Prime visibility and prime warning as moderators of affect primes' effect on effort mobilization

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Thesis

Reference

Prime visibility and prime warning as moderators of affect primes' effect on effort mobilization

FRAMORANDO, David

Abstract

The present thesis investigated the role of prime awareness as a moderator of affect priming in the context of effort mobilization. Based on the Implicit-Affect-Primes-Effort model (Gendolla, 2012), which make predictions about implicit affect primes' effect on mental effort, I investigated the role of prime visibility and prime warning as potential boundary conditions of affective influences on effort-related cardiovascular response. To do this, four experiments are reported. Cardiac pre-ejection period (PEP), systolic and diastolic blood pressure, and heart rate were recorded to assess effort-related cardiovascular response. Additionally, to monitor performance, we assessed reaction times and response accuracy.

FRAMORANDO, David. Prime visibility and prime warning as moderators of affect primes' effect on effort mobilization. Thèse de doctorat : Univ. Genève, 2019, no. FPSE 735

DOI : 10.13097/archive-ouverte/unige:120288 URN : urn:nbn:ch:unige-1202886

Available at:

http://archive-ouverte.unige.ch/unige:120288

Disclaimer: layout of this document may differ from the published version.

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Section de Psychologie

Sous la direction de Prof. Guido H. E. Gendolla

PRIME VISIBILITY AND PRIME WARNING AS MODERATORS OF AFFECT PRIMES' EFFECT 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

David FRAMORANDO

de Vaud, Suisse

Thèse No 735 GENEVE Mai, 2019

Numéro d'étudiant: 08309627

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Prime Awareness and Effort Mobilization 2

Abstract

The present thesis investigated the role of prime awareness as a moderator of affect priming in the context of effort mobilization. Based on the Implicit-Affect-Primes-Effort model (Gendolla, 2012), which make predictions about implicit affect primes’ effect on mental effort, I investigated the role of prime visibility and prime warning as potential boundary conditions of affective influences on effort-related cardiovascular response. To do this, four experiments are reported. Cardiac pre-ejection period (PEP), systolic and diastolic blood pressure, and heart rate were recorded to assess effort-related cardiovascular response. Additionally, to monitor performance, we assessed reaction times and response accuracy.

In the experiments, participants worked with moderate to challenging mental

concentration tasks during which pictures of emotional faces were presented. In Studies 1-3, prime awareness was manipulated with prime visibility: for half of the participants,

emotional primes were presented suboptimally (i.e. briefly flashed and masked), whereas primes appeared clearly visible for the other half in an optimal prime presentation condition.

Additionally, in Study 4 prime awareness was manipulated by warning participants about the priming procedure: half of the participants were informed before the task that affective faces would be presented during the mental concentration task, whereas the other half was not. Besides the primary goal of testing prime awareness as a boundary condition of affect priming in the context of effort mobilization, we also controlled for the possible role of gender as a potential moderator of this effect in Study 4.

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Results of Studies 2 and 3 revealed that briefly flashed sadness and fear primes led to higher effort mobilization than anger primes, which fits with previous research in the context of the IAPE model (e.g., Chatelain & Gendolla, 2015; Gendolla & Silvestrini, 2011; Silvestrini

& Gendolla, 2011c). By contrast, clearly visible primes’ effect on effort mobilization differed from the predictions of the IAPE model in terms of zero or contrast effects. In addition, Study 1 - in which PEP could not be analyzed due to technical problems - and Study 2 both

revealed performance effects. More specifically, in the suboptimal prime presentation condition, fear and sadness primes led to higher response accuracy than anger primes, which corresponds on the performance level to what had been predicted and previously found for effects on effort assessed as cardiac PEP (e.g., Chatelain & Gendolla, 2015;

Gendolla & Silvestrini, 2011). Importantly, the affect primes’ effects on response accuracy were inversed in the optimal prime presentation condition: we found higher response accuracy for anger primes than for fear or sadness primes, which suggests behavior

correction when the primes were clearly visible. Finally, in Study 4, prime warning was also found to moderate affect primes’ effect on cardiovascular response: participants mobilized more effort in a happiness- than in a sadness-prime condition which corresponds to the pattern of a challenging task, but only when participants were not warned about the occurrence and the possible effect of the primes. Taken together, the results of the present studies suggest that prime visibility and prime warning induced controlled prime processing that moderated implicit affects’ effect on effort mobilization. In addition, Studies 3 and 4 found that this moderator effect applied especially to men. The present findings are discussed and ideas for possible future research are brought to attention.

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Chapter 1. Introduction

We are every day confronted with a vast amount of visual information that could implicitly affect our behavior (Bijleveld, Custers, & Aarts, 2009; Chartrand & Bargh, 1996;

Dijksterhuis & Van Knippenberg, 1998; Fazio, Sanbonmatsu, Powell, & Kardes, 1986; Koole &

Coenen, 2007). The implicit processing of visual information and its impact on behavior is defined by Bargh (1992) as automaticity - the processing of visual information triggers automatic processes that modify our opinions, choices, or states of mind. Only a few of the numerous studies that investigated automaticity effects were interested in implicit affective stimuli’s impact on behavior (e.g., Brosschot, Verkuil, & Thayer, 2010; Winkielman, Berridge,

& Wilbarger, 2005; Zemack-Rugar, Bettman, & Fitzsimons, 2007). Considering this, the present thesis focuses on automatic processes triggered by implicit affect. More specifically, the present thesis aimed to understand how and when the automatic processes triggered by the implicit affect work.

Recently, the behavioral impact of implicit affective stimuli was investigated in the context of effort mobilization - implicitly priming emotional faces during a mental

concentration task induced automatic processes that determined the amount of effort mobilized during the task (e.g., Chatelain & Gendolla, 2015; Freydefont, Gendolla, &

Silvestrini, 2012; Gendolla & Silvestrini, 2011; Silvestrini & Gendolla, 2011b, 2011c). This is explained by the Implicit-Affect-Primes-Effort (IAPE) model (Gendolla, 2012) with the idea that affective primes activate mental concepts that impact the magnitude of subjective task demand, which in turn influences effort mobilization according to the principle of motivation intensity theory (Brehm & Self, 1989). Of major importance, recent studies suggest that automaticity depends on the unawareness of the presence or influence of primes (Bijleveld,

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Custers, & Aarts, 2011; Glaser & Banaji, 1999; Murphy, Monahan, & Zajonc, 1995; Murphy &

Zajonc, 1993; Verwijmeren, Karremans, Bernritter, Stroebe, & Wigboldus, 2013). Gendolla (2015) proposes that the knowledge of the priming procedure should lead to controlled processes, which in turn should induce behavior correction. However, only few studies report such effects with implicit affective stimuli. Consequently, the aim of the present thesis was to contribute to the emerging research on moderator variables of automaticity in the context of implicit affect. I will start by describing existing research on automaticity, then introduce the concept of implicit affect, and subsequently present the IAPE model, which couples implicit affect effects with effort mobilization. Next, I will describe controlled processes that could arise when people become aware of priming procedures. Finally, I will discuss prime awareness as a potential moderator of implicit affect effects in the effort context.

