Avoiding Choking

ALLEVIATING CHOKING UNDER PRESSURE USING IMAGERY

A Dissertation

Submitted to the Graduate School

of the University of Notre Dame

in Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

by

Sabine A. Krawietz

G.A. Radvansky, Director

Graduate Program in Psychology

Notre Dame, Indiana

December 2012

ALLEVIATING CHOKING UNDER PRESSURE USING IMAGERY

Abstract

by

Sabine A. Krawietz

The main purpose of the current research was to investigate a novel approach to

prevent choking under pressure using a sensorimotor task. Choking is defined as

suboptimal performance in situations filled with performance pressure. Three main

experiments were conducted to systematically give rise to performance decrements and

to, subsequently, use imagery practice to prevent such choking. Experiment 1 served to

replicate the commonly-found interaction between direction of attention and the

cognitive demands of the task. Here, novice golfers were found to perform optimally

under skill-focused attention but suboptimally when concurrently doing an auditory

word monitoring task while the opposite pattern emerged for expert golfers.

Experiment 2a sought to establish an equally high level of performance pressure

as perceived by participants putting in scenarios induced with outcome and monitoring

pressure and a significantly higher level of perceived pressure than other participants

putting in the no pressure control condition. Experiment 2b, then, provided further

support for the recent finding of an interaction between type of pressure and the

Sabine A. Krawietz

cognitive demands of a task. Novice golfers, for which putting represents a working

memory - reliant task, exhibited choking under outcome but not under monitoring

pressure whereas the opposite trend was found for the expert group.

Finally, Experiment 3 set out to test whether imagery practice, in particular, first-

and third-person imagery, affected performance as a function of skill level when

performing in a single-task (i.e., no pressure) and a pressure-filled environment.

Importantly, choking, as had been found for novices under outcome and experts under

monitoring pressure, was prevented using a brief introduction and one block practice

session of imagery practice. In particular, it was found that when novices imagined

themselves make a successful putt from a third-person perspective, their performance

no longer fell prey to the negative effects of perceived outcome pressure. In the same

vein, experts who used first-person imagery performed optimally under those

conditions of monitoring pressure that had previously been found harmful of their

putting performance.

Importantly, this research showed that choking under pressure can be prevented

through imagery practice, and is best used when matching visual imagery perspective to

the cognitive demands of the performer. These results are further discussed in light of

current theory of choking under pressure, in particular, self-focus theory and the

distraction hypothesis.

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CONTENTS

FIGURES ............................................................................................................................... iv

TABLES .................................................................................................................................. v

ACKNOWLEDGMENTS ......................................................................................................... vi

CHAPTER 1: INTRODUCTION ............................................................................................... 1

1.1 Choking Under Pressure ................................................................................... 4

1.1.1 Cognitive Demands ............................................................................ 5

1.1.2 Direction of Attention ........................................................................ 9

1.1.3 Type of Pressure .............................................................................. 12

1.1.4 Regulatory Focus .............................................................................. 14

1.2 Theories of Choking Under Pressure .............................................................. 17

1.2.1 Early Theories ................................................................................... 17

1.2.2 Recent Theories ............................................................................... 18

1.3 Alleviating Choking Under Pressure................................................................ 20

1.3.1 Previous Research ............................................................................ 20

1.3.2 Alleviating Choking Using Imagery Practice ..................................... 26

1.3.2.1 Visual Imagery Perspective ............................................... 28

1.3.2.2 Perspectives in Sports Performance ................................. 29

1.3.2.3 Perspectives in Memory and Emotional Processing ......... 33

1.4 Summation ...................................................................................................... 36

1.5 Overview of Experiments ................................................................................ 37

CHAPTER 2: EXPERIMENT 1: ATTENTION REPLICATION ................................................... 38

2.1 Method ........................................................................................................... 38

2.1.1 Participants ...................................................................................... 38

2.1.2 Materials .......................................................................................... 39

2.1.3 Procedure ......................................................................................... 40

2.1.4 Replication Criteria .......................................................................... 42

2.2 Results ............................................................................................................. 43

2.3 Discussion ........................................................................................................ 45

CHAPTER 3: EXPERIMENT 2A: PRESSURE REPLICATION ................................................... 47

3.1 Method ........................................................................................................... 48

iii

3.1.1 Participants ...................................................................................... 48

3.1.2 Materials .......................................................................................... 48

3.1.3 Procedure ......................................................................................... 50

3.1.4 Replication Criteria .......................................................................... 55

3.2 Results ............................................................................................................. 58

3.2.1 Self-Report and Heart Rate Measures ............................................. 58

3.2.2 Putting Performance ........................................................................ 60

3.3 Discussion ........................................................................................................ 62

CHAPTER 4: EXPERIMENT 2B: EFFECTS OF PRESSURE ON PERFORMANCE ...................... 64

4.1 Method ........................................................................................................... 65

4.1.1 Participants ...................................................................................... 65

4.1.2 Materials and Procedure ................................................................. 65

4.2 Results ............................................................................................................. 66



4.3 Discussion ........................................................................................................ 73

CHAPTER 5: EXPERIMENT 3: ALLEVIATING CHOKING THROUGH IMAGERY ..................... 76

5.1 Method ........................................................................................................... 76

5.1.1 Participants ...................................................................................... 76

5.1.2 Materials .......................................................................................... 77

5.1.3 Design ............................................................................................... 79

5.1.4 Procedure ......................................................................................... 79

5.2 Results ............................................................................................................. 82



5.3 Discussion ...................................................................................................... 102

5.3.1 Imagery (Only)................................................................................ 102

5.3.2 Imagery under Pressure ................................................................. 105

CHAPTER 6: CONCLUSIONS ............................................................................................. 106

REFERENCES .................................................................................................................... 118

iv

FIGURES

Figure 2.1 Bar graph including error bars (standard error of the mean) for difference scores of the distance from hole measure clustered by skill level and attention condition in Experiment 1 ..................................................................................... 44

Figure 4.1 Bar graph including error bars (standard error of the mean) for difference scores clustered by skill level and attention condition for combined data for Experiment 2a and 2b. .......................................................................................... 72

Figure 5.1 Overview of study design of Experiment 3. ..................................................... 79

Figure 5.2 Bar graph including error bars (standard error of the mean) for difference scores clustered by skill level and imagery perspective for Experiment 3. .......... 96

Figure 5.3 Bar graph including error bars (standard error of the mean) for difference scores for novice (a) and expert (b) golfers clustered by type of pressure and imagery for Experiment 3. .................................................................................... 99

v

TABLES

Table 2.1 Means and Standard Errors (in Parentheses) for Block and Difference Scores of Putting Data by Skill Level and Pressure Condition for Experiment 1 ............. 43

Table 3.1 Sample Size, Means, and Standard Errors (in Parentheses) of Importance, Pressure, and State Anxiety Scores per Pressure Condition of Prior Studies ....... 54

Table 3.2 Means and Standard Errors (in Parentheses) for Block and Difference Scores on all Measures by Pressure Condition for Experiment 2a .................................. 56

Table 3.3 Means and Standard Errors (in Parantheses) for Putting Performance by Skill Level and Pressure Condition for Experiment 2a ................................................. 61

Table 4.1 Means and Standard Errors (in Parentheses) for Block and Difference Scores on all Measures by Pressure Condition for Experiment 2a and 2b ...................... 68

Table 4.2 Means and Standard Errors (in Parantheses) by Skill Level and Pressure Condition for Experiment 2a and 2b..................................................................... 71

Table 5.1 Means and Standard Errors (in Parentheses) for Block and Difference Scores on all Measures by Pressure and Imagery Condition for Novices (Only) of Experiment 3 ......................................................................................................... 83

Table 5.2 Means and Standard Errors (in Parentheses) for Block and Difference Scores on all Measures by Pressure and Imagery Condition for Experts (Only) of Experiment 3 ......................................................................................................... 87

Table 5.3 Means and Standard Errors (in Parantheses) for Block and Difference Scores by Skill Level and Imagery Condition for Experiment 2 (No Pressure Condition Only) and Experiment 3 (Imagery Block Only) ............................................................... 95

Table 5.4 Means and Standard Errors (in Parentheses) for Block and Difference Scores by Skill Level and Pressure and Imagery Condition for Experiment 3 ....................... 98

vi

ACKNOWLEDGMENTS

I would like to sincerely thank my advisor, G.A. Radvansky, for his guidance,

understanding, patience, and most importantly, for his friendship during my doctoral

studies at Notre Dame. His mentorship was vital in providing a well-rounded teaching

and research experience consistent with my interests and career aspirations. He

encouraged me to continue my studies in difficult times and I will be forever thankful for

his support in completing this important academic step. Thank you also for your humor

on this journey throughout our lab meetings and conference visits.

I would also like to thank the Department of Psychology at Notre Dame, and

especially the members of my doctoral committee, Bradley Gibson, Jerry Haeffel, and

Jessica Payne, for their valuable input, discussions, and accessibility. You have all

inspired me to become a more thorough scientist and better person overall. I am also

grateful for having learned from and worked with enthusiastic and passionate

professors such as Jessica Payne and Scott Maxwell who I wish to be like in the future.

Finally, I wish to thank my family and dear friends who have supported me, at

times from far away, throughout my academic career in the US.

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CHAPTER 1:

INTRODUCTION

The study of human performance per se has not been established in unified

form; instead, researchers, practitioners, and consultants in counseling, business, sports

psychology, and, more recently, cognitive psychology have worked largely

independently, identifying ways to develop and facilitate optimal performance while

preventing poor performance. Practitioners, consultants, and researchers have

investigated how performers can reach a mental state that allows optimal or peak

performance by helping them effectively regulate emotion (e.g., anxiety and anger

control) and attention (e.g., focus control), overcome mental blocks (e.g., stereotype

threat), and develop effective pre-performance routines, to name just a few.

The need to perform optimally is critical to numerous situations including sports

performance (e.g., tennis, ice skating, or weightlifting), public speaking (e.g., an

inspirational political speech before elections, a college professor nailing a lecture, or a

manager holding a business meeting), test taking (e.g., tests in schools and colleges or to

gain a driver’s license), military, police, and rescue services (e.g., soldiers in combat, fire

fighters, or paramedics), the performing arts (e.g., acting, singing, or dancing), and

other high risk-professions such as flying airplanes or conducting surgery.

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Optimal performance in skilled tasks depends on numerous factors. When asking

elite athletes what all has to be in line for them to perform well, they might answer with

sleep, nutrition, physical fitness and lack of injuries, functioning equipment, social

support and a lack of personal problems, financial security, having practiced skills

recently to have established a “good feel” and confidence, and having competed

recently to be used to retrieving skills in context of competition. Even when a performer

enters a critical performance well prepared and with the motivation to excel,

performance decrements can occur. The current study is concerned with what

performers can do to maintain an optimal performance level during early skill learning

processes and once the fundamental skills have been fully acquired. In particular, it will

be investigated under which circumstances performance break downs occur in

beginning and advanced skill performers and whether strategies can be taught to

prevent them.

Hence, performance under pressure is the main topic of this research.

Performance pressure is a strong desire to perform at a high level in a situation (Hardy,

Mullen, & Jones, 1996) and, therefore, depends on the perceived importance to

perform well (Baumeister, 1984). Examples of high pressure situations are a pilot

landing an airplane under difficult conditions (e.g., the 2009 U.S. Airways flight 1549

Hudson River airline landing), a surgeon operating on a heart patient, and a golfer

making a putt in a decisive moment (e.g., to win the PGA Championship). The

consequences of failing to perform optimally in pressure-filled situations can be

dramatic as in the case of losing lives when crashing airplanes or failing heart surgery.

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Thus, finding ways to prevent subotpimal performance, or choking under pressure, is

important for the successful completion of tasks laden with responsibility.

Choking is defined as “poor performance in response to what an individual

perceives as an important and stress-filled situation” (Beilock & Gray, 2007, p. 426). It is

less-than-average or suboptimal performance in response to perceived performance

pressure. Thus, choking differs from other types of performance decrements such as

those caused by injuries, lack of practice, recent changes in skill processes, or a long-

lasting performance slump, in that the sole cause for the impairment lies in the

presence of perceived performance pressure. In this sense, optimal performance would

resume once the situation was relieved of the perceived pressure. Choking is usually

accompanied by feelings of anxiety and worry, loss of attentional and emotional control,

heart racing, and palpitations. Yet, it does not occur every time pressure is perceived by

the performer, and it is the aim of current research to identify the conditions in which

choking occurs and to develop strategies to prevent it.

In recent years, several studies investigated when and why choking occurs and

made early attempts to prevent it. The aim of this research is examine how different

types of pressure affect performance on a sensorimotor task and finding a new way of

alleviating choking. In the next two sections, I first review the current literature on

choking under pressure and, then, introduce a new method (i.e., imagery practice) that

will be tested as a way to alleviate choking.

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1.1 Choking Under Pressure

Prior work primarily stemming from research in cognitive and sports psychology

has revealed several patterns that make the vulnerability to choking more predictable.

In particular, I discuss several factors that have been found to systematically affect

performance under pressure. Interactions between the cognitive demands of the task

(WM-reliant vs. proceduralized) and the direction of attention (skill-focused vs. non-

skill-focused) have consistently been found in a variety of studies including soccer

dribbling (Beilock, Carr, MacMahon, & Starkes, 2002; Smith & Chamberlin, 1992), golf

putting (Beilock & Carr, 2001; Lewis & Linder, 1997; Masters, 1992), hockey dribbling

(Leavitt, 1979; Jackson, Ashford, & Norsworthy, 2006), baseball batting (Gray, 2004),

mathematical problem-solving (Beilock, Kulp, Holt, & Carr, 2004; Beilock & Carr, 2005;

Beilock & DeCaro, 2007), test taking (Ashcraft & Kirk, 2001; Eysenck, 1979; Kahneman,

1973; Wine, 1971), intellectual reasoning (Gimmig, Huguet, Caverni, & Cury, 2006), and

category learning (Markman, Maddox, & Worthy, 2006). Another line of research

investigating direction of attention has examined the effects of focusing on the

movement of the skill (internal focus) and its movement effect (i.e., external focus) in a

variety of tasks including golf pitching (Bell & Hardy, 2009; Wulf, Lauterbach, & Toole,

1999; Wulf, McNevin, & Shea, 2001), a balancing task on a stabilotmeter (McNevin,

Shea, & Wulf, 2003; Wulf, Hoeß, & Prinz, 1998), a ski-slalom simulation task (Wulf, et al.,

1998), and volleyball and soccer (Wulf, McConnel, Gaertner, & Schwarz, 2002).

Moreover, there is preliminary evidence from category learning and key pressing

paradigms (DeCaro, Thomas, Albert, & Beilock, 2011) that the type of pressure faced in

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a critical performance situation interacts with the cognitive demands of a task in a

similar way as direction of attention does. Finally, the reward structure of the task (i.e.,

losses vs. gains) plays an important role in the fragility of choking and further interacts

with the cognitive demands of the task and the direction of attention (Grimm,

Markman, Maddox, & Baldwin, 2008; Markman, et al., 2006; Plessner, Unkelbach,

Memmert, Baltes, & Kolb, 2009; Worthy, Markman, & Maddox, 2009).

In this section on choking under pressure, I first introduce these factors and

show how they systematically influence performance: (a) the cognitive demands of the

task, (b) the direction of attention, (c) the type of pressure, and (d) the task reward

structure. Then, I review theories that try to explain how and why choking occurs,

drawing from different perspectives such as drive, behavioral, and cognitive views.

Lastly, I review currently-tested methods on preventing choking including implicit

learning, self-consciousness training, and practicing under mild anxiety.

1.1.1 Cognitive Demands

Cognitive demands of a task vary from working memory-reliant (WM-reliant) to

proceduralized tasks and can depend on a person’s level of expertise (i.e., cognitive vs.

autonomous level of skill acquisition) or the nature of the task (e.g., rule-based vs.

information-based, complexity of cognitive tasks).

WM-Reliant Tasks. WM-reliant tasks are characterized by a need to monitor the

individual steps or processes used in task completion. These include actions in the early,

“cognitive” stage of skill acquisition (Fitts & Posner, 1967) (e.g., novice motor actions),

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altered ways of completing an action in the late, “autonomous” stage of skill acquisition

(e.g., changing aspects of well-learned motor action), and analytical tasks that, typically,

are not heavily proceduralized (e.g., complex arithmetic problem solving). For example,

a tennis player relies on monitoring the step-by-step processes involved in hitting a

forehand stroke during a rally. Specifically, attention needs to be paid to the speed,

direction, and slope of the incoming ball, which foot to start running with to get to the

ball, the position of the feet while hitting the ball, the back and through swing of the

racket, the angle in which the racket head makes contact with the ball, and the direction

of the follow-through.

In the beginning of skill acquisition, a novice player may consciously think about

one or more of these aspects while playing. An expert tennis player typically does not

need to pay conscious attention to the individual processes because the skill has been

automatized or proceduralized. However, if changes are made to the procedure of the

stroke, WM processes of skill execution are reengaged and the task reverts back to a

WM-reliant one. For example, if there is a change in stance from a closed to an open

one, there would be a need to adjust the movement of the racket and the rest of the

body accordingly. Furthermore, complex tasks which do not allow for the repetition of

actions or processes do not lend themselves to becoming overly proceduralized. For

example, many instances of analytical reasoning, arithmetic problem-solving, and rule-

based category-learning remain of WM-reliant nature and are completed in a step-by-

step fashion regardless of expertise level. That is not to say that these tasks cannot be

practiced and automatized; however, typically, people do not memorize these to the

7

extent of direct retrieval. With respect to this research, golf putting represents a WM-

reliant task for novice golfers.

In WM-reliant tasks, skills are represented in declarative memory and require

attentional resources for successful completion. Performance is closely monitored

within working memory. As these tasks afford controlled attention, anything that

distracts or consumes attentional resources has the potential to cause performance

decrements as has been shown in dual-task paradigms ranging from sensorimotor tasks

such as golf putting (e.g., Beilock & Carr, 2001, Lewis & Linder, 1997) and baseball

batting (Gray, 2004) to cognitive tasks such as category learning (e.g., Markman et al.,

2006) and mathematical problem-solving (e.g., Beilock et al., 2004). In sum, these

studies have shown that when completing a WM-reliant task, people need to attend to

what they are doing, otherwise they fail.

Proceduralized Tasks. When acquiring a skill, people start out by learning the

individual processes that make up the skill. After practice, the individual parts of a skill

are combined resulting in one gross, fluent movement that is automatized or

proceduralized. For a proceduralized skill, the need to consciously use the individual

processes is reduced and a much greater emphasis is placed on the whole action. Many

tasks that people do, even on a daily basis, can be automatized such as driving a car,

washing dishes, or speaking a foreign language. For example, after automatization,

drivers do not consciously attend to where the gas, break, and clutch pedals are and at

which speed to shift up or down. With respect to this research, golf putting is a

proceduralized task for expert golfers.

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Proceduralized tasks are executed automatically and largely outside of

conscious awareness. According to the stages of skill acquisition, they fall into the final,

the autonomous stage (Fitts & Posner, 1967). In this stage, cognitive monitoring is

nearly eliminated and once a proceduralized action is initiated, it is difficult to interrupt.

In fact, explicit monitoring to the individual processes of proceduralized skills can harm

performance as has been shown in numerous studies ranging from sensorimotor (e.g.,

Beilock et al., 2002; Jackson et al., 2006) to cognitive tasks (e.g., Beilock & Carr, 2005;

Gimmig et al., 2006).

In terms of the neural mechanisms involved, two different memory systems have

been identified corresponding to declarative (i.e., feedback- or rule-based) and

nondeclarative (i.e., paired-associate) versions of a classification task (i.e., weather

prediction task) (Poldrack et al., 2001; Poldrack & Packard, 2003). Use of the declarative

version yielded in brain activation in the medial temporal lobe (i.e., hippocampus),

whereas use of the nondeclarative task yielded in activation in the striatum (i.e.,

caudate putamen). Interestingly, it was also found that activation in the two memory

systems was negatively correlated. This finding supports the idea that the rule-based

and paired-associate tasks activate brain areas that are, at least in part, mutually

exclusive.

The architecture of the weather prediction task with its flexibility to alter the

nature of the task is comparable to that of the categorization tasks used in studies of

choking under pressure as discussed above. Presumably, the underlying neural

processes found in the weather prediction task are similar to those initiated in category

9

learning. It would seem that novice golfers for which putting represents a WM-reliant

task would show similar brain activation as the rule-based weather prediction task.

Likewise, expert golfers for which putting represents a proceduralized task may show

similar activation patterns as those of the paired-associate classification task. Along

these lines, it can be deduced that novice and expert putting activates brain areas that

are, at least in part, mutually exclusive, further suggesting that changes in instruction

(e.g., direction of attention or imagery) or in the environment (e.g., inducing pressure)

may lead to different performance outcomes.

1.1.2 Direction of Attention

Attention has been manipulated in terms of skill-focused vs. distraction (Beilock

et al., 2002, Beilock & Carr, 2001) and focusing on the movement (itself) vs. movement

effect (Bell & Hardy, 2009; McNevin, et al., 2003; Wulf, et al., 1998, 2002; Wulf,

Lauterbach, & Toole, 1999; Wulf, McNevin, &Shea, 2001; Wulf & Prinz, 2001), what has

also been coined internal and external focus.

According to the work by Beilock and her colleagues (Beilock et al., 2002, 2004;

Beilock & Carr, 2001; Beilock & DeCaro, 2007), direction of attention has been tested

with regards to skill-focus and distraction and has been found to interact consistently

with the cognitive demands of the task in a variety of tasks as discussed above. Skill-

focused attention occurs when the focus of attention is on a particular aspect of skill

execution as in single-task paradigms such as attending to the inner side of one’s foot

while dribbling a soccer ball or monitoring the movement of the clubhead during golf

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putting (e.g., Beilock et al.). Distraction or outcome-focused attention involves attending

to aspects other than skill execution such as in visual and auditory dual-task paradigms

(e.g., monitoring an audio recording for a target tone while putting a golf ball) (Beilock

et al.; Beilock & Carr). WM-reliant tasks require skill-focused attention for optimal

performance and are impaired when attention is disrupted (i.e., distraction or outcome-

focused attention). For example, Beilock et al. showed that novices dribbled a soccer

ball worse when they had to do a secondary task than when they only had to focus on

dribbling. For novices, dribbling is WM-reliant and they need more attentional resources

to do well and their performance breaks down when attention is partially engaged in

another task.

Conversely, proceduralized tasks suffer from skill-focused attention but remain

unaffected by distraction and outcome-focused attention. In the same study, Beilock et

al. (2002) showed that expert dribblers performed better under dual-task attention and

choked under skill-focused attention. Dribbling is encoded in chunks, supporting real-

time performance and is impaired when attentional monitoring and control are

imposed. Attending to the act of dribbling is not only unnecessary but hurts

performance.

