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4 LIBRARY
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This is to certify that the
thesis entitled

THE EFFECTS OF PSYCHOLOGICAL SKILLS
TRAINING ON THE COGNITIONS AND
PERFORMANCE OF HIGH SCHOOL SOFTBALL
PLAYERS

presented by

Jill A. Elliott

has been accepted towards fulﬁllment
of the requirements for the

MS. degree in Kinesology

 

 

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_*

THE EFFECTS OF PSYCHOLOGICAL SKILLS TRAINING ON THE COGNITIONS
AND PERFORMANCE OF HIGH SCHOOL SOFTBALL PLAYERS

By

Jill A. Elliott

A THESIS
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Kinesiology

2003

ABSTRACT

THE EFFECTS OF PSYCHOLOGICAL SKILLS TRAINING ON THE COGNITIONS
AND PERFORMANCE OF HIGH SCHOOL SOFTBALL PLAYERS

By

Jill A. Elliott

The purpose of this study was to investigate the effects of a psychological skills
training (PST) program, under the direction of a coach, on the cognitions and
performance of high school softball players. Self-conﬁdence, competitive anxiety, and
offensive performance were measured (with the SSCI the CSAI-2 and season offensive
statistics) and compared between an experimental team and a control team throughout an
entire softball season. Participants included 28 female softball players (Experimental
team, N = 12; Control team, N = 16), grades 10 to 12 (Experimental team, M = 10.83;
Control team M = 11.51). The experimental team began PST in the pre-season and
continued throughout the entire season while the control team proceeded with their
season as usual. Group means and standard deviations were calculated and compared
using a multivariate analysis of variance (MANOVA). A positive effect of PST for the
experimental team as compared to the control team resulted. Although the control team
was an older, more experienced team, the experimental team reported higher levels of
self-conﬁdence, lower levels of anxiety and ﬁnished the season with better offensive
performance statistics than the control team. It was concluded that athletes of high

school age and ability will beneﬁt from PST and that a coach can effectively teach PST.

DEDICATION

To my parents who taught us to always ﬁnish what we start.

iii

ACKNOWLEDGEMENTS

A very special thank you to my advisor and thesis committee chair Dr. Marty Ewing.
Your time, patience, and support are truly appreciated. Also, thank you to my thesis
committee members, Dr. Dianne Ulibarri, Karen Langeland, and Dr. Crystal Branta. I
especially appreciate your high expectations.

Thanks to Pat Sommers and the members of her softball team for their commitment to
this study throughout the entire softball season. Also, thanks to the players on my
soﬁball team, the experimental team, your desire to learn made coaching fun!

Thanks to my family, especially to my “technical advisors,” Steve and Corey, without
your help, I would still be working. And to Ryan for words of encouragement from ISU.

TABLE OF CONTENTS

LIST OF APPENDICES .................................................................. vii
LIST OF TABLES ......................................................................... viii
LIST OF FIGURES ....................................................................... x
CHAPTER I
Introduction ................................................................................ 1
Hypotheses ................................................................................. 7
Operational Deﬁnitions .................................................................. 7
Limitations ................................................................................. 8
CHAPTER 11
REVIEW OF THE LITERATURE
The Arousal Performance Relationship ................................................ 10
Measurement of Competitive Anxiety .............................................. 12
Inverted-U Hypothesis ................................................................ l3
Cusp Catastrophe Model of Anxiety and Performance ........................... 15
Self-Conﬁdence ........................................................................... 1 8
Self-Efﬁcacy Theory .................................................................. 19
Testing Bandura’s Theory ........................................................... 22
Sport-Conﬁdence ..................................................................... 24
Measurement of Sport-Conﬁdence .................................................. 27
Psychological Skills Components ...................................................... 3O
Goal-Setting ................................................................................ 3O
Relaxation .................................................................................. 35
Imagery ..................................................................................... 38
Self-talk .................................................................................... 44
Psychological Skills Training Package Research ...................................... 48
CHAPTER III
METHODS
Participants ................................................................................. 52
Instrumentation ............................................................................ 57
Procedures ................................................................................... 59
Data Analysis .............................................................................. 63
CHAPTER IV
RESULTS
Pre-season .................................................................................. 64
State Sport-Conﬁdence ................................................................... 64

Competitive State Anxiety .............................................................. 69

Pre-Game Competitive State Anxiety ................................................. 7O
Cognitive Anxiety .................................................................... 7O
Somatic Anxiety ...................................................................... 71
Conﬁdence ............................................................................ 74

Pre-Game, Post Season Competitive State Anxiety ................................. 75
Cognitive Anxiety .................................................................... 75
Somatic Anxiety ...................................................................... 78
Conﬁdence ............................................................................ 79

Post Game Competitive State Anxiety ................................................ 8O
Cognitive Anxiety .................................................................... 8O
Somatic Anxiety ...................................................................... 81
Conﬁdence ............................................................................ 83

Performance ............................................................................... 84
On-Base Average ..................................................................... 84
Batting Average ....................................................................... 85
Runs Scored ........................................................................... 86

CHAPTER V

DISCUSSION ............................................................................. 88

APPENDICES ............................................................................ 116

REFERENCES ............................................................................ 140

vi

LIST OF APPENDICES

Appendix A. Demographic Survey ...................................................... 117
Appendix B. State Sport-Conﬁdence Inventory (SSCI) .............................. 120
Appendix C. Competitive State Anxiety Inventory (CSAI-2) ....................... 123
Appendix D. University Committee on Research Involving Human Subjects
(UCRIHS) Approval ...................................................... 125
Appendix E. Psychological Skills Season Schedule ................................... 127
Appendix F. Psychological Tools ........................................................ 131

Appendix G. Post Game, Post Season Means for State Sport-Conﬁdence
Inventory ..................................................................... 139

vii

LIST OF TABLES

TABLE 1. Summary of Test Statistics for Norm Samples by Competitive Level
and Gender ................................................................... 14

TABLE 2. Demographic Information ................................................. 53

TABLE 3. Game by Game Summary of Runs Scored (RS) and Runs Against
(RS) ........................................................................... 54

TABLE 4. Offensive Team Totals for the Experimental and Control
Teams ......................................................................... 56

TABLE 5. District Game Summary for the Experimental and Control
Teams, Score by Inning, Offensive Totals ............................... 57

TABLE 6. Pre-Season Means and Standard Deviations for State Sport-
Conﬁdence Inventory and Competitive State Anxiety Inventory-2... 64

TABLE 7. Post Game Means and Standard Deviations for State Sport-
Conﬁdence Inventory ...................................................... 66

TABLE 8. Post Game, Post Season Means and Standard Deviations for
State Sport-Conﬁdence Inventory ........................................ 69

TABLE 9. Pre-Game Cognitive Anxiety Means and Standard Deviations
for Competitive State Anxiety Inventory-2 .............................. 70

TABLE 10. Pre-Game Somatic Anxiety Means and Standard Deviations
for Competitive State Anxiety Inventory-2 .............................. 72

TABLE 11. Pre-Game Conﬁdence Means and Standard Deviations
for Competitive State Anxiety Inventory-2 .............................. 74

TABLE 12. Pre-Game, Post Season Cognitive Anxiety Means and Standard
Deviations for Competitive State Anxiety Inventory-2 ............... 76

TABLE 13. Pre-Game, Post Season Somatic Anxiety Means and Standard
Deviations for Competitive State Anxiety Inventory-2 ............... 78

TABLE 14. Pre-Game, Post Season Conﬁdence Means and Standard
Deviations for Competitive State Anxiety Inventory-2 ............... 79

viii

TABLE 15. Post Game Cognitive Anxiety Means and Standard Deviations

for Competitive State Anxiety Inventory-2 ............................. 80
TABLE 16. Post Game Somatic Anxiety Means and Standard Deviations

for Competitive State Anxiety Inventory-2 ............................. 81
TABLE 17. Post Game Conﬁdence Means and Standard Deviations

for Competitive State Anxiety Inventory-2 .............................. 83
TABLE 18. Season On-Base Averages and Batting Averages ....................... 86

ix

LIST OF FIGURES

FIGURE 1. Post Game Means for State Sport-Conﬁdence Inventory ................ 67

FIGURE la. Post Game, Post Season Means for State Sport-Conﬁdence
Inventory ....................................................................... 139

FIGURE 2. Pre-Game Somatic Anxiety Means for Competitive State Anxiety
Inventory-2 ..................................................................... 73

FIGURE 3. Pre-Game, Post Season Cognitive Anxiety Means for Competitive
State Anxiety Inventory-2 .................................................... 77

FIGURE 4. Post Game Somatic Anxiety Means for Competitive State Anxiety
Inventory-2 ..................................................................... 82

CHAPTER I
INTRODUCTION

Many coaches will argue that once athletes reach the "automatic" phase of
learning the difference between success and failure becomes “mental.” This mental
aspect of sport performance can be deﬁned in terms of mental or psychological skills. It
is believed that many successful athletes acquire psychological skills through a trial and
error process rather than through formal instruction by coaches. A lack of formal
instruction exists for several reasons. First, many coaches believe psychological skills, to
a certain extent are innate. Second, coaches lack the knowledge to teach these skills
(Martens, 1987). Furthermore, many coaches believe that psychological skills training is
for elite athletes only (Weinberg & Gould, 1999). However, Weinberg and Williams
(2001) state that, "If beginning athletes are taught to set realistic goals, increase self-
conﬁdence, visualize success, and react constructively, we can expect their performance
and personal development to progress faster than the performance and personal
development of athletes who do not receive similar mental training" (p. 349). Also, it
could be argued that the use of psychological skills should result in a greater number of
individuals having more positive experiences in sport. To date, however, very little
research has been done to support these beliefs.

The systematic implementation of techniques and strategies used to teach or
enhance the mental skills that “facilitate performance and a positive approach to sport
competition” are described by the term psychological skills training or PST (Vealey,
1988a). The knowledge base for PST is derived, to a large extent, from research with

elite athletes. Orlick and Partington (1988), for example, found “mental readiness” to be

an extremely important factor inﬂuencing the performance of the most successful
Canadian Olympians at the 1984 Olympic Games. An analysis of data obtained from 235
athletes revealed that the most successful athletes had mental plans, which enabled them
to deal with distractions, overcome adversity and fully focus on the immediate task. In
addition, these athletes set daily goals, practiced positive imagery and were high in self-
conﬁdence. Similarly, Gould, Eklund, and Jackson (1992) found successful athletes, as
compared to less successful athletes, had better concentration, higher self-conﬁdence,
lower anxiety, and more task-oriented thoughts. In order to duplicate the positive
attributes that seem to lead to such success, sport psychologists developed a variety of
psychological intervention techniques.