Automaticity

We are exposed every day to a huge amount of information, which we process according to our needs, values, and goals (Dijksterhuis & Aarts, 2010). A certain portion of this information is processed without consciousness (see Lamme, 2003); in the present thesis, this is called implicit processing of the stimuli to which we are exposed. Most

importantly, psychological literature (e.g., Chartrand & Bargh, 1996; Custers & Aarts, 2007;

Dijksterhuis & Van Knippenberg, 1998) from the last decades supports the possibility that the processing of such information at the implicit level could influence behavior.

The research on the behavioral effects of implicit stimuli processing used priming procedures: priming is defined as the “impact of the activated knowledge structures on subsequent reactions” (Fiedler, 2003). Förster, Liberman, and Friedman (2009) identify three

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types of priming procedures: semantic priming, procedural priming, and goal priming. Goal priming is defined as the activation of goals that facilitate actions directed to goal

attainment, whereas procedural priming is the process that priming a procedure (e.g.

“strategies”, “way of processing a task”) should facilitate the execution of a subsequent action that shares the same procedure. For instance, completing mathematical operations should facilitate performance in a successive task that requires the solving of other

problems. Semantic priming, which is most relevant in the context of the present thesis, refers to the idea that primed concepts become more accessible and facilitate the processing of meaningfully related constructs (Neely, 1977). For instance, activating

knowledge about positive valence with the prime word “enjoy” should facilitate the reading of words that share the same construct of positivity - for instance reading the word

“happiness” (Fazio et al., 1986). In addition, semantic activation should also lead to perceptual assimilation (e.g., Payne, Cheng, Govorun & Stewart, 2005); in our previous example, judgments of stimuli preceded by the prime word “enjoy” should be influenced by the activated knowledge of positivity and be rated as more positive.

Empirical Evidence

Because of the huge volume of research in the field of automaticity, we will present only a few of the relevant studies on priming—all fields combined (goal priming, procedural priming, and semantic priming). The purpose of the presentation of these results is to enable the reader to form an impression of the great variety of priming procedures and their effects on behavior. This will facilitate the understanding of how the priming procedure are

investigated in the present thesis works.

Initial evidence of a procedural priming effect was provided in the 1960s with the Simon effect (Simon, 1969). Simon reports that priming a lateralized motor response (left or

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right) facilitates or impedes a motor response, depending on the correspondence between the prime and the key location: when both share the same location, reaction times are faster whereas when locations are mismatched reactions times are longer. The author explains this effect as an assimilative mechanism that induces participants to behave in line with the primed constructs.

In the context of goal priming procedure, Chartrand and Bargh (1996) reported that the automatic activation of information-processing goals strongly impacts participants’

behavior. The authors primed an impression formation goal or a memorization goal and tested the primed goal effect on a subsequent memorization task: subjects were asked to form grammatically correct four-word sentences with words that refer to impression

formation (e.g. “opinion”, “personality”) or memorization (e.g. “absorb”, “remember’) goals.

The results showed that participants in the memorization goal condition performed better in the subsequent memorization task. Similarly, some researchers - using a perception-action priming procedure - also reported that the implicit activation of the concept of elder induced subjects to behave in line with the prime concepts: these participants walked slower than participants in a control condition, in which no elderly concept was activated (Bargh, Chen, &

Burrows, 1996). The authors also reported that the priming concept of rudeness led

participants to interrupt the experimenter’s speech earlier than if they were primed with the politeness concept. In addition, priming individuals with professor stereotypes or, the trait

“intelligent” increased their performance in tasks measuring general knowledge compared to priming subjects with soccer hooligan stereotypes or the trait “stupid” (Dijksterhuis & van Knippenberg, 1998).

Most relevant for the present thesis, another important line of empirical research on automaticity used semantic priming, which was described above and refers to the idea that

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primed concepts become more accessible and facilitate the processing of meaningfully related constructs (Neely, 1977). Using a sequential priming procedure – that investigates how the evaluation of a first stimulus, i.e. the prime that has to be ignored, affects the processing of a succeeding target stimulus (Wentura & Degner, 2010), Fazio et al. (1986) conducted a series of studies supporting the idea that valence information can be activated automatically by the mere implicit processing of an affect-loaded stimulus. More specifically, in their first experiment, a noun (the prime) was presented for 200 ms and was followed by a target-adjective. The prime-noun was either positive, or negative, or a sequence of three identical letters - the control condition. The participants were asked to assess the valence (positive vs negative) of a target-adjective (e.g., appealing, awful) and had to orally recite the prime-word. Results indicate that the subjects were quicker to respond to target words when the prime and the target had the same valence and slower when they had opposite valence relative to control conditions (control-positive, control-negative). Giving strength to this initial evidence in the context of the sequential priming procedure, Hermans, Houwer, and Eelen (1994) replicated these results using affective pictures. The authors asked

participants to give affective ratings of a set of coloured pictures, considered as primes, and to subsequently assess, as quickly as they could, a smaller subset of colour slides - the targets. The study revealed that when the affective valence of both primes and targets was congruent, participants were faster at discriminating the colour of the targets. Another example of semantic priming procedure was given by Gawronski and Ye (2014), who report that processing briefly flashed stimuli of positive or negative valence influenced the

subsequent evaluation of the following stimulus - a Chinese ideograph. Results showed that positive primes led to more favourable evaluations of the Chinese ideographs than negative primes (see Murphy & Zajonc, 1993).

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Overall, these studies give an idea of the strength of priming effects. It is of note that these studies are only a small part of the huge literature on priming; they were discussed here with the intention of giving the reader an idea of what priming looks like. This is important for understanding the next concept - implicit affect priming - which plays a key role in the present thesis.

Implicit affect

Whereas automaticity effects have received a lot of attention and have been studied with various procedures and illustrated with various types of differential effects (e.g., Bijleveld et al., 2009; Chartrand & Bargh, 1996; Dijksterhuis & Van Knippenberg, 1998; Fazio et al., 1986; Koole & Coenen, 2007), only a few studies have tested automaticity with implicit affective stimuli (e.g., Brosschot et al., 2010; Winkielman et al., 2005; Zemack-Rugar et al., 2007). In light of this, Gendolla (2012, 2015) proposed and tested a model that explains how implicit affect primes influence behavior and make predictions about the effects of implicit affective faces on mental effort.

What is Implicit Affect?

Implicit affect is conceptualized as the automatic activation of the mental representations of affective states (e.g., Quirin, Kazén, & Kuhl, 2009). These mental representations concern memory and information about the affective states and are activated by external stimuli we process. Implicit affect differs from explicit affect in that these activations do not lead to conscious experiences of the affective states. Niedenthal (2008) suggests that knowledge about affective states is stored in our long-term memory.

