excellent diagnostic utility (area under the curve [AUC] = 0.97 for boys and AUC = 0.88 for girls). We conclude that the presented method can be useful in forensic assessments of CSA allegations by adding a reliable statistical approach to considering background information, and to support clinical decision making and guide investigative efforts.
在儿童性虐待（CSA）指控的评估中，有价值的背景信息经常被忽视或没有得到妥善利用。因此，我们创建并测试了一种利用可获取的背景信息来计算儿童成为 CSA 受害者的可能性的工具，该工具可作为后续调查的起点。我们研究了来自 11000 多名芬兰儿童的 903 个人口统计学和社会经济学变量，确定了 42 个与 CSA 相关的特征。我们的工具——芬兰儿童性虐待调查工具（FICSA）——使用贝叶斯逻辑计算虐待的概率，针对男孩和女孩有两个独立的档案。交叉验证程序表明其具有出色的诊断效用（男孩的曲线下面积 [AUC] = 0.97，女孩的 AUC = 0.88）。我们得出结论，通过将可靠的统计方法应用于考虑背景信息，并支持临床决策制定和指导调查工作，该方法可用于 CSA 指控的法医评估。