Researchers have investigated the effects of individual intervention techniques as
well as various combinations of techniques. Greenspan and Feltz (1989) reviewed 19
studies, covering 23 interventions and concluded that, in general, educationally based
psychological interventions with individual athletes are effective in improving
performance. In addition, Vealey (1994) reviewed intervention studies through 1992 and
found 75% of those studies reported improved performance. Furthermore, Weinberg and
Comar (1994) reviewed 45 studies and found 85% of those studies had positive
performance effects. The fact that a greater percentage of more recent research has found
positive performance effects as a result of psychological interventions has been attributed
to a more in-depth, multi-modal, inclusive approach which combines different types of
psychological skills, speciﬁcally, imagery, relaxation, self-talk, and goal-setting, into a
packaged program (Weinberg & Gould, 1999; Weinberg & Williams, 2001). As an

example of such research, Thelwell and Greenless (2001) evaluated an intervention

package that included exactly those speciﬁed skills; goal-setting, relaxation, imagery and
self-talk. The authors concluded that the package was effective for enhancing
performance.

Vealey (1988a), however, suggested that multiple criteria should be focused upon
in evaluation research of PST programs. She argued that although performance is an
important criterion, other behaviors and cognitions should also be evaluated. For
example, several researchers have shown that goal-setting training has been effective in
reducing cognitive anxiety, and increasing perceptions of success and self-conﬁdence
(Burton 1989b, 1983; Miller & McAuley, 1987). Imagery training has shown similar
results (Feltz & Reissinger, 1990). Reduced cognitive anxiety and increased perceptions
of success, intuitively, should result in greater enjoyment of sport experiences. Therefore,
Vealey concluded that “PST should be viewed as important for everyone involved in
sport to help them maximize their abilities as well as their enjoyment and satisfaction
from sport participation” (p. 332). However, more studies are needed across different
skill levels, age groups, and special populations to further assess the beneﬁts of mental
training (Weinberg & Williams, 2001).

In addition, many questions remain as to the implementation of PST. Questions
such as: When should PST be implemented in relation to the competitive season? When
should PST practice take place in relation to physical skills practice? And, how much
time should be spent on PST? Most importantly, however, who should conduct the PST
program, a coach or a sport psychologist? There are beneﬁts and drawbacks to both
strategies. For instance, although a sport psychologist would be idea], it is hardly

practical to afford such a luxury at the youth or high school level! Also, it is less likely

that the sport psychologist would be able to be with the athletes on a day to day basis. On
the other hand, it has been argued that although coaches have daily access to athletes,
athletes may be less likely to discuss problem areas or seek help from the coach in that
the coach decides who plays. And then, of course, there is the issue of knowledge and
experience differences between coaches and sport psychologists in regard to PST. To
date, however, no researcher has evaluated the effects of a PST program that has been
implemented by a coach. The present study is unique in that regard.

Sport psychology researchers agree that there is a need for more studies as many
questions have yet to be answered, however, there are some common understandings.
First, although some athletes are able to learn psychological skills on their own, a PST
program is much more efﬁcient than learning through trial and error (Martens, 1987).
Second, an effective psychological intervention program should be individualized, it
should use a variety of techniques, and it should be implemented systematically over time
(Weinberg & Gould, 1999). Third, psychological skills training is much the same as
physical skills training in that the desired psychological skills have to be practiced
consistently (Martens, 1987; Weinberg & Gould, 1999). Martens (1987) emphasized that
coaches and athletes must have realistic expectations from PST and realize that PST is
not a “quick ﬁx.” It requires hard work equal to that of physical skills training. Finally,
the skills learned in a PST program not only result in better participation in sport, but also
in better participation in any achievement endeavor outside the athletic setting (Martens,
1987; Weinberg & Williams, 2001).

As more research is needed in the area of PST, the purpose of this study was to

investigate the effects of a formal psychological skills training program on the cognitions

and performances of high school softball players as compared to the cognitions and
performances of high school softball players who did not receive a formal psychological
skills training program. This study was signiﬁcant in that it used multiple criterion
measures to assess the effects of PST, with an intact interscholastic fastpitch softball
team, across the entire season. In addition, the effects were compared with a team who
did not receive PST, a team that was also assessed across the season. This comparison
will help determine the signiﬁcance of any differences from the beginning of the season
to the end of the season. F urthermore, the PST program was developed and implemented
by the head coach of the team, a unique factor in PST research. Finally, it was the intent
of this study to help further the understanding of psychological skills in sport so that
coaches can continue to improve on meeting the needs of their athletes. Most
importantly, each athlete should have the opportunity to meet her/his fullest potential
while keeping the "fun" aspect intact.

The psychological skills emphasized in this PST program were goal setting,
relaxation, imagery, and self-talk. These four skills were chosen as they are viewed as
“basic psychological skills” and “fundamental in the sense that they underlie many
others” (Hardy, Jones, & Gould, 1996).

Overall, goal-setting has been shown to lower anxiety (Burton, 1983, 1989b),
increase self-conﬁdence (Burton, 1983; Miller & McAuley, 1987), and improve
performance (Burton, 1983, 1989b; Kyllo & Landers, 1995). Furthermore, signiﬁcant to
this study, goal-setting is a skill where the accuracy of goals has been shown to improve
with practice (Burton, 1983, 1989b).

As with goal-setting, relaxation, by itself and in combination with other skills, has

been shown to positively effect cognitions and performance. Relaxation is a strategy that
has been shown to reduce excessive muscle tension (Jacobson, 193 8), and also, to reduce
cognitive anxiety through attentional redirection (N ideffer, 1985). In addition,
researchers have shown that relaxation has positively effected performance (N ideffer &
Decker, 1970; Owen & Lanning, 1982) and has reduced state anxiety (Kukla, 1976;
Lanning & Hisanaga, 1983). Also, as the perception of arousal is a source of efﬁcacy
information (Feltz, 1982), changing the symptoms of over-arousal through relaxation may
enhance self-conﬁdence.

Imagery also has been shown to be an effective strategy in enhancing cognitions
and performance. Imagery has been related to higher levels of self-conﬁdence (Vadocz,
Hall, & Moritz, 1997), the regulation and control of arousal levels (Feltz & Landers,
1983), and improved performance (Feltz & Riessinger, 1990; VanGyn, Wengner, & Gaul,
1990). However, in a review of psychological interventions, Feltz and Greenspan (1989)
concluded that a combination of relaxation and imagery was superior to relaxation or
imagery alone. The PST program in this study used imagery in conjunction with
relaxation.

Finally, self-talk was found to be related to anxiety (V anRaalte, Brewer, Rivera, &
Petitpas, 1994), self-conﬁdence (Landin & Hebert, 1999), and performance (Ming &
Martin, 1996; Rushall, Hall, Roux, Sasseville, & Rushall, 1988). Negative self-talk can
act as an attentional distracter to decrease performance, and subsequently, increase
anxiety (N ideffer, 1976), whereas positive self-talk can help individuals stay
appropriately focused (Weinberg & Gould, 1999) to enhance performance which in turn

will increase self-conﬁdence (Feltz, 1982). As with goal-setting, relaxation, imagery, and

self-talk are skills that can be learned and improved with practice (Ming & Martin, 1996;
Orlick & Partington, 1988; Williams & Harris, 2001).

Hypotheses

1. There will be no signiﬁcant difference between the control team and the experimental
team at the beginning of the season as measured by the State Sport Conﬁdence Inventory
(SSCI) or as measured by the Competitive State Anxiety Inventory - 2 (CSAI-2).

2. As measured by the SSCI, the experimental team will remain more constant across
selected games in sport-conﬁdence than the control team.

3. As measured by the SSCI, the experimental team will have signiﬁcantly increased
sport-conﬁdence at the conclusion of the season as compared to the control team.

4. The experimental team will have signiﬁcantly higher conﬁdence and lower cognitive
and somatic anxiety than the control team on all pre-game measures of the CSAI-2.

5. The experimental team will remain constant or increase conﬁdence and report lower
cognitive and somatic anxiety at the conclusion of the season signiﬁcantly more than the
control team as measured by the CSAI-2.

6. The experimental team will have signiﬁcantly higher conﬁdence and lower cognitive
and somatic anxiety than the control team on all post-game measures of the CSAI-2.

7. The experimental team will have signiﬁcantly higher on base averages and batting
averages and will score more runs as compared to players on the control team.
Operational Deﬁnitions

1. Psychological skills training program (PST) - a systematic instructional program that
includes training in goal setting, relaxation, imagery, and self-talk.

2. Sport-conﬁdence - the belief or degree of certainty individuals possess about their

ability to be successful in sport (Vealey, 1986). Sport-conﬁdence was measured by the
State Sport Conﬁdence Inventory (SSCI).
3. Cognitive state anxiety - the mental component of anxiety caused by negative
expectations about success or by negative self-evaluation, both of which precipitate
worry, and/or disturbing visual images (Martens, Burton, Vealey, Bump, & Smith, 1990).
Cognitive state anxiety was measured by the CSAI-2.
4. Somatic state anxiety - the physiological and effective elements of the anxiety
experience that develop directly from autonomic arousal (Martens et al., 1990). Somatic
state anxiety was measured by the CSAI-2.
5. Performance - selected offensive game statistics included “on base average,” “batting
average,” and total rims scored.
6. Season - the high school soﬁball season included 6-7 weeks of pre-season and 8-10
weeks in-season (depending on state tournaments and rain days).
Limitations

The psychological skills training program to be evaluated was limited to female
interscholastic fastpitch soﬁball players (15-18 years of age). The measurements of
independent psychological variables were subject to the limitations of paper-pencil tests.
Among these limitations was the honesty and thoughtfulness of the participants in their
responses. Also, performance statistics varied slightly, simply due to the interpretive
differences of each team’s scorekeeper. Although differences in games between teams
were checked for agreement, other differences were not known. The effects of the PST
program may have been inﬂuenced by coaching style and techniques of physical skills

practice as this study is being done with the researcher’s own team. The control team was

an opposing team in the same conference. It was not known what psychological
variables, if any, were practiced, it was only known that there was not a formal
psychological skills training program. Also, the exact difference in ability between the
experimental team and the control team was not known, however. it was assumed to be

similar, as both teams were competitive at the varsity level.

