scholarly journals The Police Use of Background Information Related to Alleged Victims in Mock Evaluations of Child Sexual Abuse

2019 ◽  
Vol 35 (4) ◽  
pp. 414-421 ◽  
Author(s):  
Alessandro Tadei ◽  
Pekka Santtila ◽  
Jan Antfolk
Keyword(s):  
Decision Making ◽  
Sexual Abuse ◽  
Child Sexual Abuse ◽  
Police Officers ◽  
Background Information ◽  
Support Tools ◽  
Low Probability ◽  
Individual Variables ◽  
Subject Performance ◽  
Decision Making Support

Abstract 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 CSA-unrelated background information both when placed in mock scenarios and when presented as separate, individual variables. We also measured the ability to correctly estimate the probability of CSA 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 better in recognizing whether actual CSA-related variables increase or decrease the probability of CSA. 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 CSA-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.

scholarly journals The Police Use of Background Information Related to Alleged Victims in Mock Evaluations of Child Sexual Abuse

2019 ◽  
Author(s):  
Alessandro Tadei ◽  
Pekka Santtila ◽  
Jan Antfolk
Keyword(s):  
Decision Making ◽  
Sexual Abuse ◽  
Child Sexual Abuse ◽  
Police Officers ◽  
Base Rate ◽  
Background Information ◽  
Support Tools ◽  
Low Probability ◽  
Subject Performance ◽  
Decision Making Support

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.

Online Child Pornography

2020 ◽  
pp. 226-247
Author(s):  
Giorgia Macilotti
Keyword(s):  
Decision Making ◽  
Sexual Abuse ◽  
Child Sexual Abuse ◽  
Police Officers ◽  
Child Pornography ◽  
Decision Making Process ◽  
Structured Interviews ◽  
Sexually Explicit

This chapter presents some challenges faced by the police in identifying child pornography images. In particular, three main problems will be discussed throughout this chapter. The first lies in deciding whether an image is explicit enough to be considered pornographic. The second issue lies in determining whether the victim is a child or someone who appears to be a child. A final challenge concerns how to deal with sexually explicit images produced by someone who is a child themselves. It will be argued that despite emerging investigative and forensic methods, the decision-making process engaged in by police officers still presents some specific challenges. These aspects will be discussed through an analysis of semi-structured interviews with 23 French police officers and forensic analysts working in departments specialising in policing cybercrime and online child sexual abuse.

scholarly journals Counteracting Deceptive Responding in the Finnish Investigative Instrument of Child Sexual Abuse (FICSA)

2020 ◽  
Author(s):  
Alessandro Tadei ◽  
Juulia Haajanen ◽  
Johan Pensar ◽  
Pekka Santtila ◽  
Jan Antfolk
Keyword(s):  
Sexual Abuse ◽  
Child Sexual Abuse ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Background Information ◽  
Bayes Classifier ◽  
Naïve Bayes Classifier ◽  
False Allegations ◽  
The People ◽  
Gender Specific

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.

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