Does the polygraph lead to better risk prediction for sexual offenders?

The polygraph is receiving increased attention surrounding its ability to facilitate more honest disclosures from sexual offenders concerning risk-related information (e.g., historical risk factors and acute-dynamic risk factors). In addition, the polygraph has become accepted as a standard containment tool in the US, although UK professionals appear to have taken a more cautionary approach. The aim of this review is to provide a basic overview of current risk assessment procedure in the absence of the polygraph, and then to investigate studies that use the polygraph to enhance sexual offenders' risk assessments. Specifically, studies examining historical risk factors, stable-dynamic risk factors, and acute-dynamic risk factors are examined and evaluated. We conclude that there is reasonable evidence supporting polygraph use in some areas of risk assessment. However, the vast majority of studies suffers from serious confounds that should be taken into account by professionals who use the polygraph as a standard practice in sexual offender risk assessment and management. Finally, the future of the polygraph is discussed in light of the presented empirical evidence.

Mortality disparities between geographic regions : results from a risk percentiles model for coronary heart disease

Background: Planning of disease prevention strategies requires information regarding the distribution of absolute risk in the population to allow targeting of people at high disease risk. It is well known that death rates from coronary heart disease (CHD) are higher in remote areas of Australia compared with major cities. Less well understood is the distribution of the absolute risk of CHD death within the different geographic regions. We present a mathematical model of CHD which projects the lifetime risk of death among individuals in different percentiles of CHD risk. We apply this to model the distribution of CHD risk within different geographic regions.

Methods: Using information from the Framingham1, MRFIT2 and AusDiab3 studies, the Australian population was divided into percentiles of CHD risk within age and gender groups by geographic location. Absolute mortality risk was determined at each percentile using current Australian mortality data. Survival curves were generated for each percentile using these risk estimates. Approximate confidence intervals were derived using bootstrap methods.

Conclusions: The difference in life expectancy at age 25 between those in the lowest decile of CHD risk compared to the highest was 5.8 years (95%CI:4.7,6.7) in major cities compared to 8.5 years (95%CI:7.6,9.7) in remote areas. The difference in risk of premature death (before age 75) was 12% (95%CI:10%,14%) in major cities compared to 33% (95%CI:28%,38%) in remote areas.

HealthMap: a visual platform for patient suicide risk review

Misjudging suicide risk can be fatal. Risk assessment is complicated by multiplicity of risk factors, none of which individually can reliably predict risk. This paper addresses the need for better clinical support, visualising risk factors scattered in raw electronic medical records. HealthMap is a visual tool that helps clinicians effectively examine patient histories during a suicide risk assessment. We characterise the information visualisation problems accompanying suicide risk assessments. A design driven by visualisation principles was implemented. The prototype was evaluated by clinicians and accepted into daily clinical work-flow.

Effect of mean stress on multiaxial ratcheting life: a simplified life prediction model based on average equivalent stress amplitude

This article proposes a model to predict uniaxial and multiaxial ratcheting life by addressing the three primary parameters that influence failure life: fatigue damage, ratcheting damage and the multiaxial loading path. These three factors are addressed in the present model by (a) the stress amplitude for fatigue damage, (b) mean stress-dependent Goodman equation for ratcheting damage and (c) an inherent weight factor based on average equivalent stress to account for the multiaxial loading. The proposed model requires only two material constants which can be easily determined from uniaxial symmetric stress-controlled fatigue tests. Experimental ratcheting life data collected from the literature for 1025 and 42CrMo steel under multiaxial proportional and nonproportional constant amplitude loading ratcheting with triangular sinusoidal and trapezoidal waveform (i.e. linear, rhombic, circular, elliptical and square stress paths) have shown good agreement with the proposed model.

The addition of depression to the Framingham Risk Equation model for predicting coronary heart disease risk in women

BACKGROUND: Depression is widely considered to be an independent and robust predictor of Coronary Heart Disease (CHD), however is seldom considered in the context of formal risk assessment. We assessed whether the addition of depression to the Framingham Risk Equation (FRE) improved accuracy for predicting 10-year CHD in a sample of women.

DESIGN: A prospective, longitudinal design comprising an age-stratified, population-based sample of Australian women collected between 1993 and 2011 (n=862).

METHODS: Clinical depressive disorder was assessed using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID-I/NP), using retrospective age-of-onset data. A composite measure of CHD included non-fatal myocardial infarction, unstable angina coronary intervention or cardiac death. Cox proportional-hazards regression models were conducted and overall accuracy assessed using area under receiver operating characteristic (ROC) curve analysis.

RESULTS: ROC curve analyses revealed that the addition of baseline depression status to the FRE model improved its overall accuracy (AUC:0.77, Specificity:0.70, Sensitivity:0.75) when compared to the original FRE model (AUC:0.75, Specificity:0.73, Sensitivity:0.67). However, when calibrated against the original model, the predicted number of events generated by the augmented version marginally over-estimated the true number observed.

CONCLUSIONS: The addition of a depression variable to the FRE equation improves the overall accuracy of the model for predicting 10-year CHD events in women, however may over-estimate the number of events that actually occur. This model now requires validation in larger samples as it could form a new CHD risk equation for women.

Latent heat loss of Holstein cows in a tropical environment: a prediction model

Nove vacas Holandesas lactantes com 526 ± 5 kg de peso corporal (cinco predominantemente pretas e quatro predominantemente brancas), criadas em região tropical e manejadas em pastagens, foram observadas com os objetivos de determinar simultaneamente as taxas de evaporação cutânea e respiratória em ambiente tropical e desenvolver modelos de predição. Para a medição da perda de calor latente pela superfície corporal, utilizou-se uma cápsula ventilada e, para a perda por respiração, utilizou-se uma máscara facial. Os resultados mostraram que as vacas que tinham maior peso corporal (classe 2 e 3) apresentaram maiores taxas evaporativas. Quando a temperatura do ar aumentou de 10 para 36ºC e a umidade relativa do ar caiu de 90 para 30%, a eliminação de calor por evaporação respiratória aumentou de aproximadamente 5 para 57 W m-2 e a evaporação na superfície corporal passou de 30 para 350 W m-2. Esses resultados confirmam que a eliminação de calor latente é o principal mecanismo de perda de energia térmica sob altas temperaturas (>30ºC); a evaporação cutânea é a maior via e corresponde a aproximadamente 85% da perda total de calor, enquanto o restante é eliminado pelo sistema respiratório. O modelo para predizer o fluxo de perda de calor latente baseado em variáveis fisiológicas e ambientais pode ser utilizado para estimar a contribuição da evaporação na termorregulação, enquanto o modelo baseado somente na temperatura do ar deve ser usado apenas para a simples caracterização do processo evaporativo.

Risk prediction for weed infestation using classification rules

This paper proposes a fuzzy classification system for the risk of infestation by weeds in agricultural zones considering the variability of weeds. The inputs of the system are features of the infestation extracted from estimated maps by kriging for the weed seed production and weed coverage, and from the competitiveness, inferred from narrow and broad-leaved weeds. Furthermore, a Bayesian network classifier is used to extract rules from data which are compared to the fuzzy rule set obtained on the base of specialist knowledge. Results for the risk inference in a maize crop field are presented and evaluated by the estimated yield loss. © 2009 IEEE.