Thesis
Reference
The influence of implicit anger primes on effort mobilization
FREYDEFONT, Laure
Abstract
This thesis investigates the influence of implicit affect on effort mobilization in cognitive tasks.
More specifically, this thesis focuses on the impact of implicit anger on effort mobilization.
Although the psychological literature counts numerous studies exploring motivation processes and the impact of affective states on motivation, the majority of research has focused on the directional aspect of motivation, neglecting a second aspect of motivation: its intensity. Based on the Implicit-Affect-Primes-Effort model (IAPE, Gendolla, 2012), this thesis investigates the influence of implicit affect on effort mobilization. This model predicts that implicit anger stimuli, as implicit happiness stimuli, should activate knowledge about performance ease, resulting in experiences of lower subjective demand, which influences effort according to motivational intensity theory's predictions on resource mobilization (Brehm & Self, 1989). Based on the IAPE model (Gendolla, 2012), this thesis presents a series of four studies investigating the impact of implicit anger on effort mobilization.
FREYDEFONT, Laure. The influence of implicit anger primes on effort mobilization. Thèse de doctorat : Univ. Genève, 2012, no. FPSE 519
URN : urn:nbn:ch:unige-242130
DOI : 10.13097/archive-ouverte/unige:24213
Available at:
http://archive-ouverte.unige.ch/unige:24213
Disclaimer: layout of this document may differ from the published version.
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Section de Psychologie
Sous la direction du professeur Guido H. E Gendolla
The influence of implicit anger primes on effort mobilization
THESE
Présentée à la
Faculté de psychologie et des sciences de l’éducation de l’Université de Genève
pour obtenir le grade de Docteur en psychologie
par
Laure FREYDEFONT de
Dijon , France
Thèse No 519
GENEVE Octobre 2012
Numéro d’étudiant : 08-345-33
Acknowledgments
Par qui commencer? N’oublier personne….
Une thèse est un travail individuel mais qui demande un entourage professionnel et personnel présent, solide et compréhensif dans les moments difficiles.
Tout d’abord, je tiens à remercier le Professeur Guido Gendolla, directeur de cette thèse sans qui cette aventure n'aurait pas existé. Merci à lui pour m’avoir offert l’opportunité de me dépasser tout au long de ces trois ans. Merci aussi pour sa disponibilité et sa patience.
Merci aux membres du jury, les Professeurs Peter Gollwitzer, David Sander et Fabrizio Butera pour avoir accepté d’évaluer ce travail.
Et que serait une thèse sans la bonne humeur des collègues ?
Merci à Kerstin et Michael pour m’avoir accueilli comme ils l’ont fait, pour leur disponibilité, leur patience et leur soutien à n’importe quel moment. Merci à Nicolas, pas évident de partager un bureau, et pourtant d’une grande aide à chaque instant et toujours avec le sourire. Merci également d’avoir pris le temps et la patience de relire ce travail ; merci aussi pour les précieux conseils qui m’ont permis d’améliorer ce manuscrit.
Et aussi un grand merci à Géraldine, les validations, les fous rires et tous les autres moments on fait de ces trois ans, une période mémorable.
Merci à Isa, les pauses café chaque matin étaient un rituel réellement attendu.
A Céline, Alison, Christian, Aline, Andy, Kim et tous les autres pour toutes ces séances de bavardage, et ces soirées animées qui font de simples collègues des amis.
Enfin parce mes promenades ne s’arrêtaient au 5ème étage, merci à Anne-Laure et Joseph pour leurs anecdotes plus hilares les unes que les autres.
Merci à Bastiaan pour avoir accepté de relire et de corriger l’anglais de ce travail.
Enfin merci à ma famille et à mes amis, Baptiste, Céline, Damien et Maud, qui ont fait preuve d’un soutien imparable malgré la distance.
7
Abstract
This thesis investigates the influence of implicit affect on effort mobilization in cognitive tasks. More specifically, this thesis focuses on the impact of implicit anger on effort mobilization. Although the psychological literature counts numerous studies exploring motivation processes and the impact of affective states on motivation, the majority of research has focused on the directional aspect of motivation, neglecting a second aspect of motivation: its intensity.
