We report three experiments investigating whether people’s judgments about causal relationships are sensitive to the robustness or stability of such relationships across a range of background circumstances. In Experiment 1, we demonstrate that people are more willing to endorse causal and explanatory claims based on stable (as opposed to unstable) relationships, even when the overall causal strength of the relationship is held constant. In Experiment 2, we show that this effect is not driven by a causal generalization’s actual scope of (...) application. In Experiment 3, we offer evidence that stable causal relationships may be seen as better guides to action. Collectively, these experiments document a previously underappreciated factor that shapes people’s causal reasoning: the stability of the causal relationship. (shrink)

Most theories of affective influences on judgement and choice take a valence-based approach, contrasting the effects of positive versus negative feeling states. These approaches have not specified if and when distinct emotions of the same valence have different effects on judgement. In this article, we propose a model of emotion-specific influences on judgement and choice. We posit that each emotion is defined by a tendency to perceive new events and objects in ways that are consistent with the original cognitive-appraisal dimensions (...) of the emotion. To pit the valence and appraisal-tendency approaches against one another, we present a study that addresses whether two emotions of the same valence but differing appraisals—anger and fear—relate in different ways to risk perception. Consistent with the appraisal-tendency hypothesis, fearful people made pessimistic judgements of future events whereas angry people made optimistic judgements. In the Discussion we expand the proposed model and review evidence supporting two social moderators of appraisal-tendency processes. (shrink)

Bayes nets are formal representations of causal systems that many psychologists have claimed as plausible mental representations. One purported advantage of Bayes nets is that they may provide a theory of counterfactual conditionals, such as If Calvin had been at the party, Miriam would have left early. This article compares two proposed Bayes net theories as models of people's understanding of counterfactuals. Experiments 1-3 show that neither theory makes correct predictions about backtracking counterfactuals (in which the event of the if-clause (...) occurs after the event of the then-clause), and Experiment 4 shows the same is true of forward counterfactuals. An amended version of one of the approaches, however, can provide a more accurate account of these data. (shrink)

We investigated whether motivationally determined stimulus valence can be processed in an automatic way, as is assumed in many appraisal theories (e.g., Frijda, 1986, 1993; Lazarus, 1991; Scherer, 1993a). Whereas appraisal theorists typically use conscious self-report methods to investigate their assumptions, our experiments used indirect experimental methods that leave less room for deliberate, conscious reflections of the participants. Using variants of the affective priming and Simon paradigms, we demonstrated that intrinsically neutral, but wanted stimuli facilitated responses with a positive valence, (...) whereas intrinsically neutral, but unwanted stimuli facilitated negative responses. In addition, the second experiment proved to be supportive of another assumption made by appraisal theorists according to which a relation exits between different (automatic) outcomes of motivational appraisal (positive-negative) and different action tendencies (approach-withdrawal). (shrink)