The Struggle to Prevent and Evaluate: Application of Population Attributable Risk and Preventive Fraction to Suicide Prevention Researach

Population attributable risk (PAR) estimates have been used in suicide research to evaluate the impact of psychosocial and socioeconomic risk factors, including affective disorders, traumatic life events, and unemployment. A parallel concept of preventive fraction (PF), allowing for estimation of the impact of protective factors and effectiveness of preventive interventions, is practically unknown in suicidology. The study authors discuss the application of both concepts to suicide research and prevention, and review literature on the subject. Despite several methodological and conceptual limitations, both PAR and PF are valuable instruments to inform development and evaluation of suicide prevention programs.     

Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.