NSF Award Abstract - #0239637

AWSFL008-DS3

PECASE: Toward a Model of Emotion-Specific Influences on Judgment and Choice

Abstract

Proposal Title: PECASE: Toward a Model of Emotion-Specific Influences on Judgment and Choice Institution: Carnegie-Mellon University

Once an exclusively cognitive enterprise, research on judgment and decision making increasingly addresses the powerful influence of emotion. Recent research has shown that even incidental emotion - emotion that is normatively unrelated to the judgment/decision at hand - can have a significant impact on judgment and choice. The majority of studies in this tradition have been motivated by a valence-based approach, contrasting the effects of positive versus negative emotions on judgment and choice. But there is growing evidence that specific emotions of the same valence can trigger opposing perceptions and judgments. For example, in the wake of the terrorist attacks of 9-11, experimentally induced fear produced opposite effects from anger on both risk estimates and policy preferences among U.S. citizens in a nationwide field experiment (Lerner, Gonzalez, Small, & Fischhoff, in press). From a theoretical perspective, these findings demonstrate that dimensions of emotions other than valence are also important components to include in decision models. From an applied perspective, they demonstrate how and why citizens primed for anger will endorse rather different policies than will citizens primed for fear. The purpose of the proposed research is to develop and test a parsimonious yet powerful theory that comprehensively predicts relations among specific emotions and judgment/choice outcomes. The proposed research will expand Lerner and Keltner's (2000; 2001) appraisal-tendency framework (ATF). The ATF predicts that each emotion activates an implicit cognitive predisposition - an "appraisal tendency" - to appraise future events in line with the central appraisal dimensions that triggered the emotion. Such appraisals, although tailored to help the individual respond to the event that evoked the emotion, persist beyond the eliciting situation - becoming an implicit perceptual lens for interpreting subsequent situations. The appraisal-tendency approach provides a flexible yet specific framework for developing a host of testable hypotheses concerning emotion, judgment, and decision making. The proposed research will test hypotheses concerning the effects of emotion on three fundamental cognitive processes: probability assessment, valuation, and attribution. Probability assessment, valuation, and attribution are chosen for study because they underlie countless judgments and decisions in daily life. Indeed, the first two processes also form the basis for the dominant theoretical model for decision making under uncertainty: the expected utility model. To the extent that incidental emotion influences subjective utility and/or probability estimates, it will have implications for classical decision theories and contemporary revisions. To the extent that incidental emotion influences attribution processes, it, too, will have manifold implications because attribution plays a central role in foundational theories of social cognition, mental health, physical health, and justice. The project also aims to disseminate knowledge about the effect of emotion on judgment and decision making, and about the larger field of behavioral decision research (BDR), to broader audiences of students, the public, and policymakers. Dissemination of the insights of BDR is especially important because it has clear practical implications for both public policy and private decisions. Knowledge of the field will be circulated to wider audiences through a new, interdisciplinary undergraduate major in Decision Science at Carnegie Mellon; through briefings for policymakers and interviews with the press; and through the development of a sustainable infrastructure for disseminating BDR research in concert with the National Academy of Science's Office for the Public Understand