Main Cardiovascular Measures

Numerous cardiovascular activity measures permit an evaluation of the cardiac activity at rest and during activity (physical or mental). Among these different indices, some are influenced by the sympathetic branch of the autonomic nervous system, some by the parasympathetic system, and some by both. The following measures were considered as quantitative measures of effort mobilization in numerous studies (for a review, see Wright & Gendolla, 2012).

28 I.3.3.a. Pre-ejection Period

The cardiac pre-ejection period (PEP) is defined as the time interval between the onset of the heart’s left ventricular excitation and the opening of the aortic valve (Berntson, et al., 2004). This cardiac index is measured in milliseconds (ms) and refers directly to the contractility of the left ventricle before blood ejection into the vasculature.

PEP is directly influenced by ß-adrenergic impact on the heart (Kelsey, 2012). The shorter the PEP is, the stronger is contractility. As PEP is directly influenced by ß-adrenergic impact, this indicator is the most reliable index of effort.

I.3.3.b. Systolic, and Diastolic Blood Pressure, and Heart Rate

Blood pressure can be measured by two indices: systolic blood pressure (SBP) and diastolic blood pressure (DBP). In each cardiac cycle, blood pressure varies between a maximal (systolic) and a minimal (diastolic) pressure. By definition, SBP is the maximal arterial pressure after a heart beat (during the systole). DBP is the minimal pressure during the diastole period of the cardiac cycle, i.e., the minimal arterial pressure between two heart beats. Both SBP and DBP are measured in millimeters of mercury (mmHg), with typical rest values around 120 mmHg for SBP and around 70 mmHg for DBP in young healthy adults.

SBP and DBP are both influenced by cardiac output but also by total peripheral resistance (the level of resistance to the blood flow in veins and arteries composing the systemic circulation). An increase in cardiac activity leads to an increase in blood pressure, especially SBP. Because DBP is much more influenced by total peripheral resistance, it does not represent an estimate of ß-adrenergic impact.

Heart Rate (HR) is defined as the number of beats emitted by the heart per minute.

One beat happens each cardiac cycle. A “normal” HR is around 60-80 beats/minute at rest. HR has largely been used to assess arousal. However as we will discuss in the following part, this index is influenced by both sympathetic and parasympathetic impact, and thus not very suitable for monitoring effort.

29 I.3.4. Cardiovascular Activity and Effort Mobilization

Obrist (1981) has suggested that cardiovascular activity can be a relevant indicator of task engagement (i.e., effort) in cognitive tasks. Obrist (1976) has posited that cardiac activity increases proportionally with task demand only when individuals have control over performance outcomes (active coping). More relevant, the author found that β-adrenergic impact on cardiovascular activity is proportional to task demand. Wright (1996) has integrated the active coping approach (Obrist, 1981) with motivational intensity theory (Brehm & Self, 1989). Accordingly, effort intensity during cognitive tasks can be quantified as adrenergic impact on the heart. As discussed above, ß-adrenergic impact directly influences cardiac contractility. PEP is the most reliable noninvasive index to assess ß-adrenergic impact. Consequently, PEP is the most reliable cardiovascular index of effort mobilization (Gendolla & Silvestrini, 2011; Kelsey, 2012;

Silvestrini & Gendolla, 2011c; Richter, Baeriswyl, & Roets, 2012).

However, numerous authors have also considered SBP as an index of effort (e.g., Silvestrini & Gendolla, 2007, 2009a, 2009b; Wright, 1998; Wright & Dismukes, 1995;

Wright & Kirby, 2001). SBP is systematically influenced by cardiac contractility but also by peripheral resistance. Thus, SBP cannot be considered as the better indicator of effort-related cardiac activity than PEP. DBP is even more strongly influenced by total peripheral resistance. Thus, DBP is a less suitable effort measure than SBP. HR is influenced by sympathetic and parasympathetic nervous system. Consequently, we consider PEP as the best indicator of effort among these measures (Kelsey, 2012).

However, one should record SBP, DBP and HR together with PEP to control for possible pre-load and after-load effect on PEP, as will be explained below.