Following the logic of semantic priming described above, Gendolla (2012, 2015) posits that affect primes can give access to all the pieces of information that are related to them. When

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the mental content is activated, it can influence judgements, opinions, and in general our behavior. However, the influence of the implicit affect primes on behavior is not a

continuous process. Gendolla (2012, 2015) posits that their influence on behavior depends on two factors: (1) their momentary accessibility and (2) their applicability. For instance, affect primes that are related to the concepts of negativity and performance ease should influence behavior only when the concepts of negativity or performance ease are applicable, such as judging the valence of Chinese symbols (concept of negativity is applicable) or

assessing the difficulty of a task (concept of ease is applicable).

Visual Stimuli and Implicit Affect

To activate implicit affect, Gendolla and collaborators (e.g., Chatelain & Gendolla, 2015, 2016; Chatelain, Silvestrini, & Gendolla, 2016; Freydefont & Gendolla, 2012;

Freydefont et al., 2012; Gendolla & Silvestrini, 2011; Silvestrini & Gendolla, 2011b, 2011c), exposed individuals to implicit affect primes. To do this, the visual primes were presented very briefly (25 – 27 ms) during a mental concentration task and then masked with a random dot picture, to implicitly activate the affect prime-related mental contents. Primes were briefly flashed rather than made clearly visible in order to test automatic/uncontrolled effects (Gendolla, 2012). Furthermore, Gendolla and colleagues used an “online” priming procedure, in which primes occurred during the performance of cognitive tasks.

Implicit-Affect-Primes-Effort model

The IAPE model (Gendolla, 2012, 2015) explains and predicts how implicit affects influence mental effort. The mental contents activated by affect primes include the

information of difficulty or ease, as will be explained below. As discussed above, the effects of affect primes on behavior depend on their momentary accessibility and applicability.

Considering this, the IAPE model suggests that information of ease or difficulty is relevant

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and thus applicable in the context of effort mobilization. This is because of a resources conservation principle: people are motivated to avoid any waste of resources and try to invest only those resources that are necessary for successful task execution (Brehm & Self, 1989). To prevent the waste of energy, motivation intensity theory suggests that we should use an indicator of the amount of effort that is needed to succeed on a task (Brehm & Self, 1989): task difficulty. Knowing task difficulty is of major importance for respecting the resource conservation principle. Gendolla suggests that the performance ease or difficulty affect-primes-related information becomes applicable in the mental effort context and modifies subjective task demand. This, in turn, should determine effort mobilization according to the principles of motivation intensity theory - effort should increase with task difficulty as long as success is possible and effort is justified (Brehm & Self, 1989).

To clearly explain how implicit affect influences effort, the next paragraph describes how the motivation intensity theory links effort and task difficulty. This will enable the reader to better understand the predictions of the IAPE model that will be further discussed.

Motivation Intensity Theory

Motivational intensity theory explains effort mobilization in goal pursuit (Brehm &

Self, 1989). Effort is defined as the mobilization of resources, allowing the execution of behavior; its function is to sustain the activity needed for goal attainment. Brehm and Self also suggest that effort investment is primarily governed by a resource conservation

principle (Gibson, 1900), which posits that organisms prevent any waste of energy: when we perform a task, we mobilize just the amount of resources that is necessary to succeed but no more. That is, individuals seek to avoid investing more effort than required, because this would be a waste of energy. To do this, individuals need an indicator of the amount of resources required for successful task execution. Brehm and Self posit that this information

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is provided by subjective task difficulty - the amount of resources required for task

completion should increase proportionally with the level of difficulty. However, using task difficulty to determine resource investment does not ensure that no resources are wasted.

Individuals investing effort in an impossible task, could not succeed and all the energy invested would be wasted. The same applies if an individual invests effort in a task in which the costs (effort invested) exceed the potential benefits of performing the task. Motivation intensity theory defines potential motivation as the maximum amount of effort that is justified for task success. Taking this into account, motivation intensity theory states that the amount of mobilized effort is proportional to subjective task difficulty as long as success is possible and the necessary effort is justified (see Panels A and B of Fig. 1). Success

importance and all the variables that impact success importance should only define the limit within which the relationship between task difficulty and effort holds.

As described above, task difficulty is supposed to be the major determinant of effort, because it permits individuals to avoid wasting resources by providing them with

information about the amount of resources required for successful task execution. There are, however, situations in which task difficulty is unknown or unclear. In these situations, motivation intensity theory predicts that people will use another indicator that will enable them to respect the resource conservation principle: under unclear or unknown task difficulty, Brehm and Self (1989) predict that success importance (potential motivation) is used to determine effort mobilization - i.e. the mobilization of effort increases with success importance.

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A vast amount of empirical studies found support for the predictions of motivation intensity theory (Gendolla & Wright, 2005; Gendolla, Wright, & Richter, 2012; Richter et al., 2016; Wright & Kirby, 2001 for reviews). The study by Richter, Friedrich, and Gendolla (2008) provides a good example of the research that demonstrated that effort mobilization is determined by task difficulty. In their experiment, Richter et al. (2008) exposed participants to a Sternberg task (Sternberg, 1966) with different levels of difficulty. More specifically, four letters were simultaneously displayed on the screen center for 1000 ms (easy condition), 550 ms (moderately difficult condition), 100 ms (difficult condition), or 15 ms (impossible

condition). Then, a single letter was presented, and participants had to decide whether this letter was included in the preceding four-letter series. The results showed that cardiac pre- ejection period (PEP) and systolic blood pressure (SBP) reactivity – two physiological measures of effort mobilization (see Cardiovascular measures section)-increased

proportionally with task difficulty. However, when the task was impossible (letters presented Figure 1. Motivational intensity theory predictions: effort increases with task difficulty while success importance only defines the limit within which the relationship between task difficulty and effort holds.

Figure taken from Richter, Gendolla, and Wright (2016, p. 152).

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for 15 ms), the cardiovascular reactivity was low, suggesting disengagement (PEP and SBP did not differ from rest). This study reveals that objective difficulty is a direct determinant of effort mobilization and strongly supports motivation intensity theory’s predictions.

