Where has the feeling gone? : The signal function of affective states

In the target article, Forgas (this issue) presents his affect infusion model (AIM), which attempts to account for a wide spectrum of phenomena in the interplay of affect and cognition. Specifically, it is proposed that the model explains how affect influences both what information is processed (i.e., content) and how this information is processed (i.e., process). Forgas is undoubtedly correct in his conclusion that the field needs an integration framework to bring together the numerous, and on the surface sometimes unrelated or even conflicting, findings. Given that his model is one of the few integrative approaches in the field, his work is right on target. Besides the many positive aspects of the AIM, there are some aspects that may deserve a second look. In the remainder of this commentary, I emphasize the signal function of affective states that seems to receive rather little attention within the AIM. I argue that without assuming such a signal function it is difficult to understand mood-dependent processing styles. Forgas presents convincing evidence that different affective states may elicit different processing strategies. For example, happy and sad individuals differ in the degree to which they exhibit the fundamental attribution error, they show different degrees of eyewitness distortions, and they generate arguments of different persuasive quality. This evidence converges with numerous findings in a variety of domains, for example in stereotyping (Bodenhausen, Kramer, & Siisser, 1994), persuasion (Bless, Mackie, & Schwarz, 1992), creativity and problem solving (Isen, 1987), or memory for scripted behaviors (Bless et al., 1996). The general conclusion of this research holds that minor differences in affective states may result in different processing strategies. These effects can be observed with tasks that do not involve the processing ofpositively or negatively valenced information. Although the conclusion that different affective states result in different processing strategies is predicted by the AIM, it remains unclear precisely how this conclusion is derived from the outlined core assumptions of the model. When proposing mood influences on processing strategies, Forgas suggests that happy moods are more likely to elicit a top-down processing style, whereas sad moods are more likely to elicit detailed analyses of the information at hand. In presenting this hypothesis, Forgas refers to other theorizing from which this conclusion can be derived (Bless, 2000; Fiedler, 2000; see also Bless, in press-b). It should be noted that most of the existing evidence pertaining to mood-dependent top-down versus bottom-up processing can also be captured-either directly or indirectly-by other accounts (see Isen, 1987; Schwarz, 1990; Mackie & Worth, 1989; for a discussion of evidence allowing differentiations see Bless & Schwarz, 1999). Although the various accounts share the assumption that happy and sad individuals differ in their reliance on heuristics and general knowledge structures and in their attention to the details of a situation, the models depart in their assumptions about the mechanisms that mediate these differences (see Bless, in press-a). On one hand, the AIM converges with other models in the general conclusion about mooddependent processing strategies and claims that the accumulated evidence supports the central hypotheses ("These results make sense in terms of our theoretical predictions and suggest that negative affect promotes a more careful, externally focused, and bottom-up information-processing style ."; Forgas, this issue). On the other hand, however, the model is surprisingly silent on why these processing effects are expected. Addressing this important issue could contribute to a further improvement of the model. Most explanations of the mood effects on processing strategies quite explicitly, or at least implicitly, build on the notion that individuals' affective states provide some information about an individual's current situation (this does not hold for the capacity approach, which, however, is not favored within Forgas's theorizing). For example, the mood-and-general-knowledge assumption to which Forgas refers