The line of work by Wulf and other researches (Bell & Hardy, 2009; McNevin, et

al., 2003; Wulf & Prinz, 2001; Wulf, et al., 1998; Wulf, et al., 1999; Wulf, et al., 2001;

Wulf, et al., 2002) examined the use of an internal (movement) versus an external

(movement effect) focus of attention. An internal focus of attention involves focusing on

the movement of the body when performing a task as in how to move the hands during

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a golf putt. An external focus of attention has to do with directing attention towards the

effect these body movements have as in making the ball roll in a straight line towards

the hole. Note that anything but the body itself is included in this focus of attention

even such targets as the movement of the clubhead. This categorization is in contrast to

Beilock’s skill-focused attention which would include the movement of the clubhead

under this type of attention.

The external focus of attention can be more or less distant from the body

movement. For example, Bell and Hardy (2009) had skilled golfers focus on a proximal

(i.e., movement of clubhead) or a distal (i.e., slope of flight of the ball) external focus of

attention in a golf pitching task (i.e.. golf swing with an iron club for relatively short

distance used to approach the putting green). He found that under low and high

pressure, golfers pitched closer to the target when using the distal external than the

proximal external focus of attention. Yet, both of these instructional groups performed

better than an internal focus of attention (i.e., movement of arms) group. According to

these results, the more distant the focus of attention was, the better performance

under low and high pressure. Thus, this result is consistent with the general finding of

Beilock and her colleagues’ findings that skill-focused attention hurts skilled

performance and directing attention away from skill execution (as in dual-task

paradigms) does not hurt such performance. With respect to skill learning, other

researchers found novices also benefited from an external focus of attention over an

internal one in a ski-slalom simulation and a balancing task (e.g., Wulf et al., 1998).

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These two lines of research suggest that what people focus on greatly affects

their success in skill learning and performance. Based on previous findings, it can be

predicted that skill-focused attention should help novices but hurt expert performance

and distraction as induced by a dual-task paradigm negatively affects novices but not

experts.

1.1.3 Type of Pressure

Pressure leads to worry and anxiety to perform well and people typically

respond by raising their level of effort (Baumeister, 1984). This increased effort is

accompanied by a redirection and perhaps even a narrowing of attention to certain

aspects of performance. Furthermore, it has been suggested that where attention is

directed depends, at least in part, on the characteristics of the perceived pressure

situation (DeCaro et al., 2011).

Support for this idea has been obtained by DeCaro et al (2011) who showed that

type of pressure interacts with the cognitive demands of a task using category learning

(Experiments 1-3) and key pressing (Experiment 4). Here, pressure was categorized into

outcome and monitoring pressure which were thought to induce skill-focused and

divided attention (or distraction), respectively. Monitoring pressure occurred when

people felt evaluated or being watched as when being video-recorded. Outcome

pressure was perceived during high stakes situations as when performance was

rewarded by monetary incentives and/or when people were paired up with an

imaginary partner (i.e., peer pressure). The results of DeCaro et al.’s study indicated that

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performance on the WM-reliant task (i.e., rule-based category learning) was unaffected

when being video-recorded but compromised under outcome-focused pressure. For the

proceduralized task (i.e., information-based category learning), performance was

impaired under monitoring pressure, however, was not only maintained but enhanced

under outcome pressure.

To my knowledge, this is the first study investigating how different types of

pressure categorized as monitoring and outcome pressure affect performance. Prior

studies either used what can be called outcome-focused pressure alone (Beilock & Carr,

2001; Gray, 2004; Markman, et al., 2006), or a mixture of the elements of outcome and

monitoring pressure (Reeves, Tenenbaum, & Lidor, 2007). For example, Beilock and Carr

used monetary incentives and peer pressure and found performance decrements in golf

putting for practiced participants. Similarly, Markman et al. used the same type of

pressure in a category learning paradigm (rule-based vs. information-integration). Here,

choking occurred for the rule-based category learning task only and performance was

even enhanced for the information-integration task. Finally, Gray tested the effects of

pressure on a sensorimotor task. He had expert baseball players perform a simulated

baseball batting task in a similar pressure scenario. Contrary to the findings of the

DeCaro et al (2011) study, expert golfers exhibited performance decrements under

pressure in form of increases in mean temporal swing error (MTE). That is, the athletes’

stroke became more variable and less fluid with greater inconsistencies in the timing of

hitting the ball under pressure as compared to the control condition. It is not entirely

clear why a highly proceduralized task was impaired by outcome pressure in this study.

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Finally, Reeves and his colleagues (2007) set skilled soccer players under, what

can be called, a “mixed” pressure scenario including elements of outcome (i.e.,

competition) and monitoring (i.e., social evaluation) pressure and confirmed choking

under pressure. While this study reflects a more naturalistic competitive environment, it

is unclear which aspect of the pressure scenario may have driven the performance

decrement under pressure. In sum, more research is needed to clearly establish the

effects different types of pressure have on performance, and this study attempts to do

that.

1.1.4 Regulatory Focus

Failure or success of performance under pressure depends not only on the

interaction between the cognitive demands of the task and whether a person focuses

on skill execution, but also on the task reward structure and how a person relates to the

structure (what is collectively called the regulatory focus match or mismatch).

Classic theories of achievement motivation (e.g., Atkinson, 1957) posit that

people should focus on positive outcomes, that is, trying to score rather than preventing

the other team to score (Weinberg & Gould, 2003). However, Higgins (1997, 1998)

suggested that the regulatory focus, or motivational orientation, (e.g., attempting to

score or preventing the other team to score) interacts with the reward structure, or the

intrinsic demands, of the task (e.g., offense or defense of a football team). Regulatory

focus is defined as either being directed towards potential gains (e.g., scoring a

touchdown or field goal), what is called a promotion focus, or towards preventing losses

15

(e.g., preventing the opposing team from scoring), what is called a prevention focus.

Similarly, a task is said to have an intrinsic propensity towards either a gains or losses

structure; that is, a task itself emphasizes making hits or approaching success (e.g.,

shooting baskets), or avoiding errors or failure (e.g., a flawless performance in figure ice

skating).

A regulatory focus match occurs when the regulatory focus fits the task reward

structure (Higgins, 2000); that is, a promotion focus is applied to a gains task (e.g.,

offense football team is trying to score) or a prevention focus to a losses task (e.g.,

defense football team is trying to prevent the other team to score). Regulatory focus

matches are associated with greater cognitive flexibility or an increased tendency to try

various strategies such as testing various rules and making qualitative changes to the

current strategy (Grimm et al., 2008). Moreover, they enhance explicit learning and are

quite effortful. Regulatory mismatches involve a person’s promotion focus with a losses

task (e.g., offense football team trying to avoid interceptions or incomplete passes) or a

prevention focus with a gains task (e.g., defense football team trying to tackle players

from the opposing team and to sack the quarterback). Mismatches are associated with

enhanced nondeclarative or procedural learning and decreased cognitive flexibility.

Regulatory focus relates to the cognitive demands required, as shown by work

using a category learning paradigm (Grimm et al., 2008; Maddox, Baldwin, & Markman,

2006; Markman et al., 2006; Markman, Baldwin, & Maddox, 2005; Worthy, et al., 2009).

For example, Markman, et al. (2006) found that the effects of pressure on category

learning tasks differed as a function of the task’s cognitive demands. Specifically, people

16

learned either a rule-based (i.e., WM-reliant) or an information-based (i.e.,

proceduralized) category learning task and performance was measured under low and

high pressure conditions. As expected, and in line with previous research (e.g., DeCaro,

et al., 2011), the WM-reliant task was harmed under pressure while the proceduralized

was not. This finding is also consistent with research exploring the interaction of

cognitive task demands and pressure which posits that WM-reliant tasks require more

attentional resources and that pressure compromises those resources by inducing worry

and anxiety.

Although the underlying mechanisms are still unknown, regulatory focus

matches have been found to increase executive resources while mismatches reduce

these resources (Worthy, et al., 2009). Worthy et al. proposed that pressure does not

directly reduce working memory resources but affects a person’s motivational state

which then interacts with the task reward structure. Regulatory focus matches yield a

sense of “feeling right” and increased engagement and confidence, while mismatches

lead to a sense of “feeling wrong” and increased worry and anxiety (Aaker & Lee, 2006;

Higgins, 2000).

So far, most studies of choking under pressure have used a gains task reward

structure and it has been argued that this is why only one pattern of results has

emerged (Worthy et al., 2009); that is, choking in proceduralized tasks when skill-focus

is applied and choking in WM-reliant tasks when not enough attention is paid to skill

execution. Thus, a third factor, namely, regulatory focus match, further affects the

cognitive demands of the task and direction of attention. For the purpose of this

17

research, I focus on tasks that have a gains reward structure; that is, I instruct people to

land as many putts as possible inside the hole.

1.2 Theories of Choking Under Pressure

1.2.1 Early Theories

Drive Theories. Early attempts to explain the mechanisms underlying choking

under pressure involved drive and behavioral accounts while more recently two

prominent cognitive theories emerged. Drive theories are based on the relationship

between performance and the level of arousal or “drive” (Easterbrook, 1959; Spence &

Spence, 1966; Yerkes & Dodson, 1908). For example, the Yerkes-Dodson Law and the

Easterbrook hypothesis advocated an inverted-U function between performance and

arousal or “drive,” with optimal performance occurring when arousal is neither too low

nor too high, but at some “happy” medium. Easterbrook further explained that low and

high arousal result in changes in attention, leading to foci that are either too broad or

too narrow, respectively. While this relationship accurately describes some aspects of

observed behavior, it does have some shortcomings. For example it is unclear whether

arousal is intended to be physiological, emotional or both.

Behavioral Theories. Behavioral theories entail biomechanical processes for the

implementation of skilled motor actions. Bernstein (1967), and later Vereijken, van

Emmerik, Whiting, and Newell (1992), proposed that (human) joints can be moved in

many ways and when summing those joints that are responsible for a particular skill,

then the body can potentially be moved in innumerable ways. In this sense, researchers

18

speak of joints as having multiple “degrees of freedom (df).” So, to control body

movement, novices lock some joints or couple movements of multiple joints together to

freeze some of these. As a consequence, novice performance may appear stiff and

controlled. Further along in learning, after gaining a certain level of automatization,

performers begin to defreeze the df of their joints to allow for more flexible and

perhaps fluent motor movement. In procedural tasks, choking under pressure would be

displayed when skilled performer “refroze” the df in their joints, thereby reverting back

to novice strategies (Beilock & Gray, 2007).

Support for the freezing df account provides a study of weightlifters who

exhibited a higher cross-correlation between neck and hip joints when they

underperformed in competitive situations than when they performed during practice

(Collins, Jones, Fairweather, Doolan, & Priestley, 2001). Further support was obtained in

a computer-simulated batting (Higuchi, Imanaka, & Hatayama, 2002) and novice rock

climbing tasks (Pijpers, Oudejans, Holsheimer, & Bakker, 2003).

1.2.2 Recent Theories

Cognitive Theories. Pressure initiates a heightened feeling of importance

towards one’s performance, frequently displayed as anxiety or ruminative thought

(Baumeister, 1984). A person tries to reduce such anxiety by investing more effort.

Initially, two competing theories emerged in response to disparate patterns of findings

of choking. On the one hand, it was repeatedly found that pressure impaired

performance because it led to directing attention towards skill execution which harms

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proceduralized tasks (Beilock & Carr, 2001; Beilock et al., 2002; Gray, 2004; Jackson et

al., 2006; Masters, 1992; Lewis & Linder, 1997; Leavitt, 1979; Smith & Chamberlin,

1992). These findings led to what can be called self-focus theories which include the

explicit monitoring and conscious processing hypotheses. Proceduralized tasks run

mostly outside of working memory and are harmed during step-by-step skill monitoring

that disrupts automatized performance. Such skill-focused attention causes the

integrated control structure of these tasks to break down into smaller units, similar to

what it was like during early learning (Masters, 1992). This process leads to an overall

slowing of performance and increased opportunities for errors between the single units.

The person may believe that the extra attention towards skill execution must result in

better performance and does not anticipate that this focus turns out to be maladaptive.

On the other hand, distraction theories emerged mainly from research on test

taking and posit that pressure hurts performance because it can lead to diverting

attention away from skill execution (Beilock & DeCaro, 2007; Beilock et al., 2004;

Gimmig, et al., 2006; Markman, et al., 2006). WM-reliant tasks require all or most

attentional resources for successful task completion and are impaired when those

resources are compromised by distraction or ruminative thoughts as when performing

under pressure (Beilock & Carr, 2001; Lewis & Linder, 1997; Wine, 1971). Essentially,

these task-irrelevant thoughts then compete with task-relevant ones and take up

attentional resources that are needed for successful task completion, turning what was

once a single-task into a dual-task.

20

How can pressure lead to both directing attention towards and away from task

completion and lead to such disparate findings in proceduralized and WM-reliant tasks?

A recent study (DeCaro, et al., 2011) showed that pressure can originate from different

sources and, thus, can have varying effects on attention. As described above, monitoring

pressure draws attention towards skill execution and especially hurts proceduralized

task performance while distraction pressure floods the performer with thoughts of

worry and anxiety which compromises WM-reliant task performance. More research is

needed to confirm these relationships and it is one aim of this study to extent this

findings on a proceduralized task.

1.3 Alleviating Choking Under Pressure

1.3.1 Previous Research

Because choking is predictable to some extent, methods that prevent or reduce

the severity of choking can be developed. As noted earlier several factors systematically

affect performance under pressure. These factors vary in the extent to which they can

readily be manipulated. That is, cognitive demands of the task (e.g., skill level), pressure,

and the intrinsic nature of the task (e.g., gains reward structure) cannot be readily

altered as they are more or less set or fixed for a given performance event. That is not

to say that skill level does not change, it certainly does; however, this change typically

takes time and the focus of this research is to find methods to alleviate choking that can

be spontaneously and flexibly implemented to the given individuals and situational

conditions. Thus, skill level will be treated as a fixed factor here. However, one can

21

change how performers perceive and approach the more or less set situation. These

more variable factors (discussed here) include what performers focus on (e.g., skill

focus, movement effect). For example, task instructions can be phrased to draw

attention towards or away from skill execution and can induce a prevention or a

promotion focus.

Methods of alleviating choking involve matching those variables that can be

manipulated to the more or less fixed situation. For example, for WM-reliant tasks that

involve a gains reward structure, choking occurs when people do not use enough

attentional resources for skill execution. Thus, finding ways to help performers engage

most or all of their attentional resources towards skill execution and preventing

distraction will help preventing choking. In contrast, for highly proceduralized tasks

(involving a gains structure), choking has been found when attention is explicitly

directed towards skill execution. Here, finding ways to avoid such unnecessary (or extra)

skill focus and the direction of attention in conducive ways may help prevent choking.

To date, three methods have been proposed to alleviate choking: (a) implicit or

errorless learning (Masters, 1992), (b) self-consciousness training (Beilock & Carr, 2001),

and (c) practicing under mild anxiety (Oudejans & Pijpers, 2010). Implicit learning

involves teaching people how to execute a skill without explicit knowledge (i.e., implicit

learning) (Masters, 1992). Masters (1992) trained people on a golf putting task under

either explicit instructions or a dual-task paradigm (i.e., implicit learning) and then

exposed them to a high pressure scenario. While the implicit learning group improved

during high pressure, the explicit instruction group did not. However, it should be noted

22

that the implicit learning group exhibited slower learning than the explicit instruction

group before the pressure scenario as they putted with lower accuracy. Thus, a

disadvantage of implicit training may be that learning occurs more slowly and can only

be circumvented by prolonged periods of practice (Maxwell, Masters, & Eves, 2000).

Moreover, there is a growing body of work suggesting that implicit training may prove

to be a promising avenue in preventing or reducing choking under pressure (Poolton,

Maxwell, & Masters, 2004).

Another method to alleviate choking is skill monitoring or self-consciousness

training. This method provides people with practice at dealing with feeling monitored

and/or evaluated (Beilock & Carr, 2001; Reeves et al., 2007). In Beilock and Carr’s study,

people received a considerable amount of training in golf putting under one of two

training conditions, and were then exposed to a pressure situation. The baseline training

condition involved a single-task learning paradigm which involved golf putting training

only. In the second training condition, people were video-recorded and were told that

the recording would be used for subsequent analysis by experts. This self-consciousness

training condition directed attention towards skill execution during training, the

mechanism that had previously been found to cause choking under pressure in skilled

performance (e.g., Lewis & Linder, 1997). Beilock and Carr found that performance

decrements occurred in the control (no self-consciousness training) but not the self-

consciousness training condition. However, no such choking occurred now that

participants had gotten used to being monitored, showing signs of being immune to the

pressure situation.

23

It is not entirely clear why self-consciousness training alleviated the effects of

pressure on performance and several explanations can be given. One possibility is that

skill monitoring during practice helped people adapt to the otherwise detrimental

effects of skill-focus induced by pressure. In other words, dealing with skill-focus in

training helped dealing with skill-focus under pressure. Another explanation is that the

self-consciousness condition accustomed people to dealing with pressure in general, as

in a moderate amount of pressure during training prepares one to perform well in high

pressure situations (see below; Oudejans & Pijpers, 2010). More research is warranted

to resolve these possibilities.

Lastly, it has been suggested that practicing under mild anxiety can help prevent

choking under high anxiety (Mesagno, Marchant, & Morris, 2008; Oudejans & Pijpers,

2010). It may be that one aspect of the self-consciousness training used by Beilock and

Carr (2001) was to induce mild anxiety during practice. Oudejans and Pijpers (2010) had

people practice dart throwing under mild anxiety and found that people did not

experience performance decrements under high anxiety conditions while people who

practiced under no (or low) anxiety choked. Anxiety was induced by having people

throw darts from platforms in three different heights (low anxiety = .14m; mild anxiety =

1.84m; high anxiety = 3.96m) and subsequent manipulation checks in form of self-report

confirmed the heightened perception of distress with increasing height by assessing

anxiety, perceived effort, and heart rate during all phases of the experiment. The

experimental group practiced under low and mild anxiety conditions while the control

group practiced under low anxiety conditions only. The experimental group’s

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performance was maintained and choking prevented in all anxiety conditions while the

control group’s performance declined in the high anxiety condition. Anxiety scores as

well as heart rate and effort gradually increased with increased height on the climbing

wall (i.e., increased induced anxiety), while performance broke down in the high anxiety

condition only for those who did not practice under mild anxiety. According to Oudejans

and Pijpers (2010), increased perceived effort led to more effective self-regulatory

activity and people faced with mild anxiety in practice were able to develop coping

strategies to deal with pressure and anxiety that helped them maintain regular

performance levels under higher pressure. Thus, the induction of mild anxiety into the

practice sessions prior to completion proves to be a promising avenue in the prevention

of choking.

While implicit learning, self-consciousness training, and practicing under mild

pressure have been shown to reduce choking in some situations, they vary in their

applicability. First, all three methods take a long time to be implemented. Implicit

learning has to do with instructions during skill acquisition, that is, the development

from novice to skilled performance. Self-consciousness training and practicing under

mild pressure both involve, at least, a few sessions of practice (i.e., 270 putts or dart

throws) prior to the critical performance. Second, these methods vary in their extent to

how flexibly they can be applied to changing situations. They all involve practicing the

skill under one set of instructions that potentially alleviate choking for one set of

circumstances. For example, self-consciousness training and training under mild anxiety

have been shown to alleviate choking for somewhat skilled performers (novices with

25

extensive practice) in one particular pressure scenario. More recently, it has been found

that the architecture of the pressure scenario can have an impact on performance and

differentially affect performers of differing skills or of tasks with differing cognitive

demands (DeCaro et al., 2011). It is yet to be determined whether or not the effects of

self-consciousness training and practice under mild anxiety will transfer to pressure

scenarios and skill levels other than the ones that have been tested so far.

Finally, the three methods vary in how easily they can be integrated into

practice. While it does not take much effort to set up a situation in which a performer

feels being evaluated or under mild pressure, finding just the right amount pressure,

that is not too much and not too little, can be challenging. People perceive situations

differently and some may be more susceptible to pressure than others. Not only do

these methods need to be tailored for each individual, they also “discourage” group

practice sessions. Implicit learning is not feasible in that performers need to be isolated

from explicit instruction during the entire phase of skill acquisition and it may take a

long time to acquire expertise.

The aim of the proposed research is to find a new way to alleviate choking that

can be readily and flexibly applied to differing situations and that does not take a long

time to acquire. Moreover, it will entail directing attention to stimuli that are conducive

to performance as shown by patterns in performance from previous research of choking

under pressure. Essentially, I am trying to instill a focus of attention that is conducive to

skill execution and can be matched to skill level and situational and task demands.

Specifically, the goal is to find a new way to draw attention to skill execution during

26

WM-reliant tasks and directing attention away from skill execution during

proceduralized tasks in a way that is preserved during various pressure situations.

1.3.2 Alleviating Choking Using Imagery Practice

If choking is caused, in part, by the maladaptive direction of attention in

response to pressure, then manipulating what a person attends to can reduce the rate

and severity of choking. If choking can occur in WM-reliant tasks when attention is

directed away or otherwise consumed by distractions, then focusing on the general

framework of task execution should lead to less choking under pressure. Similarly, if

choking can occur in proceduralized tasks when attention is directed towards the

individual steps of skill execution, then avoiding explicit monitoring should reduce

choking under pressure. Thus, the question arises of whether we can instill a certain

way of self-focus or self-evaluation that helps the performer to maintain an attentional

focus that is conducive to his or her cognitive demands?

One way of manipulating attention is through imagery practice in which one

internally simulates performing a task without externally moving. Indeed, imagery is

comparable to the actual experience of actions including the sensation of diverse senses

(i.e., visual, kinesthetic, auditory, olfactory, and gustatory) only that these occur

imaginatively (Weinberg & Gould, 2003). Along with self-talk and arousal regulation,

imagery practice has been said to be one of the most important practice methods for

the development and fine tuning of cognitive abilities in the field of sports psychology

27

(Mayer & Hermann, 2010). Yet, it has also been shown to be transferrable to other fields

such as rehabilitation, business and economy (Immenroth et al., 2008). Ultimately, the

goal of the inner rehearsal of the movement processes is to positively affect skill

execution (Mayer & Hermann). As it pertains to this research, it will be tested whether

imagery practice can lead to more efficient skill acquisition and more robust overall skill

performing under various external conditions such as outcome and monitoring pressure.

Several factors have been identified to affect the effectiveness of imagery

practice on performance such as imagery ability (Driskell, Copper, & Moran, 1994),

expectancy (Bandura, 1977), arousal level (i.e., being relaxed immediately before or

during imagery practice), and imagery contents (Mayer & Hermann, 2010). Imagery

ability plays an important role in the extent to which the practice will improve

performance and studies have identified individual differences (Morris et al., 2005) that

can be assessed via different aptitude tests such as the Revised Vividness of Movement

Imagery-2 (VMIQ-2; Roberts, Callow, Hardy, Markland, & Bringer, 2008) or the

Movement Imagery Questionnaire-Revised (MIQ-R; Hall & Martin, 1997). It has been

shown to be beneficial when performers enter a relaxed state immediately before and

during the imagery practice to be able to focus more intensively on the mental

simulation (e.g., Eberspächer, 2001). Furthermore, it has been discussed that the

presence of kinesthetic feelings during imagery increases its effectiveness (e.g., Hardy &

Callow, 1999), that positive imagery is more effective than negative or no imagery

(Beilock, Afremow, Rabe, & Carr, 2001), and that imagery is even useful in novices with

little experience performing the task (Mayer & Hermann). Finally, the visual imagery

28

perspective or vantage point has been greatly discussed with respect to its effectiveness

in skill learning and performance with yet unequivocal findings. It is the aim of this

research to, firstly, test if differences in cognitive demands may shed light on the

conditions in which first- and third- person imagery might be used best and, secondly, to

use imagery to prevent choking under pressure.