Testing whether task difficulty is a direct determinant of mental effort, other

research tested the impact of several variables influencing effort mobilization through their impact on task demand. For instance, perceived ability and fatigue (e.g., Wright & Dill, 1993;

Wright, Martin, & Bland, 2003; Wright, Wadley, Pharr, & Butler, 1994), pain (e.g., Silvestrini, 2018), and dysphoria (e.g., Brinkmann & Gendolla, 2008; Franzen & Brinkmann, 2015) were all found to modify the perception of task demand and thus effort mobilization. Most relevant for the present thesis, moods were found to influence effort mobilization because of their informational impact – people use their mood as a piece of diagnostic information and integrates it with all other available information when evaluating task demand

(Gendolla, 2000). This is explained by the Mood-Behavior-Model (Gendolla, 2000), which posits that people should use their mood as direct, diagnostic information for task demand appraisals. Mood functions as a general information about task demand, and due to a mood congruency effect (e.g., Abele & Petzold, 1994) judgments of task difficulty are more

pessimistic in a sad mood than in a happy mood. Consequently, people in a sad mood should evaluate a task they are engaged in as more difficult and – following the principles of

motivation intensity theory (Brehm & Self, 1989) – mobilize higher effort than in a happy mood, as long as success is possible and justified. This was supported by experiments (e.g., Gendolla, Abele, & Krüsken, 2001; Gendolla & Krüsken, 2001).

Effects of Implicit Affect on Effort

Going a step further, Gendolla (2012) proposed that also mere affect knowledge should have a similar impact on effort as consciously experienced feeling states. Gendolla

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posits in his IAPE model that implicit affect should determine effort mobilization by

influencing the evaluation of subjective task demand. As mentioned above, this assumption builds on the idea that it is in our interest to use all available information to assess task demand in order to avoid the waste of resources. This is because information about task difficulty should permit us to mobilize the amount of energy that is necessary to succeed on the task, but not more, which is consistent with the resource conservation principle. The IAPE model proposes that implicit affect informs about task demand. In our past

experiences, we have learned that coping with challenges is easier in some affective states than in others. Therefore, affective states became associated with performance difficulty or ease: sadness and fear are associated with performance difficulty, whereas anger and happiness are associated with performance ease.

More specifically, anger, compared to fear, is associated with high optimism, positive expectations, and experiences of high coping potential (Lerner & Keltner, 2001) - the feeling of efficacy relative to a task (Scherer, 2009). High and low coping potentials have been shown to respectively reduce and increase the experience of difficulty and effort during task performance (e.g., Wright & Dismukes, 1995). Considering this, anger should be linked to the experience of ease. In contrast, fear is associated with low coping potential (Lerner &

Keltner, 2001) and should consequently be linked to the experience of difficulty.

Similarly, based on recent studies on the impact of explicit affect on effort

mobilization (e.g., De Burgo & Gendolla, 2009; Gendolla & Krüsken, 2002), joy and sadness have been related to experiences of ease and difficulty (see Mood-Behavior-Model;

Gendolla, 2000). These experiments manipulated participants’ conscious moods with videos and investigated the impact of mood on effort mobilization during a mental concentration task. Results show that participants mobilized more effort when they were in a sad mood

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relative to a happy mood. Those results are interpreted to be a consequence of mood- congruency effects on demand appraisals - experienced demand is higher in a sad mood, which determine higher effort mobilization than in a happy mood.

According to the automaticity concept described above (Bargh, 1992), the IAPE model posits that rendering the idea of performance difficulty accessible via implicit priming should influence perceived task difficulty and consequently effort mobilization. Knowing this, priming fearful and sad faces should activate the concept of difficulty, whereas priming happy or angry faces should activate the concept of ease (Fig. 2). Consequently, as effort is proportional to the task difficulty (Brehm & Self, 1989), participants should in general mobilize more effort when they are primed with sad and fearful faces relative to happy and angry faces.

Figure 2. Implicit-Affect-Primes-Effort model (Gendolla, 2012). Figure taken from Gendolla (2012, p. 127).

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In summary, the IAPE model (Gendolla, 2012) posits that the implicit processing of emotional faces should render information about difficulty (sadness/fear) or ease

(happiness/anger) accessible. The accessible information of difficulty or ease should then influence task demand during a mental concentration task. In turn, task demand should determine the magnitude of effort mobilization as long as effort is justified and success is possible.

General Effects

The predictions of the IAPE model have been tested and confirmed in several experiments (e.g., Chatelain & Gendolla, 2015, 2016; Chatelain et al., 2016; Freydefont &

Gendolla, 2012; Freydefont et al., 2012; Gendolla & Silvestrini, 2011; Lasauskaite, Gendolla,

& Silvestrini, 2013; Silvestrini & Gendolla, 2011b, 2011c). The first experiments that

investigated the effect of implicit affect primes on effort mobilization contrasted the primes of sadness, anger, and happiness (Gendolla & Silvestrini, 2011) during mental concentration tasks. Gendolla and Silvestrini (2011) used a D2 (Experiment 1) and a Sternberg (Experiment 2) task during which the participants were primed in 1/3 of the trials by briefly flashed emotional (sad, happy, and angry) faces. In the remaining 2/3 trials, the subjects were

primed with neutral faces to prevent fast habituation effects. It is of note that this procedure differs from other frequent priming procedures, which usually first expose participants to a stimulus and assess its effect on the performance of a successive task or even on the evaluation of a successive stimulus (see Förster et al., 2009; Wentura & Degner, 2010). The authors expected that presenting affective faces during the task would activate the affect- related performance difficulty or ease information, which in turn should influence task demand and determine effort mobilization. The results showed that participants primed with sad faces mobilized more effort compared to participants primed with happy or angry

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faces. This is because sadness primes should activate the performance difficulty concept, which is used to assess task difficulty. Task difficulty would hence be perceived as higher, which would determine higher effort mobilization. In contrast, primes of happiness and anger should activate a performance ease concept, which should result in lower task demand and determine lower mental effort. In addition, participants rated subjective task difficulty as higher in the sadness prime condition relative to the happiness and anger primes conditions, which is consistent with the idea that affect primes modify effort mobilization because of their impact on the task demand. Consistently, successive research reported that contrasting fear with anger or happiness leads to similar effects on mental effort (Chatelain

& Gendolla, 2015): on moderately difficult tasks, participants primed with faces of fear mobilized more effort than participants primed with faces of anger, which is consistent with the predictions of the IAPE model, given that affect primes of fear should activate the difficulty concept (high task demand and high mental effort) and primes of anger or

happiness should activate the ease concept (low task demand and low effort mobilization).

Recently, Lasauskaite et al. (2017) reported direct evidence for associations between affect primes and performance difficulty and ease using a sequential priming paradigm - effects of affect prime’s were measured through the categorization of a successive stimulus (see Wentura & Degner, 2010). Individuals were asked to categorize ease-related (e.g.

“relaxed”) or difficulty-related (e.g. “complex”) words as referring to difficulty or ease.

