3. Moods and judgments

3.1. Mood as priming

The associative-network models of memory (e.g., Wyer & Carlston, 1979; Bower, 1981; M. S. Clark

& Isen, 1982; Isen, Shalker, Clark & Karp, 1978) launched the study of mood effects on cognitive

processes. The model developed by Bower (1981; 1991) was certainly one of the most influential accounts of the interaction between affect and cognition. Thus, the influence of mood on cognitive processes was first interpreted as a consequence of semantic priming in mood according to the network theory of memory (Bower, 1991). Initially, Bower’s model (1981) applied to specific emotions rather than moods. It referred to the nodes of memory involving specific emotions that initiated the activation of other units linked to this node. Accordingly, emotions represent information units or nodes in individuals' semantic memory network, where they are connected with associative pointers (Bower, 1981; M.S. Clark & Isen, 1982). Every emotion (joy, anger, sadness, ...) then corresponds to a specific node in memory, each connected to other nodes which contain data to define the various aspects of that emotion. The model was based on the classical properties of a network model and more precisely on the idea of spreading activation (introduced by Wyer & Carlston, 1979). This model with its extensions (Bower, 1987, 1992, Bower & Cohen, 1982) was used as a starting point for most research on the effects of affect on memory. Later (Bower, 1991, M. S. Clark & Isen, 1982), Bower’s model was extended by postulating the existence of nodes in memory associated with mood. Activation of mood states would influence memory for specific events (Bower, 1991). According to this idea, people in a positive mood make more optimistic judgments concerning evaluations/expectations/situations than people in a negative mood, because they activate mood congruent concepts in memory. By other words, once activated an elated mood influences information processing by the spreading of activation through the associative network, so that situations are more likely to be interpreted or appraised positively.

These mood congruent effects depend on the extent of activated information and on its mood congruency (e.g., Forgas & Bower, 1987). Therefore, the main implication of the mood-as-priming view is that moods influence judgments (e.g., demand appraisals) by making mood-congruent information highly accessible. It is assumed that people in a positive mood make more optimistic judgments concerning evaluations/expectations/situations than people in a negative mood, because they activate more positive mood-congruent concepts in memory.

Studies testing these assumptions have achieved mixed results, with some supporting the model (e.g., Bower, 1981, 1991; Forgas & Bower, 1987) and others refuting it (see Blaney, 1986; Isen, 1987;

Morris, 1989, for reviews). Mood-congruent recall is a fragile phenomenon that is difficult to replicate and it is most likely to be obtained for self-referenced material (Schwarz & Clore, 1988). An explanation for the several failures to demonstrate mood-congruent recall was advance by Niedenthal and colleagues (e.g., Niedenthal, Halberstadt, & Setterlund, 1997; Niedenthal & Settedund, 1994). They posited that mood refers to a valence dimension (positive-negative affect), while affect-related

information is stored in categories (specific emotions). Consequently, unspecific affect cannot increase the accessibility of specific knowledge. Niedenthal and colleagues demonstrated that inducing sadness facilitated retrieving sadness-related information, while impairing access to anger-related information.

Since both sadness and anger share the same (negative) valence, this contradicts the assumption that unspecific affect can increase the accessibility of affective information. These researchers claimed a specific emotion priming idea. However, it is also possible that moods are more specific than simply positive or negative, as Ekman (1984) argues. Due to methodological aspects of the studies from Niedenthal and collaborators, their results can also be interpreted as supporting mood-as-priming effects. Wyer, Clore, and Isbell (1999) proceeded with a more blunt argument: affective states cannot prime any information. Affective priming is indirect and depends on the extent of thinking about the affective state, rather than on affect per se. Results from Niedenthal et al. (1997) demonstrate that this view is incorrect and that it does not work as an alternative explanation.

