When outcomes are not completely certain, we have to grapple with risk. Different individuals have characteristically different attitudes to risk - something that has been extensively investigated in psychology and psychiatry, albeit largely using venerable measures that lack certain axiomatically-desirable properties. Here we consider a modern risk measure for modeling human and animal decision-making called conditional value at risk (CVaR) which is particularly apposite because of its preferential focus on worst-case outcomes. We discuss theoretical characteristics of CVaR in single and multi-step decision-making problems, relating our findings to avoidance and worry. This is joint work with Chris Gagne.