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Purpose To conduct a test of the principles underpinning crime linkage (behavioural consistency and distinctiveness) with a sample more closely reflecting the volume and nature of sexual crimes with which practitioners work, and to assess whether solved series are characterized by greater behavioural similarity than unsolved series. Method A sample of 3,364 sexual crimes (including 668 series) was collated from five countries. For the first time, the sample included solved and unsolved but linked‐by‐DNA sexual offence series, as well as solved one‐off offences. All possible crime pairings in the data set were created, and the degree of similarity in crime scene behaviour shared by the crimes in each pair was quantified using Jaccard's coefficient. The ability to distinguish same‐offender and different‐offender pairs using similarity in crime scene behaviour was assessed using Receiver Operating Characteristic analysis. The relative amount of behavioural similarity and distinctiveness seen in solved and unsolved crime pairs was assessed. Results An Area Under the Curve of .86 was found, which represents an excellent level of discrimination accuracy. This decreased to .85 when using a data set that contained one‐off offences, and both one‐off offences and unsolved crime series. Discrimination accuracy also decreased when using a sample composed solely of unsolved but linked‐by‐DNA series (AUC = .79). Conclusions Crime linkage is practised by police forces globally, and its use in legal proceedings requires demonstration that its underlying principles are reliable. Support was found for its two underpinning principles with a more ecologically valid sample.

Purpose: This study compared the utility of different statistical methods in differentiating sexual crimes committed by the same person from sexual crimes committed by different persons.Methods: Logistic regression, iterative classification tree (ICT), and Bayesian analysis were applied to a dataset of 3,364 solved, unsolved, serial, and apparent one-off sexual assaults committed in five countries. Receiver Operating Characteristic analysis was used to compare the statistical approaches.Results: All approaches achieved statistically significant levels of discrimination accuracy.Two out of three Bayesian methods achieved a statistically higher level of accuracy (Areas Under the Curve [AUC] = 0.89 [Bayesian coding method 1]; AUC = 0.91 [Bayesian coding method 3]) than ICT analysis (AUC = 0.88), logistic regression (AUC = 0.87), and Bayesian coding method 2 (AUC = 0.86). Conclusions:The ability to capture/utilize between-offender differences in behavioral consistency appear to be of benefit when linking sexual offenses. Statistical approaches that utilize individual offender behaviors when generating crime linkage predictions may be preferable to approaches that rely on a single summary score of behavioral similarity. Crime linkage decision-support tools should incorporate a range of statistical methods and future 2 research must compare these methods in terms of accuracy, usability, and suitability for practice.

Purpose – The purpose of this paper is to explore the differences (if any) between serial and hard-to-solve one-off homicides, and to determine if it is possible to distinguish the two types of homicides based on offence behaviours and victim characteristics. Design/methodology/approach – A sample of 116 Italian serial homicides was compared to 45 hard-to-solve one-off homicides. Hard-to-solve one-off homicides were defined as having at least 72 hours pass between when the offence came to the knowledge of the police and when the offender was caught. Logistic regression was used to predict whether a killing was part of a series or a one-off offence. Findings – The serial killers targeted more strangers and prostitutes, displayed a higher level of forensic awareness both before and after the killing, and had more often an apparent sexual element in their offence. Conversely, the one-off homicides were found to include more traits indicative of impulsive and expressive behaviour. The model demonstrated a good ability (AUC=0.88) to predict whether a homicide belonged to the serial or one-off category. Research limitations/implications – The findings should be replicated using local homicide data to maximise the validity of the model in countries outside of Italy. Practical implications – Being able to distinguish between serial and one-off homicides based on information available at a new crime scene could be practically useful for homicide investigators managing finite resources. Originality/value – Studies comparing serial homicides to one-off homicides are scarce, and there are no studies explicitly trying to predict whether a homicide is an isolated case or part of a series.

PreambleIn Finland, specialised university hospital units have taken on much of the role of the Barnahus in other Nordic countries, ensuring a childfriendly and expert environment for child interviews in cases of suspected crimes against children. The personnel consist of multi-professional teams including expertise in forensic psychology, paediatrics, child psychiatry and social work. There are units in the country's five university hospitals, thus covering the whole country. The units provide expert assistance when required by the police, in practically all cases involving preschool and young school-aged children as well as particularly vulnerable child victims. Finnish guidelines promote a hypothesis -testing approach and the use of expert interviewers (forensic psychologists with knowledge of human memory, child interviewing strategies, child development and suggestibility issues as well as the phenomena of child disclosure and trauma) within the pre-trial process, ensuring an evidence-based practice of investigating child abuse suspicions.

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This study explored whether a coding bias due to knowledge of which crimes have been committed by the same offender exists when behavioural variables are coded in serial murder cases. The study used an experimental approach where the information given to the participants (N = 60) concerning correct linkages between a number of murder series was manipulated. The participants were divided into three different groups (n = 20 in each). These three groups received correct, incorrect, or no information about the linked series prior to the coding. The results showed that there is no clear evidence to support the hypothesis of a bias in the coding. The risk of expectancy effects and suggestions on how to minimise them in behavioural crime linking research were discussed, and suggestions on how to improve the validity of possible future replications of the experiment were given. The practical implications of expectancy effects on behavioural crime linking decisions for the justice system were also discussed. Copyright © 2012 John Wiley & Sons, Ltd.

Purpose Crime linkage analysis (CLA) can be applied in the police investigation-phase to sift through a database to find behaviorally similar cases to the one under investigation and in the trial-phase to try to prove that the perpetrator of two or more offences is the same, by showing similarity and distinctiveness in the offences. Lately, research has moved toward more naturalistic settings, analyzing data sets that are as similar to actual crime databases as possible. One such step has been to include one-off offences in the data sets, but this has not yet been done with homicide. The purpose of this paper is to investigate how linking accuracy of serial homicide is affected as a function of added hard-to-solve one-off offences. Design/methodology/approach A sample (N = 117–1160) of Italian serial homicides (n = 116) and hard-to-solve one-off homicides (n = 1–1044, simulated from 45 cases) was analyzed using a Bayesian approach to identify series membership, and a case by case comparison of similarity using Jaccard’s coefficient. Linking accuracy was evaluated using receiver operating characteristics and by examining the sensitivity and specificity of the model. Findings After an initial dip in linking accuracy (as measured by the AUC), the accuracy increased as more one-offs were added to the data. While adding one-offs made it easier to identify correct series (increased sensitivity), there was an increase in false positives (decreased specificity) in the linkage decisions. When rank ordering cases according to similarity, linkage accuracy was affected negatively as a function of added non-serial cases. Practical implications While using a more natural data set, in terms of adding a significant portion of non-serial homicides into the mix, does introduce error into the linkage decision, the authors conclude that taken overall, the findings still support the validity of CLA in practice. Originality/value This is the first crime linkage study on homicide to investigate how linking accuracy is affected as a function of non-serial cases being introduced into the data.