1.3.2.1 Visual Imagery Perspective

Imagery can be practiced from either a first- (or internal) or a third- (or external)

person perspective. For example, an athlete can use a first-person imagery perspective

when preparing herself for an important tennis match. She would then imagine herself

as if she was actually playing; that is, looking out from her eyes at the tennis court and

the opponent, focusing on external factors that might influence the match. As such, this

perspective most closely resembles actual experience and may be accompanied by

kinesthetic sensations, thoughts, and feelings that typically arise during actual

performance.

Conversely, a tennis player may use a third-person imagery perspective as pre-

competition preparation. Here, she would look at herself from another person’s vantage

point and at her (own) body while she is playing the match. Therefore, the focus would

be on how she moves her body and overall appearance. This experience is similar to

that of watching another person of oneself on video. A wide range of visual angles and

distances to the actor can be manipulated, ranging from “standing” right in front or next

to the actor to high up from above as in a bird’s eye view (e.g., Callow & Ross, 2010). As

29

such, it has the potential to emphasize different aspects of the action such as the skill,

the actor, the environment, the target etc. Taking a golf putt as an example, third-

person imagery from a frontal viewpoint may focus attention more on the skill (i.e., skill-

or movement-focused) whereas imaging oneself from a rear viewpoint might emphasize

the aim of the ball (i.e., outcome- or movement effect-oriented). In essence, imagery

perspectives can be used to manipulate attention and, thus, can influence the learning

and performance of skills in different ways.

1.3.2.2 Perspectives in Sports Performance

Visual imagery perspective has been a point of discussion in the sports literature

for some time. Since Mahoney and Avener (1977) reported that U.S. gymnasts who

qualified for the Olympics used an internal (i.e., first-person) visual imagery perspective

more than their less successful counterparts, the debate on the effectiveness started.

Other studies found no significant differences in the effectiveness of external (i.e., third-

person) versus internal visual imagery practice in unskilled and skilled racquetball player

(Meyers, Cooke, Cullen, & Liles, 1979) and in practiced figure skaters performing a

senior level figure (Mumford & Hall, 1985). Finally, Ungerlinder and Golding (1991)

reported that U.S. track and field trialists who qualified for the Seoul Olympics were

found to use more external imagery than their less successful counterparts. Equivocal

findings plagued the early phase of this research; however, more clarity has been

reached since then reflected in, what can be grouped into, two main hypotheses about

the choice of visual imagery perspective in sports.

30

One group of researchers (Hardy, 1995, 1997; Hardy & Callow, 1999; White &

Hardy, 1995) argues that the type of task (open vs. closed skills) is found to be the

driving factor while another group (Mayer & Hermann, 2010; Munzert, Dültgen, &

Möllmann, 2000) suggests that the purpose of the imagery exercise decides which

perspective would be most suitable in a given situation. On the one hand, Hardy (1997)

and White and Hardy (1995) argue that task differences may influence the use of

imagery perspective. Hardy (1997) suggested that an internal perspective would be

more effective in the acquisition and performance of tasks that depend on anticipation

and perception of the situation as is the case in tennis and hockey (i.e., open skills).

Open skills are typically performed in a changing and interactive environment.

Conversely, a external perspective would facilitate the acquisition and performance of

tasks that emphasize form such as gymnastics and ice-skating (i.e., closed skills). Closed

skills are performed in relatively stable environments and are rather predictable and

often self-paced. White and Hardy argue that imagery practice should add important

information for skill execution that is typically not available to the performer during

performances. So, when people perform a task that is reliant on form (e.g., gymnastics

floor routine) then they would find information on the precision of their movements as

seen from an external viewpoint as most useful because they cannot be “seen” from an

internal visual perspective. It is further argued that tasks that are not complex in their

execution, are well-learned (or highly proceduralized), and/or in which the interaction

with the environment is important (e.g., slalom canoeing) and which do not rely on

technical form and, therefore, external imagery would not add much useful information

31

to the performer. However, successful execution of these tasks relies on mental

rehearsal of the precise spatial locations, environmental conditions, and timings at

which key movements are to be initiated, attributes that are said to be more easily

acquired via internal imagery.

At first, White and Hardy (1995) partially confirmed their hypothesis in that

participants exhibited superior learning in the acquisition and retention when learning

rhythmic sports gymnastics sequence using external compared to internal imagery.

However, results on a wheelchair slaloming (acting as a canoe slaloming) task were less

clear. Participants made fewer mistakes when using internal imagery but were overall

faster when using external imagery. To my knowledge, no other studies testing the

effectiveness of imagery perspective on closed sports has been conducted to this day.

Later, Hardy and Collow (1999) showed that an external visual imagery perspective led

to superior performance than an internal one in three experiments involving sports that

emphasize form (i.e., performing karate katas, gymnastics, and rock climbing). In their

first experiment, experienced karatists learned a new kata consisting of 52 separate

movements and were assigned to practice internal imagery, external imagery, or stretch

(control group) before each physical exercise of the kata. Professional judges then

scored the performances of the karatists. Those who practiced imagery from an external

perspective in conjunction with the kata obtained the highest scores on all three tested

time points, followed by the internal imagery group which, in turn, performed better

than the control group. In the second and third experiment, Hardy and Callow divided

the imagery conditions along two factors, namely, visual perspective (internal vs.

32

external) and kinesthetic feelings (presence or absence thereof). When novices learned

a simple gymnastic floor routine, external imagery proved to be more effective than

internal imagery with no effects of kinesthetic feelings (Experiment 2). In their last

experiment, an effect for imagery perspective and kinesthetic feelings emerged in that

experienced rock climbers performed difficult boulder problems best when using

external imagery and when adding kinesthetic feelings to their imagery. Thus, the

researchers confirmed that skills that heavily rely on form as defined here benefit more

from external than internal imagery practice. Golf has previously been considered to be

a sport that emphasizes form (e.g., Arvinen-Barrow, Weigand, Thomas, Hemmings, &

Walley, 2007; Craft, Magyar, Becker, & Feltz, 2003), thus, it would be expected that all

performers regardless of skill level show superior performance using external as

compared to internal imagery.

On the other hand, the effectiveness of imagery perspective has been proposed

to depend on the purpose or the goal of the practice (Mayer & Hermann, 2010; Munzert

et al., 2000). An external imagery perspective would be best suited for the learning of

movement sequences of skills, for instance, when first linking the individual steps that

make up the whole movement of a skill. As such, this type of imagery seems conducive

to the needs of unskilled performers who are in the beginnings of learning a skill. It is

less clear whether expert golfers would benefit from this type of imagery or whether

their performance might even be hurt due to a potential extra focus on skill execution.

An internal imagery perspective is said to be most helpful when performers

rehearse skill movement in kinesthetic form to preserve fluent skill execution. Typically,

33

kinesthetic feelings are not present when a person first learns a skill but they arise with

practice. Thus, it is argued that a prerequisite for the successful application of internal

imagery is that expertise has been acquired to some extent with the skill, a point with

which the first group of researchers agrees (e.g., Hardy, 1997; Hardy & Callow, 1999).

Moreover, and along the lines with the hypothesis by Hardy and his colleagues, this

group of researchers also argues that internal imagery is compatible with the learning of

situational anticipation of change in the environment. Thus, internal imagery is held

useful when performers use imagery to anticipate what an opponent might do and to

develop strategies to counter that. According to this viewpoint on imagery perspective,

it can be hypothesized that internal imagery is compatible with the potential imagery

goals of expert golfers. Conversely, novice golfers may find this type of imagery difficult

and unhelpful.

1.3.2.3 Perspectives in Memory and Emotional Processing

Memories are associated with different perspectives. In memory research, first-

person perspective memories are called “field memories” and third-person perspective

memories are called “observer memories.” Field memories are more recent, more

emotional, include more information on affective, physical, and physiological states, and

are associated with less self-awareness than observer memories which are found to be

older, more descriptive, and less affect-laden (Nigro & Neisser, 1983; Robinson &

Swanson, 1993). Furthermore, people focusing on the self rather than the event tend to

adopt an observer perspective during the retrieval of autobiographical memories (Frank

34

& Gilovich, 1989; Wells, Clark, & Ahmad, 1998). Perspective in memories is strongly

related to how one sees oneself and is a main component of episodic memory retrieval.

With regard to performance under pressure, it is plausible to assume that

pressure arouses people to have emotional experiences. So, let’s now consider effects

of memory perspective for negative emotional experiences. McIssac and Eich (2004)

assessed vantage point for traumatic memories (i.e., car accidents, physical and sexual

assault, war incidents, witness homicide, and witness non-fatal harm). Field memories

were mostly about the person’s affective reactions, physical sensations, and

psychological states during the trauma, while observer memories included information

on the person’s physical appearance, spatial relations in the event, and peripheral

details not directly related to the trauma. Paralleling findings of non-traumatic

memories, traumatic observer memories were associated with less emotion and more

description than traumatic field memories. In sum, this research in memory suggests

that, for non-pathological individuals, memories from a first-person perspective (field

memories) are more emotional and less descriptive of the context than third-person

(observer) memories.

Inconsistent with these findings is the way social phobics relate to their

environment and from which perspective they typically perceive it (Wells &

Papageorgiou, 1998, 1999). Social phobics are characterized by feeling anxious in a wide

range of social situations in that they think that others see them in some negative way.

They remember anxiety-provoking social situations primarily as observer memories

(Wells et al., 1998) which is not the case for the other phobics (e.g., agoraphobics and

35

blood/injury phobics). Here, observer memories were associated with greater negative

affect and the maintenance of such a perspective in memory may be one example of

maladaptive emotional processing. Furthermore, Wells and Papageorgiou (1999)

demonstrated that negative affect felt by social phobics can be reduced by having them

focus attention on the external environment (and away from themselves). This shift of

attention was also accompanied with a shift from observer to field perspective imagery.

Even though the current research does not deal with phobics or highly emotional

experiences that may lead to trauma, these findings suggest that a change in imagery

perspective can influence anxiety-laden situations such as when performing under

pressure.

Lastly, perspectives have been investigated in the processing of emotional

events (Ayduk & Kross, 2008; Kross & Ayduk, 2008; Kross, Ayduk, & Mischel, 2005). In all

of their studies, Kross and his colleagues differentiated between what they call self-

immersed (akin to first-person) and self-distanced (akin to third-person) perspective.

Overall, a self-distanced perspective was most effective in processing experiences with

general negative affect including anger (Kross, et al.) and depressive experiences (Kross

& Ayduk) and in the reduction of cardiovascular reactivity (Ayduk & Kross). For example,

Kross and his colleagues manipulated what a person focused on when thinking about an

emotional event; that is, people either concentrated on what emotions they felt

including specific feelings or sensations experienced during the event (what-focus) or on

why they experienced these emotions concentrating on the reasons and underlying

feelings (why-focus). The researchers found interactions between perspective and type

36

of focus. The most successful strategy for the processing of a negative event was a self-

distanced perspective with a why-focus, which led to a “cool,” reflective, cognitive

analysis and helped people to make sense of their feelings. This strategy is different

from emotional avoidance, intellectualizing, and rumination because the emotions are

faced and experienced to some degree without reactivating excessive negative affect.

Furthermore, a why-focus coupled with a self-immersed perspective led to the greatest

emotional distress. While perspective is not completely accountable for successful

emotional processing, two other studies that did not manipulate type of focus found

that the self-distances analysis was most effective in the processing of depressive

experiences over time and in the reduction of blood pressure reactivity to negative

emotions (Ayduk & Kross; Kross & Ayduk). The researchers concluded that perspective

plays an important role in the successfulness of processing negative emotions. This

conclusion gives further support to the idea that perspective can play a role in

performance under pressure and that actively changing perspective can have an

influence on the successfulness of processing negative emotions.

1.4 Summation

The current research involves finding a flexible way of reducing choking under

pressure applicable to a number of settings including sports performance, the

performing arts, and the professional world (e.g., surgeons, air traffic controllers, pilots).

Once pressure causes one to adopt an attentional focus that is harmful to performance,

it is difficult to shift attention back into a more conducive state. It may be that instilling

37

a favorable attentional focus prior to the emergence of perceived pressure will reduce

the negative consequence that can follow from it. There is initial research showing that

implicit learning, self-consciousness training, and practicing under mild pressure can be

successful approaches in reducing choking under high pressure in skilled performance

(e.g., Beilock & Carr, 2001; Masters, 1992). This research is aimed at expanding recent

findings of the effects of type of pressure on performance of actors with varying skill

level (DeCaro et al., 2011) and at providing a novel approach in the prevention of

choking under pressure.

1.5 Overview of Experiments

This research consists of three main experiments all involving a golf putting task

after Beilock et al. (2002). In Experiment 1, the relationship between skill level and

direction of attention is tested in an attempt to replicate the commonly-found

interaction of these two factors. In the Experiment 2 series, type of pressure is divided

into outcome and monitoring pressure with 2a serving as a way to check the

manipulation of pressure against each other and against a no pressure control

condition. Experiment 2b follows with an analysis of the relationship of type of pressure

and skill level on putting performance to identify when choking occurs. Finally, in

Experiment 3, imagery is tested as a way to alleviate choking under pressure.

38

CHAPTER 2:

EXPERIMENT 1: ATTENTION REPLICATION

Previous research has consistently found that skilled golfers perform better

under dual-task than under skill-focused conditions when they do a familiar putting task

while the opposite pattern has been found for unskilled or novice golfers (Beilock et al.,

2002, 2004; Beilock & Carr, 2001). To begin, these findings were sought to be replicated

to establish a common ground with the findings of other research labs. Moreover, this

data will serve as source of comparison with the results of later experiments.

2.1 Method

2.1.1 Participants

The skilled participants (n = 22) were golfers who had at least two years of high

school or college varsity golf experience, a Professional Golfers Association (PGA)

handicap of lower of 12 or lower, and/or, at least, three years of instruction or playing

experience. The novices (n = 16) had little to no experience playing golf with no high

school or college varsity experience.

39

2.1.2 Materials

The golf putting task was done on a 2.44m x 3.66m (8 x 12 feet) artificial indoor

putting green with a stimp of 10-11. Stimp is a measure of speed of a putting green and

is determined by measuring the distance (in feet) traveled by a ball given a particular

force. A stimp of 10-11 corresponds to medium to fast speed. This speed was chosen

based on a recommendation by varsity head coach of Notre Dame’s golf team. Standard

golf putters and balls were used to complete the task.

Importance Rating. Participants rated on a one-item scale how important it was

for them to perform at a high level (Beilock et al., 2004). The importance scale ranged

from 1 (not at all important to me) to 7 (extremely important to me). Because

performance pressure, by definition, only occurs when people feel it is important to do

their best (Baumeister, 1984), reporting, at least, moderate task importance is a

criterion for participation in experiments exploring choking (Beilock & Gray, 2007).

Therefore, I include in the analysis only those people who respond with, at least, 3 or

higher on the importance item. The concept of importance is related to that of

perceived effort which was also assessed in other studies (e.g., Oudejans & Pijpers,

2010).

Pressure Rating. The pressure rating was also based on a one-item scale on

which participants rated how much performance pressure they felt to perform at a high

level (Beilock et al., 2004). The pressure scale ranged from 1 (very little performance

pressure) to 7 (extreme performance pressure). Even though pressure was not

40

manipulated in this experiment, the ratings will serve as a source of comparison to

those of the other experiments.

Postperformance Questionnaires. This questionnaire assesses participants’ golf

and other sports experiences including number of years and current frequency of

playing the sport and number of years of varsity experience.

2.1.3 Procedure

The procedure was adopted from studies by Beilock and her colleagues (Beilock

& Carr, 2001; Beilock et al., 2004). Participants putted from nine different locations on

the green, with three spots at three distances (140cm, 150cm, and 160cm) from the

target. Participants were asked to land as many putts as possible inside a standard size

hole (108 mm or 4.25 in diameter) while also attempting to get as close to the hole as

possible. All participants followed the same random alteration of putting from the nine

locations and took part in both attention conditions. Specifically, participants took 9-18

practice putts (i.e., one or two putts from each of the nine locations) on their own and

with the experimenter not looking at them to become familiar with the materials and

the task. Next, they performed the critical three trials of the putting task: 27 putts in a

single-task environment (of which the last 18 counted towards their baseline trial), 18

putts in the skill-focused condition, and 18 putts in the dual-task condition. Note that all

participants did the single-task condition first while the order of the attention conditions

was counterbalanced.

41

Single-task condition. Participants putted without specific instructions and were

asked to simply do their best. Only the last 18 putts of this condition served as the

baseline trial. The first nine putts were not analyzed because they served as practice

putts under conditions of the experimenter measuring.

Skill-focused attention condition. The golfers were told to attend to three

aspects of a golf putt. First, to position the ball somewhere in the center between their

feet, reflecting how to position oneself around the ball. Second, to keep their putter

head square to the hole to easily position the club head in line to the hole. Finally, to

keep their head down until they finished the stroke. This instruction helps the player to

swing the club straight. These components of the swing were chosen as the basis for the

skill-focused manipulation because they reflect essential and, in part, rather basic

processes in a good golf putt (Jones, Davis, Crenshaw, Behar, & Davis, 1998).

Dual-task attention condition. The golfers did an auditory word-monitoring task

while putting. Specifically, a series of words were played over headphones and people

had to say the word “vase” aloud each time they heard the target word (i.e., vase).

Responses were recorded using a digital recorder and accuracy scores computed and

compared with putting performance. There were 113 filler words of up to two

presentations per word, yielding a recording length of 6:56 minutes total. Note that the

duration of 18 putts varied across participants and so did the number of items heard on

the recording (no one reached the end of the recording). When examining secondary

task performance, proportion correct was computed. Words occurred at a random time

period once within, on average, every 2.6s time interval. Target words occurred on

42

average every 3.3 words and the number of filler words between target words ranged

from zero to five. The random placement of the words within the 2.6s time interval and

the random embedding of the target word within the filler words were designed to

prevent participants from anticipating the word presentation.

Questionnaires. After each putting trial, the importance and pressure ratings

were collected. After the putting task was finished, people completed a demographics

and sports questionnaire and were thanked and debriefed.

2.1.4 Replication Criteria

Previous research (Beilock et al., 2002, 2004; Beilock & Carr, 2001) has

consistently found that experienced golfers putt more accurately under dual-task than

under skill-focused conditions whereas novices do better under skill-focused than under

dual-task conditions. Importantly, these studies have found significant interactions

between skill level and direction of attention. Thus, the criterion for replicating these

findings was to reach a significant interaction between novice and expert golfers and

the skill-focused and dual-task condition as measured by average distance hole for each

block of trials. Moreover, these findings have been confirmed when comparing the

mean values of the skill-focused and dual-task attention conditions directly (e.g., Beilock

et al., 2004; Beilock & Carr) and the difference scores between each critical condition

and the baseline performance score (DeCaro et al., 2011). The primary focus of this

study is on how performance changes from baseline to critical conditions, therefore, the

43

analyses conducted here, as well as in all upcoming experiments, focused on the

difference scores.

2.2 Results

The difference scores of the mean distance from the target were used as

measures of performance. Means, standard errors, and difference scores are provided

in Table 2.1 and Figure 2.1. Difference scores for the skill-focused and dual-task

attention condition were calculated by subtracting each participant’s mean baseline

putting distance from that of the respective attention condition.

TABLE 2.1

MEANS AND STANDARD ERRORS (IN PARENTHESES) FOR BLOCK AND

DIFFERENCE SCORES OF PUTTING DATA BY SKILL LEVEL AND

PRESSURE CONDITION FOR EXPERIMENT 1

Skill Level

Block Difference Scores

Baseline Skill-Focused Dual-Task Skill-Focused Dual-Task

Novices Experts

23.51 (2.69) 16.58 (1.48)

21.38 (1.91) 17.77 (2.16)

27.19 (2.40) 13.95 (1.25)

-2.13 (2.06) 1.50 (1.65)

3.81 (2.20) -2.18 (1.08)

44

The data were first submitted to a 2 (skill level: expert vs. novice) X 2 (direction

of attention: skill-focused vs. dual-task) ANOVA on the difference score of the distance

measure. Neither the main effect for skill level nor for condition were significant, Fs < 1.

More importantly, the interaction between skill-level and condition was

significant, F(1, 72) = 7.78, MSE = 429, p = .007, suggesting that direction of attention

affected novices differently from experts. Tests of simple effects revealed that novices

putted marginally more accurately under skill-focused than under dual-task conditions,

Figure 2.1 Bar graph including error bars (standard error of the mean) for difference scores of the distance from hole measure clustered by skill level and attention condition in Experiment 1

45

F(1, 30) = 3.90,MSE = 282, p = .063. The opposite trend was found for experts. They

putted marginally more accurately under dual-task than under skill-focused attention

conditions, F(1, 42) = 3.48, MSE = 149, p = .071.

Because the aim of this experiment is to replicate previous findings and most

studies analyzed data on the mean as opposed to the difference scores, the analyses of

this experiment were repeated using the mean scores of distance from hole (for

Experiment 1 only). First, the data were submitted to a 2 (skill level: expert vs. novice) X

2 (direction of attention: skill-focused vs. dual-task) ANOVA. The main effect for skill

level was significant, F(1, 75) = 18.33, MSE = 1312, p < .001, while the main effect for

condition was not, F < 1. Experts putted more accurately overall than novices across

conditions. More importantly, the interaction between skill-level and condition was

significant, F(1, 75) = 6.00, MSE = 430, p = .029, confirming the effect found in the

difference scores. Tests of simple effects revealed that novices putted marginally more

accurately under skill-focused than under dual-task conditions, F(1, 30) = 3.58, MSE =

270, p = .074. While the simple effect was not significant for experts, F(1, 42) = 2.33,

MSE = 160, p = .14, the data reflect the same trend as previous research.

2.3 Discussion

Experiment 1 replicated the commonly-found interaction between skill level and

direction of attention (Beilock et al., 2002, 2004; Beilock & Carr, 2001, 2005; Beilock &

DeCaro, 2007; Gimmig et al., 2006; Gray, 2004; Jackson et al., 2006; Lewis & Linder,

1997; Markman et al., 2006). Analyses were performed on difference and mean scores

46

of the critical and baseline conditions, all of which revealed that novices exhibited

superior putting performance under skill-focused and experts under dual-task attention

conditions. Now that a common ground with previous research was established, the

study of the effects of type of pressure on performance in differently skilled actors

followed.

