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How do static and dynamic risk factors work together to predict violent behaviour among offenders with an intellectual disability?
Author(s) -
Lofthouse R. E.,
Totsika V.,
Hastings R. P.,
Lindsay W. R.,
Hogue T. E.,
Taylor J. L.
Publication year - 2014
Publication title -
journal of intellectual disability research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.941
H-Index - 104
eISSN - 1365-2788
pISSN - 0964-2633
DOI - 10.1111/j.1365-2788.2012.01645.x
Subject(s) - proxy (statistics) , psychology , risk assessment , dynamic assessment , human factors and ergonomics , intellectual disability , poison control , developmental psychology , computer science , medicine , psychiatry , computer security , machine learning , environmental health
Background Research on risk assessment with offenders with an intellectual disability ( ID ) has largely focused on estimating the predictive accuracy of static or dynamic risk assessments, or a comparison of the two approaches. The aim of this study was to explore how static and dynamic risk variables may ‘work together’ to predict violent behaviour. Methods Data from 212 offenders with an ID were analysed. Risk assessment tools included one static measure ( V iolence R isk A ppraisal G uide), and two dynamic measures ( E motional P roblems S cale and the S hort D ynamic R isk S cale). Six‐month concurrent prediction data on violent behaviour were collected. A structured methodology was employed to explore putative relationships between static and dynamic factors. Results Static risk factors temporally preceded dynamic ones, and were shown to dominate both dynamic measures, while there was a non‐zero relationship between the static and the two dynamic measures. According to K raemer et al ., these findings suggest that dynamic risk factors function as proxy risk factors for static risk. Conclusions Dynamic and static risk factors appear to capture elements of the same underlying risk associated with violent behaviour in individuals with an ID . This is the first study to empirically explore risk interrelationships in the forensic ID field. We discuss the importance of the contribution of dynamic variables in the prediction and management of risk.