The Finnish Investigative Instrument of Child Sexual Abuse (FICSA) is a computerized tool that uses Bayesian statistics to provide a base rate for an alleged child sexual abuse (CSA), using population-level information about correlates of CSA. FICSA can, thus, assist decision-making in investigations of CSA. Here, we compared forensic experts’ and students’ ability to use FICSA and whether its use affected the estimates of the probability of CSA in mock-scenarios. The use of FICSA was compared to only having access to the empirical information about CSA risk and protective factors, which FICSA is based on, and to unassisted decision-making. The 54 participants analyzed two scenarios of possible CSA and estimated the probability of the CSA allegation being true. The results show that participants using FICSA were prone to make technical mistakes that affect the correctness of the probability estimation. The performance of experts and students was equivalent in all the conditions, with the exception of the group using FICSA, where experts tended to deviate from the probability provided by FICSA more than students. Having only access to empirical information did not improve estimates compared to unassisted decision-making. Both students and experts tended to adjust the estimates provided by FICSA downwards, that is, to decrease the probability of abuse. We conclude that FICSA has the potential to assist investigators to correctly integrate evidence and calculate probabilities but that proper training is required.

When statistically related to child sexual abuse (CSA), background information can assist decision-making in investigations of CSA allegations. Here, we studied the use of such background information among Finnish police officers. We analyzed their ability to identify and interpret CSA-related and -unrelated background information both when placed in mock scenarios and when presented as separate variables. We also measured the ability to correctly estimate the base-rate of CSA allegations being true based on such background information. In the context of mock scenarios, officers were better in discarding CSA-unrelated variables than in identifying CSA-related ones. Within-subject performance across different scenarios was, however, not consistent. When information was presented as separate variables, officers tended to incorrectly consider many CSA-unrelated variables as CSA-related. Officers performed well in recognizing whether CSA-related variables increase or decrease CSA risk. Finally, officers were inaccurate in identifying variables that are CSA-related only for boys or only for girls. When asked to estimate the CSA probability of mock scenarios, participants were accurate only in assessing low-probability cases, and this was not associated with the ability to identify CSA-related and -unrelated variables. We conclude that police officers would benefit from more training in using background information and from using available decision-making support tools in the context of investigating CSA allegations.

Unfounded child sexual abuse (CSA) allegations take investigative resources from real cases and have detrimental consequences for the people involved. The Finnish Investigative Instrument of Child Sexual Abuse (FICSA) supports investigators by estimating the probability of a CSA allegation being true based on the child’s background information. In the current study, we aimed at making FICSA resistant to deception. Two gender-specific questionnaires with FICSA questions and additional “trap” questions were constructed. The trap questions seemed statistically related to CSA but were not. We combined the answers of 278 real victims and 275 16–year-old students, instructed to simulate being CSA victims, to build a Naïve Bayes classifier able to separate the two groups (AUC = 0.91 for boys and AUC = 0.92 for girls). By identifying false allegations early in the investigation, authorities’ resources can be directed towards allegations that are probably true, effectively helping actual CSA victims.