A Bayesian Decision-Support Tool for Child Sexual Abuse Assessment and Investigation

A1 Journal article (refereed)

Internal Authors/Editors

Publication Details

List of Authors: Alessandro Tadei, Johan Pensar, Jukka Corander, Katarina Finnilä, Pekka Santtila, Jan Antfolk
Publisher: Sage Publications
Publication year: 2017
Journal: Sexual Abuse
Journal acronym: SAJRT
eISSN: 1573-286X


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.


Bayesian logic, child sexual abuse, child sexual abuse investigations, Decision making, multimodal assessment

Last updated on 2020-04-06 at 03:51