CHAPTER II

REVIEW OF THE LITERATURE

When considering a psychological skills training program and the resultant
effects, there are several factors to be considered. Factors such as arousal, anxiety, self-
conﬁdence, and their relationship to performance must be considered. In addition,
individual psychological skill components and their relationship to arousal/anxiety, self-
conﬁdence, and performance also must be considered. Individual components of this
psychological skills training program (PST) included; goal-setting, imagery, relaxation,
and positive self-talk. Finally, although the effect of a psychological skills training
program as a complete package has received little attention in sport psychology research,
it is important to understand PST package research as it relates to arousal/anxiety, self-

conﬁdence, and performance. This review explored the research in each of these areas.

The Arousal Performance Relationship

9’ 6‘ 99 66'

“Peak performance, optimal performance, in the zone,” are all phrases that
have been used at one time or another to describe a situation where an athlete’s
performance has met or exceeded expectations. How does it happen? How does it NOT
happen? Why do some athletes “come through” in pressure situations? Why do some
athletes come through most of the time but not all of the time and why do other athletes
rarely come through? Possible explanations for this phenomenon could lie in the
literature on the arousal performance relationship. Several theories involving the arousal

performance relationship were included in this review. First however, it is important to

understand theoretical constructs of the arousal performance relationship.

10

Arousal is a motivational construct that describes the intensity level of behavior.
Arousal varies along a continuum from deep sleep to high excitement. The higher levels
of arousal, often referred to as anxiety, are those levels that produce feelings of
discomfort and/or excessive concern and have been described as “...feelings of distress”
(Lazarus & Averill, 1972), or “feelings of nervousness and tension” (Gould, Greenleaf, &
Krane, 2002). Responses to anxiety can be divided into three separate yet interacting
categories: cognitive, physiological, and behavioral (Brokovec, 1976).

Cognitive responses include worry, or apprehension, negative concerns about
performance, and an inability to concentrate. Physiological responses include increased
heart rate, increased muscle tension, shaking, sweating, and “butterflies.” Behavioral
responses may appear in the form of restlessness, performance decrements, and changes
in communication patterns. Each response category is separate but interacting in that a
response in one category may inﬂuence responses in other categories, yet, each may be
separately inﬂuenced by different environmental conditions. Also, responses to anxiety
differ among individuals. Thus, anxiety is viewed as a complex, multifaceted construct

(Landers, 1980).

In addition, anxiety in sport is differentiated in terms of competitive trait anxiety
and competitive state anxiety (Martens, 1977). According to Martens, competitive trait
anxiety is a personality disposition acquired through experience, and is the tendency to
perceive competitive situations as threatening (or dangerous) and to respond to these
situations with feelings of apprehension and tension. On the other hand, competitive state
anxiety, or A-State, are situation speciﬁc feelings of apprehension and tension that may

change with time, feelings that are experienced at a particular moment.

11

Furthermore, competitive state anxiety is multidimensional in nature in that it has
two subcomponents, cognitive anxiety and somatic anxiety. The multidimensional nature
of competitive state anxiety has been continually supported through research (Burton,
1988; Caruso, Dzewaltowski, Gill, McEIroy, 1990; Krane & Williams, 1987). It has also
been theorized that cognitive and somatic anxiety change differently prior to and during
performance evaluation (Gould, Petlichkoff, & Weinberg, 1984; Karteroliotis & Gill,
1987). In addition, cognitive and/or somatic responses to perceived threatening situations
vary among individuals and situations (Krane & Williams, 1987). The complex,
multidimensional nature of anxiety, in addition to the tendency of individuals to respond
to anxiety differently, suggests that it is imperative to begin to understand each athlete

and her/his response to various situations when designing a PST program.

Measurement of Competitive Anxiety. To further understand the complex
constructs of competitive anxiety, Martens (1977) argued a need for sport speciﬁc
measures. Theoretical advances of anxiety as a multidimensional construct lead to the
development and validation of the CSAI-2. As stated in Martens, Vealey, and Burton
(1990), the value in measuring cognitive and somatic A-state separately is based on the
conceptual arguments and empirical evidence that these two anxiety components are
elicited by different antecedents and that they inﬂuence behavior differently. The C SAI-2
separately measures the cognitive and somatic components of state anxiety. However,
factor analysis of the initial scale unexpectedly revealed a third component, self-
conﬁdence. Therefore, in the 27 item CSAI-2, the 9 negatively worded items comprise
the cognitive anxiety subscale and the 9 positively worded items, originally assumed to

form a part of the cognitive anxiety subscale, comprise the self-conﬁdence subscale. The

12

remaining 9 items comprise the somatic anxiety subscale which represents perceived

autonomic reactions versus actual physiological reactions (See Appendix C).

Reliability for the CSAI-2 was estimated by examining the internal consistency of
the scale. Alpha coefﬁcients for the cognitive subscale ranged from .79 to .83, for the
somatic subscale from .82 to .83, and for the self-conﬁdence subscale from .88 to .89.
The authors concluded that this demonstrates “a sufﬁciently high degree of internal
consistency for each of the CSAI-2 subscales” (Martens et al., 1990). The authors also
found evidence to “ﬁrmly support” concurrent validity, and through a “systematic
progression of research studies,” found evidence to support construct validity. In
addition, the many research studies by Martens and his colleagues have provided
normative data for each of the three subscales. Norms by competitive level and gender
are reported in Table 1. To date, the CSAI-2 remains the most commonly used

multidimensional anxiety measure (Gould et al., 2002).

So far, discussion has included constructs of anxiety, and a means by which these
constructs are measured. The question remains, what is the relation of all of this to
performance? The following section is a review of the arousal performance relationship

theory.

Inverted-U Hypothesis. The inverted-U hypothesis is a theory that has greatly
assisted in the understanding of the arousal performance relationship. Also known as the
Yerkes- Dodson Law (1908), it attempted to explain physiological responses to anxiety.
The Inverted-U hypothesis proposes that as an individuals’ arousal increases along a

continuum from drowsiness to alertness there is a progressive increase in performance,

13

Table 1

Summary of Test Statistics for Norm Samples by Competitive Level and Gender
(Martens et al., 1990)

 

 

 

CSAI-cog C SAI-som CSAI-sc
Sample N M SD M SD M SD
High School
Male 284 18.48 5.35 17.70 5.53 24.73 5.52
Female 309 21.61 6.47 18.92 5.97 22.50 5.51
College
Male 158 17.88 4.84 17.68 4.86 25.37 5.15
Female 220 18.40 5.99 16.85 4.94 24.67 5.90
Elite
Male 161 19.29 4.80 16.29 4.65 26.21 4.81
Female 102 20.1 1 5.42 17.98 5.20 24.56 5.33

 

when arousal increases beyond alertness to high excitement there is a progressive
decrease in performance. Thus, there is a curvilinear relationship between the intensity of
arousal and the effectiveness of performance. This curvilinear relationship infers an

“optimal” level of arousal for “optimal performance.”

However, there are mediating factors that exist in this arousal performance
relationship. First, there is the effect of an individual’s trait and state anxiety levels.
Each individual’s optimal level of arousal may be different and each situational peak may
be different. From a practical perspective, this could be problematic in knowing if an
individual’s arousal level is too high or too low at any given time in any given situation.
Second, the task complexity may alter this optimal peak. Oxendine (1970) suggests that

high levels of arousal are best for optimal performance in speed, endurance, and strength

14

tasks and at the other end of a continuum of sport skills, low arousal is best for Optimal

performance in activities requiring ﬁne muscle control and cognitive judgment.

Early research generally has supported the inverted-U hypothesis for explaining
physiological arousal and its relation to performance (Fenz & Epstein, 1967; Gould.
Petlichkoff, & Weinberg, 1987; Martens & Landers, 1970). However, the hypothesis has
come under some criticism, especially in that it fails to recognize the multidimensional
nature of arousal. The inverted-U does not explain the role of cognitive anxiety. Out of
dissatisfaction with the inverted-U hypothesis and other related anxiety theories, Hardy
and Fazey (1987, cited in Hardy, 1996) proposed the cusp catastrophe model of anxiety

and performance.

Cusp Catastrophe Model of Anxiety and Performance. Similar to the inverted-U
hypothesis, the cusp catastrophe model predicts that an increase in arousal will facilitate
performance up to an optimal level. However, the catastrophe model differs from the
inverted-U hypothesis in that it predicts a dramatic decrease (rather than a progressive
decrease) in performance when the athlete goes beyond that optimal level; a “catastrophe”
from which it is difﬁcult to recover, even to a moderate level of performance. The cusp
catastrophe model also differs from the inverted-U hypothesis in that it attempts to
describe the interactive effects of cognitive anxiety and physiological arousal on

performance.

The cusp catastrophe model is a three dimensional model that includes cognitive
anxiety and physiological arousal as independent variables and performance as a

dependent variable. In essence, it predicts that performance is associated with increases

15

in physiological arousal, however, the effects are moderated by cognitive anxiety. There
are three important predictions of performance based on the interaction of cognitive

anxiety and physiological arousal.

The ﬁrst of these predictions is that high cognitive anxiety will lead to enhanced
performance when physiological arousal is low but to impaired performance when
physiological arousal is high. Second, cognitive anxiety will not always impair
performance; it can sometimes enhance performance. However, under conditions of high
cognitive anxiety, “the model predicts that performers’ best performances should be
signiﬁcantly better, and their worst performances should be signiﬁcantly worse” (Hardy,

1996, p. 148). And third, under conditions of high cognitive anxiety, “hystersis” occurs.

Hystersis is explained by the prediction that with high cognitive anxiety, the
graph of performance in relation to physiological arousal will be different depending on
whether physiological arousal is increasing or decreasing. More precisely, with high
cognitive anxiety, performance drops at a higher level of physiological arousal when
physiological arousal is increasing. Yet, when physiological arousal is decreasing, the
level of physiological arousal must be lower for performance to return. Hystersis is not
predicted to occur under conditions of low cognitive anxiety. Under conditions of low
cognitive anxiety, physiological arousal should have relatively small effects on

performance and reﬂect a normal inverted-U distribution.

