Characteristics that predict firesetting in male and female mentally disordered offenders

Few studies have adequately explored the characteristics of male and female mentally disordered firesetters and compared these to those of non-firesetting mentally disordered offenders. Furthermore, there is a paucity of research examining the characteristics which can predict repeat firesetting within this population. The current study aimed to examine similarities and differences in the characteristics of (1) male and female mentally disordered firesetters, (2) male and female mentally disordered firesetters compared to non-firesetting offenders, and (3) one-time and repeat firesetters. Furthermore, the ability of these characteristics to predict offence status (i.e. firesetter or non-firesetter) and repeat firesetting was explored. Information was collected from patient hospital records for 77 (43 firesetters, 34 non-firesetters) mentally disordered offenders; including sociodemographic, family and personal background, psychiatric, and offence history factors. The findings suggest that mentally disordered firesetters are similar to their non-firesetting counterparts on key characteristics; however, firesetters are more likely to have an expressed interest in fire/explosives and a diagnosis of a schizophrenic disorder and female firesetters are more likely to have a higher number of firesetting incidents than males. Furthermore, findings suggest that fire interest is the largest predictor of repeat firesetting. Clinical implications in terms of treatment and risk assessment are discussed.     

Measuring the validity and reliability of forensic likelihood-ratio systems

There has been a great deal of concern recently about validity and reliability in forensic science. This paper reviews for a broad target audience metrics of validity and reliability (accuracy and precision) which have been applied in forensic voice comparison and which are potentially applicable in other branches of forensic science. The metric of validity is the log likelihood-ratio cost (C_llr), and the metric of reliability is an empirical estimate of credible intervals. A revised procedure for the calculation of credible intervals is introduced.