Numerous studies have demonstrated that affective stimuli influence judgments and human behavior (Aarts, Custers, & Marien, 1998; Bargh, 1990; Fowles, 1987). Also the influence of affective states on motivation was largely investigated (Darwin, 1872;
Izard, 1991; Izard & Ackerman, 2000). Nevertheless, previous work focused on the directional aspect of motivation. Based on the Implicit-Affect-Primes-Effort model (IAPE, Gendolla, 2012), this thesis investigates the influence of implicit affect on effort mobilization. This model predicts that implicit anger stimuli, as implicit happiness stimuli, should activate knowledge about performance ease, resulting in experiences of lower subjective demand, which influences effort according to motivational intensity theory’s predictions on resource mobilization (Brehm & Self, 1989). By contrast, implicit sadness stimuli should activate knowledge about difficulty, resulting in experiences of higher subjective demand and leading to higher effort intensity than implicit anger stimuli as long as success is important and justified.
In order to provide quantified measures of mental effort intensity, Wright (1996) has integrated motivational intensity theory (Brehm & Self, 1989) with Obrist’s (1981) active coping approach (when individuals can control outcomes), resulting in the prediction that ß-adrenergic sympathetic nervous system impact on the heart responds proportionally to the level of experienced task demand. Cardiac pre-ejection period (PEP) is the most reliable non-invasive index of ß-adrenergic impact.
Based on the IAPE model (Gendolla, 2012), this thesis presents a series of four studies investigating the impact of implicit anger on effort-related cardiovascular response.
8 The first two studies provided evidence for a facilitating effect of implicit anger stimuli during task performance. Results showed that implicit anger stimuli led to lower effort-related cardiac response than implicit neutral stimuli.
The third study demonstrated that implicit anger stimuli moderate the effect of objective task difficulty on cardiac response. Results showed a significant joint effect of implicit affect primes and objective task difficulty on effort intensity.
The fourth study demonstrated a joint influence of implicit affect primes and monetary incentive on effort-related cardiac response. Results found a significant interaction between implicit affect stimuli and incentive.
This thesis provides evidence for the specificity of implicit anger effect on the intensity aspect of motivation. This work demonstrates that implicit anger stimuli influence effort differently than other negative affective stimuli, such as sadness primes.
Moreover, this thesis contributes to the test of a new theoretical model, the Implicit- Affect-Primes-Effort model (Gendolla, 2012), explaining the influence of implicit affect during task performance.
9
Table of contents
Abstract ... 7
I. Theoretical part ... 15
I.1. Impact of Affect on Motivation ... 19
I.1.1. Definitions ... 19
I.1.2. Some Theoretical Models ... 20
I.2. Effort Mobilization: The Intensity of Motivation ... 22
I.2.1. Definitions ... 22
I.2.2. The Motivational Intensity Theory ... 22
I.2.3. Difficulty and Effort Mobilization ... 22
I.3. Cardiovascular Measures of Mental Effort ... 25
I.3.1. The Cardiovascular system ... 25
I.3.1.a. The Heart ... 25
I.3.1.b. The Cardiac Cycle ... 26
I.3.2. Sympathetic and Parasympathetic Systems ... 27
I.3.3. Main Cardiovascular Measures... 27
I.3.3.a. Pre-ejection Period ... 28
I.3.3.b. Systolic, and Diastolic Blood Pressure, and Heart Rate ... 28
I.3.4. Cardiovascular Activity and Effort Mobilization... 29
I.4. Implicit Affect and Effort Mobilization ... 31
I.4.1. Definitions ... 31
I.4.2. Implicit Affect Primes and Behavior ... 32
I.4.3. The Implicit-Affect-Primes-Effort Model ... 32
10
I.5. Anger: A Particular Affect ... 36
I.5.1. Definition ... 36
I.5.2. The Particularity of Anger ... 36
I.5.3. Implicit Anger and Effort Mobilization: Predictions ... 37
I.6. This Present Thesis... 39
I.6.1. Objectives ... 39
I.6.2. Predictions ... 39
II. Experimental Part ... 41
II. 1. Overview of the Studies ... 43
II.2. Studies 1 and 2
:
Implicit Anger versus Implicit Sadness: Effects on Effort- Related Cardiovascular Response ... 45II.2.1. Abstract ... 45
II.2.2. Introduction ... 47
II.2.2.a. Implicit Affect and Effort Mobilization ... 47
II.2.2.b. Anger Effects ... 48
II.2.2.c. Effort-Related Cardiovascular Response ... 48