Before the apparition of the words, participants were primed with briefly flashed emotional faces - happiness vs. sadness – or with neutral faces (control condition). Results show that happiness primes facilitated the classification of ease-related words as referring to ease, while sadness primes facilitate the classification of difficulty-related words as referring to difficulty. This was expected because happiness faces should activate the ease concept while

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sadness faces should activate the difficulty concept. Activating these concepts should then facilitate the categorization of the target words in case of congruency, because they benefit from a compatibility effect between the prime and the response (Wentura & Rothermund, 2014). In the study by Lasauskaite et al. (2017), the prime and the response share a

response-relevant critical feature - the same difficulty and ease feature. Therefore, this study provides evidence for ease and difficulty affect-related associations posited by the IAPE model (Gendolla, 2012). In more general terms, these findings are consistent with the idea that implicit affect primes are related to the concepts of difficulty and ease, which are used to assess task demand to determine mental effort in a context where that information can be applied (mental effort context/evaluative judgment context).

Conscious Affect?

The IAPE model posits that affect primes influence mental effort without eliciting conscious emotional feelings. This is a critical point, because conscious feelings were

previously shown to impact effort mobilization through their direct informative influence on demand appraisals (see Gendolla & Brinkmann, 2005). In light of this, Gendolla and coll.

measured affect states before and after exposure to affect primes to control whether the affect primes’ effect on effort mobilization was not induced by conscious feelings. None of the experiments suggests that affect primes might have had an impact on consciously experienced affective states (Freydefont et al., 2012; Gendolla & Silvestrini, 2011; Silvestrini

& Gendolla, 2011b, 2011c; Lasauskaite Schüpbach et al., 2014; Chatelain & Gendolla, 2015;

Chatelain et al., 2016a; Chatelain et al., 2016b).

However, “zero effects” do not permit firm conclusions. In response, Lasauskaite et al. (2013) conducted an experiment to test the role of emotional feelings in the systematic impact of implicitly processed affect primes on mental effort. Participants were briefly

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flashed with happiness vs. sadness primes while working on a mental concentration task.

Half of the participants were warned before the task that “flickers” would be presented during the task, which could possibly influence their feelings. This manipulation was

previously shown to reduce the impact of conscious feelings on mental effort (see Gendolla

& Krüsken, 2002). Apart from the expected increased effort mobilization with faces of sadness compared to faces of happiness (see IAPE model; Gendolla, 2012), results reveal that instead of reducing the prime’s effects on mental effort, the cue manipulation

significantly increased participants’ efforts in general. Lasauskaite et al. (2013) suggest that the cue warning increased task demand because participants had to concentrate on both the task and the possible impact of the “flickers”. These results oppose to the idea that affect primes’ effect on effort is mediated by conscious emotional feelings. Otherwise, implicit affect primes’ effect on effort mobilization in the warning condition should have been reduced, as previously demonstrated (see Gendolla & Krüsken, 2002). Given the present results and the fact that there is yet not any evidence that conscious mood is affected by processing implicit affect primes (Chatelain & Gendolla, 2015, 2016; Chatelain et al., 2016;

Freydefont et al., 2012; Gendolla & Silvestrini, 2011; Lasauskaite et al., 2013; Silvestrini &

Gendolla, 2011b, 2011c), it appears that implicit affect primes should not elicit conscious emotional feelings.

The implicit affect primes’ effect on effort, rather, can be explained by the IAPE model (Gendolla, 2012) - the implicit processing of affective stimuli activates “affect

knowledge” (performance difficulty or ease), which, in turn, influences evaluative judgement such as the assessment of task demand (Niedenthal, 2008). Once activated, the happiness- related and sadness-related information about performance ease or difficulty should, in the

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context of mental effort, be used to evaluate task difficulty, because this knowledge becomes an applicable information in the context of effort mobilization.

Moderators of the Implicit Affect’s Effect on Mental Effort

As discussed by Gendolla (2015), research on the IAPE model has found several moderators of implicit affective priming effects, namely task difficulty, incentive, and prime frequency. Of major importance for this project, there is initial evidence for the role of controlled prime processing as an additional moderator of affect primes’ effect on mental effort. The next sections present the different moderators of implicit affect priming, followed by a detailed discussion of the literature highlighting controlled processing as another moderator of priming effects and an introduction to the recent evidence suggesting that prime awareness is another powerful moderator of affective priming on mental effort.

Task Difficulty

Objective task difficulty is the first identified moderator of the effects of implicit affect priming on mental effort (Silvestrini & Gendolla, 2011c). Research on the IAPE model reports that during an objectively difficult task, happiness and anger primes leads to higher effort mobilization compared to primes of sadness or fear (Chatelain et al., 2016; Freydefont et al., 2012; Lasauskaite Schüpbach, Gendolla, & Silvestrini, 2014; Silvestrini & Gendolla, 2011c). More specifically, according to the IAPE model, priming happiness or anger should activate the performance ease concept. Coupling the performance ease information to an objectively difficult task should result in a subjectively difficult but feasible task, which should trigger relatively high effort. In contrast, priming fear or sadness should activate the performance difficulty concept. Adding information of difficulty to a task that is already challenging should render the task as too demanding and result in disengagement, as suggested by motivation intensity theory (Brehm & Self, 1989): if the task appears to be

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impossible or requires too much effort, people should stop mobilizing resources, because mobilizing resources for a task in which they will not succeed is in conflict with the

conservation of resources principle (Brehm & Self, 1989).

Success Importance

Incentive was also reported to modify affect primes’ effect on effort (e.g. Chatelain &

Gendolla, 2015; Freydefont & Gendolla, 2012). Incentive was generally operationalized as promising participants monetary reward for success - the higher the promised reward, the higher the incentive. Freydefont and Gendolla (2012) exposed participants to anger vs.

sadness primes in an objectively difficulty task. Half of the participants expected low monetary incentive, whereas the other half expected high monetary incentive for success.

The authors report that participants in the sadness-prime-low-monetary-incentive condition mobilized less effort compared to participants in the sadness-prime-high-incentive condition and participants in both anger-prime conditions. This is because participants in the sadness- prime conditions had access to difficulty information, which increased subjective task demand. This, in turn, led to very high task demand and thus disengagement in the low- incentive condition, where the high subjectively necessary effort was not justified. In contrast, participants in the high-incentive-sadness-prime condition mobilized very high effort, because subjective demand was very high and the higher incentive justified this high effort. In addition, participants in the anger-prime conditions mobilized moderate effort, because the activated information of ease resulted in high but feasible subjective demand and incentive could thus not boost effort as in the sadness-prime condition.

Prime Frequency

Another moderator of affect primes’ effect on effort concerns the frequency of the primes’ presentation during task performance. In the initial experiment that investigated

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affect primes’ effect on effort, Gendolla and Silvestrini (2011) presented affect primes in 1/3 of the trials and neutral faces in the other 2/3. This was done to prevent fast habituation to the affect primes. In a subsequent experiment, the authors tested whether the affect primes’ effect on mental effort would weaken due to the habituation effect (Silvestrini &

Gendolla, 2011b). More specifically, the authors contrasted happiness with sadness primes during a moderately difficult mental concentration task with the following emotional-neutral faces ratio: 1/3 vs. 2/3 vs. 3/3. Results suggest that the expected priming effects were

stronger in the 1/3 emotional-neutral faces ratio condition compared to the 2/3 and 3/3 ratio conditions. This supports the idea that too much exposure to affect primes diminished their effect on mental effort. Correspondingly, Wright et al. (2001) also report that repeated exposition to emotional stimuli leads to habituation and to a decrease in their influence.

