Typology of acquaintance rapist: Criminal profiling based on latent class analysis (LCA)

Purpose The purpose of this study was to identify and characterize latent subtypes of acquaintance rapists using latent class analysis (LCA), with the goal of developing probabilistic criminal profiling models based on sociodemographic variables and criminal dynamics, thus optimizing the forensic tools available to investigate complex cases. Design/methodology/approach The research adopted a quantitative, nonexperimental and ex post facto design, using LCA to analyze sociodemographic data and criminal dynamics of 250 cases of rape committed by acquaintance rapists in Chile. The R statistical packages poLCA and LCAvarsel were used to identify latent classes and build criminological profiles. Findings The results suggest four subtypes of acquaintance rapists: intrafamilial rapists of minor victims, intrafamilial rapists of adult victims, extrafamilial rapists of minor victims and extrafamilial rapists of adult victims. Specific patterns and probability of occurrence of 22 sociocriminogenic variables were identified for each profile, establishing significant criminogenic differences between the groups. Research limitations/implications Several methodological limitations were identified that could affect the findings, such as the exclusive use of police records, the lack of clinical indicators and the absence of comparison with a control group or international samples. This restricts the generalizability of the results and calls for future studies with greater data diversity and longitudinal approaches. Practical implications The findings have important implications for forensic practice by identifying four latent classes of acquaintance rapists, providing an empirical model to characterize this type of offender according to criminogenic patterns. This could optimize the construction of criminal profiles, strengthen hypotheses and facilitate investigative decisions in highly complex cases with limited evidence. New studies along these lines could bring their application closer to judicial contexts to improve risk assessments and the prevention of crimes of this nature. Social implications The findings highlight the need for social strategies that raise awareness about the complexity of sexual crimes committed by known offenders, promote reporting, reduce revictimization and foster public policies based on criminological profiles to improve victim protection and secondary prevention. Originality/value The originality of the study lies in the use of LCA in profiling acquaintance rapists, addressing a significant gap in the literature. Its value lies in offering an innovative approach to identifying criminogenic patterns, improving criminal investigation and decision-making in forensic contexts.

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Publication Details

Journal
Journal of Forensic Practice
Published
2025-04-26
DOI
https://doi.org/10.1108/jfp-08-2024-0044
Primary Topic
Computational and Text Analysis Methods
Type
article
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article

Typology of acquaintance rapist: Criminal profiling based on latent class analysis (LCA)

Francisco Ceballos-Espinoza
Journal of Forensic Practice
Computational and Text Analysis Methods
article

Typology of acquaintance rapist: Criminal profiling based on latent class analysis (LCA)

Francisco Ceballos-Espinoza
article en

Abstract

Purpose The purpose of this study was to identify and characterize latent subtypes of acquaintance rapists using latent class analysis (LCA), with the goal of developing probabilistic criminal profiling models based on sociodemographic variables and criminal dynamics, thus optimizing the forensic tools available to investigate complex cases. Design/methodology/approach The research adopted a quantitative, nonexperimental and ex post facto design, using LCA to analyze sociodemographic data and criminal dynamics of 250 cases of rape committed by acquaintance rapists in Chile. The R statistical packages poLCA and LCAvarsel were used to identify latent classes and build criminological profiles. Findings The results suggest four subtypes of acquaintance rapists: intrafamilial rapists of minor victims, intrafamilial rapists of adult victims, extrafamilial rapists of minor victims and extrafamilial rapists of adult victims. Specific patterns and probability of occurrence of 22 sociocriminogenic variables were identified for each profile, establishing significant criminogenic differences between the groups. Research limitations/implications Several methodological limitations were identified that could affect the findings, such as the exclusive use of police records, the lack of clinical indicators and the absence of comparison with a control group or international samples. This restricts the generalizability of the results and calls for future studies with greater data diversity and longitudinal approaches. Practical implications The findings have important implications for forensic practice by identifying four latent classes of acquaintance rapists, providing an empirical model to characterize this type of offender according to criminogenic patterns. This could optimize the construction of criminal profiles, strengthen hypotheses and facilitate investigative decisions in highly complex cases with limited evidence. New studies along these lines could bring their application closer to judicial contexts to improve risk assessments and the prevention of crimes of this nature. Social implications The findings highlight the need for social strategies that raise awareness about the complexity of sexual crimes committed by known offenders, promote reporting, reduce revictimization and foster public policies based on criminological profiles to improve victim protection and secondary prevention. Originality/value The originality of the study lies in the use of LCA in profiling acquaintance rapists, addressing a significant gap in the literature. Its value lies in offering an innovative approach to identifying criminogenic patterns, improving criminal investigation and decision-making in forensic contexts.

Journal of Forensic PracticeVol. 27(4)
Universidad de La Frontera (CL)
Openalex Percentile: Top 88%
Computational and Text Analysis Methods
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