II.2.2.d. Overview Over the Present Studies ... 49
II.2.3. Study 1 ... 51
II.2.3.a Method ... 51
. Participants and Design ... 51
. Affect Primes ... 51
. Apparatus and Physiological Measures ... 52
. Procedure ... 52
11
II.2.3.b. Results ... 54
. Cardiovascular Baselines ... 54
. Cardiovascular Reactivity ... 55
. Pre-ejection Period (PEP) Reactivity ... 56
. SBP reactivity ... 57
. DBP and HR Reactivity ... 58
. Task Performance ... 58
. Task Rating ... 59
. Affect Rating ... 59
. Funnel Debriefing ... 60
II.2.3.c. Discussion ... 60
II.2.4. Study 2 ... 62
II.2.4.a. Method ... 62
. Participants and Design ... 62
. Affect Primes ... 62
. Apparatus and Physiological Measures ... 63
. Procedure ... 63
II.2.4.b. Results ... 64
. Cardiovascular Baselines ... 64
. Cardiovascular Reactivity ... 65
. Pre-ejection Period (PEP) Reactivity ... 66
. SBP, DBP, and HR Reactivity ... 67
. Task Performance ... 67
. Affect Rating ... 68
. Task Rating ... 68
. Funnel Debriefing ... 68
II.2.5. General Discussion ... 69
12 II.3. Study 3: Beyond Valence: The Differential Effect of Masked Anger and
Sadness Stimuli on Effort-Related Cardiac Response. ... 73
II.3.1.Abstract ... 73
II.3.2. Introduction ... 75
II.3.2.a. Cardiovascular Reactivity and Effort Mobilization ... 76
II.3.2.b. Anger, Sadness and Effort ... 77
II.3.2.c. The Present Experiment ... 77
II.3.3. Method ... 79
II.3.3.a. Participants and Design ... 79
II.3.3.b. Affect Primes ... 79
II.3.3.c. Apparatus and Physiological Measures ... 79
II.3.3.d. Procedure ... 80
II.3.4. Results ... 81
II.3.4.a. Cardiovascular Baselines ... 81
II.3.4.b. Cardiovascular Reactivity ... 82
. Pre-ejection Period (PEP) Reactivity ... 82
. SBP, DBP, and HR Reactivity ... 84
II.3.4.c. Task Performance ... 86
II.3.4.d. Task Rating ... 86
II.3.4.e. Affect Rating ... 87
II.3.4.f. Funnel Debriefing and Prime Recognition Test ... 87
II.3.5. Discussion ... 88
13 II.4. Study 4
:
Incentive Moderates the Impact of Implicit Anger versusSadness Cues on Effort-Related Cardiac Response. ... 91
II.4.1.Abstract ... 91
II.4.2. Introduction ... 93
II.4.2.a. Implicit Affect Primes Effect on Effort Mobilization ... 93
II.4.2.b. The Role of Incentive ... 95
II.4.2.c. Effort Mobilization and Cardiovascular Response ... 95
II.4.2.d. The Present Experiment ... 96
II.4.3. Method ... 98
II.4.3.a. Participants and Design ... 98
II.4.3.b. Affect Primes ... 98
II.4.3.c. Apparatus and Physiological Measures ... 98
II.4.3.d. Procedure ... 99
II.4.3.e. Data Analysis ... 101
II.4.4. Results ... 102
II.4.4.a. Cardiovascular Baseline ... 102
II.4.4.b. Cardiovascular Reactivity ... 103
. PEP Reactivity ... 104
. HR Reactivity ... 105
. SBP and DBP Reactivity ... 106
II.4.4.c. Task Performance ... 107
II.4.4.d. Affect Ratings ... 107
II.4.4.e. Task Ratings ... 108
II.4.4.f. Funnel Debriefing ... 109
II.4.5. Discussion ... 110
14
III. General Discussion ... 115
III.1. Main Results ... 117
III.1.1. Cardiovascular Reactivity ... 117
III.1.1.a. Pre-ejection Period Reactivity ... 118
III.1.1.b. Heart Rate Reactivity ... 119
III.1.1.c. Systolic and Diastolic Blood Pressures Reactivity ... 120
III.1.2. Task Performance ... 120
III.1.3. Subjective Ratings ... 121
III.1.4. Affect Ratings ... 121
III.1.5. Recognition Task and Funnel Debriefing ... 122
III.2. Perspectives ... 123
III.2.1. Implicit Anger and Effort Intensity ... 123
III.2.2. Conscious or Unconscious Influence of Affect ... 124
III.2.3. Duration of Implicit Priming ... 125
III.3. Limitations and Suggestions ... 126
III.4. Conclusions ... 128
IV. References ... 129
French Abstract
...147
1. Influence des Affects sur la Motivation ... 149
2. Intensité de l’Effort et Motivation ... 150
3. Les Indices Cardiovasculaires et leur Implications dans la Mesure Quantitative de l’Effort ... 151
4. Le Modèle « Implicit-Affect-Primes-Effort » ... 151
5. La Colère ... 152
6. Objectifs de cette Thèse ... 153
7. Etudes Expérimentales : Objectifs et Descriptions ... 153
8. Principaux Résultats ... 155
9. Conclusions et Limites ... 156
Theoretical Part
17
I. Theoretical Part
In everyday life, we have to deal with our affective states. Our affect (emotions and moods) influences our judgments and behavior. In psychology, and more specifically in the field of affective sciences, the role of emotions on behavior is at the center of the actual research. As a behavioral booster or inhibitor, affect has an impact on our motivation (Weiner, 1986, 1992).