Consistently, these habituation effects were also reported with rapid visual presentations of emotional faces (e.g., Breiter et al., 1996) and, most relevantly, with unconscious affective priming (e.g., Wong & Root, 2003).

Controlled Prime Processing

Of major relevance for the present project, there is initial evidence suggesting that controlled prime processing is another powerful moderator of affect primes’ effect on effort mobilization. The IAPE model bases its predictions on the automatic processes triggered by the presentation of briefly flashed emotional primes, described by Bargh (1992) as

automaticity. The implicit processing of these stimuli should activate mental representations about affective states, which include performance difficulty or ease concepts. This, in turn, influences subjective task demand and determines effort mobilization. However, Gendolla (2015) recently suggested that implicit affect prime’s effect on behavior depends on individuals’ unawareness of primes’ influence. This is based on the idea that automaticity

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works only if individuals regard their actually primed mental content as a valid basis for their behavior (e.g., Loersch & Payne, 2011; Wheeler, DeMarree, & Petty, 2007). If people prefer autonomy and basically think that they act in accordance with their own decisions (Ryan &

Deci, 2000), they should dislike being manipulated and may react to perceived external influences with behavior correction (Brehm, 1966). This is consistent with studies reporting that primes lose their effects when people become aware of the priming procedure

(Bijleveld et al., 2011; Glaser & Banaji, 1999; Murphy et al., 1995; Murphy & Zajonc, 1993;

Verwijmeren et al., 2013). Murphy and Zajonc (1993), in one of the first experiments that investigated affect primes’ awareness effect on behavior, reported that affect primes lost their effects when participants were conscious of the presence and the content of the primes. More specifically, prime-congruent assimilation effects on evaluative judgments of neutral targets were only found when the primes were presented suboptimally (very briefly flashed primes). When the primes were clearly visible, the effect of the primes was inversed, suggesting controlled processes and correction of the prime’s influence.

Such findings were replicated in a series of experiments that investigated priming in automatic evaluation (Glaser & Banaji, 1999). These authors reported that when participants saw extreme word primes that could potentially skew the response to a target, they resisted to this external influence by correcting their behavior. Such findings strongly emphasize the idea that primes are more likely to influence behavior when individuals do not suspect them to influence their thoughts (Loersch & Payne, 2011). In the studies by Glaser and Banaji (1999), extreme words created suspicion, which probably motivated behavior correction.

Most relevant, this effect was recently replicated using several different experimental paradigms: warning of the primes’ presence (Verwijmeren et al., 2013), manipulating the thought attribution – external vs. internal - (Loersch & Payne, 2012) or even manipulating

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doubt in mental contents (DeMarree et al., 2012) have all been shown to moderate prime effects.

In the context of the IAPE model (Gendolla, 2012), affect primes’ effect on effort mobilization should only work if the participants have no suspicion about the prime impact on their mental content. This assumption received initial support from two recent studies that investigated the effect of affect primes’ visibility on effort (Chaillou, Giersch,

Bonnefond, Custers, & Capa, 2015; Lasauskaite Schüpbach et al., 2014). Both studies tested the effect of briefly flashed (suboptimal) primes vs. clearly visible (optimal) primes on effort mobilization. Results indicate that the effect of the primes followed the predictions of the IAPE model in the suboptimal prime presentation condition. Conversely, if affect primes were clearly visible, results differed from the predictions of the IAPE model in the form of zero or contrast effects. These results provide initial evidence that prime awareness is a potential moderator of affect priming in the context of effort mobilization. However, both studies contrasted positive vs. negative affect primes, giving rise to the question of whether the prime visibility moderation effect is emotion-specific, affect prime’s effects explained with the predictions of the IAPE model (Gendolla, 2012) - rather than valence-specific. In addition, the prime awareness moderation effect on affect priming was only operationalized as prime visibility. This leads to the question about the existence of other prime awareness variables that could moderate the effect of affective priming in the context of effort.

To close this gap, the goal of the present thesis was to pursue the investigation of prime awareness as a moderator of affective priming, by testing implicit primes of the same valence but with opposite effects on task demand according to the IAPE model (Gendolla, 2012).

Reporting results with implicit affect with the same valence would speak for an emotion- specific effect rather than the valence-specific effect predicted by the IAPE model. In addition,

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we test prime warning as another potential moderator of affective priming in the context of effort mobilization. This would enable us to extend the list of potential moderators of affective priming in the mental effort context.

Measuring effort

Effort-Related Cardiovascular Response

Most of the previously cited studies that investigated the impact of various variables on effort mobilization focused on cardiovascular measures, especially cardiac pre-ejection period (PEP), which reflects the contractility force of the heart. Wright (1996) has integrated motivation intensity theory (Brehm & Self, 1989) with the active coping approach by Obrist (1981). Accordingly, effort can be quantified as beta-adrenergic sympathetic influence on the heart.

Active Coping Approach

Active coping can be distinguished from passive coping in function of individuals’

ability to control performance outcomes (Obrist, 1976, 1981). During active coping, control is possible, whereas during passive coping, people feel “helpless” and thus, minimally engaged in the task. In early studies, Obrist (1981) found that active coping is indeed reflected by beta-adrenergic sympathetic influence on the heart. This was shown in a series of studies in which coping settings were manipulated (active vs. passing coping) and cardiovascular reactivity was measured. Participants were instructed that they could avoid or could not avoid the receipt of an aversive stimulus. At the beginning of the experiment, increases of HR and carotid DP/dt (measures of myocardial force) were similar for both conditions.

However, over trials, the increments of HR and carotid DP/dt remained greater for participants who thought that they could avoided shocks compared to participants in the

“helpless” condition. In a second experiment, all participants initially believed that they

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could avoid aversive stressors. Subsequently, the avoidance of aversive stressors was impossible in a first condition, was possible but difficult in a second condition, and was very easy in the third condition. First HR and carotid dP/dt increased equally in all conditions.

However, after two minutes, HR and carotid dP/dt began to diminish for participants in conditions 1 (success impossible) and 3 (success granted), which are situations of passive coping, because participants either learned that avoidance was impossible or that the challenge was minimal. By contrast, condition 2 was a situation of active coping, because active engagement of the participant was necessary to succeed. Based on these findings, Obrist suggested that active coping differs from passive coping and that active coping is well reflected by beta-adrenergic sympathetic impact on the heart.

Of major importance, Wright (1996) integrated motivational intensity theory (Brehm

& Self, 1989) with the active coping approach (Obrist, 1981): accordingly, beta-adrenergic impact on the heart reflects effort and increases with task difficulty as long as success is possible and the necessary effort is justified.

