Role of assessment components and recent adverse outcomes in risk estimation and prediction: use of the Short Term Assessment of Risk and Treatability (START) in an adult secure inpatient mental health service

The Short Term Assessment of Risk and Treatability is a structured judgement tool used to inform risk estimation for multiple adverse outcomes. In research, risk estimates outperform the tool's strength and vulnerability scales for violence prediction. Little is known about what its’component parts contribute to the assignment of risk estimates and how those estimates fare in prediction of non-violent adverse outcomes compared with the structured components. START assessment and outcomes data from a secure mental health service (N=84) was collected. Binomial and multinomial regression analyses determined the contribution of selected elements of the START structured domain and recent adverse risk events to risk estimates and outcomes prediction for violence, self-harm/suicidality, victimisation, and self-neglect. START vulnerabilities and lifetime history of violence, predicted the violence risk estimate; self-harm and victimisation estimates were predicted only by corresponding recent adverse events. Recent adverse events uniquely predicted all corresponding outcomes, with the exception of self-neglect which was predicted by the strength scale. Only for victimisation did the risk estimate outperform prediction based on the START components and recent adverse events. In the absence of recent corresponding risk behaviour, restrictions imposed on the basis of START-informed risk estimates could be unwarranted and may be unethical.

Considerations in the use of high intensity leg cycle ergometry as a test of muscular performance

High intensity leg cycle ergometry is a widely used method of measuring muscular performance during maximal exercise. Until recently, it was deemed to be a predominantly lower body activity; however, there is now evidence to suggest that the upper body could be making a significant contribution to power output, as demonstrated by the intense electrical activity of the forearm musculature. As high intensity cycle ergometry often is used to measure performance in untrained cyclists it is important they are given at least two familiarisation trials to ensure results are both reliable and reproducible. In addition, diurnal variations exist during a single high intensity bout of exercise. It is likely these daily fluctuations are influenced by a number of biochemical and physiological variables. The purpose of this article is to outline factors that contribute to our interpretation of data following high intensity cycle ergometry.