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Purpose: The present study compared the performance of a Large Language Model (LLM; ChatGPT) and human interviewers in interviewing children about a mock-event they witnessed. Methods: Children aged 6-8 (N = 78) were randomly assigned to the LLM (n = 40) or the human interviewer condition (n = 38). In the experiment, the children were asked to watch a video filmed by the researchers that depicted behavior including elements that could be misinterpreted as abusive in other contexts, and then answer questions posed by either an LLM (presented by a human researcher) or a human interviewer. Results: Irrespective of condition, recommended (vs. not recommended) questions elicited more correct information. The LLM posed fewer questions overall, but no difference in the proportion of the questions recommended by the literature. There were no differences between the LLM and human interviewers in unique correct information elicited but questions posed by LLM (vs. humans) elicited more unique correct information per question. LLM (vs. humans) also elicited less false information overall, but there was no difference in false information elicited per question. Conclusions: The findings show that the LLM was competent in formulating questions that adhere to best practice guidelines while human interviewers asked more questions following up on the child responses in trying to find out what the children had witnessed. The results indicate LLMs could possibly be used to support child investigative interviewers. However, substantial further investigation is warranted to ascertain the utility of LLMs in more realistic investigative interview settings. [ABSTRACT FROM AUTHOR]

We developed a serious game with avatars driven by empirically-based algorithms of suspect behavior to train participants in using the Evidence Framing Matrix (EFM), a component of the SUE technique. Ninety-six participants were allocated into four groups (i.e. Control, Training, Feedback, and Training & Feedback) for two interviews. EFM-trained participants used the EFM more than untrained participants in the first interview. Receiving feedback improved EFM use in the second interview. Theoretical training plus feedback made participants use within-statement (in)consistencies more to evaluate avatar statements. The results suggested the potential for using algorithm-driven suspect avatars in investigative interview training. [ABSTRACT FROM AUTHOR]

The present research compared geographic profiling (GP) methods, including spatial distribution strategies (SDS) and probability distance strategies (PDS), to account for the effect of the number of crimes on the accuracy of GP. Comparing the accuracy of GP methods among three burglar groups (a total of 333 offenders) with different sizes of crimes (1–5, 6–15 and 16 or more) committed before arrest showed that the accuracy decreased in a group with a larger size of crime. Comparing the accuracy of GP methods among the number of crimes (3–10) using 150 offenders who committed 10 or more crimes showed a slight improvement in the accuracy with the increasing number of crimes. In addition, the PDS (vs. SDS) showed a higher accuracy with the increasing number of crimes. The findings encourage practitioners to use the PDS and research implications are discussed. [ABSTRACT FROM AUTHOR]

Simulated avatar interview training has been proven to be effective in improving child sexual abuse interview quality. However, the topic of perceived realism of the avatars and whether they cause emotional reactions has not been previously investigated. Such reactions could affect both learning from the interview simulations as well as how actual interviews are conducted. We wanted to understand whether participants perceive allegedly sexually abused child avatars as realistic and how they emotionally respond to avatars revealing they were actually abused vs. not-abused. Psychology students and recent graduates (N = 30, Mage = 27.9 years) watched eight avatars (four boys, four girls, four with a CSA and four with a no-CSA scenario) providing a series of details about what had happened. Before and after observing each avatar, the participants' emotional reactions and perceived realness of the avatars were measured. Also, during each observation, the participant's facial expressions were recorded. The participants self-reported more negative (anger, sadness, disgust) and more positive (relief) emotions to confirmed CSA and disconfirmed CSA scenarios, respectively, while results for facially expressed emotions were less clear. Higher general emotionality related to CSA and higher perceived realness of the avatars made the differences generally stronger. [ABSTRACT FROM AUTHOR]

Previous research has shown that simulation training using avatars with repeated feedback improves child sexual abuse interview quality. The present study added a hypothesis-testing intervention and examined if the combination of two interventions, feedback and hypothesis-testing, would improve interview quality compared to no intervention and to either intervention alone. Eighty-one Chinese university students were randomly assigned to a control, feedback, hypothesis-testing, or the combination of feedback and hypothesis-testing group and conducted five simulated child sexual abuse interviews online. Depending on the assigned group, feedback on the outcome of the cases and question types used in the interview were provided after each interview, and/or the participants built hypotheses based on preliminary case information before each interview. The combined interventions group and feedback group showed a higher proportion of recommended questions and correct details from the 3rd interview onward compared to the hypothesis-building and control groups. The difference between the number of correct conclusions was not significant. hypothesis-testing alone exacerbated the use of non-recommended questions over time. The results show that hypothesis-testing may impact question types used negatively but not when combined with feedback. The potential reasons for hypothesis-testing alone not being effective and the differences between the present and previous studies were discussed. [ABSTRACT FROM AUTHOR]