Research support for the model at this point, although generally supportive, is
limited (Hardy, Jones, & Gould, 1996) as the complexity of the model makes it difficult

to test (Weinberg & Gould 1999). Furthermore, the studies that have been done have

16

been criticized for inappropriate statistical tests and for the way researchers manipulated
arousal (Landers & Arent, 2001). However, the cusp catastrophe model has some

important implications for PST.

First, the cusp catastrophe model is unique in that it predicts that cognitive
anxiety can sometimes be facilitative. Researchers have indeed found that cognitive
anxiety can have both facilitative and debilitative effects. For example, Jones and Swain
(1995) found no difference in the intensity of cognitive anxiety symptoms between elite
and nonelite cricket players. However, the elite performers interpreted cognitive anxiety
states as being more facilitative to performance than the nonelite performers. Also, in the
nonelite group, cricketers who reported their anxiety as debilitative had higher cognitive
anxiety levels than those who reported anxiety as facilitative. Overall, the key for the
debilitative versus facilitative effect of cognitive anxiety appears to be the level of
physiological arousal plus the interpretation of anxiety. Cognitive anxiety is more likely
to be facilitative when physiological arousal is low and athletes interpret their symptoms
as being beneﬁcial to performance. This ﬁrst prediction of the model suggests that
relaxation plus positive self-talk would be important components of an effective PST
program.

Second, the model predicts that if physiological arousal becomes too high, a
cognitively anxious athlete will experience a sudden and dramatic drop in performance,
thus, illustrating the ﬁne line between optimal performance and disaster. Furthermore,

once this drop occurs, it will take a great reduction in physiological arousal to regain

previous performance levels. Hardy (1996) suggests that following a catastrophe,

l7

recovery may be more quickly achieved if both cognitive anxiety and physiological
arousal are simultaneously reduced. The need for a simultaneous reduction would lend
itself to multi-modal stress management strategies. In fact, Hardy recommends the
athlete physically relax, cognitively restructure, then, once the previous performance level
is regained, initiate a controlled reactivation. Being skilled in relaxation, positive self-
talk, imagery, and even goal-setting would allow the athlete to accomplish these

strategies.

To further add to the complexity of the catastrophe model, self-conﬁdence also
appears to play a role. As opposed to conventional theory where anxiety and self-
conﬁdence are viewed as at opposite ends of a continuum (Martens et al., 1990),
researchers of the catastrophe model suggest that cognitive anxiety and self-conﬁdence
can be experienced at the same time. They also suggest that self-conﬁdence will increase
the probability that athletes experiencing cognitive anxiety can tolerate higher levels of
physiological arousal before experiencing a decrease in performance. Furthermore, it has
been suggested that “self-conﬁdence may be one of the most powerful qualities that elite
performers possess, certainly more powerful than anxiety or arousal management skills”
(Hardy, Jones & Gould, 1996). Therefore, it is also important to understand self-
conﬁdence as it relates to performance.

Self-Conﬁdence

As with competitive anxiety, self-conﬁdence is a complex multifaceted construct
with several theories that relate it to motivation and performance. Bandura (1977, 1986)
proposed a situation-speciﬁc concept of self-conﬁdence in his theory of “self-efﬁcacy.”

Vealey (1986, 1988) theorized a sport-speciﬁc concept of self-conﬁdence she termed

18

“sport-conﬁdence.” This section is a review both of these theories as they relate to each
other and to performance.

Self-Eﬂicacy Theory. Self-efﬁcacy as deﬁned by Bandura (1977) is the belief or
strength of conviction that one can successfully execute a behavior, carry out a task or
produce a desired outcome given one’s capabilities. In other words, self-efficacy is an
individual’s perception of performance potential given one’s skills. Self-efﬁcacy differs
from self-conﬁdence in that it is a situationally speciﬁc form of self-conﬁdence. Self-
conﬁdence is typically viewed as a more global belief and is usually treated as a
personality trait whereas self-efficacy is speciﬁc to a particular situation. According to
self-efﬁcacy theory, given the appropriate skills and adequate incentives, an individual’s
efficacy expectations will not only determine the choice of activities attempted, but the
amount of effort expended toward the activity, and the persistence with which to
complete the activity. In essence, self-efﬁcacy will predict performance.

Self-efﬁcacy theory continues on the basis of three dimensions of efﬁcacy
cognitions or expectations: level, strength, and generality. The level of self-efﬁcacy
refers to the individual’s expected performance attainment and the number of tasks that
can be performed where strength refers to the certainty with which an individual expects
to successfully attain each level. Finally, generality refers to the number of domains one
considers self-efﬁcacious, or the ability of efficacy expectations to predict behavior in
related tasks that require parallel skills. Also in the self-efficacy formula, are four
principle sources of information that inﬂuence efﬁcacy expectations: performance

accomplishments, vicarious experience, verbal persuasion, and physiological arousal.

l9

Performance accomplishment is an especially powerful source of information
because it is based on personal experiences of success. However, just as previous
successes will increase perceptions of abilities, previous failures will decrease perceptions
of abilities. Performance accomplishments that are achieved on difﬁcult tasks, tasks
independently attempted, and tasks attempted early in learning with only occasional
failures carry greater efﬁcacy value than easy tasks, tasks accomplished with external
aids, or tasks in which repeated failures are experienced early in the learning process
(F eltz, 1984). Also, there is a predicted reciprocal relationship between performance
accomplishments and self-efﬁcacy. Previous experiences inﬂuence efﬁcacy expectations
and efﬁcacy expectations inﬂuence future performances. Therefore, if previous
experiences are perceived to be successful, efﬁcacy expectations are increased and future
performances are also likely to be successful, which will then further increase efﬁcacy
expectations. Thus, performance exposure which leads to success is the best method for
instilling self-efﬁcacy (Carton, 1984).

Although generally weaker, vicarious experience is also a source of efficacy
information. The observation of another individual performing a threatening or difﬁcult
task can contribute to the expectation of success. Research shows vicarious experience
most often occurs through modeling in which the model is live or ﬁlmed (Feltz, 1988;
Gould & Weiss, 1981), or symbolic in the form of imagery (Feltz & Riessigner, 1990).
Modeling is generally most effective when: 1) the observer has little or no experience
with the task, 2) the observer has perceived similarities with the model, 3) multiple
models are observed being successful with a task, 4) the models are seen overcoming

obstacles, and/or 5) there is a clear outcome to the performance (i.e., not just the pitch but

20

where it was caught in relation to the target). However, just as observing successful
performances may increase efficacy expectations, observing unsuccessful performances
may lower expectations (Bandura, 1986).

Verbal persuasion, also less powerful than performance accomplishments,
includes persuasion by signiﬁcant or nonsigniﬁcant others, persuasion by the performer in
the form of self-talk, and/or persuasion by performance deception (convincing the
individual that the task is easier that it looks). Gould, Hodge, Peterson, and Giannini
(1989) showed that elite wrestling coaches ranked verbal persuasion 7th of 13 effective
strategies used to enhance self-efficacy in athletes. In the same study, coaches ranked the
use of positive self-talk, a form of verbal persuasion, 2nd (of 13), as they felt it was a
“very effective strategy.” Also important, the effectiveness of persuasion is inﬂuenced by
the perceived credibility and trustworthiness of the persuader, and is only effective when
the persuasive feedback is realistic. It should be noted, however, that the increase in
efficacy expectations through persuasion would be temporary if the subsequent effort
results in poor performance.

Finally, physiological arousal affects behavior through cognitive evaluation. An
individual appraises the information conveyed by arousal and then makes judgments
about her/his ability to perform. If an individual interprets the symptoms as anxiety or
fear and the symptoms are perceived to be debilitative, performance will not be
successful. Likewise, if the symptoms are interpreted as “readiness” to perform and are
perceived to be facilitative, performance will be successful. The cognitive interpretation
of arousal is an important key in determining efficacy expectations and, ultimately,

performance. In support of this prediction, F eltz and Mungo (1983) found perceived

21

physiological arousal to be a stronger predictor of self-efﬁcacy than actual arousal.
However, it was not found to be a predictor of performance.

Research by Feltz and Riessinger (1990) supported these four sources of self-
efﬁcacy as proposed by Bandura. Using a questionnaire, they categorized subject
responses according to the four principal informational sources of self-efﬁcacy. As
predicted, performance accomplishments were shown to be the most signiﬁcant source of
conﬁdence with 86% of the responses, physiological arousal followed with 9%, verbal
persuasion with 8%, and ﬁnally, vicarious experience with 2% of the responses.

In addition to the components of Bandura’s theory, proper incentives and
necessary skills must be present for self-efﬁcacy to be a major determinant of behavior.
If an individual has the necessary skill and high self-efficacy but no incentive to perform,
efﬁcacy expectations will exceed actual performance. Also, causal attributions are
signiﬁcant in the relationship between self-efficacy and performance. Successes are more
likely to enhance self-efﬁcacy if performances are perceived as resulting from ability
rather than ﬁom luck. Conversely, individuals can talk themselves out of succeeding by
attributing failure to inherent ability rather than bad luck or reduced effort (Feltz, 1984).

Testing Bandura ’s Theory. Research by Feltz (1982), with female college
students attempting a modiﬁed back dive, found self-efficacy to be a major predictor of
performance just as Bandura’s theory hypothesizes. However, self-efficacy was
determined to be a major predictor of performance on the ﬁrst trial only. After the ﬁrst
trial, performance on the previous trial was the major predictor on the next trial. As a
result, Feltz suggested that the reciprocal relationship between performance and self-

efﬁcacy as proposed by Bandura, is not equal, as performance was found to be a stronger

22

inﬂuence on self-efﬁcacy than self-efﬁcacy on performance. Feltz then proposed a
respeciﬁed model to predict that both previous performance and self-efficacy would
directly inﬂuence “approach/avoidance” performance on the back dive. Physiological
arousal, although “neither a predictor nor an effect of self-efﬁcacy,” would be an
additional inﬂuence on the initial trial.

