Classifying missing persons cases: an analysis of police risk assessments using multi-dimensional scaling

Abstract

Missing persons cases present a complex challenge for law enforcement globally and require a nuanced understanding of their typologies. This study provides a comprehensive analysis of cases from the United Kingdom, from within a single police service, focusing on the alignment of police missing person risk assessment (RA) factors with existing typologies. Utilizing data exclusively from nearly 5000 police RAs, the study undertakes a multi-stage analysis, examining RA factors for congruence with established typologies and exploring data subsets based on gender, case outcomes, and risk gradings. Using Jaccard’s similarity coefficient and smallest space analysis (SSA), the study interprets and visualizes the cases to explore relationships. Results are reported using visual and descriptive statistics. Key findings include confirmation of alignment to existing typologies and research that has identified ‘unintentional–accidental/drift’ as the dominant missing person typology, identifying it in 65% of the cases. Notably, the typology was also the dominant theme in 45% of the cases resulting in a harmful outcome and 42% graded as high-risk. Categorical nuances are identified within subsets, with 47% of long-term missing and 63% involving men relating to the intentional–dysfunctional typology. 31% of the cases involving females, and 30% and 45% of the cases graded as medium and no apparent risk, respectively, were dominated by the ‘intentional–escape’ typology. We discuss how these findings can be used to improve the police RA process and guide initial risk grading and case prioritization enhancing the understanding and response to missing person cases.