More globally, Isen (1987) proposed that the posited memory nodes were more related to the dimension of emotional valence states: There was information related to both positive affects, and to negative affects. In addition, it has been suggested that positive affect is linked to more information and thus to more elaborated information, due to their pleasantness. This has been shown, for example, in creative tasks (e.g., Isen et al., 1987, Isen, Johnson, Mertz, & Robinson, 1985). Isen (1984) also considered the distinction between controlled and automatic processes concerning mood effects. These processes suggest that if mood can have an automatic influence on cognition and on behavior, mood can also influence intentional behaviors, which need effort (e.g., attempts to regulate mood – Silvestrini

& Gendolla, 2007).

Another criticism to Bower’s model comes from Mecklenbrauker and Hager (1984). They argued that this model is too general to allow accurate predictions about the effects of mood on memory, and, moreover, it does not take into account the individuals’ conscious or controlled strategies. According to Teasdale and Barnard (1993), Bower’s associative network theory cannot explain the cognitive-emotional activation underlying depression, due to formal reasons. Indeed, if several nodes are activated simultaneously, the activation is then divided. This reduced activation of a node makes the representation congruent with the mood less accessible, resulting in an increase in the activation threshold. This may call in to question the principle of accessibility of congruent representations defined by Bower’s model (1981). Other criticisms concern the inability of the model to explain the effects of

“mood-incongruency” (Parrott & Sabini, 1990; Smith & Petty, 1995) or the asymmetry highlighted by numerous studies (see Blaney, 1986, for a review).

3.1.1. Other network models

Although most of the research on mood and judgments concerns negative mood and its clinical implications (e.g., MacLeod, 1999; Mineka & Gilboa, 1998; Scott & Ingram, 1998; Williams, Watts, MacLeod & Mathews, 1997, for reviews), there is also some research on positive mood influences on cognitive processing.

Focusing on positive mood, research by Isen (1993, 1999, 2000) generated a large number of results showing positive mood effects on a wide variety of social behaviors and activities or even on complex cognitive processing (learning, memory, resolution problems, categorization, decision making, risk assessment, ...). It should be noted that in most situations, positive mood has a facilitator and not a disruptive influence (Isen, 1993, 1999, 2000).

Isen (1984, 1987) suggests that positive mood causes a change in cognitive organization and an increased perception of relations between concepts. Positive mood is expected to lead to broader, richer cognitive organization; therefore more qualitatively different ideas would be perceived as potentially related or similar. Isen (1987) suggested that the creation of a more complex cognitive context in a positive mood is the result of a preferential activation of positive information, more and better integrated in memory (following a mood-as-priming perspective). However, in a more complex cognitive environment, the positive mood leads to a parallel decrease in cognitive resources available and thus to the use of heuristic processing (which is easier). The processes invoked are mainly strategic, although an automatic component remains. The influence of positive mood on the organization of knowledge has been demonstrated in many experimental situations (Bless, Schwarz, & Wieland, 1996;

Isen, Niedenthal, & Cantor, 1992; Isen, Daubman, & Gorgoglione 1987; Kahn & Isen, 1993; Lee &

Sternthal, 1999; N. Murray, Sujan, Hirt, & Sujan, 1990). N. Murray et al. (1990) have also shown that positive mood facilitates not only the organization of items into broader categories but also greater cognitive flexibility.

Hänze and Hesse (1993) proposed other processes involved in the positive mood influences on cognitive reasoning. According to these authors, positive mood has a direct influence on cognitive processes. They assumed that positive mood facilitates the spread of activation within the semantic network, and thus positive mood has a direct impact by changing the permeability of the network. Isen’s conceptualization of positive mood influences on cognitive processes is mostly strategic: positive mood would cause a decrease in the amount of available resources. Hänze and Meyer (1998) have confirmed and extended the assumptions made by Hänze and Hesse (1993). Accordingly, positive mood fosters the

spread of automatic activation, and additionally the implementation of automatic processes. People in a positive mood would be more likely to choose automatic data processing at the expense of a more controlled, strategic analysis. More specifically, it is predicted that positive mood promotes the recovery of direct and simple solutions in memory while inhibiting the execution of complex and relatively slow processing. According to this approach, positive mood generates the implementation of automatic processes and inhibits the spontaneous use of controlled strategies, which are privileged by neutral or negative moods (Hesse & Spies, 1996).

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