47

CHAPTER 3:

EXPERIMENT 2A: PRESSURE REPLICATION

After having replicated previous findings, I assessed how different types of

pressure affect performance. To my knowledge, only one study (DeCaro, et al., 2011)

differentiated between two types of pressure, and that study used a category learning

paradigm. In their study, DeCaro et al. found an interaction between type of pressure

(monitoring vs. outcome pressure) and type of task (WM-reliant vs. proceduralized). In

particular, they found that choking occurred for the WM-reliant task under outcome

pressure and for the proceduralized task under monitoring pressure. Performance was

maintained when doing the WM-reliant task under monitoring pressure and improved

when doing the proceduralized task under outcome pressure. The aim of the following

two experiments (2a + 2b) was to replicate and extend these findings using a

sensorimotor task, namely, golf putting.

First, I experimented with aspects of the two pressure scenarios to make them

equally unsettling and significantly more unsettling than a non-pressure control

condition (Experiment 2a). Then, I tested the effects of type of pressure on performance

in golf putting (Experiment 2b). Contrary to Experiment 1, the critical conditions were

tested between rather than within subjects (for all upcoming experiments) because it

48

turned out to be unfeasible to instruct participants on two elaborate pressure scenarios

and remain believable. The control condition was also chosen to assess how

performance changes in the second block with respect to practice effects.

3.1 Method

3.1.1 Participants

Thirty-six participants were assigned randomly to one of the three conditions

(monitoring pressure, the outcome pressure, or the control condition) with the

restriction of equal sample size across groups. There were six novices and six experts in

the control, five novices and seven experts in the outcome pressure, and seven novices

and 5 experts in the monitoring pressure condition.

3.1.2 Materials

The green, putters, and balls were identical to the those used in Experiment 1. In

addition to the importance and pressure ratings and the post-experimental

questionnaires used in Experiment 1, pleasantness, arousal, and controllability ratings,

trait and state anxiety inventories, and positive and negative affect scales were added.

Lastly, average and peak heart rate was measured using a standard heart rate monitor.

Self-Assessment Manikin (SAM; Hodes, Cook, & Lang, 1990). SAM was originally

devised as a computer program to assess affective responses to events and objects.

Later, a paper-and-pencil version was created (Bradley & Lang, 1994). The three

emotional dimensions valence, arousal, and dominance are assessed in pictorial,

49

nonverbal form with a series of five figures set on a continuum. Valence ranges from

pleasant depicted by a smiling, happy figure to unpleasant displayed by a frowning,

unhappy figure. Arousal ranges from excited depicted by a wide-eyed figure with jagged

circle in the stomach area (i.e., tension) to calm with a closed-eyed, relaxed figure.

Dominance ranges from controlled with a miniaturized manikin to in-control with a large

manikin. Responders mark an “x” over any of the five figures or between any two

figures. Thus, scores are recorded on a 9-point rating scale. Note that for arousal, lower

scores reflect feelings of distress and, thus, this item can be seen as negatively-phrased.

State-Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, & Lushene, 1970). The

STAI is a widely-used measure and consists of two separate 20-item scales, a long-term

(trait) and a short-term (state) measure of anxiety. The trait form assesses how fearful,

worrisome, uneasy one generally feels by responding to items such as I am a steady

person and I have disturbing thoughts on a 4-point Likert scale ranging from 1 (almost

never) to 4 (almost always). The state form measures an individual’s feelings at a

particular moment. Examples items are, “I feel calm” and “I am jittery” and the answer

choices range from 1 (not at all) to 4 (very much so). The final score on both scales is

computed by reverse-scoring negatively-phrased items and, then, summing the scores

of all items. The minimum score of 20 (very low anxiety) and a maximum score of 80

(very high anxiety) can be reached.

Positive and Negative Affect Scale (PANAS; Watson, Clark, & Tellegen, 1988). The

PANAS is a well-known measure in which participants are asked to rate the extent to

which a particular emotion is experienced. The 10 positive (e.g., interested or excited)

50

and 10 negative (e.g., distressed or upset) items are presented in mixed form and with a

5-point anchoring scale ranging from 1 (very slightly or not at all) to 5 (extremely).

Subscale scores for positive and negative affect are computed by summing the

responses of the respective 10 items and, thus, range from 5 to 25 points. Reliability for

PANAS has been good, ranging from .86 to .90 and .84 to .87 for the positive and

negative subscale, respectively.

Heart rate monitor. The heart rate monitor used was the Polar FT60 training

computer (i.e., wrist watch) that was linked to the matching WearLink transmitter (i.e.,

chest strap). The chest strap was tied around the chest with elastic bands just below the

sternum of the participant and held a small plastic signal transmitter at the front. The

wrist watch was worn by the participant for the duration of the experiment due to the

small reach of the signal transmission between watch and transmitter. Average and

peak heart rate for the duration of blocks (e.g., 18 putts under pressure) was recorded

by simply starting and stopping the desired time for which these parameters would be

measured. The watch is equipped to save up to 100 such recordings; thus, heart rate

was recorded after study completion of each or several participants and did not intrude

with study administration.

3.1.3 Procedure

Participants were assigned randomly to one of the three conditions (monitoring

pressure, the outcome pressure, or the control condition) with the restriction of equal

sample size across groups. The pressure scenarios are described below. Note that

51

participants in the control condition putted under the same circumstances as in the

single-task condition.

Some self-report measures were administered before the putting area was

approached, most of which were repeated after each block of the putting task. Resting

heart rate, trait anxiety, and pre-performance scores for the SAM scale and PANAS were

collected before the start of the putting procedure. Resting heart rate was measured

when the participant was sitting and was recorded while the experimenter pretended to

test the functionality of the apparatus. To discourage participants from thinking about

potential anxiety-related aspects of the study, they were told that heart rate was

measured to control for physical exertion. The other questionnaires were jointly

collected while the participant sat in a small room.

Then, the participant was brought to the putting green located in the room next

door. The experimenter gave the participant the putter and two balls and explained the

putting task. Participants putted from the same nine locations in the same random

alteration of locations on the green as in Experiment 1. They first took 9-18 practice

putts on their own and, then, completed the putting task under the single-task

condition. Again, this block consisted of 27 putts of which only the last 18 putts counted

toward the putting baseline score. For this block of 18 putts, the experimenter turned

on the heart rate monitor which automatically measured and saved average and peak

heart rate for the duration of this period. Immediately after this putting block,

participants completed a series of questionnaires, namely, the importance and pressure

rating, the three items on the SAM scale, the state form of the STAI, and the PANAS.

52

Next, depending on the assigned condition, the experimenter described the

respective scenario (i.e., monitoring or outcome pressure condition) or asked them to

simply do their best again (i.e., control condition). Then, participants completed the

experimental putting block and the same series of questionnaires again as after

baseline. After the debriefing, participants filled out the demographic and

postexperiment questionnaires and were thanked for participation.

Monitoring pressure scenario. Participants were told that this study was done in

collaboration with the Notre Dame Physical Education department to create an

instructional golf putting video to be used for freshman college courses and to be

posted on its departmental website. A confederate acted as the Physical Education

department’s golf professional who stood near and in clear sight of the participant for

the duration of the putting block while taking notes on a clipboard. Also, participants

were video-recorded by a small camera mounted on a hip-high tripod with the live video

being projected on a smartboard screen that was set right next to the putting green. As

such, participants could see themselves putt in real time on the 66-inch monitor. The

camera was set up so that participants were made aware of its presence while the

camera did not intrude with the golf putting task. Before the first putt of this series, the

experimenter conspicuously turned on the camera and selected the record button on

the smartboard screen to start the live video-recording. After the last putt, the

recording was stopped and the camera put away. Note that at the end of their

participation all participants immediately debriefed about the purpose of the scenario.

Also, to diminish any feelings of discomfort associated with the recording process,

53

participants were present and made aware of the deletion of their video during

debriefing.

Outcome pressure scenario. No confederate, camera, or tripod were present for

this condition. Participants were told that, in an attempt to motivate participants to do

their best, they would be entered in a competition with the chance of winning a gift

certificate to the ND bookstore (1st prize: $50, 2nd: prize $30, 3rd prize: $10). At this

point, a leaderboard depicting the latest update on the ranking for this competition was

shown on the smartboard which remained up for the duration of this block of putts. The

experimenter, then, explained that this study was also about teamwork and that

participants were randomly paired with each another to obtain a combined score. An

excel sheet showing the pairing procedure was then displayed on the smartboard. Team

scores were said to be computed by subtracting the average distance-from-hole score of

the pressure block (e.g., P1: 21 cm; P2: 34 cm) from the average distance-from-hole

score of the baseline block (e.g., P1: 27 cm; P2: 41 cm) for each participant (P1diff: 6 cm;

P2diff: 7 cm) and then added (Total team score: 13). Furthermore, participants were

told that their “partner” had already obtained a high score and was anxious to win a

prize. Note that in the end, all participants were entered in a lottery regardless of their

score to win the gift certificates.

54

TABLE 3.1

SAMPLE SIZE, MEANS, AND STANDARD ERRORS (IN PARENTHESES) OF IMPORTANCE,

PRESSURE, AND STATE ANXIETY SCORES PER PRESSURE CONDITION OF PRIOR STUDIES

Measure

Study Condition n Importance

Rating Pressure

Rating State Anxiety

Beilock et al. (2004) Exp 1 Low Pressure High Pressure Exp 3 Low Pressure High Pressure

40

28

4.63 (.21) 5.03 (.19)

-4.12 (.32)

3.95 (.24) 5.08 (.21)*

-4.95 (.25)*

32.08 (1.20) 42.68 (1.82)*

-

38.96 (1.70)*

Beilock & DeCaro (2007) Exp 1 Low Pressure High Pressure Exp 2 Low Pressure High Pressure

48 44

45 46

-

4.95 (.18)b

-

4.43 (.24)b

-

4.93 (.22)b

-

4.93 (.19)b

-

49.21 (1.24)b

-

50.91 (1.48)b

DeCaro et al. (2011) Exp 2 Control Outcome Pressure Monitoring Pressure Exp 3 Outcome Pressure Monitoring Pressure Exp 4 Control Outcome Pressure Monitoring Pressure

47 43 40

15 22

20 24 21

a

a

a

a

a

a

a

a

4.29 (.20)

4.95 (.20)*

5.15 (.15)*

5.07 (.41) 4.96 (.51)

4.68 (.27) 4.96 (.28) 5.26 (.27)

- - - - -

36.56 (2.55) 41.71 (2.36)*

41.83 (2.55)*

Note: aOnly participants with scores of 4 or higher were included in the analysis and no means

were reported. bNo comparisons to low pressure group or other pressure group were made;.

*Significantly different at p < .05 to control or low pressure group.

55

3.1.4 Replication Criteria

In this study, several arousal- and affect-related self-report measures as well as

heart rate monitoring were used as indicators for feelings of pressure. Before testing the

effects of type of pressure on putting performance, the two pressure scenarios used in

this study should yield similar and significantly higher levels of stress-induced thoughts

and feelings and physiological responses as compared to a non-pressure context.

Moreover, it is useful to compare scores and group differences to those of prior studies

that used the same measures. Importance ratings, pressure ratings, and state anxiety

scores as well as sample size per study are summarized in Table 3.1 for comparison of

scores in the current study. Note that Beilock et al. (2004) and Beilock and DeCaro

(2007) used several sources of pressure including aspects of monitoring and outcome

pressure types in their high pressure condition. Moreover, in one study (Oudejans &

Pijpers, 2010), researchers increased from the no pressure control (M = 109.8, SD =

15.75), to the mild anxiety (M = 116.7, SD = 16.00) and high anxiety (M = 124.3, SD =

19.37) condition.

56

TABLE 3.2

MEANS AND STANDARD ERRORS (IN PARENTHESES) FOR BLOCK AND DIFFERENCE

SCORES ON ALL MEASURES BY PRESSURE CONDITION FOR EXPERIMENT 2A

Control Outcome Pressure

Monitoring Pressure

Measure M SE M SE M SE

Importance 1 2 DIFF

4.92 4.50 -.42

(.40) (.40) (.26)

5.33

6.42

1.09*

(.28) (.23) (.23)

4.67 5.25 .58*

(.26) (.33) (.23)

Pressure 1 2 DIFF

3.50 3.33 -.17

(.42) (.31) (.24)

3.58 5.33 1.75*

(.50) (.43) (.33)

3.00 4.58 1.58*

(.37) (.36) (.19)

SAM Pleasantness Pre-performance 1 2 DIFF Arousal Pre-performance 1 2 DIFF Controllability Pre-performance 1 2 DIFF

2.83 2.92 2.83 -.08

4.92 4.50 4.92 .42

5.50 5.17 5.50 .33

(.32) (.45) (.42) (.29)

(.26) (.26) (.45) (.31)

(.42) (.51) (.44) (.19)

2.58 3.50 3.67 .17

5.83 4.50 3.17

-1.33*

5.00 5.92 6.33 .42†

(.34) (.45) (.45) (.59)

(.32) (.52) (.44) (.36)

(.41) (.68) (.36) (.60)

3.00 3.58 4.33 .75

5.75 4.75 3.42

-1.33*

5.17 5.58 4.00

-1.58*†

(.41) (.29) (.40) (.39)

(.41) (.43) (.36) (.33)

(.47) (.51) (.54) (.23)

TABLE 3.2 (CONTINUED)

57


Monitoring Pressure


STAI Trait State 1 2 DIFF

35.83

32.08 29.58 -2.50

(2.21)

(2.22) (2.02) (1.06)

33.08

32.08 36.75 4.67*

(1.46)

(1.87) (2.16) (2.23)

36.00

33.50 40.08 6.58*

(1.92)

(2.22) (2.79) (1.80)

PANAS Positive affect Pre-performance 1 2 DIFF Negative affect Pre-performance 1 2 DIFF

32.75 32.75 32.50 -.25

13.83 12.00 11.33 -.67

(1.82) (2.34) (2.65) (.84)

(.75) (.69) (.59) (.47)

34.25 34.08 36.58 2.50

12.50 12.08 14.33 2.25*

(1.49) (1.96) (1.63) (1.18)

(.65) (.68)

(1.22) (.93)

30.92 28.67 30.00 1.33

12.67 12.67 15.00 2.33*

(1.40) (1.42) (1.35) (1.56)

(.58) (.96)

(1.14) (1.10)

Heart Rate Resting HR Average HR 1 2 DIFF Peak HR 1 2 DIFF

85.83

90.50 89.75 -.75

98.42 98.25 -.17

(6.08)

(3.89) (3.84) (.68)

(3.88) (3.96) (1.00)

86.08

93.00 94.67 1.67

102.75 104.50

1.75

(3.35)

(3.95) (3.81) (1.22)

(4.07) (3.79) (1.86)

82.25

85.25 88.00 2.75

94.25 98.75 4.50*

(3.94)

(3.35) (3.47) (1.55)

(3.52) (3.82) (1.02)

Note. 1 = baseline putting block; 2 = experimental putting block; DIFF = difference score of experimental and baseline block; SAM = Self-Assessment Manikin; STAI = State-Trait Anxiety Inventory; PANAS = Positive Affect Negative Affect Scale; HR = heart rate; *Significantly different at p < .05 to control group; †Significantly different at p < .05 to other pressure group

58

3.2 Results

3.2.1 Self-Report and Heart Rate Measures

Means and standard errors per block and difference scores on all measures are

summarized in Table 3.2. First, one-way ANOVAs were run on all measures’ difference

scores and a number of them indicated significant differences among the three pressure

conditions (i.e., control, outcome pressure, and monitoring pressure). These were

Importance ratings, F(2, 33) = 12.21, MSE = .644, p < .001, Pressure ratings, F(2, 33) =

15.58, MSE = .826, p < .001, SAM Arousal, F(2, 33) = 9.14, MSE = 1.341, p = .001, SAM

Controllability, F(2, 33) = 8.32, MSE = 1.692, p = .001, STAI state form, F(2, 33) = 7.38,

MSE = 37.290, p = .002, and PANAS negative affect, F(2, 33) = 4.24, MSE = 8.735, p

=.023. Marginally significantly different were the difference scores of average, F(2, 33) =

2.43, MSE = 16.742, p = .10, and peak heart rate, F(2, 33) = 3.03, MSE = 21.604, p = .063,

while nonsignificant differences were found for SAM Pleasantness and PANAS positive

affect, all Fs < 1.1.

Moreover, planned pairwise comparisons with Tukey’s honestly significant

difference (HSD) correction followed for all measures that showed significant or

marginally significant results in difference scores for the one-way ANOVA. Difference

scores of several measures for the outcome and monitoring pressure conditions were

significantly different from the control condition but not different from each other

including Importance ratings, t(22) = 4.83, p < .001 and t(22) = 3.30, p = .006, Pressure

ratings, t(22) = 4.94, p < .001 and t(22) = 4.72, p < .001, SAM Arousal, t(22) = 3.46, p <

59

.004 for each contrast, and STAI state form, t(22) = 2.87, p = .019 and t(22) = 3.64, p =

.003, respectively. Scores for PANAS negative affect showed the same trend compared

to control with a significant difference to the outcome pressure group, t(22) = 2.49, p =

.047, and a marginally significant difference to the monitoring pressure group, t(22) =

2.42, p = .054. Furthermore, participants under monitoring pressure rated a significantly

higher decrease in SAM Controllability scores than those in the control group, t(22) =

3.61, p = .003, and those under outcome pressure, t(22) = 3.45, p = .004, with the latter

two not differing from each other, t < .1. No other comparisons between the two

pressure scenarios yielded significant differences in the difference scores, ts < 1. Finally,

heart rate difference scores were noticeably different only for the contrast of the

monitoring pressure and the control group with a marginally significant difference for

average heart rate, t(22) = 2.34, p = .063, and a significant difference for peak heart rate,

t(22) = 2.46, p = .049.

These results indicate that both scenarios elicited a similar increase in levels of

stress-induced thoughts and feelings but significantly higher levels than in the no

pressure control condition as shown by several measures such as perceptions of

performance pressure, state anxiety, and arousal. Also, when comparing the raw mean

scores of the experimental putting block of this experiment to those of prior studies, a

common trend and similar mean scores can be found especially in ratings of pressure

and state anxiety. With respect to heart rate, raw mean values as well as difference

scores were lower in this experiment than those in Oudejans and Pijpers’ (2010) study.

Yet, a significant trend emerged in the same direction with participants in pressure

60

scenarios showing an elevated heart rate. Overall, it can be said, that the replication

criteria of checking if the manipulation of pressure yielded the desired effect were met.

3.2.2 Putting Performance

Means and standard errors per block and difference scores on mean distance

from hole are summarized in Table 3.3. For the purpose of this experiment, analyses on

putting performance were run to explore the overall trend of the data only. Given the

additional factor of skill level in this analysis, more power is needed to detect effects

confidently, to be achieved in Experiment 2b. The data were submitted to a 2 (Skill

Level: novices vs. experts) X 3 (Type of Pressure: none vs. outcome vs. monitoring)

ANOVA on the difference scores of mean putting distance. Neither the main effect for

Skill Level, F(1, 30) = 2.30, MSE = 18.15, p = .14, nor for Type of Pressure, F < 1, was

significant but the interaction was, F(2, 30) = 6.46, MSE = 18.15, p = .005, suggesting

that type of pressure affected novices differently from experts. To understand this

interaction, each skill level was examined separately.

61

TABLE 3.3

MEANS AND STANDARD ERRORS (IN PARANTHESES) FOR PUTTING PERFORMANCE BY

SKILL LEVEL AND PRESSURE CONDITION FOR EXPERIMENT 2A


Monitoring Pressure


Novices 1 2 DIFF

35.83 30.50 -5.33

(2.21) (2.85) (1.56)

22.20

23.40

1.20

(2.67) (4.06) (3.06)

21.86 17.71 -4.14

(2.06) (1.95) (1.37)

Experts 1 2 DIFF

16.67 16.00 -.50

(2.31) (2.30) (1.26)

16.29 12.43 -3.86†

(2.59) (1.65) (1.77)

20.00 22.60 2.60†

(1.82) (2.89) (1.17)

Note. 1 = baseline putting block; 2 = experimental putting block; DIFF = difference score of experimental and baseline block; *Significantly different at p < .05 to control group;

†Significantly different at p < .05 to other pressure

group

62

First, a one-way ANOVA on putting distance difference scores yielded a

marginally significant effect for the novice golfer group, F(15) = 2.88, MSE = 22.60, p =

.088. Planned comparisons using Tukey’s HSD correction then showed a marginally

significant performance decrement in outcome pressure compared to control, t(15) =

2.27, p = .092, and an effect trending towards significance compared to monitoring

pressure, t(15) = 1.92, p = .17, with the latter two not differing from each other, t < 1.

Thus, the overall trend is in line with the predictions made by the distraction hypothesis,

in that choking under pressure occurred for novices when placed under outcome but

not under monitoring pressure.

Then, the one-way ANOVA on expert golfers’ difference scores of the mean

distance measure was significant, F(15) = 4.50, MSE = 13.70, p = .029. Planned multiple

comparisons using Tukey’s HSD yielded a significant effect only for the outcome and

monitoring pressure contrast, t(15) = 2.98, p = .024. Also, this data was in line with self-

focus theories in that experts performed better under outcome than under no pressure

conditions and worse under monitoring than under no pressure conditions. Yet, more

data will be collected in the following experiment to confirm this effect.

3.3 Discussion

Overall, the two pressure scenarios adequately induced perceived feelings of

pressure. In most of the arousal- and affect-related self-report measures, a common

trend was observed in which monitoring and outcome pressure were perceived as

similarly distressing and more distressing than no pressure, replicating findings of prior

63

studies (Beilock et al., 2004; DeCaro et al., 2011). In particular, it was observed that

importance, pressure, and arousal ratings as well as the more established state anxiety

measure of the STAI state form all showed a similarly-distressing subjective experience

of the two scenarios but higher distress than in the no pressure condition. This trend

also emerged in the average and peak heart rate measure, yet, the differences were

only marginally significant. It is yet to be clearly established whether heart rate

consistently rises as level of pressure goes up. Finally, exploratory analyses on putting

performance resulted in a trend compatible with current distraction and self-focus

theory. That is, novices performed better under monitoring than under outcome

pressure conditions and the opposite was true for expert golfers. Given the relatively

small sample size, these findings did not all reach statistical significant and more data

will be considered in Experiment 2 to more clearly detect an effect.

64

CHAPTER 4:

EXPERIMENT 2B: EFFECTS OF PRESSURE ON PERFORMANCE

Now that the outcome and monitoring pressure scenarios were established, the

close examination on putting performance followed. As shown by DeCaro and her

colleagues (2011) and the exploratory analyses of Experiment 2a, novices are expected

to show performance decrements under outcome but not under monitoring pressure

while experts are hypothesized to exhibit choking under monitoring but not under

outcome pressure. Based on recent cognitive theory of choking under pressure, WM-

reliant tasks are harmed when performers are distracted or engage in ruminative

thoughts (i.e., distraction theory) while highly proceduralized tasks are impaired when

extra attention is being directed towards skill execution (i.e., self-focus theory).