Cardiovascular Reactivity as Indicator of Effort

Obrist (1981) suggested that the best indicators of engagement in an effortful activity, are cardiovascular measures that reflect sympathetic beta-adrenergic activity. Pre- ejection period (PEP), which is the time interval (in ms) between the onset of left ventricular depolarization and the opening of the left aortic valve (Berntson, Lozano, Chen, & Cacioppo, 2004), has been reported to be the best indicator of beta-adrenergic activity (Kelsey, 2012).

The shorter is the time between left ventricular depolarization and the opening of the aortic valve, the stronger is the engagement during an activity. Therefore, a shorter PEP reflects stronger engagement, whereas a longer PEP reflects weaker engagement. As found in the

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above discussed studies, Richter et al. (2008) reported a link between PEP reactivity and variation in perceived task demand.

Systolic blood pressure (SBP) has also been used to assess effort in several

experiments (Gendolla & Richter, 2010; Wright & Gendolla, 2012; Wright & Kirby, 2001).

Systolic Blood Pressure is defined as the maximal arterial pressure and is also systematically influenced by beta-adrenergic impact via contractility influence on cardiac output (CO).

However, SBP is also influenced by peripheral vascular resistance, which is not systematically influenced by beta-adrenergic impact (Levick, 2003). Diastolic blood pressure (DBP), the minimum arterial pressure between two hearth beats, is even more strongly influenced by peripheral vascular resistance, which makes it not a reliable measure of effort. Furthermore, heart rate (HR) has also been used to assess mental effort (e.g., Eubanks, Wright, & Williams, 2002; Zafeiriou & Gendolla, 2017, 2018). However, HR is controlled by both sympathetic and parasympathetic impact (Berntson, Cacioppo, & Quigley, 1993). Therefore, PEP appears to be the best indicator of beta-adrenergic activity among these indices. Nevertheless, PEP should always be assessed with HR and DBP in order to control for possible preload (ventricular filling) or afterload (arterial pressure) effects on PEP (Sherwood et al., 1990).

Increased preload can decrease PEP due to higher ventricular filling and decreased afterload can decrease PEP because it takes shorter to build up the necessary force to open the aortic valve.

Outline of the present studies

Priming effects have been largely reported using many different procedures and effects on behavior (e.g., Bijleveld et al., 2009; Chartrand & Bargh, 1996; Dijksterhuis & Van Knippenberg, 1998; Fazio et al., 1986; Koole & Coenen, 2007). Previous findings also

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reported that knowledge about the presence and content of primes – named prime

awareness - is a moderator of the primes’ effect (Bijleveld et al., 2011; Glaser & Banaji, 1999;

Murphy et al., 1995; Murphy & Zajonc, 1993; Verwijmeren et al., 2013). Most relevant, in the context of the IAPE model (Gendolla, 2012, 2015), which predicts the effects of implicit affect on mental effort, there is initial evidence that prime visibility is a moderator of affect primes’ effect on effort (Chaillou et al., 2015; Lasauskaite Schüpbach et al., 2015) Based on this initial evidence, the aim of this thesis was to further understand the role of prime awareness in the context of implicit affect’s effect on mental effort. Thus, I investigated two potential moderators of affect primes’ effect on effort mobilization: prime visibility and prime warning.

All experiments are based on the predictions of the IAPE model (Gendolla, 2012), which suggests that affect primes can modify perceived task difficulty by rendering the prime-related information about difficulty and ease accessible. Experiments 1, 2, and 3 manipulated the visibility of affective primes that were either briefly flashed (25 ms) and masked (suboptimal condition) or appeared clearly visible (775 ms) (optimal condition). In these experiments, we expected that affect prime should work as predicted by the IAPE model in the suboptimal prime presentation condition. This was expected because affect primes should be processed automatically. By contrast, we expected that this affect prime effect should be moderated in the optimal prime presentation condition. Here, controlled processes should be possible and should lead to zero or contrast effect, reflecting behavior correction (Gendolla, 2015).

In Experiment 4, we manipulated prime awareness by warning half of our

participants about the priming procedure. We expected that warning participants about the priming procedure should lead to behavior correction. More specifically, we expected that

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the prime effects should either be attenuated (e.g., Chaillou et al., 2015; Verwijmeren et al., 2013), or even turn into a prime-contrast effect in the case of overcorrection (e.g.,

Lasauskaite Schüpbach et al., 2014).

Besides the primary goal of testing whether prime visibility and prime-warning are boundary conditions of implicit affects’ impact on effort mobilization, Experiment 4

controlled for the possible role of gender. In most of our previous experiments, participants were psychology students. Consequently, the gender distribution was imbalanced - the samples were composed of far more women than men. Therefore, we cannot exclude that previously reported effort effects may be limited to women, or even women studying psychology. Consequently, we recruited larger samples composed of students from various study domains, that permitted to control for the role of gender as a potential moderator of affect primes’ effect on effort-related cardiovascular response.

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Chapter 2. The effect of fear and sadness prime visibility on effort and performance

Abstract

Based on the IAPE model (Gendolla, 2012, 2015), the present experiment investigated prime visibility as a moderator of affect primes’ effect on effort mobilization. Participants worked on a d2 mental concentration task with integrated briefly flashed pictures of fearful vs. angry faces, which were presented either suboptimally (25 ms) vs. optimally (775 ms). To assess effort-related

cardiovascular response, we measured cardiac pre-ejection period (PEP), systolic (SBP) and diastolic (DBP) blood pressure, and heart rate (HR). Additionally, to monitor performance, we assessed reaction times and response accuracy. Unfortunately, the results for PEP were non interpretable due to a technical problem. However, in the suboptimal condition response accuracy was higher in the fear-prime condition than in the anger-prime condition – which is consistent with previous research (e.g., Chatelain & Gendolla, 2015). By contrast, in the optimal condition, the primes had the opposite effect on response accuracy.

Introduction

Implicit processing of emotional faces during cognitive tasks have been consistently shown to impact effort-related cardiovascular response: briefly flashed sadness and fear primes during easy to moderate concentration tasks lead to higher effort mobilization compared to briefly flashed faces of happiness and anger (e.g., Chatelain & Gendolla 2015;

Gendolla & Silvestrini 2011; Lasauskaite et al. 2013; Silvestrini & Gendolla 2011c). This was predicted by the IAPE model (Gendolla, 2012) in that affect primes activate information about ease or difficulty, which modifies the magnitude of subjective task demand and, as a consequence, effort mobilization.

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IAPE Model

The IAPE model (Gendolla, 2012) posits that information about performance ease and difficulty are features of individuals’ mental representations of affective states, because they have learned that performance is easier in some affective states than in others: Sadness and fear are both associated with low coping potential and thus difficulty, while happiness and anger are both related to high coping potential and thus ease. Affect primes, like

implicitly processed facial expressions of emotions during task performance, can make these ease and difficulty concepts accessible, influence subjective demand, and determine effort in accordance of the principles of motivation intensity theory (Brehm & Self 1989): effort rises proportionally with subjective demand as long as success is possible and the necessary effort is justified.