Besides reflecting ß-adrenergic impact, some authors suggest that cardiac pre-load and after-load can influence PEP reactivity (Sherwood, Dolan, & Light, 1990). The pre-load effect refers to the amount of ventricular filling during the diastole (Newlin &

Levenson, 1979). This means that an increase in ventricular filling increases the force of myocardial contractility, and thus shortens PEP. In this case, decreases in PEP do not reflect increase in ß-adrenergic activity. If PEP is influenced by pre-load, HR will decrease. Observing of an increases or stability of HR coupled with a decrease in PEP indicates the absence of a pre-load effect.

30 The after-load effect refers to the load against which the ventricle contracts (Newlin, 1979). The left ventricle exerts pressure until the aortic valve opens. This means that if PEP is influenced by peripheral resistance (after-load effect) and not by ß-adrenergic activity, we should observe a decrease in PEP together with a decrease in DBP. Observing increased or stable DBP coupled with a decrease in PEP can be interpreted as indicating an absence of after-load effects. Moreover, in studies investigating effort intensity in cognitive tasks, in a stable position of the body, pre-load effects are very unlikely (Bernston et al., 1993; Cacioppo et al., 2000; Kelsey, 1991).

To summarize, based on Obrist’ work (1976, 1981) and Wright’s (1996) elaboration, effort in active coping can be quantified as ß-adrenergic impact on the heart (Gendolla, 2004). Among cardiovascular indices, PEP constitutes the purest non-invasive indicator of ß-adrenergic impact (Kelsey, 2012; Sherwood et al., 1990), and thus the most reliable index of effort.

As discussed above, this thesis focuses on the intensity aspect of motivation and the impact of implicit affect primes on effort mobilization. Thus, the next chapter of this introduction will introduce the influence of implicit affect on effort mobilization.

31 I.4. Implicit Affect and Effort Mobilization

A large body of recent work has shown that mechanisms of motivation are generated by cognitive, affective, and action-related systems to execute behavior (Aarts, Custers, & Marien, 1998; Bargh, 1990). Among them, research investigating the relationship between affective states and goal striving suggests that positive emotional states, compared to negative emotional states, facilitate goal striving (Kazén & Kuhl, 2005). In this study, the authors found a Stroop interference (Stroop, 1935) reduction after positive achievement primes. By contrast, they observed increased Stroop interference after primes related to negative achievement episodes.

However, numerous studies investigating the influence of affect on motivation use experimental paradigms which permit implicit (i.e., suboptimally) stimuli presentation.

After having defined the concepts of “priming” and “implicit”, we will present the Implicit-Affect-Prime-Effort model (Gendolla, 2012), which makes predictions about the influence of implicit affect on effort mobilization.

I.4.1. Definitions

Implicit priming is a process permitting to activate mental representations by presenting stimuli suboptimally (outside of awareness). Usually, priming increases the level of accessibility of concepts in memory. The literature on motivation reports numerous studies showing an impact of implicit priming on the activation of goal concepts (see Dijksterhuis & Aarts, 2010, Kruglanski et al., 2002). Moreover, implicit priming is also used to activate implicit affect.

Implicit affect priming refers to the automatic activation of affect-related knowledge in memory (Quirin, Kazen, & Kuhl, 2009). Accordingly, it has been posited that affective stimuli activate knowledge about affective states and systematically influence behavior without eliciting explicit affect intensity of conscious feeling (Gendolla, 2012).

32 I.4.2. Implicit Affect Primes and Behavior

Numerous studies have found that exposure to suboptimally presented affective stimuli systematically influences evaluative judgments and human behavior (e.g., Murphy

& Zajonc, 1993; Öhman, Flykt, & Lundquist, 2000; Winkielman, Berridge, & Wilbarger, 2005). For example, Winkielman and collaborators (2005) reported that implicit affect priming influences consumption behavior. The authors demonstrated that participants primed with happiness stimuli drink higher quantities of an unknown beverage than participants primed with anger stimuli. Correspondingly, Isen and Reeves (2005) have demonstrated that induced explicit positive affect increases the degree to which an enjoyable task is liked.