Again, self-report and heart rate measures accompanied the continued

assessment of perceived pressure on performance, with more distress to be expected

by participants in the pressure compared to the control conditions.

65

4.1 Method

4.1.1 Participants

Additional ninety participants were assigned randomly to one of the three

conditions (control, outcome pressure, and the pressure monitoring condition) with the

restriction of equal sample size across conditions. There were 30 participants in each

pressure condition. Ten participants were excluded from the analysis because they did

not meet the importance rating criterion of 3 or higher on either block. Five participants

were excluded because their putts landed outside of the measurement area and three

subjects did not believe the scenario was real. Thus, a total of 72 participants were

added to Experiment 2a’s data, yielding a total sample size of 108 participants.

Again, participants were categorized into one of two skill levels using the same

criteria as in previous experiments. In sum, there were 21 novices and 20 experts in the

control condition, 13 novices and 19 experts in the outcome pressure condition, and 18

novices and 18 experts in the monitoring pressure condition. The heart rate monitor did

not adequately function for one participant in the control and, thus, the data was

excluded from the average and peak heart rate analyses.

4.1.2 Materials and Procedure

The materials and procedure was the same as in Experiment 2a.

66

4.2 Results


Means and standard errors per block for all measures are provided in Table 4.1.

As in Experiment 2a, the data of all difference scores were submitted to one-way

ANOVAs comparing scores between the three pressure conditions and the measures of

Importance rating, F(2, 106) = 12.16, MSE = .82, p < .000, Pressure ratings, F(2, 106) =

27.11, MSE = .97, p < .001, SAM Pleasantness, F(2, 106) = 5.73, MSE = 2.44, p = .004,

SAM Arousal, F(2, 106) = 13.59, MSE = 1.45, p > .001, SAM Controllability, F(2, 106) =

4.40, MSE = 1.92, p = .015, average heart rate, F(2, 105) = 4.17, MSE = 12.16, p = .018,

STAI state form, F(2, 106) = 14.34, MSE = 56.89, p < .001, and PANAS negative affect,

F(2, 106) = 7.63, MSE = 10.12, p = .001, yielded significant effects. Peak heart rate and

PANAS positive affect were not significant, all Fs < 1.

Again, multiple planned comparisons using Tukey’s HSD correction were

performed on all difference scores that were significant on the one-way ANOVAs. First,

no significant differences were found for any of the difference score contrasts between

the two pressure scenarios. However, difference scores for several measures of both the

outcome and monitoring pressure conditions were significantly different from the

control condition including Importance ratings, t(106) = 4.58, p < .001 and t(106) = 3.71,

p = .001, Pressure ratings, t(106) = 6.88, p < .001 and t(106) = 5.46, p < .001, SAM

Pleasantness, t(106) = 2.66, p = .024 and t(106) = 3.07, p =.008, SAM Arousal, t(106) =

5.01, p < .001 and t(106) = 3.55, p =.002, STAI state form, t(106) = 4.55, p < .001 and

67

t(106) = 4.58, p < .001, PANAS negative affect, t(106) = 3.63, p = .001 and t(106) = 2.94, p

= .011, and average heart rate, t(105) = 2.44, p = .043 and t(106) = 2.49, p =.038,

respectively. Moreover, difference scores on SAM Controllability were significantly

higher for the no pressure as compared to the monitoring pressure condition, t(106) =

2.94, p = .011.

When analyzing the data of Experiment 2, almost all of the arousal and affect-

related measures yielded a significant effect of pressure on performance. Indicators of

perceived feelings of importance and pressure, pleasantness, arousal, state anxiety,

negative affect, and average heart rate were elevated for individuals putting in either of

the two pressure conditions as compared to the no pressure condition, while no

significant differences for those feelings were found between the pressure conditions.

Thus, it can be said that the two pressure scenarios induced comparable levels of

distress but significantly higher levels than the no pressure comparison condition.

68

TABLE 4.1

MEANS AND STANDARD ERRORS (IN PARENTHESES) FOR BLOCK AND DIFFERENCE

SCORES ON ALL MEASURES BY PRESSURE CONDITION FOR EXPERIMENT 2A AND 2B


Monitoring Pressure


Importance 1 2 DIFF

4.71 4.73 .02

(.17) (.19) (.16)

5.09

6.09

1.00a

(.20) (.21) (.17)

4.54 5.31 .79a

(.16) (.19) (.12)

Pressure 1 2 DIFF

3.41 3.76 .34

(.19) (.23) (.13)

3.22 5.16 1.94a

(.26) (.25) (.20)

3.07 4.64 1.57a

(.19) (.22) (.17)

SAM Pleasantness Pre-performance 1 2 DIFF

2.80 3.49 2.98 -.51

(.18) (.26) (.21) (.22)

2.97 3.28 3.75 .47a

(.17) (.27) (.27) (.34)

3.17 3.39 3.97 .58a

(.24) (.19) (.22) (.22)

Arousal Pre-performance 1 2 DIFF

5.17 4.51 4.66 .15

(.17) (.20) (.24) (.14)

5.84 4.63 3.34

-1.28a

(.22) (.30) (.30) (.25)

5.89 4.94 4.11 -.83a

(.25) (.28) (.30) (.22)

Controllability Pre-performance 1 2 DIFF

5.95 5.68 5.98 .29

(.21) (.29) (.26) (.22)

5.00 5.78 5.75 -.03

(.43) (.43) (.35) (.31)

5.03 5.39 4.75 -.64a

(.40) (.36) (.34) (.31)


69


Monitoring Pressure


STAI Trait 35.32 (1.10) 34.38 (1.06) 38.11 (1.30) State 1 2 DIFF

35.49 33.49 -2.00

(1.59) (1.48) (1.27)

32.75 38.84 6.09a

(1.32) (1.52) (1.19)

34.22 40.11 5.89a

(1.37) (1.66) (1.26)

PANAS Positive affect Pre-performance 1 2 DIFF

30.93 30.49 31.32

.78

(1.03) (1.15) (1.21) (.78)

32.50 32.91 33.78

.88

(.92)

(1.33) (1.28) (.84)

30.69 29.22 29.53

.31

(1.00) (1.00) (1.03) (.76)

Negative affect Pre-performance 1 2 DIFF

13.44 13.49 12.95 -.44

(.52) (.74) (.64) (.47)

13.25 12.38 14.66 2.28a

(.53) (.61) (.69) (.60)

13.39 12.53 14.22 1.69a

(.46) (.44) (.59) (.53)

Heart Rate Resting HR

80.98

(2.80)

85.58

(2.99)

84.00

(2.48)

Average HR 1 2 DIFF

91.23 91.18 -.05

(2.20) (1.99) (.46)

92.91 94.88 1.97a

(2.66) (2.50) (.63)

89.19 91.14 1.94a

(2.28) (2.31) (.66)

Peak HR 1 2 DIFF

100.10 101.30

1.20

(2.19) (1.99) (.84)

101.69 105.03

3.03

(2.69) (2.46) (1.03)

98.03

101.17 3.14

(2.25) (2.27) (.82)

Note: 1 = baseline putting block; 2 = experimental putting block; DIFF = difference score of experimental and baseline block; SAM = Self-Assessment Manikin; STAI = State-Trait Anxiety Inventory; PANAS = Positive Affect Negative Affect Scale; HR = heart rate; aSignificantly different at p < .05 to control group;

bSignificantly different at p < .05 to other pressure

group

70


As for the self-report data, the putting performance data of Experiments 2a and

2b were also analyzed together and are summarized in Table 4.2 and Figure 4.1. The

data were first submitted to a 2 (Skill Level: novices vs. experts) X 3 (Type of Pressure:

none vs. outcome vs. monitoring) ANOVA on difference scores. The main effect for

Condition was marginally significant, F(2, 102) = 2.94, MSE = 41.95, p = .057, the

interaction was significant, F(2, 102) = 7.00, MSE = 41.95, p = .001, while the main effect

for Skill Level was not, F(1, 102) = 1.89, MSE = 41.95, p = .172. Tests of simple effects

using Tukey’s HSD correction revealed that the participants improved their putting

performance marginally significantly more in the no pressure than in the monitoring

pressure condition regardless of skill level, t(103) = 2.31, p = .059. No other simple

effects were significantly different from each other, ts < 1.

To understand the interaction, one-way ANOVAs were run separately for each

skill level group and reached a significant effect for the novice golfer group, F(2, 49) =

3.95, MSE = 53.19, p = .026. Planned comparisons using Tukey’s HSD found choking for

the outcome pressure compared to control group, t(49) = 2.80, p = .020. All other

contrasts were nonsignificant, ts < 1. Therefore, novice golfers’ performance was

impaired when putting under outcome but not under monitoring pressure conditions.

This finding provides further support for the predictions made by the distraction

hypothesis.

71

TABLE 4.2

MEANS AND STANDARD ERRORS (IN PARANTHESES) BY SKILL LEVEL AND PRESSURE

CONDITION FOR EXPERIMENT 2A AND 2B


Monitoring Pressure


Novices 1 2 DIFF

32.24 26.43 -6.05

(1.82) (1.51) (1.81)

24.46

25.62

1.15*

(1.18) (1.70) (.90)

26.89 22.89 -3.89

(1.19) (3.22) (3.54)

Experts 1 2 DIFF

19.10 16.98 -2.15

(2.27) (1.57) (1.82)

16.32 12.53 -3.89

(1.87) (1.08) (1.65)

17.65 20.00

2.47*†

(1.99) (2.30) (1.76)

Note. 1 = baseline putting block; 2 = experimental putting block; DIFF = difference score of experimental and baseline block; *Significantly different at p < .05 to control group; †Significantly different at p < .05 to other pressure group

72

Figure 4.1 Bar graph including error bars (standard error of the mean) for difference scores clustered by skill level and attention

condition for combined data for Experiment 2a and 2b.

73

Furthermore, the one-way ANOVA on the expert group data supported the

finding of Experiment 2a with a significant difference in gain scores between the three

conditions, F(2, 53) = 6.08, MSE = 31.56, p = .004. Planned analysis further confirmed

less improvement in mean putting distance from the baseline to the pressure block in

the monitoring pressure condition as compared to both the control, t(53) = 2.49, p =

.041, and outcome pressure condition, t(53) = 3.39, p = .004. Again, the outcome

pressure group did not differ significantly from control, t < 1. Thus, experts displayed

choking under more self- or skill-focused pressure conditions, further supporting self-

focus theories. Although their performance improved when being placed in a

competitive and peer pressure-filled situation, this effect did not reach statistical

significance.

4.3 Discussion

In sum, the general effect of perceived pressure induced by the two pressure

scenarios as assessed by several arousal- and affect-related self-report and physiological

measures was replicated from Experiment 2a. The most consistent results between the

two pressure scenarios and the control condition were found for the Importance and

Pressure ratings, SAM Arousal and Pleasantness, the STAI state form, average heart rate,

and PANAS negative affect with significant effects for all contrasts testing whether the

pressure scenarios were perceived to be significantly more distressing than the control

condition but nonsignificantly more distressing from each other. Thus, according to the

self-report and the examination of heart rate, it can be inferred that the introduction of

74

external elements that simulate conditions found in pressure-filled situations resulted in

a significant higher level of perceived performance pressure than the no pressure

control condition.

In terms of the effect of type of pressure on performance, choking was found

when expert golfers performed under monitoring pressure conditions. This finding is in

line with self-focus theories which argue that when attention is focused on the step-by-

step mechanisms of a highly proceduralized task, performance decrements occur. From

this hypothesis, it seems plausible that the environment of being video-taped, watching

the recording in real time on a large screen right next to the putting green, and being

evaluated by a golf professional may have induced an attentional focus on the self or

skill execution which impaired expert performance but left novice performance

unharmed. Moreover, expert performance was unaffected by the outcome pressure

environment, a finding also supported by current theory.

Furthermore, the unskilled golfers displayed performance decrements when

putting under outcome pressure but not under monitoring pressure conditions.

According to distraction theory, performance of WM-reliant tasks can be harmed when

attention is diverted from the individual processes of skill execution (but not when

attention is focused on these). A competitive environment, filled with monetary

incentives in which one does not want to let down a partner can induce ruminative

thought about the situation, turning what was initially a single-task into a dual-task

situation. As a consequence, performance is more vulnerable to break downs and the

likelihood for choking increases. Overall, the interaction between type of pressure and

75

skill level found in this experiment is in line with recent findings by DeCaro et al (2011)

using a category learning paradigm. Thus, this study supports and extends this

interaction using a sensorimotor task.

76

CHAPTER 5:

EXPERIMENT 3: ALLEVIATING CHOKING THROUGH IMAGERY

The purpose of Experiment 3 is two-fold. The primary aim is to find a way to

reduce choking under pressure as identified by Experiment 2 (i.e., novices under

outcome and experts under monitoring pressure) by using imagery practice. Equally

important is the investigation of whether imagery practice might hurt performance in

those instances in which it was previously left unharmed (i.e., novices under monitoring

and experts under outcome pressure). But before considering its effects on pressure,

imagery practice by itself will be tested for its effectiveness in novice and expert golfers

in a non-pressure environment. Specifically, it will be determined whether there are

differences in golfers of varying skill levels in how well they perform a putting task using

imagery practice from either a first- or third-person perspective.

5.1 Method

5.1.1 Participants

Sixteen participants were recruited per group (e.g., 16 participants using first-

person imagery under no pressure; see study design in Figure 3 for details). Importance

ratings of three participants did not reach the criterion of 3 or higher on every block of

77

putting trials and, thus, were excluded from further analyses. A total of 93 participants

were left including 49 novices and 44 experts who were recruited and categorized in the

same way as in prior experiments. There were 15 novices (8 first-person and 7 third-

person imagery) and 15 experts (7 first-person and 8 third-person imagery) for the

control, 18 novices (11 first-person and 7 third-person imagery) and 16 experts (7 first-

person and 9 third-person imagery) for the outcome pressure, and 16 novices (8 first-

person and 8 third-person imagery) and 13 experts (7 first-person and 6 third-person

imagery) for the monitoring pressure condition.

Equipment failure led to the exclusion of heart rate data of 28 participants,

leaving a sample size for the heart rate analysis of 10 novices (4 first-person and 6 third-

person imagery) and 10 experts (3 first-person and 7 third-person imagery) for the

control, 12 novices (7 first-person and 5 third-person imagery) and 13 experts (7 first-

person and 6 third-person imagery) for the outcome pressure, and 11 novices (6 first-

person and 5 third-person imagery) and 10 experts (5 first-person and 5 third-person

imagery) for the monitoring pressure condition. Data is still reported and analyses were

still run for average and peak heart rate; however, results should be interpreted with

caution.

5.1.2 Materials

The green, putters, and balls were identical to those in Experiment 1 and 2.

However, two additional questionnaires for the assessment of imagery-related

mechanism were administered.

78

Imagery Rating. Participants rated on a one-item scale how successful they

thought they were in using their assigned imagery practice. The Imagery Rating scale

was adapted from a golf putting study which manipulated instructional cues and

subsequently checked for whether the manipulation was effectively implemented by

the participant (Gucciardi & Dimmock, 2008). As the Importance and Pressure Ratings,

this scale also ranged from 1 (unsuccessful) to 7 (successful).

Revised Vividness of Movement Imagery-2 (VMIQ-2; Roberts et al., 2008). This

questionnaire assesses the ability to visually and kinesthetically imagine a variety of

movements. The 12-item VMIQ-2 which assesses imagery on three factors (i.e., internal

or first-person, external or third-person, and kinesthetic imagery) was adapted from the

original 24-item and two-factor (i.e., internal and external imagery) version (VMIQ;

Isaac, Marks, Russel, 1986). The 12 (and former 24) items measure imagery in six

different situations such as basic body movements (e.g., walking), movement with

controlling an object (e.g., kicking a ball in the air), and movements that cause

imbalance and recovery (e.g., jumping off a high wall). Participants were asked to try

their best at imaging the activities as clearly and as vividly as they could and, then, rate

the degree of clearness and vividness of their image using a 5-point Likert scale, ranging

from 1 (perfectly clear and vivid) to 5 (no image at all). Preliminary support for adequate

psychometric properties of the revised questionnaire has been obtained (Roberts et al.,

2008). Of particular interest in this study were generic differences in imagery ability

between novice and skilled golfers as potential covariates for the effectiveness of

79

imagery as a method to alleviate choking. Therefore, participants were asked to

complete the exercise without appointing a particular imagery perspective.

5.1.3 Design

This experiment includes three between-subjects factors (i.e., skill level, pressure

type, and imagery practice), leading to a total of twelve conditions (see Figure 6 for

study design). That is, for each skill level there was a first- and third-person imagery

group per pressure condition (i.e., none, outcome, and monitoring).

NOVICES

no pressure monitoring pressure outcome pressure

1st person imagery

3rd person imagery

EXPERTS

no pressure monitoring pressure outcome pressure

1st person imagery

3rd person imagery

Figure 5.1 Overview of study design of Experiment 3.

5.1.4 Procedure

Putting task. The procedure was the same as in Experiment 2 with the addition

of an imagery practice block of (18) putting blocks between the baseline and pressure

blocks. The same pressure scenarios were used as in Experiment 2. Participants were

instructed to engage in imagery practice before each putt (see imagery instructions

80

below). The experimenter repeated the imagery instructions before the tenth putt to

remind participants of the specific instructions and to assure that they were actually

doing the practice. Positive imagery (i.e., landing a putt inside the hole) was chosen to

control for confounding effects other types of imagery (e.g., negative imagery) have on

performance (Beilock et al., 2001).

First-person visual imagery group. Participants were instructed to imagine

themselves making a successful putt from a first-person perspective. Specifically, they

were told: “You see yourself taking this putt through your own eyes, just as you would

see it as if it was actually occurring. That is, you see your arms, the putter, the ball, and

the hole in the foreground and your surroundings in the background. I’d like you to

imagine taking a putt that rolls into the hole. You should see yourself swinging the club

back and through so that the ball lands inside the hole.” Participants were asked to

imagine the scene before each putt and were reminded of the imagery by reading the

instructions again before the tenth putt of an 18-putt series.

Third-person visual imagery group. Participants were instructed to imagine

themselves making a successful putt from a third-person perspective. Specifically, they

were told: “You see yourself taking this putt from a third-person perspective, just as you

would see it as it was actually occurring to your distant self. That is, you see yourself

from the back, with the ball behind the hole. I’d like you to imagine taking a putt that

rolls into the hole. You should see yourself swinging the club back and through in a

straight line so that the ball lands inside the hole.” Participants were asked to imagine

81

the scene before each putt and were reminded of the imagery by reading the

instructions again before the tenth putt of an 18-putt series.

Thus, participants started with 9-18 practice putts and 27 single-task putts

without manipulation. Again, the last 18 single-task putts served as the baseline

measure. Then, there followed 18 putts using the assigned imagery perspective and,

finally, another 18 putts using the same imagery practice under the assigned type of

pressure condition. For example, one third of the novices took 9-18 practice putts, 27

single-task putts, 18 first-person imagery putts, and 18 putts using first-person imagery

under monitoring pressure.

Self-report and heart rate measures. Again, participants were subject to

assessment before the beginning of the putting task and after each block of trials. First,

preperformance measures were taken of SAM, the STAI trait form, and the PANAS. After

the baseline block of putting blocks, Importance and Pressure ratings, the three items of

SAM, the STAI state form, and the PANAS were completed. The experimenter, who had

not mentioned imagery practice until that point, then gave a general explanation of

imagery practice and visual perspective use to the participant. Next, the participant was

given time to complete the VMIQ-2. Subsequently, the specific imagery instructions

were given to the participant and were clarified when necessary. After the imagery

putting block, participants filled out the Importance, Pressure, and Imagery ratings, the

SAM, the STAI state form, and the PANAS, which they completed after the pressure

block of putting as well. At the end of the study, participants filled out the demographic

and postexperiment questionnaire.

82

Resting heart rate as well as average and peak heart rate was recorded before

and during the putting blocks as in Experiments 1 and 2. Lastly, participants were all

thanked and debriefed.

5.2 Results

Means and standard errors per block for all measures are provided in Table 5.1

and 5.2. Again, results for self-report and heart rate measures will be presented first,

followed by the putting performance analysis with results on the imagery block and

pressure block separately. As in prior experiments, difference scores of the critical and

the baseline block of trials were analyzed.


Imagery block. The data were submitted to a 2 (Skill Level: novices vs. experts) X

2 (Imagery Perspective: first- vs. third-person) ANOVA on the difference scores (imagery

- baseline block) of all measures. Only the main effect for skill level of SAM

Controllability was trending towards significance, F(1, 58) = 2.30, MSE = 1.02, p = .14,

and the main effect for imagery perspective of PANAS positive affect was significant,

F(1, 58) = 10.11, MSE = 12.81, p =.002. Thus, experts perceived a slight increase of

controllability when using imagery compared to novices and both groups reported a

decrease in positive affect when using third-person compared to first-person imagery.

No other effects were significant, all Fs < 1.7.