Our actions are “driven” by motivation. Each movement or engagement in a goal pursuit is the result of motivational processes. To attain a goal, two aspects of motivation are necessary: the direction of action and the intensity involved in goal pursuit (Elliot, 2006). In the psychological literature, numerous studies have investigated the directional aspect of motivation (Aarts, Custers, & Marien, 1998; Bargh, 1990; Gollwitzer, 1990;
Gollwitzer, & Oettingen, 2002; Oettingen, & Gollwitzer, 2009), but the second aspect, the intensity aspect of motivation, has received rather little attention.
The present thesis investigates the influence of implicit affect on effort intensity.
More specifically, this thesis focuses on the impact of implicit anger on effort mobilization. Anger, although categorized as a negative affect, shares some motivational specificities with positive affect. Based on the psychological literature referring to affect and motivation, the Implicit-Affect-Primes-Effort model (IAPE, Gendolla, 2012) posits that implicit affective stimuli influence effort mobilization. Testing this model, numerous studies have investigated the influence of masked happiness and sadness stimuli on effort mobilization (see Gendolla, 2012). Nevertheless, despite of its particularity, the influence of implicit anger primes on effort mobilization has not really been investigated. This present work aims to test anger stimuli’s specific effect on the intensity aspect of motivation.
The first part of the introduction will discuss the influence of affective states on human behavior and more specifically on motivation.
Then, the second part of the introduction will introduce motivational intensity theory (Brehm & Self, 1989), describing principles guiding effort mobilization.
18 The third part of this introduction will discuss cardiovascular measures and how cardiovascular indices can quantify mental effort intensity.
The fourth part will present the IAPE model (Gendolla, 2012) suggesting that implicit affect systematically influences effort mobilization in active coping (i.e., when behavioral outcomes can be controlled).
The fifth part of this introduction will be dedicated to the specificity of our particular affect of interest: anger. This part will also focus on the empirical evidence for the particularity of anger stimuli.
To wrap up, the last part of this introduction will summarize empirical evidence, leading to the presentation of a general hypothesis and specific predictions investigated in the studies conducted in this thesis to investigate the impact of implicit anger on resource mobilization.
19 I.1. Impact of Affect on Motivation
This first part will introduce some definitions of key concepts of this thesis and their role in human behavior. Then, some theories describing the influence of affective states on motivation will be discussed (Damasio, 1994; Fazio, 2001; Zajonc, 1980).
I.1.1. Definitions
“Affect” is used as a general term for subjective experiences with positive or negative valence including emotions and moods (Schwarz & Clore, 2007). These experiences differ in terms of their origin, function, intensity, duration, bodily reaction, behavioral effects, and rapidity of change (Scherer, 2005). “Affect” is generally used for feeling states as compared with rational thinking (Frijda & Scherer, 2009).
Even if the field of emotion is largely investigated, there is no consensus about the definition of “emotion” (see Sander & Scherer, 2009; Scherer, 2005). Nevertheless, Frijda and Scherer (2009) have described features of emotion. Emotion is defined as “an episode of interrelated, synchronized changes in the states of all or most of the five organismic subsystems in response to the evaluation of an external or internal stimulus event as relevant to major concerns of the organism” (Scherer, 2005).
Emotions have an influence on cognitive processes as attention (Baumann &
Kuhl, 2005; Friedman & Förster, 2005), and memory (Isen, 1987, 2008), and on physiological responses (Kriebig, 2010).
By contrast, “moods” are defined as relatively long lasting affective states that are experienced without concurrent awareness of their origins (Frijda, 1993; Schwarz &
Clore, 2007).
“Feeling” can be defined as a subjective cognitive experience, reflecting a unique experience of mental and bodily changes in the context of being confronted with a particular event. There is no other access to feeling than to ask individuals to report on the nature of their experience (Scherer, 2005).