As masked words or objects can activate semantic knowledge in long-term memory (Förster & Liberman, 2007; Higgins, 1996), masked affective stimuli can influence evaluative judgments and behavior by activating emotion concepts (see Niedenthal, 2008). As concepts are mental representations of experiences, situations, and actions in memory, Niedenthal defines emotion concepts as knowledge about affective states. Activated, this knowledge provides information for judgments and evaluations.

Recent studies have also revealed that implicit affect primes, activating emotion concepts, influence the subjective evaluation of task difficulty and consequently effort mobilization in task performance contexts (Gendolla & Silvestrini, 2011; Lasauskaite, Gendolla, &

Silvestrini, 2012; Silvestrini & Gendolla, 2011b, 2011c).

I.4.3. The Implicit-Affect-Primes-Effort Model

As demonstrated in several studies, affective states influence effort mobilization (e.g., Brinkmann & Gendolla, 2007, 2008; Silvestrini & Gendolla, 2009a, 2009b). Based on the Mood-Behavior-Model (Gendolla, 2000), moods influenced the subjective evaluation of task difficulty. Gendolla, and Krüsken (2001) demonstrated that after music presentation manipulating mood states, participants modulated their effort mobilization during subsequent task performance. The authors reported that in an easy task context, sad mood led to higher effort-related cardiovascular response than happy mood. By contrast, in a difficult task context, the authors observed the opposite pattern: higher

33 effort-related cardiovascular response in a happy mood than in a sad mood. However, these effects were demonstrated with conscious moods.

As reported above, implicit affect primes can influence judgments and behavior.

Recent research showed that implicit affect primes, by activation of emotion concepts in memory, also influence evaluative judgments (see Niedenthal, 2008). Based on these results, implicit affect primes could have the same effect on effort as conscious moods. In this sense, implicit affect primes should influence effort mobilization by their impact on subjective task demand.

Figure 2. The basic assumptions of the IAPE model about a link between affect primes (sadness, fear, happiness, and anger), activated knowledge about ease or difficulty, experienced task demand, and effort mobilization as long as success is possible and justified (Figure from Gendolla, 2012, facial pictures from the AKDF- Lundqvist, and Litton, 1998).

34 The Implicit-Affect-Primes-Effort model (IAPE, Gendolla, 2012) posits that implicit affect primes influence evaluative judgments and behavior by activating emotion knowledge. The primes’ influence depends on the accessibility and applicability of mental representations according to general principles of knowledge activation, i.e., priming-effects on judgment and behavior (see Förster & Liberman, 2007).

The IAPE model explains the influence of implicit affect on effort mobilization in active coping. According to motivational intensity theory (Brehm, and Self, 1989), effort is mobilized proportionally to the level of subjective task demand as long as success is possible and justified (Brehm & Self, 1989; Wright & Kirby, 2001). The IAPE model suggests that effort, respecting the resource conservation principle, will be mobilized in dependence on the evaluation of available information concerning task difficulty. Implicit affect stimuli will influence the subjective evaluation of task demand according to accessible information about performance ease or difficulty, which is typical for the respective emotion accessible. As depicted in Figure 2, happiness and anger stimuli are associated with ease. Consequently, subjective demand will be low. By contrast, sadness and fear stimuli are associated with difficulty and will increase subjective task demand.

As subjective task demand influences effort mobilization, implicit sadness and fear cues will lead to higher effort intensity than implicit happy and anger cues, as long as success is possible and justified.

Studies from our laboratory testing of the IAPE model used the same procedure (Gendolla, & Silvestrini, 2011; Lasauskaite et al., 2012; Silvestrini & Gendolla, 2011a, 2011b, 2011c). First, the authors assessed biographical data and self-report measures of participants’ feeling state before exposure to the affect primes. Next, the protocol started with a habituation period (8 min) assessing cardiovascular baseline values at the rest.

During this period, participants watched a hedonically neutral video. Then participants received task instructions and performed training trials followed by the task. Usually, participants performed a mental concentration (Brickenkamp, 1981) or a short term memory task (Sternberg, 1966).

To test the influence of implicit affect on effort-related cardiac response, briefly flashed and backward-masked pictures of emotional expressions were integrated into the task. Each trial started with a fixation cross at the center of the screen (1000 ms) followed by a flashed facial expression (26 ms) directly followed by a backward mask (133 ms).