83

TABLE 5.1

MEANS AND STANDARD ERRORS (IN PARENTHESES) FOR BLOCK AND DIFFERENCE SCORES ON ALL MEASURES BY PRESSURE AND

IMAGERY CONDITION FOR NOVICES (ONLY) OF EXPERIMENT 3

No Pressure Outcome Pressure Monitoring Pressure

1st Person 3rd Person 1st Person 3rd Person 1st Person 3rd Person

Measure M SE M SE M SE M SE M SE M SE

Importance 1 2 3 DIFF (Imagery) DIFF (Pressure)

3.75 4.50 4.50 .75 .75

(.37) (.46) (.33) (.25) (.25)

3.71 3.71 3.43 .00 -.29

(.47) (.42) (.53) (.38) (.36)

4.09 4.27 5.18 .18

1.09

(.25) (.33) (.38) (.23) (.32)

4.29 4.43 5.57 .14

1.29

(.57) (.42) (.57) (.26) (.18)

3.63 4.00 4.38 .38 .75

(.26) (.38) (.38) (.38) (.31)

3.29 3.86 4.43 .57

1.14

(.68) (.55) (.48) (.43) (.51)

Pressure 1 2 3 DIFF (Imagery) DIFF (Pressure)

3.00 3.88 4.00 .88

1.00

(.57) (.58) (.50) (.48) (.50)

2.57 2.86 2.71 .29 .14

(.48) (.51) (.52) (.42) (.51)

3.00 3.27 4.82 .27

1.82

(.41) (.49) (.26) (.47) (.35)

2.57 3.29 4.14 .71

1.57

(.37) (.64) (.46) (.47) (.30)

3.00 3.63 4.38 .63

1.38

(.42) (.50) (.65) (.32) (.50)

3.00 3.29 4.57 .29

1.57

(.72) (.68) (.30) (.47) (.65)

Imagery 2 3

4.13 3.63

(.48) (.46)

4.57 5.29

(.37) (.47)

4.27 4.00

(.30) (.30)

4.29 4.57

(.61) (.53)

4.13 3.25

(.52) (.37)

4.14 4.57

(.46) (.61)

TABEL 5.1 (CONTINUED)

84




SAM Pleasantness Preperformance 1 2 3 DIFF (Imagery) DIFF (Pressure)

2.88 3.63 3.63 4.00 .00 .38

(.35) (.65) (.53) (.57) (.54) (.57)

2.14 2.43 3.00 2.14 .57 -.29

(.40) (.30) (.44) (.34) (.30) (.29)

3.64 4.36 4.27 4.00 -.09 -.36

(.35) (.49) (.45) (.60) (.64) (.64)

3.50 3.43 3.43 4.29 .00 .86

(.40) (.57) (.65) (.68) (.62) (.60)

3.88 3.50 3.88 4.57 .38

1.29

(.61) (.46) (.55) (.53) (.46) (.52)

2.86 3.71 4.57 3.29 .86 -.43

(.14) (.71) (.75) (.42) (.63) (.65)

Arousal Preperformance 1 2 3 DIFF (Imagery) DIFF (Pressure)

6.13 5.38 5.25 5.88 -.13 .50

(.72) (.71) (.80) (.48) (.58) (.54)

6.14 4.43 5.57 5.71 1.14 1.29

(.46) (.69) (.57) (.78) (.83) (.78)

6.45 5.00 5.73 4.55 .73 -.45

(.41) (.30) (.52) (.49) (.30) (.49)

5.33 4.43 5.00 4.29 .57 -.14

(.76) (.57) (.31) (.61) (.75) (.46)

6.38 4.88 4.88 4.86 .00 .00

(.72) (.40) (.52) (.40) (.33) (.38)

5.14 4.71 4.71 5.00 .00 .29

(.46) (.52) (.47) (.38) (.38) (.47)

Controllability Preperformance 1 2 3 DIFF (Imagery) DIFF (Pressure)

5.75 5.63 5.75 5.00 .13 .63

(.62) (.38) (.37) (.46) (.23) (.53)

5.00 5.29 4.57 5.57 -.71 .29

(.76) (.47) (.53) (.43) (.36) (.29)

5.73 5.82 5.73 5.55 -.09 -.27

(.41) (.38) (.36) (.58) (.37) (.36)

6.00 5.71 6.57 6.00 .86 .29

(.52) (.26) (.43) (.49) (.46) (.64)

5.75 5.25 5.38 4.86 .13 .14

(.37) (.45) (.53) (.77) (.23) (.40)

5.29 5.00 4.86 5.57 -.14 .57

(.64) (.62) (.71) (.69) (.46) (.61)


85




STAI Trait State 1 2 3 DIFF (Imagery) DIFF (Pressure)

38.00

36.13 37.50 36.88 1.38 .75

(2.07)

(2.84) (2.56) (2.53) (2.38) (2.56)

33.57

35.43 34.57 30.57 -.86

-4.86

(2.92)

(2.67) (2.94) (2.76) (1.39) (1.44)

38.45

36.27 34.09 40.64 -2.18 4.36

(2.43)

(2.41) (2.85) (2.53) (1.84) (2.45)

38.14

39.57 38.29 42.14 -1.29 2.57

(2.11)

(1.77) (2.84) (2.76) (2.70) (3.55)

39.00

36.75 39.00 44.00 2.25 7.25

(4.05)

(3.54) (3.01) (3.67) (2.53) (2.87)

41.63

38.88 38.50 38.38 -.38 -.50

(3.04)

(4.49) (4.15) (3.18) (2.31) (3.82)

PANAS Positive affect Pre-performance 1 2 3 DIFF (Imagery) DIFF (Pressure)

25.75 26.75 28.75 23.88 2.00 -2.88

(1.31) (1.95) (2.25) (2.45) (.88)

(2.81)

29.14 29.86 26.43 29.29 -3.43 -.57

(1.08) (2.17) (2.74) (3.06) (1.57) (1.77)

27.80 26.50 27.40 28.70

.90 2.20

(2.11) (1.61) (1.88) (2.17) (.98)

(1.34)

30.50 30.14 29.00 32.43 -1.14 2.29

(2.93) (3.19) (2.90) (3.66) (1.37) (1.92)

25.38 27.63 23.00 22.38 -4.63 -5.30

(1.70) (1.71) (1.95) (2.14) (1.50) (2.19)

26.25 26.88 26.50 26.63 -.38 -.25

(2.14) (1.39) (1.57) (1.40) (.73) (.73)

Negative affect Pre-performance 1 2 3 DIFF (Imagery) DIFF (Pressure)

13.88 12.50 12.50 12.00

.00 -.50

(.92)

(1.00) (.80) (.85) (.95) (.54)

12.57 12.29 12.43 11.00

.14 -1.29

(.37) (.84) (.92) (.44) (.80) (.57)

12.30 12.20 11.70 14.40 -.50 2.20

(.68) (.77)

(2.06) (2.05) (.56)

(1.45)

15.83 13.43 12.00 15.57 -1.43 2.14

(1.97) (1.11) (1.92) (2.09) (1.51) (1.57)

12.63 12.75 13.88 14.25 1.13 1.50

(1.13) (1.33) (1.58) (1.58) (1.02) (2.81)

16.63 15.13 15.88 14.38

.75 -.75

(1.90) (2.03) (2.20) (.82)

(1.15) (1.77)


86




VMIQ

28.63 (4.63) 23.33 (1.52) 29.91 (1.39) 25.71 (1.63) 21.83 (1.30) 27.25 (2.39)


83.00

(4.92)

91.29

(5.15)

86.75

(5.14)

80.40

(5.57)

91.57

(5.61)

69.40

(2.73)

Average HR 1 2 3 DIFF (Imagery) DIFF (Pressure)

89.50 87.50 87.25 -2.00 -2.25

(3.52) (3.67) (4.05) (1.47) (1.84)

98.83 94.83 95.67 -4.00 -3.17

(4.48) (4.10) (3.69) (.86)

(1.17)

97.75 95.88 96.25 -1.88 -1.50

(3.00) (2.71) (2.40) (1.26) (1.60)

96.60 94.80 98.80 -1.80 2.20

(5.50) (5.46) (7.45) (.74)

(3.51)

106.33 101.83 105.50 -2.20 -2.20

(4.34) (4.18) (3.70) (1.53) (1.39)

85.80 85.20 82.60 -.60

-3.20

(3.57) (3.64) (3.33) (2.94) (1.88)

Peak HR 1 2 3 DIFF (Imagery) DIFF (Pressure)

97.75 97.25 98.50 -.50 .75

(2.63) (4.21) (4.74) (2.63) (3.50)

109.33 104.50 105.00 -4.83 -4.33

(4.19) (3.45) (3.45) (2.40) (2.45)

104.75 105.50 106.50

.75 1.75

(2.75) (2.58) (2.37) (1.87) (1.54)

106.20 108.00 107.33

1.80 2.33

(6.95) (4.76)

(11.67) (2.35) (1.45)

115.40 111.00 113.00 -2.75 -.75

(2.75) (2.58) (2.37) (1.87) (1.54)

94.80 94.50 97.25 -2.50 .25

(2.75) (2.58) (2.37) (1.87) (1.54)

Note: 1 = baseline putting block; 2 = imagery putting block; 3 = pressure block; DIFF (Imagery) = difference score of imagery and baseline block; DIFF (Pressure) = difference score of pressure and baseline block; SAM = Self-Assessment Manikin; STAI = State-Trait Anxiety Inventory; PANAS = Positive Affect Negative Affect Scale; HR = heart rate; a

Significantly different at p < .05 to control group; b

Significantly different at p < .05 to other pressure group; c Significantly different at p < .05 to control group

87

TABLE 5.2

MEANS AND STANDARD ERRORS (IN PARENTHESES) FOR BLOCK AND DIFFERENCE SCORES ON ALL MEASURES BY PRESSURE AND

IMAGERY CONDITION FOR EXPERTS (ONLY) OF EXPERIMENT 3




Importance 1 2 3 DIFF (Imagery) DIFF (Pressure)

5.57 5.43 5.57 -.14 .00

(.37) (.48) (.53) (.14) (.22)

4.38 4.75 4.75 .38 .38

(.46) (.45) (.41) (.18) (.18)

4.57 5.00 6.29 .43

1.71

(.53) (.62) (.42) (.20) (.47)

5.22 5.56 6.11 .33 .89

(.28) (.29) (.46) (.29) (.39)

5.00 4.71 6.14 -.29 1.14

(.69) (.61) (.34) (.42) (.40)

4.17 5.17 5.33 1.00 1.17

(.70) (.70) (.56) (.37) (.31)

Pressure 1 2 3 DIFF (Imagery) DIFF (Pressure)

3.14 3.57 3.86 .43 .71

(.74) (.78) (74) (.75) (.78)

2.13 3.13 3.13 1.00 1.00

(.44) (.61) (.52) (.50) (.38)

3.57 4.29 5.57 .71

2.00

(.65) (.68) (.43) (.36) (.31)

3.44 3.67 4.44 .22

1.00

(.58) (.58) (.67) (.52) (.29)

3.14 3.29 5.14 .14

2.00

(.60) (.64) (.51) (.26) (.58)

2.33 3.67 4.50 1.33 2.17

(.56) (.67) (.43) (.56) (.75)

Imagery 2 3

5.00 5.14

(.82)

(1.35)

5.13 5.25

(.99) (.71)

5.00 4.57

(.53) (.34)

4.89 4.67

(.47) (.15)

4.86 5.00

(.26) (.38)

4.00 4.67

(.26) (.33)


88




SAM Pleasantness Preperformance 1 2 3 DIFF (Imagery) DIFF (Pressure)

3.29 3.43 3.29 3.86 -.14 .43

(.29) (.75) (.52) (.40) (.77) (.53)

2.75 2.50 2.75 2.75 .25 .25

(.56) (.33) (.56) (.37) (.68) (.49)

2.86 3.14 2.57 3.14 -.57 .00

(.34) (.46) (.30) (.63) (.30) (.43)

2.78 3.11 3.33 3.11 .22 .00

(.15) (.39) (.55) (.48) (.47) (.73)

2.57 3.71 3.43 3.86 -.29 .14

(.37) (.71) (.72) (.34) (.84)

(1.00)

2.33 3.50 4.00 3.83 .50 .33

(.42) (.34) (.37) (.31) (.34) (.56)

Arousal Preperformance 1 2 3 DIFF (Imagery) DIFF (Pressure)

6.71 4.86 6.57 5.86 1.71 1.00

(.52) (.77) (.61) (.55) (.92) (.66)

5.88 5.50 5.50 5.88 .00 .38

(.69) (.76) (.76) (.67) (.57) (.73)

6.43 5.14 5.14 3.14 .00

-2.00

(.65) (.51) (.51) (.40) (.62) (.58)

5.56 4.67 5.00 3.67 .33

-1.00

(.78) (.82) (.76) (.67) (.55) (.41)

5.00 4.86 5.14 4.43 .29 -.43

(.22) (.26) (.51) (.43) (.42) (.43)

5.83 4.33 3.83 3.67 -.50 -.67

(.60) (.21) (.31) (.42) (.34) (.49)

Controllability Preperformance 1 2 3 DIFF (Imagery) DIFF (Pressure)

6.71 5.57 6.29 5.86 .71 .29

(.52) (.57) (.36) (.40) (.57) (.52)

6.63 6.63 6.63 6.13 .00 -.50

(.68) (.63) (.57) (.67) (.19) (.33)

5.29 4.86 6.00 5.71 1.14 .86

(.47) (.51) (.66) (.52) (.40) (.55)

5.22 5.00 5.22 5.78 .22 .78

(.52) (.76) (.70) (.70) (.15) (.36)

5.29 5.57 5.43 5.29 -.14 -.29

(.68) (.43) (.53) (.64) (.67) (.92)

4.50 4.33 4.67 4.67 .33 .33

(.76) (.42) (.33) (.21) (.33) (.56)


89




STAI Trait State 1 2 3 DIFF (Imagery) DIFF (Pressure)

37.86

32.29 28.86 33.57 -3.43 1.29

(1.35)

(4.54) (1.35) (3.29) (2.38) (2.36)

35.50

31.13 30.13 29.00 -1.00 -2.13

(2.96)

(2.00) (2.39) (2.51) (.95)

(1.27)

33.57

30.29 28.57 35.14 -1.71 4.86

(1.73)

(1.92) (2.00) (3.26) (1.34) (1.82)

40.00

36.38 37.63 38.00 1.25 1.63

(2.38)

(2.74) (3.05) (2.68) (3.19) (1.59)

34.86

33.71 32.14 36.29 -1.57 2.57

(2.54)

(3.00) (2.25) (3.48) (2.20) (2.73)

36.17

35.00 37.83 36.33 2.83 1.33

(2.47)

(2.21) (4.46) (2.94) (2.36) (2.40)

PANAS Positive affect Pre-performance 1 2 3 DIFF (Imagery) DIFF (Pressure)

31.00 33.57 32.00 31.00 -1.57 -2.57

(2.14) (1.65) (2.37) (2.19) (1.09) (1.63)

32.75 33.13 31.50 27.75 -1.63 -5.38

(1.58) (1.90) (1.46) (2.03) (.87)

(2.52)

27.00 30.14 33.14 36.00 3.00 5.86

(1.80) (2.48) (2.58) (2.42) (.79)

(1.42)

31.56 33.00 30.78 35.11 -2.22 2.11

(2.43) (3.56) (3.32) (3.74) (1.16) (1.53)

34.00 32.14 34.29 32.29 2.14 .14

(1.94) (2.08) (2.84) (2.14) (1.49) (1.39)

30.00 30.67 30.33 30.50 -.33 -.17

(2.96) (2.11) (2.51) (1.78) (1.17) (.95)

Negative affect Pre-performance 1 2 3 DIFF (Imagery) DIFF (Pressure)

13.00 13.14 11.29 12.86 -1.86 -.29

(.93) (.52)

(2.49) (2.20) (2.38) (.36)

12.75 11.38 10.75 10.50 -.63 -.88

(1.33) (.60) (.25) (.38) (.50) (.66)

11.14 11.71 11.57 13.14 -.14 1.43

(.34) (.52) (.84) (.86) (.63) (.61)

17.78 15.11 14.11 17.56 -1.00 2.44

(2.09) (1.88) (1.84) (2.64) (1.52) (1.91)

13.14 13.71 12.00 13.29 -1.71 -.43

(1.12) (1.29) (.79)

(1.09) (1.25) (.90)

13.83 12.67 13.50 12.67

.83

.00

(1.49) (1.15) (1.23) (1.26) (.70) (.97)


90




VMIQ

24.57 (3.29) 21.88 (3.11) 26.57 (3.31) 24.44

(2.85) 25.71 (1.94) 28.17 (2.30)


70.67

(5.36)

84.13

(4.88)

87.14

(5.26)

85.17

(3.42)

82.60

(2.11)

77.00

(6.29)

Average HR 1 2 3 DIFF (Imagery) DIFF (Pressure)

79.00 77.33 78.67 -1.67 -.33

(5.29) (2.85) (3.67) (2.60) (2.19)

97.86 94.71 93.86 -3.14 -4.00

(4.48) (4.10) (2.20) (2.38) (.36)

94.57 92.14 96.00 -2.43 1.43

(4.78) (4.55) (4.21) (1.21) (2.03)

97.50 96.33

103.60 -1.17 5.00

(4.79) (4.19) (7.84) (1.78) (3.99)

92.80 89.60 89.20 -3.20 -3.60

(2.58) (3.57) (3.60) (1.11) (1.29)

89.40 86.40 85.60 -3.00 -3.80

(4.55) (4.01) (4.05) (.84) (.97)

Peak HR 1 2 3 DIFF (Imagery) DIFF (Pressure)

89.33 87.33 87.33 -2.00 -2.00

(4.70) (4.10) (4.86) (2.52) (3.00)

106.43 106.00 104.43

-.43 -2.00

(2.97) (2.40) (2.68) (1.66) (1.16)

108.00 108.29 115.71

.29 7.71

(3.41) (2.38) (2.48) (2.62) (4.20)

107.17 106.80 114.40 -2.80 4.80

(5.57) (4.89) (8.11) (1.69) (3.68)

101.60 97.80

100.00 -3.80 -1.60

(3.20) (3.37) (3.21) (1.83) (1.29)

97.20 96.00 96.60 -1.20 -.60

(5.00) (3.52) (4.46) (2.01) (2.77)

Note: 1 = baseline putting block; 2 = imagery putting block; 3 = pressure block; DIFF (Imagery) = difference score of imagery and baseline block; DIFF (Pressure) = difference score of pressure and baseline block; SAM = Self-Assessment Manikin; STAI = State-Trait Anxiety Inventory; PANAS = Positive Affect Negative Affect Scale; HR = heart rate; a

Significantly different at p < .05 to control group; b

Significantly different at p < .05 to other pressure group; c Significantly different at p < .05 to control group

91

Pressure block. The data were submitted to a 2 (Skill Level: novices vs. experts) X

2 (Imagery Perspective: first- vs. third-person) X 3 (Type of Pressure: none vs. outcome

vs. monitoring) ANOVA on the difference scores (pressure - baseline block) of all

measures. A main effect for skill level was found only for SAM Arousal, F(1, 62) = 4.10, p

= .048, with experts experiencing a greater increase in arousal overall than novices. One

main effect for imagery perspective reached significance, namely, STAI state

form, F(1, 62) = 4.86, p = .032, with people reporting greater anxiety when practicing

first- than third-person imagery.

Several measures resulted in a main effect for pressure, all of which were

followed up with planned comparisons using Tukey’s HSD correction. Four measures

resulted in the same trend of data that was observed under pressure in Experiment 2;

that is, the two pressure groups leading to equally high and, at least, marginally

significantly higher indicators of distress than the control group including Importance

rating (main effect: F(2, 50) = 9.58, p < .001; none –outcome contrast: t(50) = 3.80, p =

.001; none – monitoring contrast: t(50) = 4.23, p < .001), Pressure rating (main effect:

F(2, 50) = 3.64, p = .033; none – outcome contrast: t(50) = 2.23, p = .075; none –

monitoring contrast: t(50) = 2.85, p = .017), SAM Arousal (main effect: F(2, 50) = 3.62, p

= .034; none – outcome contrast: t(50) = 2.90, p = .015; none – monitoring contrast:

t(50) = 2.09, p = .10), and STAI state form (main effect: F(2, 50) = 3.32, p = .044; none –

outcome contrast: t(50) = 2.51, p = .040; none – monitoring contrast: t(50) = 2.37, p =

.056). Taken together, the key affect- and arousal-related self report measures reflected

the same trend in perceived performance pressure as in Experiment 2, in which no

92

imagery practice was applied. Interestingly, these results suggest that imagery does not

make performers immune to sensing performance pressure.

Furthermore, another trend was reflected in the data in which the control

condition was, at least, marginally significantly different from the outcome pressure

condition which in turn was, at least, marginally significantly different from the

monitoring pressure condition including average heart rate (main effect: F(2, 50) = 8.15,

p = .001; none – outcome contrast: t(50) = 3.17, p < .007; outcome – monitoring

contrast: t(50) = 3.60, p = .002), and peak heart rate (main effect: F(2, 49) = 5.05, p =

.010; none – outcome contrast: t(49) = 3.39, p = .004; outcome – monitoring contrast:

t(49) = 2.57, p = .035), PANAS positive affect (main effect: F(2, 50) = 11.04, p < .001;

none – outcome contrast: t(50) = 4.69, p < .001; outcome – monitoring contrast: t(50) =

3.60, p = .002), and PANAS negative affect (main effect: F(2, 50) = 9.58, p < .001; none –

outcome contrast: t(50) = 2.76, p = .022; outcome – monitoring contrast: t(50) = 2.08, p

= .106).

Furthermore, several two-way interaction yielded significance including the skill

level by imagery perspective interaction for PANAS positive affect, F(1, 62) = 6.88, p =

.011, and the skill level by type of pressure interaction for the PANAS positive affect

measure, F(2, 62) = 5.95, p = .005. The imagery perspective by type of pressure

interaction for average heart rate was trending towards significance, F(1, 62) = 2.33, p =

.11, while the same interaction was marginally significant for STAI state form, F(1, 62) =

2.43, p = .098, PANAS positive affect, F(1, 62) = 3.03, p = .057, and PANAS negative

affect, F(1, 62) = 2.86, p = .067. Finally, the three-way interaction was significant for a

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number of measures including Importance rating, F(2, 62) = 3.99, p = .025, SAM

Pleasantness, F(2, 62) = 3.47, p = .039, SAM Arousal, F(2, 62) = 2.51, p = .091, STAI state

form, F(2, 62) = 5.98, p = .005, and PANAS positive affect, F(2, 62) = 2.29, p = .11.


Imagery block. The putting data are summarized in Table 5.3 and Figure 5.2. To

begin, a 2 (Skill Level: novices vs. experts) X 2 (Imagery Perspective: first- vs. third-

person) ANOVA was run on the difference scores of the imagery and the baseline block

of trials. The main effects for skill level and imagery perspective were not significant, Fs

< 1, but the interaction was, F(1, 80) = 8.831, MSE = 67.62, p = .004. This result suggests

that imagery is most effective when the visual perspective is altered according to the

skill level of the performer. Thus, the skill level groups were examined separately.

A one-way ANOVA revealed that novices exhibited a greater improvement in

putting performance from the baseline to the imagery block when practicing third- as

compared to first-person imagery, F(47) = 5.88, MSE = 93.13, p = .019. This finding is in

line with prior research suggesting that third-person imagery is best suited for the

learning of the individual steps of skill movement (Mayer & Hermann, 2010). Moreover,

first-person imagery might be a more demanding task for novices than third-person

imagery, leading to a performance decrement in the putting task when using the first-

person perspective but not when using third-person perspective.

For expert golfers, the one-way ANOVA yielded a trend opposed to the novices’

data in that experts did better under first- than under third-person imagery, F(41) =

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4.13, p = .049. This result is in line with Mayer and Hermann’s (2010) argument that

third-person imagery helps to rehearse kinesthetic movement feelings. Furthermore,

third-person imagery somewhat impedes experts’ performance for reasons not yet

clearly determined. It is possible that this imagery perspective draws attention to the

self or skill execution in a way similar to skill-focused attention, and thus, disrupts the

otherwise automatic movement processes.

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TABLE 5.3

MEANS AND STANDARD ERRORS (IN PARANTHESES) FOR BLOCK AND DIFFERENCE

SCORES BY SKILL LEVEL AND IMAGERY CONDITION FOR EXPERIMENT 2 (NO PRESSURE

CONDITION ONLY) AND EXPERIMENT 3 (IMAGERY BLOCK ONLY)

Experiment 2 Experiment 3

No Imagery 1st Person 3rd Person


Novices 1 2 DIFF

30.80 24.13 -5.33

20.14 17.39 -2.86

(1.82) (1.51) (1.81)

(2.27) (1.57) (1.82)

32.97 34.96

2.04†*

(1.46) (2.07) (1.56)

29.46 24.89 -4.68†

(1.34) (1.66) (1.37)

Experts 1 2 DIFF

19.74 16.07 -4.27†

(1.28) (.98)

(1.20)

17.88 17.00 -.88†

(1.23) (1.41) (1.16)

Note. 1 = baseline putting block; 2 = experimental putting block; DIFF = difference score of experimental and baseline block; *Significantly different at p < .05 to no imagery group;

†Significantly different at p < .05 to other imagery

group

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Figure 5.2 Bar graph including error bars (standard error of the mean) for difference scores clustered by skill level and imagery

perspective for Experiment 3.

