“There is nothing more difficult to take in hand, more perilous to conduct or more uncertain in its success than to take the lead in the introduction of a new order of things.”
Niccolo Machiavelli
As mentioned in the previous theoretical sections, the role of moods in motivation is not clear.
Namely it is not clear if moods have stable motivational implications or if they are context-dependent.
Most of the presented studies focus on the influence moods can have on cognitive processing styles.
Moreover, motivation is a broad concept, and studies linking mood and motivation have taken into account the different dimensions of motivation, such as initiation, direction, persistence, and intensity of behavior (Geen, 1995; Vallerand & Thill, 1993). For example, studies focusing on mood effects on cognitive processes can be related to the initiation and direction of behavior; most of the studies on mood regulation have their focus on the direction of behavior; whereas the pioneer study on mood context-dependency by Martin and colleagues (1993) was centered on persistence. The motivational element of intensity and its relation with mood has been rather neglected. The MBM and the resulting experiments using predictions from this model focused on motivational intensity theory (Brehm & Self, 1989) and offer a perspective to analyze mood effects on resource mobilization. Therefore, both these conceptualizations constitute the main background of the following studies. Besides the controversial data regarding the stability of mood effects, there are no conclusive tests regarding the informational mood impact, since previous studies only measured informational mood impact. Thus, by providing further support for one of the main mood effects admitted by the MBM – the informational mood impact –, the context-dependency of moods will also be investigated.
Our research program included four studies with a similar experimental paradigm across them.
Students of the University of Geneva were exposed to the same procedure consisting of three main parts, within which physiological activity was assessed. Physiological activity was first assessed in a
“relaxation phase”, during which participants observed a documentary movie or the alphabet for about 10 min. The mood manipulation followed by the presentation of movie clips (8 min): a funny excerpt from the movie “Naked Gun 2 ½”, for positive mood induction, while for the negative mood conditions, the depressing end of the movie “Love Story” was presented. Finally, participants had 5 min to perform a mental task – a memory or a concentration task, depending on the studies.
The first study tested the hypothesis if moods per se are motivational states. Our hypothesis was that if moods do not have stable motivational implications, people would only mobilize effort if there is an explicit demand for it; otherwise, no effort or just a modest level of effort mobilization should be observed. After the mood manipulation, the experimental design was implemented in order to present conditions that directly demanded effort (explicit instruction for intentional memorizing) or not (where no incidental memorizing should occur, according to our predictions).
The second study intended to provide a conclusive test of the idea of an informational mood impact on resource mobilization as conceptualized in the MBM (Gendolla, 2000). Thus, moods’ effective diagnostic value for demand appraisals and the difficulty of the cognitive task presented were manipulated, since mood effects on resource mobilization are moderated by objective task difficulty, because individuals use all available information to evaluate the extent of task demand. The main prediction was that moods’ informational impact on effort mobilization diminishes when their diagnostic value is called in to question. Participants were exposed to the mood induction, and before the random allocation to an easy or difficult task, half of them received an explicit reference to the possible effects of the movie clips on their feelings (cue conditions), whereas to the other half of participants no remark was made (no-cue conditions). In the no-cue conditions we expected that the additive effect of mood and objective task difficulty on experienced demand followed the MBM’s predictions: more effort in the negative-mood/easy and the positive-mood/difficult conditions and lower engagement in the positive-mood/easy and the negative-mood/difficult conditions. These differences would be due to subjective demand appraisals: Individuals in a negative mood mobilize more effort than individuals in a positive mood because subjectively experienced demand is higher in a negative mood than in a positive mood. However, if a task is difficult, people in a negative mood mobilize less effort than people in a positive mood, because demand is already experienced as being too high, resulting in disengagement. On the other hand, in the cue condition, we anticipated that task difficulty influence would be preponderant and that the mood impact would be significantly reduced;
thus, more effort should be observed for the difficult task than for the easy task, independently of the mood valence.
Regarding the third and fourth studies, they focused on examining the context-dependency of mood effects on effort intensity. More precisely, the studies tested the hypothesis that moods have no stable motivational effects and that their effect on resource mobilization is determined by a context-dependent informational mood impact as posited in the MBM and inspired from Martin and colleagues’
(e.g., Martin, Ward et al., 1993) research on persistence. To test this assumption we manipulated the type of judgment that participants were asked to use for appraising the task, via “effort mobilization rules”. Different conditions of effort-rules were presented: “enjoy-rule”, “enough-rule”, or no mention to effort mobilization at all (“no-rule”). Participants facing an enjoy-rule should ask themselves if they were enjoying the task; if the answer was yes, they should invest more effort, if the answer was no, they should decrease the amount of effort invested. Participants confronted with an enough-rule, had to evaluate “Do I already invest enough effort?” and guide their effort mobilization by investing less if the answer was yes and by investing more effort if the answer was no. According to MBM, it was expected that with the enough-rule or no-rule, individuals in a positive mood would mobilize less effort than individuals in a negative mood – it was expected that their answer (“Yes, I am investing enough effort”) would lead them to invest less effort. By opposite, it was expected that for the same positive mood, but with an enjoy-rule, individuals would mobilize more effort. Since this last prediction is the most outstanding effect, contrasting with the basic MBM premises, study 4 intended to replicate the enjoy-rule condition. Studies 3 and 4 were integrated with another experiment conducted formerly by Richter (2001), in which results pointed to the context-dependency direction. Therefore, Study 3 and 4 correspond to Experiment 2 and 3 on the last paper presented.
Effort expenditure (or motivational intensity) – our main dependent variable – was operationalized as cardiovascular reactivity, following evidences obtained from the studies from Wright and colleagues (see Wright, 1996, 1998: Wright & Kirby, 2001, for reviews) and Gendolla and collaborators (see Gendolla & Brinkmann, 2005; Richter et al., 2006, for reviews). The assessed cardiovascular indices were SBP, DBP and HR. The three periods (rest, mood manipulation, and task performance) of measurement allowed the observation of changes in cardiovascular activity from rest (baseline level) to task performance. According to Wright’s (1996) integration of Obrist’s (1981) active coping approach with Brehm’s theory of motivational intensity (Brehm & Self, 1989), beta-adrenergic sympathetic influences on the myocardium are proportional to effort or task engagement.
Consequently, among the cardiovascular parameters mentioned above, SBP reactivity is the most reliable indicator of resource mobilization (as explained in further detail in the Theoretical part – section 4.4.).
Besides this main dependent variable, some studies included EDA, as a way to facilitate the definition of a more objective and consolidate view of the informational mood impact. EDA is another autonomic nervous system parameter, linked to sympathetic arousal, and referring to effort
mobilization (Cacioppo et al., 2000). However this measure was considered in an exploratory perspective, since the MBM has no clear predictions regarding EDA (see section 4.8. for a more detailed description).