To avoid fast adaptation to the emotional expression, only 1/3 of the trials presented an

35 emotional expression, while 2/3 presented neutral expressions. Then, the item of the cognitive task appeared followed by the message “response entered” presented for 3 sec.

minus participants’ reaction time in order to keep the task duration identical for each participant. To prevent affective reactions that could interfere with the affect primes’

impact (e.g., Kreibig, Gendolla, & Scherer, 2010), we gave no feedback in the experimental trials.

After the task, participants retrospectively rated subjective demand and the same affect items that had been assessed at the beginning of the experiment to assess possible affect prime effects on conscious feelings. To finish, the efficiency of the implicit priming procedure was assessed with prime recognition test or a funnel debriefing procedure (Bargh & Chartand, 1996).

To summarize, there is no doubt that affective states influence human behavior.

Numerous studies have demonstrated the impact of emotions on judgment and behavior.

Moreover, Gendolla’s (2012) IAPE model explains the influence of implicit affect on effort mobilization. Nevertheless, the majority of studies presented refer to the impact of positive or negative affects, especially happiness and sadness (Silvestrini & Gendolla, 2011c). The IAPE model suggests that implicit anger primes influence effort mobilization similarly as happiness stimuli. However, despite the specificity of anger, the influence of implicit anger on effort mobilization is still under investigated. In a recent study, Gendolla and Silvestrini (2011) found that implicit anger faces lead to lower effort intensity than implicit sadness faces in a “do your best” task context. These results demonstrated, for the first time, the influence of implicit anger primes on effort intensity in active coping context. Nevertheless, investigations on the impact of implicit anger stimuli still uncompleted.

36 I.5. Anger: A Particular Affect

The aim of this thesis is to test the IAPE model predictions’ concerning the influence of implicit anger on effort mobilization. After discussion of relevant anger characteristics, this fifth part of the present introduction will outline general predictions guiding the studies conducted in this thesis.

I.5.1. Definition

“Anger is a negatively valenced emotion characterized by high arousal” (Kuppens, 2008). Anger has been characterized as one of the basic emotions described by Ekman and Friesen (1975) and Plutchik (1980). Moreover, anger serves a variety of adaptive functions in self-defense (Izard & Kobak, 1991; Lemeris & Dodge, 2008; Lewis et al., 1992). Appraisal theories of emotions (e.g., Scherer, Schorr, & Johnstone, 2001) suggest that anger is elicited by the appraisal of an event as relevant, important for the self, but incongruent with the personal’s motives and well-being (Kuppens, 2008). Theoretically, anger stimuli induce threat and avoidance. Accordingly, it has been posited that anger stimuli should induce feelings of fear (Berkovitz & Harmon-Jones, 2004a, 2004b).

Nevertheless, based on Fridja’s works about action tendencies (1986, 2007), fear predisposes avoidance. By contrast, anger itself motivates attack, i.e., behavioral approach. Moreover, from a functionalist perspective, anger’s function is to overcome potential obstacles in goal pursuit (Saarni et al., 2006).

I.5.2. The Particularity of Anger

Although anger is classified as a negative affect, numerous studies suggest that anger stimuli lead to behavioral responses that are similar to those of happiness stimuli.

From a neuroscientific point of view, it has been shown that anger stimuli activate the left prefrontal cortex (Jones, 2003a; Jones & Allen, 1998; Harmon-Jones et al., 2003; van Honk & Schutter, 2006; Wacker, Heldmann, &, Stemmler, 2003).

These studies have demonstrated that anger stimuli lead to similar neural activations as positive affective stimuli, illustrating the special status of anger in comparison with others negative affects, which activate the right prefrontal cortical region.

37 Moreover, recent studies have demonstrated that anger is associated with activation of the Behavioral Approach System (BAS) (Caver & Harmon-Jones, 2009;

Harmon-Jones, 2003b; Harmon-Jones & Allen, 1998; Harmon-Jones et al., 2009).

