Almond, Louise, Martin, Elias and Mcmanus, Michelle Ann ORCID: 0000-0002-0095-1071 (2021) Predicting the Criminal Records of Male-on-Female UK Homicide Offenders From Crime Scene Behaviors. Journal of Interpersonal Violence, 36 (21-22). NP11852-NP11876. ISSN 0886-2605
Preview |
PDF (Author Accepted Manuscript)
- Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives. 376kB |
Official URL: https://doi.org/10.1177/0886260519888522
Abstract
Offender profiling follows the idea that if offenders’ crime scene actions can be empirically linked to their background characteristics, it will be possible to predict one from the other. There is a lack of research exploring whether homicide offenders’ crime scene actions are predictive of their criminal histories, despite the potential utility of such information. The current study addresses this gap in the literature. A sample of 213 adult male-on-female homicides with sexual or unknown motive was drawn from a U.K.-wide database. Relationships between 13 preconviction variables and 29 crime scene behaviors were explored using a bivariate statistical approach. Subsequently, binary logistic regression models were used to predict the presence, or absence, of specific preconvictions based on a combination of offense behaviors. Analyses highlighted 16 statistically significant associations between key offense behaviors and previous convictions, these associations were often “less likely” to result in previous conviction. The analysis failed to find any association for various other variables, most notably sexual preconvictions. Results indicate offenders’ criminal histories can be predicted from their offense behaviors, though not all preconvictions may be similarly suited. Implications for practice are discussed.
Repository Staff Only: item control page