Based on evolution theory (Darwin, 1872), expressions of affects are at the origin of adaptive behaviors. Affects influence the preparation of adaptive behavior and play an
20 important role for survival (Plutchik, 1970, 1994). From the evolutionist point of view, numerous authors have described the impact of affects on processes that underlie actions and behavioral responses. Thus, it is natural that numerous authors investigated the impact of affect on motivation, as process responsible for action, adaptation, and survival.
“Motivation” has been largely defined in the psychological literature. Geen (1995) has described three basic aspects of motivation: the initiation, the intensity, and the persistence of behavior. Moreover, Geen has suggested that motivation is a complex process involving the definition of a goal based on personal aspiration, a selection of a course of action leading to goal attainment, and the execution of the chosen course of action.
I.1.2. Some Theoretical Models
As introduced above, some authors have posited that emotions have an adaptive impact on behavior (Darwin, 1872; Izard, 1991; Izard & Ackerman, 2000). Emotions activate approach and avoidance behavior. From this perspective, numerous theories explain the role of emotions in motivation. Most of them explore the influence of affects on the directional aspect of behavior (see Aue, 2009).
Among them, Plutchik (1970, 1980, 1994) has suggested, in a psycho- evolutionary model, that emotions are indicators of expressions and physiological changes. Based on Darwin’s works, Plutchik posits that eight basic emotions (joy, anticipation, anger, disgust, sadness, surprise, fear and acceptation) are associated with specific adaptive behaviors in specific contexts. An event leads to a cognitive evaluation of the situation, triggering the associated emotion followed by a physiological reaction and then behavior. The function of this sequence is protection and survival.
A different approach is taken by Lang and colleagues (Lang 1994; Lang, Bradley,
& Cuthbert, 1990) who has suggested that behavior is organized on an appetitive-aversive dimension. The authors have distinguished two motivational systems: one for appetitive behavior and the other one for aversion. The motivational system responsible for the appetitive dimension leads to behavioral approach. By contrast, the motivational system responsible for the aversive dimension leads to a behavioral avoidance. This model posits
21 that one of the systems can inhibit the other come involving a moderating effect of positive and negative events.
Among other theoretical models considering motivational-affective systems underlying adaptive behavior, Gray (1994) has proposed three motivational systems: a system managing fight/flight motivation (FFS), a system managing behavioral inhibition (BIS) and a system referring to approach motivation (BAS). Based on this model, numerous studies suggest that positive affect is associated with the BAS, leading to approach, and that negative affect is associated with the BIS, leading to avoidance (see Carver & White, 1994).
These discussed theoretical models focus essentially on the directional aspect of motivation. However, motivation consists of a second aspect: intensity. The Mood Behavior Model (MBM, Gendolla, 2000) suggests predictions about how mood influences effort mobilization during cognitive tasks, investigating the influence of affect on the intensity aspect of motivation. This model posits that moods influence effort mobilization by their informational impact on task demand appraisals via mood- congruency effects (Brinkmann & Gendolla, 2007, 2008; Gendolla, Brinkmann, &
Richter, 2007; Gendolla & Krüsken, 2001; Silvestrini & Gendolla, 2007, 2009a, 2009b).
This results in lower task demand in a happy mood than in a sad mood, leading, in accordance with motivational intensity theory (Brehm & Self, 1989), to lower effort intensity in a happy mood than in a sad mood as long as success is possible and justified (Gendolla, Abele, & Krüsken, 2001; Richter, Gendolla, & Krüsken, 2006).
To summarize, numerous approaches have considered the influence of affective states on motivation. Although the majority of theoretical models focuses on the directional aspect of motivation, the MBM (Gendolla, 2000) explains how moods influence the intensity aspect of motivation. Before discussing the impact of implicit affect on effort mobilization, the second part of this introduction will now focus on the intensity aspect of motivation and discuss variables influencing effort mobilization.
22 I.2. Effort Mobilization: The Intensity of Motivation
I.2.1. Definitions
As already mentioned earlier, the term “motivation” refers to the process determining the direction and the intensity of behavior (Elliot, 2006; Gendolla, Wright, &
Richter, 2012). In this work, we will focus on the second aspect of motivation: effort intensity during cognitive tasks.
Effort is defined as the mobilization of resource to execute instrumental behavior (Gendolla & Wright, 2009). Effort is systematically involved in achievement contexts and goal pursuit (Gollwitzer, 1990, 1993). The factors influencing effort intensity have been described in motivational intensity theory (Brehm & Self, 1989).