Introduction: In forensic settings interviewers are advised to ask as many open-ended questions as possible. However, even experts may have difficulty following this advice potentially negatively impacting an investigation. Here, we sought to investigate how emotions and psychophysiological parameters are associated with question formulation in real time in an ongoing (simulated) child sexual abuse (CSA) interview. Method: In a experimental study, psychology students (N = 60, Mage = 22.75) conducted two interviews with child avatars, while their emotions (anger, sadness, disgust, surprise and relief), GSR and heart rate (HR) were registered. Results: First, we found that general emotionality related to CSA and perceived realness of the avatars was associated with stronger overall emotional reactions. Second, we found that closed (vs. open) questions were preceded by more facially observable anger, but not disgust, sadness, surprise or relief. Third, closed (vs. open) questions were preceded by higher GSR resistance and lower heart rate. Discussion: Results suggest for the first time that emotions and psychophysiological states can drive confirmation bias in question formulation in real time in CSA. [ABSTRACT FROM AUTHOR]

Purpose: Research has shown that confirmation bias plays a role in legal and forensic decision‐making processes and, more specifically, child interviews. However, previous studies often examine confirmation bias in child interviews using non‐abuse‐related events. We enrich the literature by examining interviewers' behaviours in simulated child sexual abuse (CSA) cases. Method: In the present study, we used data from a series of experiments in which participants interviewed child avatars to examine how an assumption of abuse based on preliminary information influenced decision‐making and interviewing style. Interview training data (Ninterview = 2084) from eight studies with students, psychologists and police officers (N = 377) were included in the analyses. Results: We found that interviewers' preliminary assumption of sexual abuse having taken place predicted 1) a conclusion of abuse by the interviewers after the interview; 2) higher confidence in their judgement; 3) more frequent use of not recommended question types and 4) a decreased likelihood of reaching a correct conclusion given the same number of available relevant details. Conclusion: The importance of considering how preliminary assumptions of abuse affect interview behaviour and outcomes and the implications for the training of investigative interviewers were discussed. [ABSTRACT FROM AUTHOR]

Although previous research has confirmed the effectiveness of simulated child sexual abuse interviews with feedback, its validation is limited to Western contexts and face-to-face settings. The present study aims to extend this research to non-Western and online/remote training conditions. Thirty-two Japanese undergraduate students were randomly assigned to a control or feedback group. The feedback group conducted a set of six online simulated child sexual abuse interviews while receiving feedback after each interview in an attempt to improve the quality of their questioning style. The feedback consisted of the outcome of the alleged cases and the quality of the questions asked in the interviews. The control group conducted the interviews without feedback. The feedback (vs. control) increased the proportion of recommended questions (first interview: 45%; last interview: 65% vs. first: 43%; last: 42%, respectively) by using fewer not-recommended questions and eliciting fewer incorrect details. Furthermore, only participants in the feedback group (7 out of 17) demonstrated a reliable change in the proportion of recommended questions. The present study explores the efficacy of simulated interview training with avatars in a different cultural setting and in the context of remote administration. The differences between the present study and previous research are discussed in light of cultural and logistical aspects. [ABSTRACT FROM AUTHOR]

Abstract: This study examines the effects of neighbourhood attractiveness on the residential burglar's crime location choice process using a discrete choice model. We show that past crime data are an important index of a neighbourhood's attractiveness and can be combined with other attractiveness indices adapted from previous studies. We used data from 369 solved cases committed by 70 offenders and related these data to 1,134 areas (500 m grid cells) in Sendai City, Japan. The results showed that residential burglars were attracted to the following potential locations for crimes: (a) areas in proximity to his or her own residence; (b) areas having many or at least a higher proportion of residential burglaries in the past; (c) areas having many residential units; and (d) areas having a higher proportion of single‐family dwellings. The results confirm the validity of past crime data as an index of a neighbourhood's attractiveness for residential burglary. [ABSTRACT FROM AUTHOR]