Feltz and Mungo (1983) replicated this 1982 study to test the respeciﬁed model
and found similar results. However, this study found that the perception of arousal was a
stronger source of initial self-efﬁcacy than past related experience but was not as strong
as previous performance in predicting subsequent self-efﬁcacy. Feltz (I988) looked at
gender differences and found the respeciﬁed model to ﬁt the data better for females than
for males. Also, females showed a reciprocal relationship between self-efficacy and
performance, yet males showed a reciprocal relationship between autonomic perception
and heart rate. Previous performance and self-efficacy were found to be strong predictors
of subsequent performance for both females and males. Results that were consistent over
the three aforementioned studies are 1) the reciprocal relation between self-efﬁcacy and
performance, 2) that performance more strongly inﬂuenced self-efﬁcacy than self-efﬁcacy
inﬂuenced performance, and 3) the ﬁrst trial performance was the strongest predictor of
subsequent performances.

George (1994) looked at testing Bandura’s theory in an actual sport setting.
Subjects were 53 male intercollegiate baseball players who completed self-report
measures over a 9 game period during the baseball season. Results provided support for
the reciprocal relationship between self-efficacy and performance and in agreement with

Feltz (1982, 1988) and Feltz and Mungo (1983), in that the relationship existed but was

23

not equal. Past performance was a stronger and more consistent inﬂuence on self-
effrcacy than self-efficacy on performance. In addition, moderate support was found for
the prediction that self-efficacy is a determinant of effort. This ﬁnding is important in
that it “addresses Bandura’s (1977) assertion that self-efﬁcacy inﬂuences effort, and other
motivational behaviors such as choice of activities and persistence” (p. 395).

Bandura’s theory, however, has been criticized in that it suggests that self-efficacy
is a cause of performance, rather self-efficacy has been found to be an effect of
performance. Also, although “found to be an important and necessary cognitive
mechanism in explaining motor behavior,” research ﬁndings show the theory model may
be too simplistic to account for all behavioral change in motor performance (Feltz, 1984).
In addition, self-efﬁcacy studies rely on self-report measures that have been
operationalized in many different ways for every different situation studied. An attempt
to “parsirnoniously operationalize self-efﬁcacy in sport situations has proved low in
predictive validity” (V ealey, 1986, p. 222). For this reason, Vealey (1986) offered a
sport-speciﬁc conceptualization and measurement instrumentation in the name of sport-
conﬁdence.

Sport-Conﬁdence. Sport-conﬁdence as theorized by Vealey (1986), is a more
general conceptualization of self-conﬁdence than self-efﬁcacy. Self-efficacy is situation
speciﬁc, dealing with individual skills within the same sport and/or within a speciﬁc
competition (i.e., an individual’s self-efficacy may be greater for pitching than for hitting
within a particular game of softball). In contrast, sport-conﬁdence is more global dealing
with overall performance expectancies in sport and/or speciﬁc competitions. Drawing

from the literature on self-efficacy, perceived competence, and performance expectancy,

24

Vealey proposed a model of sport-conﬁdence where sport-conﬁdence is deﬁned as "the
belief or degree of certainty individuals possess about their ability to be successful in
sport” (p. 222). Within the model, sport-conﬁdence is separated into two constructs, trait
sport-conﬁdence (SC-trait) and state sport-conﬁdence (SC-state). SC-trait is a disposition
construct deﬁned as “the belief or degree of certainty individuals usually possess about
their ability to be successful in sport.” SC-state, on the other hand, is a “right now”
construct deﬁned as “the belief or degree of certainty individuals possess at one
particular moment about their ability to be successful in sport” (p. 223).

As the perception of success is critical to the deﬁnitions of sport-conﬁdence, a
third construct of competitive orientation is included in the sport-conﬁdence model.
Based on the work of Maher and Nicholls (1980) that success means different things to
different people, competitive orientation “was established to indicate a tendency for
individuals to strive toward achieving a certain type of goal in sport” (p. 222). Because
sport-conﬁdence is based on perceptions of ability, Vealey proposes that competitive
orientation “should reﬂect an athlete’s belief that attainment of a certain type of goal
demonstrates competence and success” (p. 222). Therefore, competitive orientation is
based on two distinct types of goals: performance goals (i.e., performing well), and
outcome goals (i.e., winning). It is theorized that although an individual usually strives to
perform well and to win, the achievement of one goal may be a more important indicator
of competence and success to the individual than the achievement of the other goal. It is
further theorized that through successive sport experiences, individuals may become
performance oriented or outcome oriented. Hardy, Jones, and Gould (1996) noted that

Vealey’s distinction between performance orientation and outcome orientation appears to

25

be similar to Nicholl’s (1980) earlier distinction between task orientation and ego
orientation.

The sport-conﬁdence model is an interactional model that takes into account an
individual’s competitive orientation and sport-conﬁdence level and, thus, attempts to
explain and predict behavior. Speciﬁcally, it proposes that SC-trait and competitive
orientation interact with an objective sport situation to produce SC-state. SC-state is
“predicted to be the most important mediator of behavior as it is based on the mutual
inﬂuence of situational factors and individual differences” (Vealey, 1986, p. 224). The
perception of behavioral responses then leads to subjective outcomes.

The subjective outcomes construct includes causal attributions, perceptions of
success, and performance satisfaction, and is theorized to have a reciprocal relationship
between sport-conﬁdence, competitive orientation, and behavior. In other words, sport-
conﬁdence (trait and state) and competitive orientation (performance or outcome) both
inﬂuence, and are inﬂuenced by subjective outcomes. Therefore, the model predicts that
positive subjective outcomes are likely to enhance sport-conﬁdence and, in turn, should
increase an individual’s degree of certainty that they can be successful in sport. Also,
negative subjective outcomes are likely to undermine sport-conﬁdence and, in turn, make
an individual uncertain that they can be successful in sport. Reciprocally, individual
differences in SC-trait and competitive orientation interact to inﬂuence perceptions of
behavior that result in positive or negative subjective outcomes. For example, low SC -
trait individuals may blame their failure on lack of ability even if other factors may have

contributed to the negative outcome. Outcome oriented individuals may perceive

26

themselves as successful only if they win, (even if they perform well) regardless of their
actual performance (Vealey, 1986).

Measurement of Sport-Conﬁdence. As stated earlier, the conceptualization of
sport-conﬁdence was motivated, in part, by a need for a much more parsimonious
operationalization of self-conﬁdence that would be able to predict behavior across a wide
range of sport situations. Vealey’s sport-conﬁdence model indicated a need for the
development of three instruments, one to measure trait sport-conﬁdence, one to measure
state sport-conﬁdence, and another to measure competitive orientation. Efforts to do so
resulted in the Trait Sport-Conﬁdence Inventory (TSCI), the State Sport-Conﬁdence
Inventory (SSCI), and the Competitive Orientation Inventory (COI). Instrument
reﬁnement and reliability/validity were determined over the course of ﬁve phases within
the study. For the purposes of this review, the SSCI will be the primary focus.

The initial version of the SSCI consisted of 19 items and used a 5-point likert
scale that ranged ﬁom “extremely conﬁdent” to “not at all conﬁdent.” Following phase 1
of the study, it was determined that the SSCI should be reﬁned by reducing the number of
items for the instrument to 13. Also, the scale was changed to a 9-point likert scale to

,9 ‘6

“provide a broader range” and the labels of the scale were changed to “high, medium,”
and “low” because they seemed “less reactive.” In addition, a comparison to “the most
conﬁdent athlete” known was added to anchor the top of the scale at a level which would
be perceived to be very high. The purpose of the second phase of the study was to
replicate the ﬁrst phase using the modiﬁed version of the SSCI. All items of the SSCI

were retained following phase 2.

27

Concurrent validity, or the effectiveness of a test to predict responses to related
constructs, was determined in phase 4 as results showed all correlations to be signiﬁcant
in the predicted direction. Of particular interest, SC-trait was found to be an “effective
predictor” of SC-state as measured by the SSCI as well as the CSAI-2. And, SC-state
was found to be positively related to SC-trait and SC-state as measured by the CSAI-2.
Also, a negative relationship was found between both SC-trait and SC-state, and
cognitive and somatic competitive state anxiety (as suggested by Martens et al., 1990). In
addition, COI-performance showed a signiﬁcant positive relationship with SC-state as
measured by the SSCI, and COI-outcome showed a signiﬁcant negative relationship with
SC-state as measured by the SSCI. According to Vealey, this suggests that “focusing on
performing well is related to higher levels of SC-state, and focusing on winning and
losing is related to lower levels of SC-state” (p. 230).

In phase 5, the validation process of the SSCI, SC-state was hypothesized to be a
signiﬁcant predictor of performance. To test this hypothesis, 48 elite gymnasts were
administered the SSCI “1 1/2 hours prior” to a national meet and again “no later than 2
hours after the ﬁrst round of competition.” No signiﬁcant correlation between
performance and precompetitive SC-state was found. However, performance was
signiﬁcantly correlated with postcompetitive SC-state. These results support F eltz’s
(1982) ﬁnding that performance more strongly predicts self-conﬁdence than self-
conﬁdence predicts performance and suggest that athletes quickly internalize feelings of
competence and success based on their performance.

Also of interest, results ﬁom the testing of other related hypotheses were found to

have signiﬁcant correlations between SC-trait and postcompetitive SC-state and,

28

 

postcompetitive SC-state was found to be positively related to performance orientation
and negatively related to outcome orientation. Vealey believes the key ﬁnding of the
study was that high SC-trait perforrnance-oriented athletes were signiﬁcantly higher in
SC-state than all other groups suggesting “that the interaction of athletes’ individual
deﬁnitions of success with perception of their ability is related to their self-conﬁdence
when competing.” Although additional research is needed to support these ﬁndings,
evidence was accumulated for the SSCI as a valid operationalization of the construct of
SC-state within the conceptual model (Vealey, 1988b).

Self-efﬁcacy and sport-conﬁdence theory provide several important implications
in relation to PST. First, in that performance more strongly predicts self-conﬁdence than
self-conﬁdence predicts performance, performance that leads to success is essential. In
addition, the signiﬁcance of performance success, combined with Vealey’s (1986) ﬁnding
that a focus on performing well is related to higher state sport-conﬁdence, implicates
goal-setting as an effective strategy for enhancing self-conﬁdence. Second, the self-
efﬁcacy information sources of vicarious experience and verbal persuasion suggest that
imagery and self-talk, respectively, may also be key strategies in enhancing self-
conﬁdence. Finally, the importance of the cognitive interpretation of physiological
arousal suggests that relaxation skills would be valuable if arousal is perceived to be too
high. Furthermore, a perception of arousal symptoms as facilitative may be more likely
with training in positive self-talk.