I.2.2. Motivational Intensity Theory
Motivational intensity theory (Brehm & Self, 1989) explains resource mobilization during goal pursuit. This model is established on one important postulate.
Based on the basic principle of resource conservation, this theory posits that individuals avoid wasting energy and thus mobilize resources proportionally to subjective task demand. However, to comply further with this principle of resource conservation, effort is mobilized as long as success is possible and justified. When task demand is considered as too difficult or the necessary effort to succeed is not justified, individuals disengage.
Moreover, this model defines “potential motivation” as the maximally justified effort to attain a goal (Wright, 1996). It is determined by needs, outcome expectations, abilities, and performance-contingent incentives. According to motivational intensity theory (Brehm & Self, 1989), potential motivation influences effort mobilization indirectly via its interaction with task difficulty (Brinkmann, 2008).
I.2.3. Difficulty and Effort Mobilization
Based on the principle of resource conservation, motivational intensity theory suggests that effort increase proportionally to task demand as long as success is possible and justified. When potential motivation is low, as described in Panel A of Figure 1, the maximal effort mobilized in the task will be also low. According to the theory, there is no
23 justification to mobilize the high effort that is necessary for challenging the task. By contrast, as described in the Panel B, Figure 1, when potential motivation is high, the model predicts that individual engage in higher effort intensity. As shown in panel B (Figure 1), when task difficulty increases, effort intensity increases up to the task as long as success is possible and justified. When task difficulty is too high or success not justified, we observe disengagement.
Figure 1: Predictions of motivational intensity theory (Brehm & Self, 1989)
According to motivational intensity theory (Brehm & Self, 1989), task difficulty determines effort as long as success is possible and justified. However, if task difficulty is unclear, effort mobilization directly depends on factors influencing potential motivation as success importance. If task difficulty is unclear, individuals do not have task difficulty information and should rely on success importance in accordance with the resources conservation principle to avoid wasting resources (see Richter, 2012; Richter & Gendolla, 2006, 2007, 2009a, 2009b).
24 To summarize, effort mobilization during cognitive tasks relies on one main principle. According to motivational intensity theory (Brehm & Self, 1989), individuals, avoiding wasting energy, mobilize resources proportionately to subjective task demand as long as success is important and justified.
In order to quantify effort intensity during cognitive tasks, Obrist (1981) has demonstrated that cardiovascular activity sensitively responds to task demand in active coping, permitting to quantify effort mobilization during cognitive tasks. The next part will discuss relevant cardiovascular measures used to assess effort mobilization.
25 I.3. Cardiovascular Measures of Mental Effort
Mental effort mobilized during a cognitive task cannot be measured directly.
Numerous types of measures, such as self-reports, are available for conducting studies on effort mobilization during a cognitive task. However, Obrist (1981) has demonstrated that cardiovascular activity sensitively responds to task demand in active coping (when individuals can control outcomes). This part will discuss the functioning of the cardiovascular system and why cardiovascular measures provide relevant indicators of effort intensity.
I.3.1. The Cardiovascular System
The cardiovascular system involves complex cyclic mechanisms to maintain homeostasis. This vital system is a closed system composed of the heart (a pump) and the vasculature (peripheral system of veins and arteries). Through the flow of blood, the cardiovascular system provides oxygen and nutrients required for the functioning of the body’s organs. This transportation system responds to the demands of the body, which can vary extremely. More relevant for our work, Obrist (1981) demonstrated that the cardiovascular system also responds to mental demand.
I.3.1.a. The Heart
“The crucial pump of the cardiovascular system” (Berntson, Quigley, & Lozano, 2007) is a muscle composed of two atriums (right and left) and two ventricles (right and left). The electric activation of the sinoatrial node in the right atrium and of the atrioventricular node in the right ventricular provides the electrical trigger for the contraction of the cardiac muscle. This contraction permits the circulation of the blood through the lungs and then through the organs.
Blood, poor in oxygen, enters into the right atrium by the superior and inferior veins cava. After the filling of the atrium and the opening of the tricuspid valve, the blood fills the right ventricle. The ventricular contraction ejects the blood through the pulmonary valve and sends it into the lung for oxygenation (through the pulmonary artery). During the same contraction, the blood, rich in oxygen goes back into the heart
26 through the pulmonary vein, first into the left atrium and then into the left ventricle, with the opening of the mitral valve. With the ventricular contraction, the blood is ejected into the aorta through the aortic valve. Then the blood, rich in oxygen is transported through the body. During each cardiac contraction, blood is simultaneously ejected into the pulmonary artery and the aorta.
