@article{ref1,
title="Identifying a high-risk cohort in a complex and dynamic risk environment: out-of-bounds skiing-an example from avalanche safety",
journal="Prevention science",
year="2012",
author="Haegeli, Pascal and Gunn, Matt and Haider, Wolfgang",
volume="13",
number="6",
pages="562-573",
abstract="The development of effective prevention initiatives requires a detailed understanding of the characteristics and needs of the target audience. To properly identify at-risk individuals, it is crucial to clearly delineate risky from acceptable behavior. Whereas health behavior campaigns commonly use single conditions (e.g., lack of condom use) to identify high-risk cohorts, many risk behaviors are more complex and context dependent, rendering a single condition approach inadequate. Out-of-bounds skiing, an activity associated with voluntary exposure to avalanche hazard, is an example of such a multifaceted risk-taking activity. Using a dataset from an extensive online survey on out-of-bounds skiing, we present an innovative approach for identifying at-risk individuals in complex risk environments. Based on a risk management framework, we first examine risk-taking preferences of out-of-bounds skiers with respect to exposure and preparedness-the two main dimensions of risk management-separately. Our approach builds on existing person-centered research and uses Latent Class Analysis to assign survey participants to mutually exclusive behavioral classes on these two dimensions. Discrete Choice Experiments are introduced as a useful method for examining exposure preferences in the context of variable external conditions. The two class designations are then combined using a risk matrix to assign overall risk levels to each survey participant. The present approach complements existing person-centered prevention research on the antecedents of risk-taking by offering a process-oriented method for examining behavioral patterns with respect to the activity itself. Together, the two approaches can offer a much richer perspective for informing the design of effective prevention initiatives.<p /> <p>Language: en</p>",
language="en",
issn="1389-4986",
doi="10.1007/s11121-012-0282-5",
url="http://dx.doi.org/10.1007/s11121-012-0282-5"
}