According to the BIS (Behavioral Inhibition System) / BAS (Behavioral Approach System) model (Gray, 1982; Carver & White, 1994), positive affect is associated with approach behavior and negative affect is associated with inhibition. Most relevant, Lerner and Keltner (2001) demonstrated that angry individuals were highly optimistic and also felt they had high control over the situation. For achievement contexts, this last study suggests that a high level of control leads one to consider a task as easier. It follows that anger should reduce the subjective demand during performance (Wright & Dismukes, 1995).

Moreover, based on the systematic impact of affect stimuli on human behavior, numerous studies showed that anger stimuli systematically influence evaluative judgments (Adams, 2006; Smits & Kuppens, 2005), behavior (Wacker, et al., 2003), and attention (van Honk, et al., 2001). Van Honk and colleagues (2001) demonstrated an attentional bias for masked angry faces showing a facilitating effect of implicit anger stimuli on attention.. According to recent findings suggesting that anger is associated with ease, Putman and colleagues found that implicit anger stimuli have a facilitating effect on emotional Stroop performance (Putman, Hermans, & van Honk, 2004).

I.5.3. Implicit Anger and Effort Mobilization: Predictions

Results from the studies cited above suggest that exposure to anger primes can activate emotion knowledge about performance ease. Gendolla and Silvestrini (2011) confirmed this by showing that masked anger stimuli presented during cognitive tasks influence effort intensity. Anger and happiness primes led to lower effort than sadness primes in a “do your best” task context.

To summarize, despite clear evidence for the similarities between the effects of anger and positive affect on behavior, studies investigating the impact of implicit anger stimuli on effort mobilization during cognitive tasks are still rare.

38 Nevertheless, according to studies showing that anger stimuli share numerous motivational similarities with happiness stimuli, we can posit, according to the IAPE model (Gendolla, 2012) and Gendolla and Silvestrini’ (2011) results that implicit anger stimuli will influence effort mobilization similarly as happiness primes. Anger stimuli activate the anger emotion concept that is linked with ease, leading to reduce task demand.

39 I.6. This Present Thesis

This thesis investigates the impact of implicit affect on the intensity aspect of motivation. More specifically, this thesis aims to provide evidence for the moderating impact of implicit anger stimuli on effort intensity during cognitive tasks.

I.6.1. Objectives

Based on the IAPE model (Gendolla, 2012), implicit affective stimuli influence subjective task demand, which in turn influences effort mobilization in cognitive tasks.

Indeed, anger shares numerous motivational properties with positive affects in motivation (Harmon-Jones, 2003b). Moreover, recent studies showed a systematic influence of implicit affect primes on subjective task difficulty and effort (Gendolla & Silvestrini, 2011; Lasauskaite et al., 2012; Silvestrini & Gendolla, 2011b, 2011c). Most relevant, Silvestrini and Gendolla (2011) found that implicit anger stimuli led to lower subjective task demand than implicit sadness primes, demonstrating for the first time the moderating effect of implicit anger during task performance. This study demonstrated the facilitating effect of implicit anger stimuli on effort mobilization, but it also invite interrogations concerning the facilitating effect of implicit anger stimuli and the joint impact of task difficulty and monetary incentive on effort intensity, which will be investigated in the experimental part of this thesis.

I.6.2. Predictions

Using cardiovascular indices, and more specifically PEP as quantitative indicator of effort intensity (Kelsey, 2012), this thesis investigates the impact of implicit anger on effort-related cardiac response. Based on previous work showing that implicit affect primes can activate emotional knowledge influencing the experience of task demand, we predict that implicit anger should have a similar influence as implicit happiness on effort-related cardiac response: Implicit anger should be associated with the experience of performance ease.

Experimental Part

43

II. Experimental Part

II.1. Overview of the Studies

With the series of studies realized for this thesis, we tested the specificity of anger prime impact on effort-related cardiovascular response, compared to masked sadness stimuli. Moreover, we aimed to test the moderating effect of anger. First, we aimed to demonstrate that masked anger stimuli lead to lower effort intensity than masked neutral

With the series of studies realized for this thesis, we tested the specificity of anger prime impact on effort-related cardiovascular response, compared to masked sadness stimuli. Moreover, we aimed to test the moderating effect of anger. First, we aimed to demonstrate that masked anger stimuli lead to lower effort intensity than masked neutral