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Pressure block. Means and standard errors of putting performance are

summarized in Table 5.4 and Figure 5.3. To begin, the data were submitted to a 2 (Skill

Level: novices vs. experts) X 2 (Imagery Perspective: first-person vs. third-person) X 3

(Type of Pressure: none vs. outcome vs. monitoring) ANOVA on the putting distance

difference scores (i.e., pressure – baseline block). Only the skill level by imagery

perspective interaction was significant, F(1, 81) = 4.38, MSE = 79.71, p = .040, all other

effects were not, all Fs < 1. Thus, as for the imagery block without pressure, novices

differed in how well they performed as a function of visual imagery perspective. Then,

each skill level group was analyzed individually.

The data of the novice golfers were submitted to a 3 (Type of Pressure: none vs.

outcome vs. monitoring) X 2 (Imagery Perspective: first-person vs. third-person) ANOVA

on the putting distance difference scores. Although novices still performed slightly

better using third- compared to first-person imagery across conditions, this difference

was no longer significant, F(1, 43) = 2.23, MSE = 117.30, p = .14, and neither was any

other effect, all Fs < 1. Thus, no differences in performance among the three pressure

conditions were found, suggesting that performance decrements, as were shown under

outcome pressure in Experiment 2, no longer occurred. Therefore and importantly,

choking was prevented through imagery.

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TABLE 5.4

MEANS AND STANDARD ERRORS (IN PARENTHESES) FOR BLOCK AND DIFFERENCE SCORES BY SKILL LEVEL AND PRESSURE AND

IMAGERY CONDITION FOR EXPERIMENT 3

Control Outcome Pressure Monitoring Pressure



Novices 1 2 3 DIFF (Imagery) DIFF (Pressure)

33.54 36.95 34.70 3.41 1.15

(2.80) (3.35) (3.47) (4.81) (4.00)

30.49 27.20 25.24 -3.64 -5.20

(1.95) (4.09) (2.84) (3.91) (4.00)

32.32 31.79 25.83 -.40

-6.49

(2.37) (4.21) (4.28) (3.74) (4.17)

27.74 20.94 20.06 -6.80 -7.67

(2.66) (2.66) (3.17) (1.77) (2.13)

33.30 37.33 31.03 4.03 -2.27

(2.80) (2.04) (2.81) (2.05) (3.45)

30.08 26.32 21.31 -3.72 -8.77

(2.46) (1.41) (2.61) (2.59) (3.56)

Experts 1 2 3 DIFF (Imagery) DIFF (Pressure)

19.90 17.71 15.29 -4.06 -4.61

(2.69) (1.58) (1.29) (2.73) (1.75)

19.41 17.49 15.92 -1.92 -3.49

(2.59) (3.49) (3.39) (2.97) (2.63)

21.71 17.58 14.22 -4.14 -7.49

(1.85) (1.08) (1.40) (2.38) (2.43)

15.06 15.64 12.91

.57 -2.15

(1.31) (1.13) (1.94) (.98)

(1.71)

17.60 12.94 12.73 -4.59 -4.87

(2.08) (1.86) (1.39) (1.43) (2.89)

20.06 18.38 18.21 -1.69 -1.86

(2.19) (2.61) (2.57) (1.66) (1.73)

Note. 1 = baseline putting block; 2 = imagery putting block; 3 = pressure putting block; DIFF (Imagery) = difference score of imagery and baseline block; DIFF (Pressure) = difference score of pressure and baseline block;

*Significantly different at p < .05 to control group;

†Significantly different at p < .05 to other pressure group

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Figure 5.3 Bar graph including error bars (standard error of the mean) for difference scores for novice (a) and expert (b) golfers

clustered by type of pressure and imagery for Experiment 3.

(

(a)

(b)

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Because I am interested in whether choking, as shown in the outcome pressure

condition of Experiment 2, could be prevented through imagery, post hoc comparisons

on the difference scores of this experiment’s (first- and third-person imagery combined)

imagery practice under outcome pressure and Experiment 2’s outcome pressure data

were run. In fact, significantly better performance was observed for the imagery under

pressure compared to the no imagery pressure group, t(28) = 2.30, p = .029. Thus, when

novices were briefly instructed in imagery use and practiced it for one block before

performing in the outcome pressure environment, they no longer showed a

performance decrement. To look at this effect more closely, post hoc comparisons were

also run between the individual imagery conditions and Experiment 2’s outcome

pressure data. For first-person imagery, the effect was only marginally significant, t(21)

= 1.75, p = .095, however, for third- person imagery it was significant, t(17) = 3.38, p =

.004. Thus, it can be more clearly inferred that third-person imagery can be used to

prevent choking under outcome pressure in novice golfers.

Moreover, it was important to find out if imagery hurt performance that was

initially unharmed for novices. Comparisons between the monitoring pressure condition

of this experiment’s (combined) imagery practice and Experiment 2’s (no imagery)

group showed no significant differences in difference scores of the critical and baseline

blocks, t(32) = .489, p = .63. Therefore, imagery did not compromise novice performance

under monitoring pressure.

Finally, the data of the expert golfers were submitted to a 3 (Type of Pressure:

none vs. outcome vs. monitoring) X 2 (Imagery Perspective: first-person vs. third-

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person) ANOVA on the putting distance difference scores. Expert golfers still performed

better using first- than third-person imagery overall, however, this effect was only

marginally significant, F(1, 38) = 2.91, MSE = 37.17, p = .096, and no other effect reached

significance, all Fs < 1. As for the novice group, no differences among the three pressure

conditions were found, suggesting that those performance decrements, as occurred in

Experiment 2, were no longer present in the current experiment. Therefore, choking

was prevented for experts through imagery, too.

For the purpose of this study, the results of this experiment’s imagery under

monitoring pressure condition were compared to Experiment 2’s monitoring pressure

result to see whether imagery prevented choking. Indeed, the addition of imagery

practice (first- and third-person combined) resulted in better performance under

monitoring pressure compared to Experiment 2’s no imagery condition, t(29) = 2.78, p =

.010. When comparing each of these imagery conditions separately to Experiment 2’s

monitoring pressure data, first-person perspective resulted in a significant effect, t(23) =

2.67, p = .014, and third-person imagery in a marginally significant effect, t(22) = 1.73, p

= .098. Consequently, it can be argued that first-person imagery is best suited for the

prevention of choking under monitoring pressure in expert golfers.

As for novices, it was also important to see if imagery impaired skilled

performance under outcome pressure. No significant differences were found, t(33) =

.307, p = .76, and, therefore, imagery did not negatively affect experts under outcome

pressure.

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5.3 Discussion

The purpose of this experiment was (a) to more generally investigate visual

perspective in imagery practice considering the performer’s skill level (or cognitive

demands) with the task, and (b) to test whether imagery prevents choking in those skill

level – pressure type situations in which it occurred in Experiment 2.

5.3.1 Imagery (Only)

With respect to visual perspective, imagery was found most effective when

novice golfers practiced under third-person and experts under first-person. To more

closely examine if imagery practice helped or harmed performance under low anxiety

conditions, comparisons of this experiment’s data were made to those of Experiment 2.

Imagery across perspective conditions impeded with novice performance on the

second block when comparing its change scores to those of Experiment 2’s no pressure

(no imagery) control conditions, t(68) = 2.11, p = .038. When analyzed separately, the

first-person imagery group of the novice golfers had such a high difference score that it

was significantly different from the control condition of Experiment 2, t(46) = 2.98, p =

.005, and marginally different from that experiment’s monitoring pressure condition,

t(46) = 1.92, p = .061. In fact, this group performed equally “badly” as the outcome

pressure group, t < .5, which was concluded to exhibit choking. It might be that first-

person imagery practice is so cognitively demanding for novice golfers that it uses up

the otherwise necessary attentional resources to perform the putting task alone.

Without such explicit attention directed towards putting but turned towards the

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imagery practice, performance is initially impaired. In contrast, third-person imagery did

not impact putting performance as compared to either Experiment 2’s control or

monitoring pressure conditions, all ts < 1. One might speculate that third-person

imagery engages an actor’s attentional resources, however, in a non-harming and

perhaps conducive way to novices’ cognitive demands.

For the expert golfers, the opposite trend in performance with respect to visual

imagery perspective was observed. Overall, imagery did not affect performance when

comparing the imagery change scores to those of Experiment 2’s expert control

condition, t < 1. First-person imagery was found to lead to greater improvement than

third-person imagery, however, it did not excel beyond the performance of Experiment

2’s no imagery control group, t < 1.2. Although third-person imagery led to a smaller

performance improvement than first-person imagery, it was still statistically no worse

than Experiment 2’s control or outcome pressure conditions, all ts < 1.3, but different

(though only marginally significantly) from that experiment’s monitoring pressure

group, t(39) = 1.805, p = .079. This result suggests that experts were not negatively

affected by imagery practice on the whole.

These findings are in line with the hypothesis based on Mayer and Hermann’s

(2010) idea that first-person imagery is best when movement feelings are to be

practiced, as in expert putting, and that third-person imagery is most conducive to the

learning of the individual steps of learning a skill, as in novice putting. These findings do

not support the hypothesis that the type of skill (open vs. closed) governs the

effectiveness of visual imagery perspective on performance alone (Hardy, 1997; Hardy &

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Callow, 1999; White & Hardy, 1995). Even though golf has previously been considered to

be a closed skill sport that emphasizes form (e.g., Arvinen-Barrow et al., 2007), it could

be argued that this categorization is not entirely accurate and that it may depend on

skill level. For novices, golf certainly resembles a task in which much attention must be

paid to the technical aspects of body positioning and club movement and, thus, it

appears that form is important. However, for experts it seems less clear whether their

performance primarily depends on form or on anticipating the environment to

effectively respond to changes within it. When expert golfers putt, they certainly rely on

flawless technical execution which may already be fluent and well learned. In addition,

they also respond to the changes in the environment when “reading the green” as in

finding a good line of putting and applying the right amount of force on the ball to have

the good chance of making the putt.

When comparing scores of the self-report and heart rate measures, experts

reported a slightly greater gain in controllability than novices. Considering that novices

need most, if not all, of their attentional resources to complete the putting task, it is not

surprising that adding a second assignment, namely, a specific imagery practice, might

lead to a slight loss of feeling in control of the situation and worse performance than

doing the putting task alone. Experts might be more accustomed to the putting task and

their performance is typically not hurt by additional task demands. In addition, both skill

level groups equally experienced a greater decrease in positive affect when using third-

compared to first-person imagery. It has been shown that observing oneself from an

external viewpoint can create anxiety (e.g., Duval & Wicklund, 1972). Imagining oneself

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from a third person perspective might bring about similar thoughts and feelings about

oneself.

5.3.2 Imagery under Pressure

Novices and experts exhibited no performance decrements in any pressure

condition when using imagery. More importantly, choking under outcome pressure was

prevented when novices used third-person imagery and performance decrements that

initially arose under monitoring pressure no longer occurred when experts practiced

first-person imagery. In sum, imagery that matches the cognitive demands of the

performer prevented choking in those pressure scenarios that were initially shown to be

harmful.

Interestingly, participants in the pressure scenarios reported distress to the same

extent as in Experiment 2. The same trend in the self-report data was observed in that

Pressure ratings and responses on SAM arousal and the STAI state form indicated the

participants putting under outcome and monitoring pressure were equally distressed

but significantly more distressed than participants under no pressure. This finding

suggests that imagery succeeded in preserving optimal performance by providing the

performer with a solution to cope with the perceived distress rather than by altering the

perception of performance pressure.

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CHAPTER 6:

CONCLUSIONS

Three experiments were conducted investigating the influence of pressure and

imagery on golf putting performance on beginning and advanced golfers. Experiment 1

tested the relationship of skill level and direction of attention. This experiment

replicated the commonly-found interaction of novices performing better under skill-

focused than under distraction conditions and experts’ superior performance under

distraction than under skill-focused attention conditions. In Experiment 2, performance

pressure was induced in form of monitoring and outcome pressure and its effect on

performers of differing skill level was tested. Experiment 2a served as a means to check

the manipulation of the outcome and monitoring pressure scenarios. A number of

affect- and arousal-related self-report and physiological measures were used to validate

that the two pressure scenarios were perceived to be equally distressing and

significantly more distressing than the no pressure control condition. The aim of

Experiment 2b was to evaluate the effects of pressure on performance and it was found

that novices exhibited choking under outcome and experts under monitoring pressure

while performance was unaffected for novices under monitoring and experts under

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outcome pressure. Finally, Experiment 3 used a new method to help alleviate

performance decrements caused by pressure.

The previously found interaction (Ashcraft & Kirk, 2001; Beilock et al., 2002,

2004; Beilock & Carr, 2001, 2005; Beilock & DeCaro, 2007; Eysenck, 1979; Gimmig et al.,

2006; Jackson et al., 2006; Kahneman, 1973; Leavitt, 1979; Lewis & Linder, 1997;

Markman et al., 2006; Masters, 1992; Smith & Chamberlin, 1992; Wine, 1971) between

task demands and direction of attention was replicated and provided further support for

the robustness of this relationship. Novice golfers performed well under skill-focused

instructions but choked when they were forced to do a secondary task on top of putting.

Experts, on the other hand, showed no performance decrements when their attention

was divided between the putting task and the auditory task but displayed less-than-

average performance when attending to certain aspects of skill execution.

While this interaction has been shown across a variety of tasks, the effects of

type of pressure on performance are less well established. Only one study has

systematically examined how monitoring and outcome pressure interact with the

cognitive demands of a task (DeCaro et al., 2011). More support for this hypothesis can

be found when revisiting other studies that used pressure manipulations but did not set

out to closely examine type of pressure (Beilock & Carr, 2001; Gray, 2004; Markman, et

al., 2006, Reeves et al., 2007). Monitoring pressure, stemming from the feeling of being

evaluated or watched, has been found to hurt performance on proceduralized tasks but

not WM-reliant ones, while outcome pressure, as in high stakes scenarios, seems to hurt

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WM-reliant tasks but not proceduralized ones. The current research replicated this

finding using a sensorimotor task.

In Experiment 2, monitoring pressure was induced by video-recording

participants, projecting the life feed on a 66-inch smart board screen in clear sight of the

performer right next to the putting area, and having a golf professional watch them and

take notes of their putting block. The outcome pressure scenario involved the set up of

a competition in which participants were told they had been paired up with another

participant (i.e., peer pressure) and that their combined putting score could win them a

prize (i.e., incentives). A no pressure condition served as the control group. Before

investigating the effects of pressure on performance, it was first established that the

two pressure scenarios were reported to be equally distressing but more distressing

than the control condition (Experiment 2a). Then, the putting data of 2a and 2b were

jointly analyzed and summarized under Experiment 2b.

Replicating the findings of DeCaro et al. (2011), novice golfers, for which putting

represents a WM-reliant task, exhibited choking under outcome but not under

monitoring pressure. This result is in line with predictions made by the distraction

hypothesis in that performance is impaired when thoughts of worries compromise the

otherwise needed attentional resources to do the putting task. In contrast, monitoring

pressure leads to greater skill-focus, an attentional direction proven non-harmful to

novice performance which heavily relies on explicit monitoring. Furthermore, experts

showed performance decrements under monitoring but not under outcome pressure.

This result is in line with predictions made by self-focus theory in that highly

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proceduralized skills suffer from accessorily skill-focus but are left unharmed by

potential thoughts of worry and anxiety which have been found to arise during

competition. It should be noted that self-focus and distraction theories have been found

to make complimentary rather than contradictory predictions of choking under pressure

consisting of the match of attentional direction and the cognitive demands of a task.

Experiment 3 investigated use of imagery from first- and third person

perspective by performers of varying skill levels, first, as a pure imagery exercise and,

then, under the pressure scenarios examined in Experiment 2. First, an imagery block of

blocks was conducted to explore the effectiveness of imagery perspective on novice and

expert golfers. The findings of this study support the idea that third-person imagery is

best used when learning the individual steps of skill execution as in the early learning of

skill acquisition (e.g., novice golfers), and that first-person imagery is most suitable for

the rehearsal of kinesthetic feelings of the movement, as is important in later stages of

skill acquisition (e.g., expert golfers). This finding supports Mayer and Hermann’s (2010)

hypothesis and may help resolve the still-existing controversy over the most effective

way of using visual perspective in imagery. Given that first-person imagery is typically

accompanied by kinesthetic feelings, which are acquired through practice and are

usually not present during the early stages of skill learning, it is not surprising that

novice golfers were unable to benefit from this imagery exercise. Third-person imagery

seemed much more conducive to novices’ cognitive demands in that they might have

used the imaging of themselves from an external vantage point as a way to practice

putting together the individual steps of the whole movement of the golf putt.

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Following the imagery block, participants were assigned to one of the three

pressure conditions and putted under no, outcome, or monitoring pressure using the

same imagery practice they had been assigned to before. The main finding was that

imagery prevented choking under pressure in both novice and expert golfers.

Previously, it had been found that novice performance was compromised when putting

under outcome pressure conditions. However, the results of Experiment 3 showed that

when novices used third-person imagery, no performance decrements occurred and

choking was prevented. Expert golfers had previously exhibited choking under

monitoring pressure which no longer occurred, especially when they used first-person

imagery.

It has been proposed (e.g., Baumeister, 1984) that pressure induces an increase

in feelings of importance to perform well followed by the performer investing more

effort in his or her performance. Yet, given the varying effects different types of

pressure can have on performance, it is conceivable to assume that what is perceived to

be important may vary as a function of the source of pressure. In this sense, being

watched and/or evaluated (as in the monitoring pressure scenario here) may raise

feelings of importance to “look good” and provoke concerns in the performer with

respect to how the observer or assessor may perceive the way in which the performer

executes the skill (e.g., correctness, smoothness, effectiveness) or even in a personal

way (e.g., attractiveness, intelligence). As a consequence, the performer then invests

more effort in better skill execution and/or even appearing more attractive or intelligent

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as a person. Thus, it is plausible that sources of pressure identified as monitoring

pressure may indirectly induce skill- or self-focus and, thus, explicit monitoring.

Likewise, performing in a competitive environment in which solely one’s

performance outcome (e.g., score, number of goals made, points earned) defines the

value of one’s performance and, on top of that, in which another performer is

dependent upon this performance outcome (i.e., peer pressure), may give rise to a

different set of thoughts and feelings than a monitoring pressure environment, namely,

those of getting oneself to achieve a desired outcome. In this way, one focuses purely

on the goal, the effect of one’s behavior (e.g., making this putt, throwing the ball inside

the basket) and not on the behavior itself (i.e., skill execution) and the performer exerts

effort to maintain his or her performance outcome (if it is already at a high level) or

improve on it (if possible). Thus, it is conceivable to assume that sources associated with

outcome pressure indirectly induce an attentional focus away from skill execution but

towards performance outcomes (or effects).

Given what is known about the cognitive demands of skills, for instance, when

comparing performers of differing skill levels (e.g., novice vs. experts golfers), it is not

surprising to find similarities in results between skill-focused attention and monitoring

pressure and dual-task attentional and outcome pressure conditions. Specifically, while

there was no direct measure of attentional focus in Experiment 2 (in which pressure was

manipulated), the pattern of results, especially the interaction of type of pressure and

skill level, suggests a common theoretical basis with that of Experiment 1, in which

direction of attention was manipulated. In Experiments 1 and 2, novices performed

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optimally under skill-focused attention and monitoring pressure but choked under dual-

task or outcome pressure conditions, while experts putted well under dual-task and

outcome pressure conditions but choked under skill-focused attention and monitoring

pressure.

From this line of the current and prior research, it can be deduced that the

deciding point of whether choking occurs is in the match of the cognitive demands of

the task with the presence of explicit monitoring. Explicit monitoring as described by

self-focus theories and induced by either skill-focused attention or monitoring pressure

represents the key aspect of how choking under pressure can occur. It is necessary for

tasks which rely heavily on working memory and attentional control but it is detrimental

to tasks which are highly proceduralized or automatized. It seems as though anything

that may keep a performer from focusing on skill execution, either directly or indirectly

(e.g., dual-task attention, ruminative thought), brings about a different effect in the

performance of tasks with differing cognitive demands.

Now, the question arises, what exactly caused the lack of choking when imagery

was implemented immediately before participants were faced with the pressure

scenario? For one, the self-report data obtained in this study reveals that performers

using imagery still perceived the environment to be filled with performance pressure.

This finding implies that imagery did not cause an immunization to the sensing of

pressure, instead, it is more likely that imagery helped performers to cope with the

pressure-filled situation in a constructive way.

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But why exactly did third-person imagery help novices and first-person imagery

help experts in maintaining their performance level under pressure? Along the lines of

directing attentional focus towards or away from explicit skill monitoring, imagery

perspective can be used to provoke such skill monitoring through third-person imagery

or away from it via first-person imagery. Not only did imagery perspective seem to act in

ways that suggest that attentional focus was directed towards and away from skill

execution, but it also helped performers to maintain an optimal performance level in

face of pressure which would have otherwise led to a great likelihood of a performance

decline.

It could be argued that the additional putting block of imagery practice would

provide performers with extra practice on the putting task as compared to those in the

second experiment and that comparisons between the two experiments would

somehow favor their chances of coping with the pressure environment. However, an

additional block of single-task putting has not prevented choking in other experiments.

Moreover, participants of the second and third experiment perceived similar levels of

pressure as indicated by Pressure ratings and responses on SAM arousal and the STAI

state form. Importantly, performance under pressure was compromised when not

practicing imagery but was unaffected when practicing imagery while the perception of

pressure did not differ between the two conditions.

In the future, it would be worthwhile to further dissect monitoring as well as

outcome pressure to get at the roots of what causes choking under pressure. Because

the current pressure scenarios were made up of several elements (monitoring pressure:

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video-recording + golf professional as observer; outcome pressure: peer pressure +

incentives), it would be worthwhile to test the effects of the individual elements on

performance. Furthermore, future studies could investigate other forms of pressure and

their effect on performance. With regards to monitoring pressure, a performer can

perceive the attention as being directed towards the self (person, ego) or the skill

(movement). For example, thoughts about what one looks like (e.g., attractiveness,

body image, choice of clothing) would be more self-related and could bring about a

different effect than more skill-related thoughts such as those about what one does

(e.g., motor movement, individual technique, perceived skill level). Moreover, the

effects of type of observer could be investigated in that some characteristics (e.g.,

un/skilled, un/attractive, familiarity with the person etc.) may cause a positive and

others a negative effect on performance.

When being under outcome pressure, the focus is not on the aesthetics or the

correctness of the technique of skill movement but solely on its result (“Did I make this

putt?”). Other factors that might cause outcome pressure such as manipulations of

current score (i.e., being down, tied, or up) would be an interesting continuation to this

research. Why do some athletes perform badly when they are leading a match/game

while others get a boost in confidence and continue to win the match/game?

