Predicting violent infractions in a Swiss state penitentiary: A replication study of the PCL-R in a population of sex and violent offenders

BACKGROUND: Research conducted with forensic psychiatric patients found moderate correlations between violence in institutions and psychopathy. It is unclear though, whether the PCL-R is an accurate instrument for predicting aggressive behavior in prisons. Results seem to indicate that the instrument is better suited for predicting verbal rather than physical aggression of prison inmates. METHODS: PCL-R scores were assessed for a sample of 113 imprisoned sex and violent offenders in Switzerland. Logistic regression analyses were used to estimate physical and verbal aggression as a function of the PCL-R sum score. Additionally, stratified analyses were conducted for Factor 1 and 2. Infractions were analyzed as to their motives and consequences. RESULTS: The mean score of the PCL-R was 12 points. Neither the relationship between physical aggression and the sum score of the PCL-R, nor the relationship between physical aggression and either of the two factors of the PCL-R were significant. Both the sum score and Factor 1 predicted the occurrence of verbal aggression (AUC=0.70 and 0.69), while Factor 2 did not. CONCLUSION: Possible explanations are discussed for the weak relationship between PCL-R scores and physically aggressive behavior during imprisonment. Some authors have discussed whether the low base rate of violent infractions can be considered an explanation for the non-significant relation between PCL-R-score and violence. The base rate in this study, however, with 27%, was not low. It is proposed that the distinction between reactive and instrumental motives of institutional violence must be considered when examining the usefulness of the PCL-R in predicting in-prison physical aggressive behavior

Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset

Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1-10 cameras), and (2) by total season length (1-365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species