The goals of this study were as follows: (1) to increase the basic knowledge of offender demographics and geographical characteristics in residential burglaries by taking into account the means of transportation used in the offence; and (2) to explore the possibility that the information about the means of transportation improves the investigation of residential burglaries. A correspondence analysis of the means of transportation and offender demographics yielded two dimensions – criminality and age. Regarding geographical characteristics, from descriptive statistics of residence-to-crime distance and distance between offences, offenders using walking or a bicycle (neighbour type) had a smaller offence area near the residence than offenders using a motor vehicle, a motorcycle, or public transportation (regional type). As information intended for practical application, the ROC curve revealed that descriptive statistics of distance between offences is effective for prediction of neighbour and regional type offenders (AUC ≥ 0.70). Furthermore, as a result of applying methods of estimating the location of the offender's residence to neighbour and regional type offenders, narrow estimates of the area containing the offender's residence at a high rate were obtained for neighbour type offenders. The results were discussed in terms of their usefulness for burglary investigations. [ABSTRACT FROM AUTHOR]

When interviewing children in suspected child sexual abuse (CSA) cases, a common mistake is for interviewers to only ask questions that aim at confirming their initial assumption. Here, we sought to investigate whether experienced emotional states and psychophysiological parameters measured when following a (simulated) CSA interview would be associated with confirmation bias in subsequent question formulation. Psychology students (N = 60, Mage = 22.75) followed a (simulated) CSA interview while their facially expressed emotions (anger, sadness, disgust, surprize and relief), galvanic skin response, heart rate (HR), and HR variability (HRV) were registered. The interview was then interrupted, and the participants were asked to formulate additional questions they would ask of the interviewee. As predicted, we found that participants who got more (vs. less) disgusted by the interview asked more questions biased towards confirming CSA. Against our expectations, participants who got more (vs. less) surprized also asked more questions biased towards confirming CSA. We also found, as predicted, that lower HRV was associated with more abuse confirming questions. Results suggest that emotions and psychophysiological states participants experience when observing a CSA interview are associated with confirmation bias in how questions are formulated. [ABSTRACT FROM AUTHOR]

Previous research has indicated that investigative interviews with adult victims and witnesses are often of low quality. Earlier findings also indicate that interviewing skills exhibit improvement when the interviewers are given feedback on their performance. Technological innovations make it possible to implement such an approach in a scalable manner. Simulated interviews with child avatars have shown that repeated feedback improves the proportion of recommended questions in those interviews. We created adult witness avatars (AWA) to simulate investigative interviews with adult victims and witnesses. We examined whether avatar interviews coupled with feedback (vs no feedback) would result in improvements in interview quality. Of the 60 participants, half received process feedback after each of four simulated interviews. The avatars revealed predefined memories and made errors as a function of algorithms formulated based on previous empirical research on the response behavior of adult witnesses in experimental studies. Results showed that receiving feedback after the simulated interviews increased the proportion of recommended questions (free recall and open questions) in avatar interviews compared with not receiving feedback (90.3% vs 72.6%, respectively). There was also a significant correlation between the question types and accuracy of details, even when analyzed separately for feedback and control groups. We demonstrated that with feedback after each AWA interview, the proportion of recommended questions was significantly higher in the AWA group than in the control group. The implications for practice are discussed. [ABSTRACT FROM AUTHOR]

Previous research has shown that simulated child sexual abuse (CSA) interview training using avatars paired with feedback and modeling improves interview quality. However, to make this approach scalable, the classification of interviewer questions needs to be automated. We tested an automated question classification system for these avatar interviews while also providing automated interventions (feedback and modeling) to improve interview quality. Forty-two professionals conducted two simulated CSA interviews online and were randomly provided with no intervention, feedback, or modeling after the first interview. Feedback consisted of the outcome of the alleged case and comments on the quality of the interviewer's questions. Modeling consisted of learning points and videos illustrating good and bad questioning methods. The total percentage of agreement in question coding between human operators and the automated classification was 72% for the main categories (recommended vs. not recommended) and 52% when 11 subcategories were considered. The intervention groups improved from first to second interview while this was not the case in the no intervention group (intervention x time: p  = 0.007, η p 2  = 0.28). Automated question classification worked well for classifying the interviewers' questions allowing interventions to improve interview quality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Haginoya, Ibe, Yamamoto, Yoshimoto, Mizushi and Santtila.)