I.3.1.b. The Cardiac Cycle
One cardiac cycle occurs from one beat to the next beat. The cardiac cycle is composed of two main periods: the diastole (filling with blood) and the systole (ejection of the blood from the ventricles).
The cardiac cycle starts with the depolarization of the sinoatrial node during the diastole. This depolarization wave is followed by the atrial contraction. This contraction results in the opening of the tricuspid valve and the passage of the blood from the right atrium to the right ventricle. When the ventricular contraction is sufficiently strong (or pressure in ventricles sufficiently high), the pulmonary and the aortic valves open and the blood is ejected from the ventricles to the body. When the pressure in the ventricles falls at the end of the systole, the valves permitting blood ejection from ventricles close, and the valves linking the atriums and ventricles open. At the end of the systole, the ventricles are re-polarized. The ejection of the blood from the ventricles and the fall of the ventricles’ pressure announce the beginning of the diastole period and the beginning of a new cycle.
The heart can perform autonomously with an activity around 105-110 beats/minute. To respond to body demands, there exist two branches of the autonomic nervous system permitting an increase or a decrease of cardiovascular activity. These branches are the sympathetic and parasympathetic nervous systems.
27 I.3.2. Sympathetic and Parasympathetic Systems
The cardiovascular system is influenced by two branches of the autonomic nervous system: the sympathetic and parasympathetic nervous systems, which influence cardiac activity in two opposite ways.
The sympathetic nervous system is an important actor for the vascular cardiac muscle (Berntson et al. 2007). The sympathetic nervous system is usually identified as the system responsible of the increase of cardiac activity by an increase of the activity of ß- adrenergic receptors. The ß-adrenergic impact directly influences the contractility force of the cardiac muscle. The sympathetic nervous system also influences the cardiovascular system by affecting the contraction of the veins and arteries by increased α-adrenergic impact (Brownley et al., 2000).
By contrast, the parasympathetic nervous system is identified as supporting energy storage. It influences the cardiac system as an inhibitor system.
Consequently, the sympathetic nervous system is involved in action and increase of cardiac activity. More specifically, Obrist (1981) showed that active coping involves stronger β-adrenergic impact. Consequently, indicators of β-adrenergic impact should refer to effort mobilization.
I.3.3. 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 ß-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 (Harmon-Jones, 2003a; Harmon-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 stimuli. Secondly, we investigated the moderating effect of implicit anger stimuli on effort intensity manipulating task difficulty and monetary incentive.
In the first two studies we tried to extend results by Gendolla and Silvestrini (2011). In order to provide evidence for the facilitating impact of masked anger stimuli on effort-related cardiac response. In this vein, we added a control condition using neutral facial expressions. Results found further support for a facilitating effect of implicit anger stimuli.
With the third study, we investigated the joint effect of implicit affect primes and objective task difficulty on effort mobilization. We compared masked anger stimuli in comparison with another negative affect (sadness). As predicted, results showed a significant interaction effect between implicit affect primes and objective task difficulty on effort mobilization.
In the fourth study, we focused on the joint impact of implicit affect primes and monetary incentive. As observed in the Study 3, in a difficult task context, sadness primes lead to disengagement and masked anger prime to an increase of effort intensity. In this study, we investigated the question if incentive in a difficult task context can eliminate the effort deficit of people primed with sadness, leading to higher effort than in the implicit anger condition.
45 II.2. Studies 1 and 2
: The Facilitating Effect of Implicit Anger: More Evidence in Terms of Effort-Related Cardiovascular Response
Freydefont, L., Gendolla, G. H. E., & Silvestrini, N. (2012). The facilitating effect of implicit anger: more evidence in terms of effort-related cardiovascular response.
Manuscript submitted for publication.
II.2.1.Abstract
Previous studies have revealed that implicit anger leads, under “do-your-best”
instructions, to weaker effort-related cardiac response than implicit sadness (Gendolla &
Silvestrini, 2011). The present two experiments further tested whether implicit anger has a facilitating effect during task performance. Both studies assessed cardiovascular activity during a habituation period and a cognitive task during which participants were exposed to suboptimally presented facial anger vs. neutral vs. sadness expressions. In Experiment 1, cardiac pre-ejection period (PEP) reactivity was weaker in the anger-prime condition than in the neutral-prime condition, but only during the first minute of task performance.
In Experiment 2, PEP reactivity was weaker with anger primes than with both neutral and sadness primes. The findings further support the implicit-affect-primes-effort model (IAPE; Gendolla, 2012) and suggest a facilitating effect of implicit anger during task performance.