In conclusion, if PST in goal-setting, relaxation, imagery, and positive self-talk
can reduce the negative effects of anxiety and enhance the positive, “powerful” quality of

self-conﬁdence, then, not only will performance improve. but overall, the sport

29

experience will be more enjoyable. Therefore, it is important to further understand the
components of this PST program.
Psychological Skills Components

As previously reviewed, research indicates that both anxiety and self-conﬁdence
have an effect on sport performance. Some view anxiety and self-conﬁdence as “opposite
ends of a cognitive evaluation continuum,” and suggested that cognitive state anxiety is
the “lack of state self-conﬁdence,” or conversely, state self-conﬁdence is the “absence of
cognitive state anxiety” (Martens et al., 1990). Others view anxiety and self-conﬁdence
as orthogonal in that it is possible to experience both simultaneously (Hardy, 1996).
Nonetheless, the psychological skills for the reduction of the negative effects of anxiety
and the psychological skills for the enhancement of the positive effects of self-conﬁdence
are similar. For instance, in their chapter on “Stress Management Strategies, ” Hardy,
Jones, and Gould (1996) stated that “a number of psychological skills have been
implicated by the literature... However, it has been argued...that at least four of these are
fundamental in the sense that they appear to underlie many others; these four are goal-
setting, imagery, relaxation, and self-talk” (p. 162). At the same time, in their chapter on
“Strategies for Enhancing Self-Confidence, ” the same authors included goal-setting,
imagery, self-talk and “some form of relaxation technique” (p. 64). These four skills
were also the main focus of the psychological skills training in the present study and are
therefore, the main focus of this review, beginning with goal-setting.
Goal-Setting

One explanation for the effect of anxiety on performance is that it acts to disrupt

attention or concentration. Goal-setting is a strategy that is believed to reduce the effects

30

of anxiety through attentional redirection. If individuals are focused on goals to be
accomplished, they are less likely to be distracted by the “pressure” of the situation.
Locke and Lathum (1985) suggest “at least two ways” for goal setting to facilitate
performance under pressure; “ﬁrst, setting goals in practice develops one’s powers of
concentration” in that practice is “always sharply focused,” and “second, trying to achieve
a goal in practice entails tension,” after repeated experiences with tension, the individual
learns to “deal with it effectively” (p. 215). At the same time, goal-setting can increase
self-conﬁdence. In relation to self-efficacy theory, as performance accomplishments are a
principle source of efﬁcacy information, the accomplishment of attainable goals is likely
to enhance perceptions of self-efficacy. F urtherrnore, goal-setting provides an incentive
for individuals to persist in their efforts until performance matches their internal standards
(Feltz, 1984). Thus, goal-setting is viewed as a valuable strategy for the enhancement of
cognitions and performance.

A goal is deﬁned as an objective, a standard, an aim of some action, or level of
performance proﬁciency (Weinberg & Gould, 1999). Goals can be subjective (i.e.,
having fun, trying hard), or they can be objective. Objective goals can be general, (i.e.,
improve offensive skills) or they can be speciﬁc (i.e., improve ability to hit an outside
“strike” to the opposite ﬁeld). Goals can be long term (i.e., by the end of the season) or
they can be short term (i.e., by the end of practice). Types of goals include, outcome
goals, performance goals, and process goals (Gould, 2001). Outcome goals generally
focus on winning or doing better than an opponent, where performance goals focus on
improvements relative to one’s own past performance or, the achievement of performance

objectives independent of opponents. Process goals focus on the execution of actions

31

necessary to perform well.

Not all types of goals however, are believed to be equally effective. Goal-setting
researchers in the motor performance arena typically have examined the relationship
between types of goals and subsequent effects on cognitions and/or performance (Burton,
1983; Hall & Byme, 1988; Miller & McAuley, 1987; Weinberg, Bruya, Garland, &
Jackson, 1990). In a meta-analysis of 36 independent studies, Kyllo and Landers (1995)
concluded, that overall, goal-setting improves performance in sport. Furthermore,
performance improvement is greatest when moderate goals are set as opposed to goals
that are too easy or too difﬁcult. The authors also found that the trends of analysis
suggest that “goal-setting may be improved by specifying goals in absolute terms,” by
setting “short term” as well as “long term goals,” and by “allowing individuals to
participate in setting goals” (p. 131).

Burton (1989a) evaluated the impact of “goal speciﬁcity and task complexity” on
basketball skill development with undergraduate students. Results based on data from 20
subjects on six different basketball skills found subjects who set speciﬁc goals
signiﬁcantly out performed subjects who set general goals on two of the six skills while a
third skill approached signiﬁcance. Also, subjects who set speciﬁc goals performed
signiﬁcantly better than subjects who set general goals on low but not on high complexity
tasks. The author cited several limitations such as the sample size, the ambiguity of task
complexity, and failure to assess whether subjects who set general goals spontaneously
set more speciﬁc goals. However, he concluded that the results support previous research
that has demonstrated that “task complexity moderates goal effects” and that “goal effects

have greater latency for complex than for simple tasks.”

32

 

 

In relation to performance versus outcome goals, Burton (1983, 1989b) found
performance goals to be more effective than outcome goals. In addition, research by
Vealey (1986) showed evidence to suggest that “focusing on performing well is related to
higher levels of SC-State (state sport-conﬁdence) and focusing on winning and losing is
related to lower levels of SC-State” (p. 230). Also, Vealey (1988a) found that elite
athletes were more performance oriented than college and high school athletes. Relating
to this ﬁnding, quantitative research by Orlick and Partington (1988) with Olympic (elite)
athletes found that “the best athletes had clear daily (performance/process) goals.” It is
theorized that performance goals are more effective than outcome goals because they are
based on aspects of competition that athletes can control even if other, uncontrollable
circumstances do not allow them to win. Also, the “ﬂexibility of performance goals
allows athletes of all ability levels to raise or lower goals to keep them both challenging
and realistic, ensuring both high motivation and consistent success” (Burton, 1989b, p.
107). Process goals are believed to be effective through the direction of attention to task-
relevant cues (Gould, 2001). Recent research by Filby, Maynard, and Graydon (1999),
however, showed that groups using multiple goal strategies (performance, process, and
outcome goals) performed best. The authors suggest that outcome goals are most
beneﬁcial when combined with a “process orientation.”

Researchers have also focused on the effects of goal-setting training. Burton
(1983), for example, investigated a goal-setting training program with a collegiate men’s
and women’s swim team. The purpose of his study was to determine if a goal setting
training program would effectively teach athletes to set appropriate goals and if those

athletes who set effective performance goals would have signiﬁcantly better cognitions

33

and performance than those who adopt outcome goals. Results for the female swimmers
(as they more relate to this study), showed signiﬁcant differences between the goal-setting
training (GST) swimmers and the non-GST swimmers on expectancy accuracy (a goal-
setting component), cognitive anxiety, and performance improvement. Results also
showed a trend toward higher levels of self-conﬁdence though there was no signiﬁcant
difference at the time of the post-tests. Other hypotheses proved to be non-testable due to
lack of cooperation from the control group.

Burton (1989b) again looked at the impact of a goal-setting training program on
“perceived ability, competitive cognitions, and performance” of collegiate swimmers.
Also, he predicted that the accuracy of the goals of the GST swimmers would increase
with training and practice. Goal-setting training involved teaching subjects to set speciﬁc
rather than general goals, short-term rather than long-term goals and individual rather
than team goals. Burton reported results for the female swimmers that supported three of
four hypotheses in that “ GST swimmers had more accurate expectancies, lower cognitive
anxiety, and greater performance improvement than non-GST swimmers.” And, although
not statistically signiﬁcant, there was a “strong tren ” for support of the fourth hypothesis
of self-conﬁdence. Also, as predicted, GST swimmers demonstrated signiﬁcantly more
accurate goals than non-GST swimmers.

Goal-setting training was also the topic of investigation in Miller and McAuley’s
(1987) study. Their study, in which subjects were trained to set speciﬁc, positive,
performance goals of appropriate difﬁculty, found that the group that had experienced
“goal-training” had signiﬁcantly higher perceptions of success and self-efﬁcacy in

basketball free-throw shooting than the “non-goal-training” group. No signiﬁcant

34

difference, however, was found in free-throw accuracy. The authors suggested a
stabilizing effect of goal-setting as performance limits are reached.

In conclusion, researchers suggest that effective goal-setting can help lower
anxiety, increase self-conﬁdence and improve performance. Effective goal-setting
includes setting moderately difficult performance/process goals that are measurable
(Gould, 2001), and speciﬁc in “absolute terms.” In addition, effectiveness is improved
when short-term as well as long-term, and performance/process goals as well as outcome
goals are set. Also, individual participation in the setting of goals along with goal
training and practice may further enhance effectiveness. Finally, task complexity
moderates goal effectiveness where the beneﬁts of goals have a more direct impact on
simple tasks than on complex tasks.

Relaxation

A second explanation for the negative effect of anxiety on performance is that of
increased muscle tension. With an increase in anxiety, there may also be a simultaneous
increase in muscle tension. As a result, antagonistic muscles work against agonistic
muscles to inhibit movement efﬁciency. In relation to the “art of hitting,” renowned
Major League hitting instructor Charlie Lau (Lau & Glossbrenner, 1980) stated, “there is
probably nothing that can destroy a batter’s chances of hitting so quickly and so
completely as tension” (p. 141). Relaxation is a strategy that works to reduce the
negative effects of anxiety by reducing unnecessary muscle tension that may otherwise
create coordination difﬁculties. Also, it is theorized that relaxation can aid in the
reduction of anxiety created by worry or negative cognitions that are related to attentional

disruptions. As suggested by Nideffer (1985), an athlete cannot simultaneously

35

concentrate on instructions of relaxation and worry about competition. Also, as the
perception of arousal is a source of efﬁcacy information, changing symptoms of over-
arousal (anxiety) through relaxation can enhance self-conﬁdence.