Furthermore, how do some people cope with being the favorite or the underdog of a

match/game and what are the most effective cognitive strategies to preserve optimal

performance?

115

It would also be interesting to more closely examine how different pressure

scenarios affect performers’ physiological responses to the individual stressors. For

instance, one could assess performers’ perceptions and their cortisol levels in response

to stressful situations. Studies have shown discrepancies between the perceived and

physiological (cortisol) stress responses (Stroud, Salovey, & Epel, 2002). As a

consequence, cognitive and physiological responses might also differ when performing

under stress, a state that resembles pressure. In the Experiment 2, measurements of

average and peak heart rate indicated that pressure causes increases in heart rate. In

addition, women and men have been found to differ in these responses and gender has

been shown to interact with type of task (i.e., an achievement oriented task [outcome

pressure] vs. an evaluative task [monitoring pressure]). Overall, further research should

revisit and perhaps extent the study of the physiological effects of pressure on the stress

response.

With respect to third-person imagery perspective, it would further be

worthwhile to alter angles and distances of the vantage point used to view oneself.

Changes in the location of the vantage point can influence the extent to which skill-

focus, self-focus, outcome-focus can be applied. Presumably, variations in third-person

perspective are a rich continuation to the findings of the current research.

Along the same line, research on choking under pressure should also consider

the extent to which instructions are phrased in concrete of abstract manner. Practiced

skills are represented in memory in hierarchical form (Mackay, 1981, 1982). Mackay

(1982) suggests that this hierarchy is made up of the top node that represents the whole

116

behavior in an abstract (or holistic) form and multiple nodes at the bottom reflecting the

individual motor movements. For example, taking a golf putt can be broken down into

top, subordinate, and bottom nodes. At the top would be the holistic and abstract

representation of “taking a golf putt” which encompasses the whole action including

stance, grip, and movement. A putt can be broken down into two subordinate nodes the

backswing and the follow through. The details of these nodes can be described in terms

of simpler nodes such as moving the putter back by primarily using the shoulders,

halting, and moving the putter in a straight line forward, again using the shoulders. At

the bottom level of this hierarchy are individual hand, shoulder, head muscle

movements.

In a similar way, action identification theory (Vallacher & Wegner 1987, 1989)

and the theory of construal level (Liberman & Trope, 1998) suggest that actions can be

hierarchically structured into different levels of identification or construal. These levels

range from low (concrete) levels, which center around how an action is done and

represent events in terms of specific and subordinate features, to high (abstract) levels,

which depict why it is done and are described by general and superordinate terms. For

example, the action of “seeing if someone is home” would mark the highest and most

abstract level, while “pushing a doorbell” would be lower and “moving a finger” be the

lowest and most concrete level. Whether an action should be construed in concrete or

abstract terms depends on the context, the task, and the performer (Vallacher &

Wegner). Novel and difficult tasks tend to be construed by lower levels as well as tasks

117

performed under pressure, while familiar, easy, and heavily automatized tasks are

identified by higher levels.

With regard to my study, novice golfers would likely benefit from lower level (or

more concrete) skill representations, for instance, focusing on the step-by-step

processes of the stroke while expert performance would be facilitated by top level (or

more abstract) skill representations. Under pressure, the prediction is less clear. For

example, Vallacher and Wegner (1987) argue that concrete construals would help the

control of action in pressure situations, regardless of level of expertise while it has been

recently found that engaging in abstract construals aided self-control processes for

prospective tasks (e.g., Libby, Shaeffer, & Eibach, 2009) and, thus, might aid the control

of motor movements under pressure regardless of skill level.

Overall the domain of choking under pressure as it pertains to cognitive, sports,

and applied psychology is a promising field in shedding light on what happens when

performance breaks down and how it can be prevented. This research contributes to

the methods of alleviating choking under pressure with a strategy that can be applied to

fit the needs of the individual and situation. Imagery is a widely-used technique in the

area of skill acquisition and performance regulation and this study provides evidence

that it also helps preserve optimal performance in pressure-laden situations.

118

REFERENCES

Aaker, J. L., & Lee, A. Y. (2006). Understanding regulatory fit. Journal of Marketing Research, 43, 15-19.

Arvinen-Barrow, M., Weigand, D. A., Thomas, S., Hemmings, B., & Walley, M. (2007). Elite and novice athletes’ imagery use in open and closed sports. Journal of Applied Sport Psychology, 19(1). doi: 10.1080/10413200601102912

Ashcraft, M. H., & Kirk, E. P. (2001). The relationships among working memory, math anxiety, and performance. Journal of Experimental Psychology: General, 130(2), 224–237. doi: 10.1037/0096-3445.130.2.224

Atkinson, J. W. (1957). Motivational determinants of risk-taking behavior. Psychological Review, 64(6), 359–372. doi: 10.1037/h0043445

Ayduk, O., & Kross, E. (2008). Enhancing the pace of recovery: Self-distanced analysis of negative experiences reduces blood pressure reactivity. Psychological Science, 19(3), 229-231. doi: 10.1111/j.1467-9280.2008.02073.x

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral changes. Psychological Review, 84, 191-215.

Baumeister, R. F. (1984). Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance. Journal of Personality and Social Psychology, 46(3), 610–620. doi: 10.1037/0022-3514.46.3.610

Beilock, S. L., Afremow, J. A., Rabe, A. L., & Carr, T. H. (2001). “Don’t Miss!” The debilitating effects of suppressive imagery on golf putting performance. Journal of Sport & Exercise Psychology, 23, 200-221.

Beilock, S. L., & Carr, T. H. (2001). On the fragility of skilled performance: What governs choking under pressure? Journal of Experimental Psychology: General, 130(4), 701–725. doi: 10.1037/0096-3445.130.4.701

Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and “choking under pressure” in math. Psychological Science, 16(2), 101–105. doi: 10.1111/j.0956-7976.2005.00789.x

119

Beilock, S. L., Carr, T. H., MacMahon, C., & Starkes, J. L. (2002). When paying attention becomes counterproductive: Impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology, 8(1), 6–16. doi: 10.1037/1076-898X.8.1.6

Beilock, S. L., & DeCaro, M. S. (2007). From poor performance to success under stress: Working memory, strategy selection, and mathematical problem solving under pressure. Journal of Experimental Psychology, 33(6), 983-998. doi: 10.1037/0278-7393.33.6.983

Beilock, S. L., & Gray, R. (2007). Why do athletes “choke” under pressure? In G. Tenenbaum and R.C. Ecklund (Eds.), Handbook of sport psychology, 3rd Ed. (pp. 425-444). Hoboken, NH: John Wiley & Sons. doi: 10.1002/9781118270011.ch19

Beilock, S. L., Kulp, C. A., Holt, L. E., & Carr, T. H. (2004). More on the fragility of performance: Choking under pressure in mathematical problem solving. Journal of Experimental Psychology: General, 133(4), 584–600. doi: 10.1037/0096-3445.133.4.584

Bell, J. J., & Hardy, J. (2009). Effects of attentional focus on skilled performance in golf. Journal of Applied Sports Psychology, 21(2), 163-177. doi: 10.1080/10413200902795323

Bernstein, N. A. (1967). The co-ordination and regulation of movements, Pergamon Press, Oxford.

Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49-59.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. doi: 10.1037/0033-2909.112.1.155

Collins, D. V., Jones, B., Fairweather, M., Doolan, S., & Priestley, N. (2001). Examining anxiety associated changes in movement patterns. International Journal of Sport Psychology, 32(3), 223–242.

Cox, R. H., Martens, M. P., & Russell, W. D. (2003). Measuring anxiety in athletics: The Revised Competitive State Anxiety Inventory-2. Journal of Sport & Exercise Psychology, 25(4), 519-533.

120

Craft, L. L., Magyar, T. M., Becker, B. J., & Feltz, D. L. (2003). The relationship between the Competitive State Anxiety Inventory-2 and sport performance: A meta-analysis. Journal of Sport & Exercise Psychology, 25, 44-65.

DeCaro, M. S., Thomas, R. D., Albert, N. B., & Beilock, S. L. (2011). Choking under pressure: Multiple routes to skill failure. Journal of Experimental Psychology: General, 140(3), 390-406. doi: 10.1037/a0023466

Driskell, J. E., Copper, C., & Moran, A. (1994). Does mental practice enhance performance? Journal of Applied Psychology, 79, 481-492.

Dunlap, W. P., Cortina, J. M., Vaslow, J. B., & Burke, M. J. (1996). Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods, 1(2), 170–177. doi: 10.1037/1082-989X.1.2.170

Duval, S., & Wicklund, R. A. (1972). A theory of objective self-awareness, Academic Press, New York.

Easterbrook, J. A. (1959). The effect of emotion on cue utilization and the organization of behavior. Psychological Review, 66(3), 183–201. doi: 10.1037/h0047707

Eberspächer, H. (2001). Mentales Training. Das Handbuch für Trainer und Sportler. München: Copress.

Eysenck, M. W. (1979). Anxiety learning and memory: A reconceptualization. Journal of Research in Personality, 13(4), 363-385. doi: 10.1016/0092-6566(79)90001-1

Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brooks/Cole.

Frank, M., & Gilovich, T. (1989). Effect of memory perspective on retrospective causal attributions. Journal of Personality and Social Psychology, 57(3), 399–403. doi: 10.1037/0022-3514.57.3.399

Gray, R. (2004). Attending to the execution of a complex sensorimotor skill: Expertise differences, choking, and slumps. Journal of Experimental Psychology: Applied, 10(1), 42–54. doi: 10.1037/1076-898X.10.1.42

Gimmig, D., Huguet, P., Caverni, J. P., & Cury, F. (2006). Choking under pressure and working memory capacity: When performance pressure reduces fluid intelligence. Psychonomic Bulletin & Review, 13(6), 1005–1010. doi: 10.3758/BF03213916

Grimm, L. R., Markman, A. B., Maddox, W. T., & Baldwin, G. C. (2008). Differential effects of regulatory fit on category learning. Journal of Experimental Social Psychology, 44(3), 920-927. doi: 10.1016/j.jesp.2007.10.010

121

Gucciardi, D. F., & Dimmock, J. A. (2008). Choking under pressure in sensorimotor skills: Conscious processing or depleted attentional resources? Psychology of Sport and Exercise, 9, 45-59.

Hall, C. R. (1997). Lew Hardy's third myth: A matter of perspective. Journal of Applied Sport Psychology, 9(2), 310-13. doi: 10.1080/10413209708406490

Hall, C. R., & Martin, K. A. (1997). Measuring movement imagery abilities: A revision of the Movement Imagery Questionnaire. Journal of Mental Imagery,21(1-2), 143-154.

Hardy, L. (1997). The Coleman Roberts Griffith address: Three myths about applied consultancy work. Journal of Applied Sport Psychology, 9(2), 277-294. doi: 10.1080/10413209708406487

Hardy, L., & Collow, N. (1999). Efficacy of external and internal visual imagery perspectives for the enhancement of performance on tasks in which form is important. Journal of Sport & Exercise Psychology, 21(2), 95-112.

Hardy, L., Mullen, R., & Jones, G. (1996). Knowledge and conscious control of motor actions under stress. British Journal of Psychology, 87(4), 621–636. doi: 10.1111/j.2044-8295.1996.tb02612.x

Higgins, E. T. (1997). Beyond pleasure and pain. American Psychologist, 52(12), 1280–1300. doi: 10.1037/0003-066X.52.12.1280

Higgins, E. T. (1998). Promotion and prevention: Regulatory focus as a motivational principle. Advances in Experimental Social Psychology, 30, 1–46. doi: 10.1016/S0065-2601(08)60381-0

Higgins, E. T. (2000). Making a good decision: Value from fit. American Psychologist, 55(11), 1217-1230. doi: 10.1037/0003-066X.55.11.1217

Higuchi, T., Imanaka, K. & Hatayama, T. (2002). Freezing degrees of freedom under stress: Kinematic evidence of constrained movement strategies. Human Movement Science, 21(5-6), 831-846. doi: 10.1016/S0167-9457(02)00174-4

Hodes, R., Cook, E. W. III, & Lang, P. J. (1990). Individual differences in autonomic response: Conditioned association of conditioned fear? Psychophysiology, 22, 545-560.

Isaac, A. R., Marks, D. F., & Russell, D. G. (1986). An instrument for assessing imagery of movement. The vividness of movement imagery questionnaire. Journal of Mental Imagery, 10(4), 23–30.

122

Jackson, R. C., Ashford, K. J., & Norsworthy, G. (2006). Attentional focus, dispositional reinvestment, and skilled motor performance under pressure. Journal of Sport & Exercise Psychology, 28, 49–68.

Jones, B. T., Davis, M., Crenshaw, B., Behar, T., & Davis, M. (1998). Classic instruction in golf. New York: Broadway.

Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice Hall.

Kross, E., & Ayduk, O. (2008). Facilitating adaptive emotional analysis: Short-term and long-term outcomes distinguishing distanced- analysis of depressive experiences from immersed-analysis and distraction. Personality and Social Psychology Bulletin, 34(7), 924-938. doi: 10.1177/0146167208315938

Kross, E., Ayduk, O., & Mischel, W. (2005). When asking “why” does not hurt: Distinguishing rumination from reflective processing of negative emotions. Psychological Science, 16(9), 709-715. doi: 10.1111/j.1467-9280.2005.01600.x

Leavitt, J. (1979). Cognitive demands of skating and stickhandling in ice hockey. Canadian Journal of Applied Sport Sciences, 4(1), 46–55.

Lewis, B., & Linder, D. (1997). Thinking about choking? Attentional processes and paradoxical performance. Personality and Social Psychology Bulletin, 23(9), 937–944. doi: 10.1177/0146167297239003

Libby, L. K., Shaeffer, E. M., & Eibach, R. P. (2009). Seeing meaning in action. A bidirectional link between visual perspective and action identification level. Journal of Experimental Psychology: General, 138(4), 503-516. doi: 10.1037/a0016795

Liberman, N., & Trope, Y. (1998). The role of feasibility and desirability considerations in near and distant future decisions: A test of temporal construal theory. Journal of Personality and Social Psychology, 75(1), 5–18. doi: 10.1037/0022-3514.75.1.5

Liberman, N., & Trope, Y. (2008). The psychology of transcending the here and now. Science, 322(5905), 1201–1205. doi: 10.1126/science.1161958

Mackay, D. G. (1981). The problem of rehearsal or mental practice. Journal of Motor Behavior, 13(4), 274-285.

Mackay, D. G. (1982). The problem of flexibility, fluency and speed-accuracy trade-off in skilled behavior. Psychological Review, 89(5), 483-506. doi: 10.1037/0033-295X.89.5.483

123

Maddox,W. T., Baldwin, G. C., & Markman, A. B. (2006). A test of the regulatory fit hypothesis in perceptual classification learning. Memory & Cognition, 34(7), 1377-1397. doi: 10.3758/BF03195904

Mahoney, M. J. & Avener, M. (1977). Psychology of the elite athlete: An exploratory study. Cognitive Therapy & Research, 1(2), 135-141. doi: 10.1007/BF01173634

Markman, A. B., Baldwin, G. C., & Maddox,W. T. (2005). The interaction of payoff structure and regulatory focus in classification. Psychological Science, 16(11), 852–855. doi: 10.1111/j.1467-9280.2005.01625.x

Markman, A. B., Maddox, W. T., & Worthy, D. A. (2006). Choking and excelling under pressure. Psychological Science, 17, 944-948.

Masters, R. S. W. (1992). Knowledge, knerves, and know-how: The role of explicit versus implicit knowledge in the breakdown of a complex motor skill under pressure. British Journal of Psychology, 83, 343–358.

Maxwell, J. P., Masters, R. W., & Eves, F. F. (2000). From novice to know-how: A longitudinal study of implicit motor learning. Journal of Sport Sciences, 18, 111-120.

Mayer, J. M., & Hermann, H.- D. (2010). Mentales Training: Grundlagen und Anwendung in Sport, Rehabilitation, Arbeit und Wirtschaft. [Mental practice: Fundamentals and application in sports, rehabilitation, business, and economy.] Berlin, Germany: Springer Verlag

McIsaac, H. K., & Eich, E. (2004). Vantage point in traumatic memory. Psychological Science, 15, 248-253.

McNevin, N. H., Shea, C. H., & Wulf, G. (2003). Increasing the distance of an external focus of attention enhances learning. Psychological Research, 67, 22-29. doi: 10.1007/s00426-002-0093-6

Mesagno, C., Marchant, D., & Morris, T. (2008). A pre-performance routine to alleviate choking in “choking-susceptible” athletes. The Sport Psychologist, 22, 439-457.

Meyers, A. W., Cooke, C. J., Cullen, J., & Liles, C. (1979). Psychological aspects of athletic competitors: A replication across sports. Cognitive Therapy and Research 3, 361 - 366.

Morris, T., Spittle, M., & Watt, A. (2005). Imagery in sport. Champaign, Ill.: Human Kinetics.

124

Mumford, B., & Hall, C. (1985). The effects of internal and external imagery on performing figures in figure scating. Canadian Journal of Applied Sports Science, 10(4), 171-177.

Munzert, J., Dültgen, K., & Möllmann, H. (2000). Individuelle Merkmale von Bewegungsvorstellungen. Eine explorative Untersuchung im Badminton. [Individual characteristics of movement thoughts. An exploratory study in badminton.] Psychologie und Sport, 7, 15-25.

Murphy, S. M. (1994). Imagery interventions in sport. Medicine and Science in Sports and Exercise, 26, 486-494.

Nigro, G., & Neisser, U. (1983). Point of view in personal memories. Cognitive Psychology, 15, 467–482.

Oudejans, R. R. D., & Pijpers, J. R. (2010). Training with mild anxiety may prevent choking under higher levels of anxiety. Journal of Sport & Exercise Psychology, 11, 43–50.

Pijpers, J. R., Oudejans, R. R. D., Holsheimer, F., & Bakker, F. C. (2003). Anxiety-performance relationships in climbing: A process-oriented approach. Psychology of Sport and Exercise, 4, 283-304.

Plessner, H., Unkelbach, C., Memmert, D., Baltes, A., & Kolb, A. (2009). Regulatory fit as a determinant of sport performance: How to succeed in a soccer penalty-shooting. Psychology of Sport and Exercise, 10, 108-115.

Poldrack, R. A., Clark, J., Pare-Blagoev, J., Shohamy, D., Creso Moyano, J., Myers, C., & Gluck, M. A. (2001). Interactive memory systems in the human brain. Nature, 414, 546-550.

Poldrack, R. A. & Packard, M. G. (2003). Competition between memory systems: Converging evidence from animal and human studies. Neuropsychologia, 41, 245-251.

Poolton, J., Maxwell, J. P. & Masters, R. S. W. (2004). Rules for Reinvestment. Perceptual and Motor Skills, 99, 771-774.

Reeves, J. L., Tenenbaum, G., & Lidor, R. (2007). Choking in front of the goal: The effects of self-consciousness training. International Journal of Sport and Exercise Psychology, 5(3), 240-254.

Roberts ,R., Callow, N., Hardy, L., Markland, D., & Bringer, J. (2008). Movement imagery ability: Development and assessment of a revised version of the vividness of

125

movement imagery questionnaire. Journal of Sports and Exercise Psychology, 30, 200–221.

Robinson, J. A., & Swanson, K. L. (1993). Field and observer modes of remembering. Memory, 1, 169–184.

Smith, M. D., & Chamberlin, C. J. (1992). Effect of adding cognitively demanding tasks on soccer skill performance. Perceptual and Motor Skills, 75, 955–961.

Spence, J. T., & Spence, K. W. (1966). The motivational components of manifest anxiety: Drive and drive stimuli. In C. D. Spielberger (Ed.), Anxiety and behavior. New York, NY: Academic Press.

Spielberger, C. D., Gorsuch, R. L., & Lushene. R. E. (1970). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press

Stroud, L. R., Salovaey, P., & Epel, E. S. (2002). Sex differences in stress response: Social rejection versus achievement stress. Biological Psychiatry, 52, 318-327.

Tenenbaum, G., Lidor, R., & Reeves, J. (2007). Choking in front of the goal: The effects of self-consciousness training. International Journal of Sport and Exercise Psychology, 5, 240-254.

Ungerlinder, S., & Golding, J. (1991). Mental practice among Olympic athletes. Perceptual and Motor Skills, 72, 1007-1017.

Vallacher, R. R., & Wegner, D. M. (1987). What do people think they’re doing? Action identification and human behavior. Psychological Review, 94, 3–15.

Vallacher, R. R., & Wegner, D. M. (1989). Levels of personal agency: Individual variation in action identification. Journal of Personality and Social Psychology, 57, 660–671.

Vereijken, B., van Emmerik, R. E. A., Whiting, H. T. A. & Newell, K. M. (1992). Free(z)ing degrees of freedom in skill acquisition. Journal of Motor Behavior, 24, 133-142.

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology,

Weinberg, R. S., & Gould, D. (2003). Foundations of sport and exercise psychology, (3rd ed.). Champaign, IL: Human Kinetics.

Wells, A., Clark, D. M., Ahmad, S. (1998). How do I look in the mind’s eye: Perspective taking in social phobic imagery. Behaviour Research and Therapy, 36, 631-634.

126

Wells, A., & Papageorgiou, C. (1998). Social phobia: Effects of external attention on anxiety, negative beliefs and perspective taking. Behavior Therapy, 29, 357–370.

Wells, A., & Papageorgiou, C. (1999).The observer perspective: Biased imagery in social phobia, agoraphobia, and blood/injury phobia. Behaviour Research and Therapy, 37, 653-658.

White, A. & Hardy, L. (1995). Use of different imagery perspectives on the learning and performance of different motor skills. British Journal of Psychology, 86, 169-180.

Wine, J. (1971). Test anxiety and direction of attention. Psychological Bulletin, 76, 92-104.

Worthy, D. A., Markman, A. B., & Maddox, W. T. (2009). What is pressure? Evidence for social pressure as a type of regulatory focus. Psychonomic Bulletin & Review, 16, 344-349.

Wulf, G., Hoeß, M., & Prinz, W. (1998). Instructions for motor learning: Differential effects of internal versus external focus of attention. Journal of Motor Behavior, 30, 169–179.

Wulf, G., Lauterbach, B., & Toole, T. (1999). Learning advantages of an external focus of attention in golf. Research Quarterly for Exercise and Sport, 70, 120–126.

Wulf, G., McConnel, N., Gaertner, M, & Schwarz, A. (2002). Feedback and attentional focus: Enhancing the learning of sport skills through external-focus feedback. Journal of Motor Behavior, 34, 171–182

Wulf, G., McNevin, N. H., & Shea, C. H. (2001). The automaticity of complex motor skill learning as a function of attentional focus. Quarterly Journal of Experimental Psychology, 54A, 1143–1154.

Wulf, G., & Prinz, W. (2001). Directing attention to movement effects enhances learning: A review. Psychonomic Bulletin & Review, 8, 648-660.

Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology, 18, 459-482.

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