Key words: Anger, Implicit affect, priming, effort-related cardiac response.
47 II.2.2. Introduction
Recent studies from our laboratory have revealed that implicit affect priming systematically influences effort-related cardiovascular response (e.g., Freydefont &
Gendolla, 2012; Freydefont et al., 2012; Gendolla & Silvestrini, 2011). In these studies, implicit anger primes had a different impact on effort mobilization than sadness primes:
When participants performed under “do-your-best” instructions, implicit anger led to weaker cardiovascular response than implicit sadness. However, our previous studies did not involve neutral prime control conditions. Thus, it is still questionable if implicit anger really has a facilitating effect during task performance, as suggested by the implicit- affect-primes-effort model (IAPE; Gendolla, 2012)—the theoretical framework that guided this research. To investigate this issue, the present studies compared implicit anger primes’ effects on effort-related cardiovascular response with those of a neutral-prime control condition and a sadness-prime condition.
II.2.2.a. Implicit Affect and Effort Mobilization
Numerous studies have demonstrated that masked affective stimuli systematically influence evaluative judgments and human behavior (e.g., Murphy & Zajonc, 1993;
Öhman, Flykt, & Lundquist, 2000; Winkielman, Berridge, & Wilbarger, 2005). Implicit affect priming has these effects through the activation of mental representations of emotions (Zemack-Rugar, Bettman, & Fitzsimons, 2007). As masked words or objects can activate semantic knowledge in long-term memory (see Förster & Liberman, 2007 for a review), affect primes can influence evaluative judgments and behavior by activating emotion concepts in memory (see Niedenthal, 2008).
Recent studies from our laboratory tested the idea that affect primes that are processed during task performance systematically influence the level of experienced task demand and effort (Freydefont & Gendolla, 2012; Freydefont et al., 2012; Gendolla &
Silvestrini, 2011; Lasauskaite, Gendolla, & Silvestrini, in press; Silvestrini & Gendolla, 2011b, 2011c). According to the IAPE model (Gendolla, 2012), affect primes implicitly activate mental representations of the respective affective states that contain acquired information about performance ease and difficulty that is typical for the respective emotions, leading to experiences of lower or higher task demand during performance.
Task demand, in turn, determines effort intensity as long as success is possible and
48 justified, as outlined in motivational intensity theory (Brehm & Self, 1989; see Gendolla, Wright, & Richter, 2012 for a recent review). Supporting these ideas, studies based on the IAPE model have found that sadness primes indeed lead to stronger effort-related cardiac response than both happiness and anger primes, when people perform under “do-your- best” instructions (Gendolla & Silvestrini, 2011). These effects occurred because sadness primes led to higher subjective task demand and in turn to stronger effort-related cardiac response. Follow-up studies further confirmed the differential effect of implicit anger vs.
sadness on effort-related cardiac response (Freydefont & Gendolla, 2012; Freydefont et al., 2012).
II.2.2.b. Anger Effects
Additionally to our research on the systematic impact of implicit anger on effort- related cardiac response discussed above, there is more evidence that anger stimuli influence evaluative judgments (Smits & Kuppens, 2005), behavior (Wacker, Hedmann,
& Stemmler, 2003), and attention (van Honk, Tuiten, de Haan, van den Hout, & Stam, 2001). Although anger has negative valence, numerous studies have shown that it shares motivational properties with positive affect (Carver & Harmon-Jones, 2009; Harmon- Jones, 2003a). Anger is associated with an approach orientation (Carver & Harmon- Jones, 2009; Harmon-Jones, 2003b) and, most relevant, anger is linked to high optimism and experiences of high control (Lerner & Keltner, 2001). Moreover, Putman, Hermans, and van Honk, (2004) found a facilitating effect of angry faces on selective attention. In this study, participants with low trait anger faster identified colors in a Stroop task when they were exposed to angry faces than when neutral faces were presented. Altogether, this suggests that anger should have a facilitating effect on behavior: Anger should be associated with ease.
II.2.2.c. Effort-Related Cardiovascular Response
According to Wright’s (1996) integration of motivational intensity theory (Brehm
& Self, 1989) with Obrist’s (1981) active coping approach, beta-adrenergic sympathetic impact on the heart responds proportionally to the level of experienced task demand as long as success is possible and justified. Noninvasively, beta-adrenergic impact is best assessed as increased cardiac contractility and thus shortened cardiac pre-ejection-period