Relaxation as identiﬁed by Jacobson (1929) is the direct negative of nervous
excitement, the absence of nerve-muscle impulses. There are several modern techniques
to achieve a state of relaxation, most of which stem from Jacobson’s “progressive
relaxation” (1938). Progressive relaxation involves the tensing and relaxing of major
muscle groups, starting with one particular group and progressing, systematically, to other
groups until all muscles are completely relaxed. Progressive relaxation works on three
assumptions: 1) it is possible to learn the difference between tension and relaxation; 2) it
is not possible to be relaxed and tense at the same time; and 3) decreased muscle tension
will result in decreased mental tension (Weinberg & Gould, 1999). Other relaxation
techniques, all of which work on these same assumptions, include differential relaxation,
which entails an awareness of different levels of muscle tension (Rotella, 1985); a
progressive relaxation variation, which involves learning to relax in 20-30 seconds (Ost,
1988); and passive progressive relaxation, which involves eventually learning to relax
muscles without ﬁrst tensing them (Williams & Harris, 2001). Whatever the technique,
the goal is the same, to help individuals recognize unnecessary muscular tension and then
learn to let go of that tension.

Although there has been little research on relaxation in sport (Hardy et al., 1996),
the research that does exist has generally been supportive of relaxation as a strategy to
enhance performance. For example, Owen and Lanning (1982), in their study on

relaxation as a treatment method to enhance performance on a maze test concluded that

36

relaxation can result in an “improvement in ﬁne motor coordination in anxiety-laden
situations.” In addition, Nideffer and Decker (1970) reported a steady increase in shot
putting performance with progressive relaxation as a treatment.

Along with improved performance, research also has shown a reduction in state
anxiety. Research by Kukla (1976) used progressive relaxation with high school baseball
players and found a reduction in state anxiety as well as improved batting performance
under stressful conditions. Similarly, Lanning and Hisanaga (1983) found high school
volleyball players who used progressive relaxation to have lowered state anxiety as well
as improved serving performance.

In addition, relaxation has been found to be an important strategy with elite
athletes. Heishman and Bunker (1989), in an investigation of mental preparation
strategies of international elite female lacrosse players, found that “relaxation techniques
were used by almost everyone in the study.” Jones and Hardy (1990) conducted
interviews with elite athletes and also found the use of relaxation to be an important
strategy. Finally, Gould, Hodge, Peterson, and Giannini (1989) found anxiety reduction
through relaxation training to be a strategy of elite coaches.

More researchers looked at the use of relaxation as one component of
multicomponent treatment programs. In a 1989 review of psychological interventions,
Greenspan and Feltz found eighteen of 23 interventions, or 78%, “were multicomponent
and included relaxation in the treatment” (p. 230). Also, 67% of the interventions that
included relaxation used progressive relaxation. The authors concluded that “educational
relaxation-based interventions” are generally effective, however, studies showed that

“various combinations of some type of relaxation plus imagery, or imagery and

37

modeling,” were superior to relaxation alone. Therefore. it is also important to understand
imagery as it relates to cognitions and performance.
Imagery

Imagery has been deﬁned as “a symbolic sensory experience that may occur in
any sensory mode” (Hardy et al., 1996). In sport, imagery most often is employed in the
form of mental practice. Mental practice is deﬁned as “rehearsal of a physical task in the
absence of observable movement” (Hecker & Kaczor, 1988). Mental practice, mental
rehearsal, visualization, imagery, are terms that refer to “creating or recreating an
experience in the mind” (Weinberg & Gould, 1999). Imagery is related to self-conﬁdence
in that individuals are able to “see” themselves demonstrating mastery. It is believed that
this demonstrated mastery is not only a form of persuasion and/or a sense of performance
accomplishment, but also a vicarious experience to the imager, all of which are theorized
to be sources of information that inﬂuence self-efﬁcacy. Imagery is also effective in
optimizing arousal and attention for performance. Individuals “commonly use imagery to
psych up or calm down to meet the energy demands of a particular sport, as well as to
visualize aspects of the upcoming competition to sharpen the focus they need to be
successful” (Vealey & Greenleaf, 2001, p. 254).

Imagery is a complex concept and researchers have looked at it through many
different theories from many different aspects. In relation to the psychoneuromuscular
theory, for example, Harris and Robinson (1986) measured EMG activity during imagery.
Based on the results of the study, the authors concluded that muscular innervation is
speciﬁc to the muscles necessary to execute the task and that innervation during imagery

is not inﬂuenced by skill level. Jowdy and Harris (1990) also looked to determine if the

38

magnitude of muscular activity with mental imagery was a function of motor skill level.
Their study showed a signiﬁcant increase in muscular activity during mental imagery with
all subjects yet no signiﬁcance based on skill level. Relative to the symbolic learning
theory, Feltz and Landers (1983) in their meta-analysis of 60 research studies, found
strong support for symbolic learning in that the effects of imagery on the performance of
symbolic (cognitive) tasks were greater than the effects on the performance of motor or
strength tasks. Imagery, therefore, has been shown to produce the greatest effects on
tasks that are high in cognitive components.

Heckor and Kazor (1988) investigated imagery in sport as it relates to the
bioinforrnational theory. Subjects’ heart rates were recorded and imagery vividness was
measured during the imagery of four different speciﬁed scenes. The subject pool
consisted of 19 members of a Division I-AA NCAA softball team. The four scenes
included a neutral scene (sitting in a lawn chair...), an action scene (lifting in a weight
room), an athletic anxiety scene (approaching the batter’s box in the ﬁnal inning...), and a
fear scene (hearing an explosion while cruising in a jet airplane). The authors reported
that the “mean heart rates for the image periods were signiﬁcantly higher during the
action and athletic scenes as compared with the fear scene” (p. 369). Also, the images of
the action and athletic scenes were rated “signiﬁcantly more vivid” than for the neutral
and the fear scenes. The authors concluded that some support was provided for the
bioinforrnational theory as it applies to sport psychology in that “activation of response
information (i.e., heart rate increases) occurred during imagery of scenes with which
subjects had some familiarity and which involved physiological activation (i.e., action

and athletic scenes) and imagery for these scenes was perceived to be more vivid by

39

subjects” (p. 371). The authors also indicated that response information in the imagery
script along with experience level is associated with “changes in measurable
psychophysiological variables.”

To further illustrate the complexity of imagery, Paivio (1985) suggested that
different types of images may have different motivational and cognitive functions and
may be associated with different outcomes. These functional differences are reﬂected in
differences in imagery content. Based on this suggestion, Hall, Mack, Paivio, and
Hausenblas (cited in Martin, Moritz, & Hall, 1999) created a model of mental imagery
use in sport and within the model, identiﬁed and classiﬁed ﬁve types of imagery in terms
of imagery content. The ﬁve types of imagery include, motivational speciﬁc (imaging the
achievement of speciﬁc performance goals), motivational general-mastery (imaging focus
and mastery in challenging situations), motivational general-arousal (imaging emotions
and arousal necessary for competition), cognitive speciﬁc (imaging speciﬁc skill
performance), and cognitive general (imaging performance strategies). These ﬁve types
of imagery are related yet independent, that is, it is possible to use one type of imagery
alone yet it is also possible to use two or more types of imagery simultaneously. The type
of imagery used combined with the imagery ability (visual, kinesthetic) of the individual
determines the outcome of imagery use. Resultant outcomes of the various types of
imagery include motor skill acquisition, skill maintenance, performance of skills and
strategies, arousal and anxiety regulation, and self-conﬁdence (Murphy & Martin, 2002).
The type(s) of imagery one chooses to use depends upon the goal(s) to be accomplished.

In relation to self-conﬁdence, research by Feltz and Riessinger (1990) found a

signiﬁcant increase in self-efficacy after a brief exposure to mastery imagery. Similarly,

40

research by Moritz, Hall, Martin, and Vadocz (1996) with elite rollerskaters, revealed that
the high sport-conﬁdent skaters (as measured by the SSCI) used more motivational
mastery and arousal imagery than the low sport-confident skaters used. Their ﬁnding
suggests that “when it comes to sport-conﬁdence, the imaged rehearsal of sport speciﬁc
skills may not be as important as the imagery of sport related mastery experiences and
arousal” (p. 177). Vadocz, Hall, and Moritz (1997) also found that athletes in their study
who employed more mastery imagery had higher levels of self-conﬁdence (as measured
by the CSAI-2). In addition, arousal imagery was found to be a signiﬁcant predictor of
cognitive anxiety. Athletes who used more arousal imagery had higher levels of
cognitive anxiety. In that competitive anxiety can be debilitative or facilitative, the
authors suggest that if cognitive anxiety is a problem, engaging in arousal imagery will
probably make the situation worse.

Also in relation to anxiety, F eltz and Landers (1983) suggest that imagery can be
used as an “attentional-arousal set.” That is, imagery can enable an individual to set
appropriate pretension levels (to reduce tension when arousal is high or increase tension
when arousal is low) and also help to direct and maintain attention on task relevant cues.
Authors of present research suggests that athletes use motivational imagery the most,
especially prior to competing, and they seem to use it to help control other variables
important to performance such as competitive state anxiety and self-conﬁdence (V adocz
et al., 1997). Therefore, if imagery can be used to increase self-conﬁdence, control
arousal levels, and focus attention, then it is logical that performance will also improve.

Several studies have linked imagery to improved performance. F eltz and

Riessinger (1990) found that in addition to the increased self-efficacy, mastery imagery

4l

subjects also had significantly longer performance times on an endurance task than other
subjects. Van Gyn, Wenger, and Gaul (1990) found that imagery combined with power
training signiﬁcantly improved cycle sprint performance better than the power training
only group. The authors speciﬁed “skill imagery” (cognitive speciﬁc) as the type of
imagery taught. Research by Wrisberg and Anshel (1989) with younger subjects (10-12
year old boys), although not speciﬁcally labeled, found that a combination of mastery,
arousal and cognitive speciﬁc imagery along with a relaxation response technique was
useful as a pre-shot strategy for enhancing basketball free throw shooting performance.
Finally, Hall and Erffrneyer (1983) used visuo-motor behavioral rehearsal (V MBR) with
highly skilled female basketball players. VMBR is a technique that combines visual
imagery and relaxation. In a relaxed state, subjects viewed a videotaped model executing
consecutive foul shots with perfect form then imagined making perfect foul shots
themselves. Signiﬁcant improvement was found in foul shooting performance.

