The usability and effectiveness of the Finnish investigative instrument of child sexual abuse in mock evaluations

Alessandro Tadei, P Santtila, Jan Antfolk

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Abstract

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. Using mock-scenarios, we compared the ability of forensic experts who evaluate CSA allegations using traditional methods and students to use FICSA and how FICSA affected their estimated probabilities of CSA being true. The use of FICSA was compared to only having access to the empirical information about CSA risk and protective factors FICSA is based on, as well as to unassisted decision-making. Fifty-four participants analyzed two scenarios of possible CSA and estimated the probability of the allegation being true. The results showed that participants using FICSA were prone to make technical mistakes that affected the correctness of the probability produced. Both students and experts tended to adjust the estimates provided by FICSA downwards, that is, to decrease the probability of abuse. The performance of experts and students was similar in all conditions, but in the group using FICSA experts deviated more than students from the probability provided by FICSA. Having only access to empirical information did not improve estimates compared to unassisted decision-making. We conclude that FICSA has the potential to assist investigators to correctly integrate evidence and calculate probabilities, but that proper training is required.
Original languageEnglish
Pages (from-to)127-145
JournalNordic Psychology
Volume72
Issue number2
DOIs
Publication statusPublished - 2019
MoE publication typeA1 Journal article-refereed

Keywords

  • FICSA
  • forensic psychology
  • Bayesian statistics

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