Abstract
Promoting informed choices about alcohol use requires understanding the nature of drinkers' risk perceptions and how these influence decision-making. Fuzzy trace theory states that people use imprecise "fuzzy" risk representations, which are based on the broad cognitive and affective meanings of risk-related experiences, whereas traditionally used measures request precise unitary estimations. Fuzzy representations may be less affected by defensive self-enhancement biases inherent in unitary estimates and better predictors of decision outcomes because they better reflect risk-related affect. Conversely, unitary estimates are based in specific experience and should be better associated with objective risk. Fuzziness was operationalized as a bounded range of undergraduate drinkers' lowest and highest "possibly true" estimates of likelihood for eight alcohol-related outcomes on an unmarked scale anchored by the terms "no chance" and "certain." This allowed comparison to unitary estimates and objective alcohol-related risk (Alcohol Use Disorders Identification Test [AUDIT] scores). Consistent with self-enhancement, unitary estimates were lower than bounded estimate midpoints. An accountability manipulation, which reduces self-enhancement, increased unitary but not bounded estimates. These effects were stronger in participants scoring highly on defensive coping. Bounded estimates were better predicted by risk-related affect and they more strongly predicted intention to reduce drinking. Unitary measures were better predicted by AUDIT scores. Accountability manipulations suppress heuristic thought, reduced correlations between bounded estimates and affect and intention, and eliminated unitary and bounded differences in prediction of AUDIT scores. Drinkers prefer fuzzy representations that reflect affective information when making decisions, but improving risk-based decisions may involve combining the best elements of bounded and unitary representations.
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