Prime Visibility

However, recent studies suggested that primes only have effects if they are processed implicitly: awareness of the priming procedure was found to be a moderator of priming effects on evaluative judgments (Lombardi, Higgins, & Bargh, 1987; Murphy et al., 1995; Rotteveel, de Groot, Geutskens, & Phaf, 2001; Strack, Schwarz, Bless, Kübler, &

Wänke, 1993) and decision-making (e.g., Loersch & Payne, 2012; Verwijmeren et al., 2013).

This is because priming procedures can apparently only be effective if people misattribute their prime-related mental content to their own thoughts (Loersch & Payne, 2011). This should permit individuals to assimilate the mental concepts that are actually activated by a priming procedure to their self. This becomes difficult when participants become aware of the priming procedure (e.g., Oikawa, Aarts, & Oikawa, 2011). In such a context, based on the idea that people should prefer autonomy (Ryan & Deci, 2000) and believe to act in

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accordance with their own thoughts and decisions (Loersch & Payne, 2011), Gendolla (2015) suggested that participants should dislike being manipulated and react to the perceived external influences with behavior correction.

Importantly, there is initial evidence that prime visibility should be considered as a moderator of affect priming in the context of effort-mobilization. Two recent studies reported that the effects of positive and negative affect primes on measures of resource mobilization were moderated by prime visibility (Chaillou et al., 2015; Lasauskaite

Schüpbach et al., 2014). In contrast to suboptimal prime presentations, clearly visible affect primes produced zero or prime-contrast effect. To further explore if this effect is emotion- specific rather than valence-specific, the present experiment contrasted two affect primes of negative valence (fear vs. anger) that have been shown to have opposite effects on task demand and thus on effort-related cardiovascular response according to the IAPE model.

Conceptually replicating the findings of Chaillou et al. (2015) and Lasauskaite Schüpbach et al., (2014) by contrasting fear vs. anger instead of happiness and sadness primes would speak for the emotion-specific effect predicted by the IAPE model.

Effort-Related Cardiovascular Response

According to Wright’s (1996) integration of motivational intensity theory (Brehm &

Self, 1989) with the active coping approach (Obrist, 1981), effort is mirrored by beta- adrenergic sympathetic nervous system activity on the heart. This impact is reflected as increased cardiac contractility and thus shortened cardiac pre-ejection (PEP) - the time interval between the onset of the left ventricular depolarization and the opening of the left aortic valve (Berntson et al., 2004). In support of this reasoning, PEP sensitively responds to manipulations of task demand (Richter et al., 2008), incentive (Richter & Gendolla, 2009), and combinations of both (Silvestrini & Gendolla, 2011a) .

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Systolic blood pressure (SBP) can also reflect effort due to the systematic impact of cardiac contractility on cardiac output (the volume of blood pumped by the ventricles per minute) - several studies have quantified effort as SBP because of this effect (see Wright &

Kirby, 2001; Richter et al., 2016 for reviews). Other studies relied on heart rate (HR) as indicator of effort (e.g., Eubanks et al., 2002). Nevertheless, PEP is the more reliable measure of effort mobilization, because it can directly reflect beta-adrenergic sympathetic impact (Kelsey, 2012). Nevertheless, HR and blood pressure should always be assessed together with PEP to control for possible preload (ventricular filling) or afterload (arterial pressure) effects on PEP (Sherwood et al., 1990).

The Present Experiment

The present experiment investigated the role of prime visibility on effort

mobilization. Participants worked on an adapted version of the d2 (Brickenkamp, 1981) mental concentration task - with integrated fear or anger primes which were briefly flashed (suboptimal; 25 ms) vs. were clearly visible (optimal; 783 ms). According to the IAPE model (Gendolla, 2012), we expected stronger PEP responses, reflecting higher effort, in the fear prime/suboptimal condition than in the anger-prime/suboptimal condition. This is because fear is associated with performance difficulty (low coping potential) while anger is associated with ease (high coping potential; see Lerner & Keltner, 2001). Importantly, affect primes’

effect should be moderated by the prime visibility manipulation: it should either result in an attenuated affect prime effect (e.g., Chaillou et al. 2015; Verwijmeren et al. 2013), or even in a prime-contrast effect in the case of overcorrection (e.g., Lasauskaite Schüpbach et

al. 2014). The reason is that clearly visible primes that have nothing to do with the concentration task should induce suspicion and render the misattribution of the prime-

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related mental content to participant’s own thoughts difficult. This is turn should result in behavior correction in order to re-establish freedom and autonomy (Brehm, 1966).

Method

Participants and Design

N = 83 university psychology students (58 women, average age 21.46 years and 28 men; average age: 21.51 years) were randomly assigned to the experimental conditions of the 2 (Prime: fear vs. anger) × 2 (Visibility: suboptimal vs. optimal) between-persons design which complies with the principle to collect valid data of at least 20 participants per

between-persons condition (Simmons, Nelson, & Simonsohn, 2011). Two participants were removed from the analysis, due to very low response accuracy in the d2 task (< 60% of correct response) – leaving a final sample of N = 81.

Affect Primes

Pictures from Averaged Karolinska Directed Emotional Faces (AKDEF) database (Lundqvist & Litton, 1998) with averaged neutral (MNES and FNES), fear (MAFS and FAFS), and anger (MANS and FANS), front perspective faces were used as affect primes for this study. The pictures were in grey-scale. Half of them were averaged female faces and half were averaged male faces.

Appartus and Physiological Measures

Impedance cardiogram (ICG) and electrocardiogram (ECG) signals were noninvasively assessed (sample rate 1,000 Hz) with a Cardioscreen 1000 system (medis, Ilmenau Germany) to assess HR and PEP. Four pairs of electrodes (Ag/AgCl, Medis, Ilmenau, Germany) were placed on the left and right side of the participants’ neck and on the left and right middle axillary line at the height of the xiphoid. Signals were amplified, transformed into digital data

Prime visibility and prime warning as moderators of affect primes&#039; effect on effort mobilization

Thesis

Reference

Prime visibility and prime warning as moderators of affect primes' effect on effort mobilization

PRIME VISIBILITY AND PRIME WARNING AS MODERATORS OF AFFECT PRIMES' EFFECT ON EFFORT MOBILIZATION

THESE

Abstract

Table of contents

Chapter 1. Introduction

Automaticity

Implicit affect

Implicit-Affect-Primes-Effort model

Measuring effort

Outline of the present studies

Chapter 2. The effect of fear and sadness prime visibility on effort and performance

Abstract

Introduction

Method

Prime visibility and prime warning as moderators of affect primes' effect on effort mobilization