In all, several factors are related to imagery effectiveness. As previously
mentioned, the nature of the task is among these factors. Tasks that involve mostly
cognitive components show the greatest effects of imagery. Effects can be achieved in
motor and strength tasks, however, more time must be spent in mental practice for larger
effects to be realized (Feltz & Landers, 1983). Another factor is the experience level of
the individual. Although beneﬁts have been shown for both beginning and slightly
experienced individuals, they seem to be somewhat greater for the slightly experienced
individuals (Feltz & Landers, 1983). A third, signiﬁcant factor, is the imagery ability of
the individual. Imagery ability is linked to the vividness and controllability of the image.

The more vivid the image, the more senses and/or emotions used in creating the image

42

(particularly kinesthetic and visual senses), the greater the effects of imagery. Equally
important, controlling the image, making the image “do what the individual wants it to
do,” and being able to slow it down, speed it up, and/or visualize in the “real” time it
takes to do it, is linked to greater effects. Imagery appears to be most effective when the
image is clear, detailed, and controllable. In their extensive study with Olympic athletes,
Orlick and Partington (1988) concluded that along with attentional focus, the “quality and
control” of imagery was the “most important statistically signiﬁcant athlete skill directly
related to high level performance at the Olympic Games” (p. 129).

Also signiﬁcant, imagery ability has been shown to improve with practice.
Following interviews with elite athletes, Orlick and Partington (1988) concluded that the
best athletes had “well developed imagery skills” which were perfected “through
persistent daily practice.” Vadocz et a1. (1997) suggested that “athletes higher in imagery
ability are more likely to use imagery, and using imagery subsequently strengthens
imagery ability” (p. 251). Furthermore, imagery perspective may play a role in
effectiveness. Although research is inconclusive, there is some evidence to suggest that
internal imagery might have better results than external imagery (Weinberg & Gould,
1999). For example, Harris and Robinson (1986) found internal imagery to produce more
EMG activity than external imagery. However, it is likely that the nature of the task
and/or situation (training, competition) combined with individual differences mediates
the selection of internal versus external imagery as many individuals with high imagery
ability report switching between the two perspectives.

Finally, imagery has been shown to be an important strategy among elite athletes

and coaches. For example, Heishman and Bunker (1989) found “visualization” to be the

43

mental preparation strategy most frequently used by elite female lacrosse players. More
speciﬁcally, 98% of the subjects reported using mental practice and 65% of the subjects
considered mental practice to be as important or more important than physical practice.

In addition, Gould et al. (1989) found imagery of performance success, although used less
than other strategies, is a strategy used by elite coaches to enhance self-conﬁdence.

F urtherrnore, Orlick and Partington (1988) found “some 99%” of 235 Canadian Olympic
athletes used mental imagery as a mental preparation strategy. Following individual
interviews with 75 of the athletes, the authors concluded that the athletes “used imagery
to get what they wanted out of training, to perfect skills within the training sessions, to
make technical corrections, to imagine themselves being successful in competition, and to
see themselves achieving their ultimate goal” (p. 112).

Self-Talk

Self-talk in sport is signiﬁcant in that positive self-talk may act as a source of
efﬁcacy information to enhance self—conﬁdence. It can also help individuals stay
appropriately focused to enhance performance. Negative self-talk, however, may act as
an attentional distractor to decrease performance and subsequently, increase anxiety. In
essence, self-talk is the key to cognitive control (Zinsser, Bunker, & Williams 2001).

In general, self-talk is a difficult area to research. First, it has been argued that
there is a lack of a precise deﬁnition and operationalization of self-talk (Hardy et al.,
1996). Second, it is hard to measure an individuals’ thought content during a practice or
performance, and retrospective self-report measures may be altered by perceptions of
performance (Feltz, 1992) and/or ability to accurately recall thought content (Brewer,

VanRaalte, Linder, &VanRaalte, 1991). Third, in the end, is knowing if the type of self-

talk (positive or negative) leads to performance (positive or negative) or if performance
leads to the type of self-talk (VanRaalte, Brewer, Rivera, & Petitpas, 1994). Despite
these inherent problems, research has shown some interesting results.

Rushall, Hall, Roux, Sasseville, and Rushall (1988) attempted to avoid some of
these problems by controlling thought content. They investigated the effects of three
speciﬁc thought content conditions on the skiing performance of eighteen elite Canadian
skiers. The three thought content conditions included: 1) task-relevant statements,
hypothesized to enhance mechanical efficiency; 2) mood words, intended to increase
capabilities of performance; and 3) positive self-statements, intended to produce better
physiological efficiency. Three experiments were conducted, one for each thought
content condition, subjects played both experimental and control roles in all three
experiments. Each subject determined the speciﬁc content of thought for each condition
and practiced using it prior to the experimental session. Although the task-relevant
condition was found to be most effective, results revealed performance improvements of
more than 3% (greater than normally expected for elite performers) for all three thought
content conditions, “even though all subjects reported that they were not aware of any
performance differential.” The authors concluded that these results support the
contention that the content of thinking while skiing is a major determinant of the quality
of performance.

Ming and Martin (1996) also looked to control thought content using a self-talk
package that included the development of “key words” by four prenovice competitive
skaters (1 1-13 year olds). Subjects planned, then memorized, key words to coincide with

movements that were experienced on the ice. The authors concluded that the skaters did

45

utilize the self-talk and that the self-talk package improved performance during practice.
Also interesting, a self-report follow-up one-year later indicated that “the participants
continued to utilize the self-talk during practices and that they believed that it enhanced
their test and/or competitive performance. Along the same lines, Landin and Hebert
(1999) used one words with female collegiate tennis players to improve volleying skill.
The self-talk (cue words) was shown to be effective in improving the performance of the
two movement patterns on which the cue words focused. Also signiﬁcant, subjects
reported increased self-confidence following the intervention explaining that self-talk
helped to direct attentional focus and prompt correct movement patterns.

Rather than using speciﬁed thought content, VanRaalte et al. (1994) used
observation to analyze the audible self-talk and observable gestures of junior tennis
players. Several interesting ﬁndings emerged from their study. Among them, positive
self-talk was not associated with better performance; however, negative self-talk was
associated with worse performance. Also, players who believed in the utility of self-talk
won more points than those who reported that they did not believe. Furthermore, match
losers were signiﬁcantly more likely to lose a point following negative self-talk than
match winners, which the authors believe, indicates a difference in response to negative
self-talk. They suggested that the use of negative self-talk may be motivational to some
players and may also reﬂect that player’s perception of competence. Overall, the authors
concluded that self-talk inﬂuences competitive sport performance.

In terms of controlling anxiety, Hardy, Gammage, and Hall (2001) found the uses
of self-talk to be similar to that of imagery in that athletes reported using self-talk to

psych themselves up, to relax, and to control arousal levels. In addition, Hardy et al.

46

(1996) observed that elite athletes appear to use self-talk in high pressure situations when
there is potential for self-doubt to overpower self-conﬁdence. The authors go on to state
that the ability to “restructure cognitions from negative to positive in such situations is
also likely to be a factor in distinguishing elite athletes from their less successful
counterparts” (p. 70).

In all, negative self-talk has been found to be distracting and anxiety producing. It
can foster self-doubt, it is usually irrational, it is critical and demeaning and in general,
destructive. Positive self-talk, on the other hand, can be used to enhance performance,
control anxiety, increase self-conﬁdence, foster positive expectancies, provide self-
reward, direct attention, sustain effort and acquire new skills. Common types of self-talk
include, cognitive restructuring (working to change negative thoughts to positive
thoughts), thought stopping (learning to recognize and “stop” negative thoughts), and the
use of cue words (one or two words to speciﬁcally direct attention and/or trigger
automatic reactions).

Heishman and Bunker (1989) found 98% of elite lacrosse players “used self-talk
to maximize performance.” Similarly, Orlick and Partington (1988) found the best
athletes in their study of Canadian Olympians, had developed precompetition plans which
included positive thoughts and reminders to focus on what had worked well in the past.
These same athletes also maintained a constructive focus going into an event. Finally,
Gould et al. (1989) found elite coaches encouraged the use of positive self-talk as it was
viewed as a very effective strategy for improving conﬁdence.

If each of the psychological skill components of goal-setting, relaxation, imagery,

and self-talk have been shown to have positive effects on anxiety, self-conﬁdence, and

47

performance, then it seems logical that combining these skills into a packaged program
will have even greater positive effects on anxiety, self-conﬁdence, and performance. The
following section is a review PST package research.
Psychological Skills Training Package Research

Early research into psychological skills training packages used a variety of
combinations of various skills and measured subsequent changes in performance. For
example, Seaboume, Weinberg, Jackson, and Suinn (1985) used a packaged intervention
that included “seven different mental skills” and assessed the intervention effect on karate
performance. Similar to the present study, the mental skills included relaxation training,
mental rehearsal, and positive thought control. The remaining skills were stress
management, self-regulation, concentration, and energy control (Suinn, 1983). The
authors concluded that “the individualized and package intervention groups performed
signiﬁcantly better than all other groups (yoked, placebo control and control groups) on
karate performance measures.” In addition, they believed that having the subjects play
an active role in the selection and practice of the mental skills contributed to the
successful performances by enabling them to “gain a sense of responsibility and
commitment to their cognitive training.” In another study, Straub (1989) compared three
different packaged programs in relation to dart throwing performance. The author found
signiﬁcant group differences in posttest dart throwing performance for all three packages
but “in particular” for participants receiving the Bennett and Pravitz (1982) package.
Interestingly, in addition to self-hypnosis, this package included goal-setting, relaxation,

imagery, and affirmation statements (positive self-talk).

48

Much of the subsequent research has simpliﬁed PST packages to include three or
more of the four basic skills of goal-setting, relaxation, imagery, and self-talk. Kendall,
Hrycaiko, Martin, and Kendall (1990) looked at the effects of a relaxation, imagery
rehearsal, and self-talk package on basketball game performance. The authors found an
immediate intervention effect with all four intercollegiate basketball participants and
concluded that the skills “were effective in enhancing the performance of a speciﬁc
defensive skill in basketball game performance.” Additionally, the participants had
developed a positive attitude toward continued use of the intervention strategies. Wanlin,
Hrycaiko, Martin, and Mahon (1997) assessed the effectiveness of a goal-setting package
that, in addition to goal-setting, included positive self-talk, goal visualization, and self-
evaluation. The experimental participants were three female speed skaters that
demonstrated, as a result of the intervention, an increase in the drills and laps completed
as well as a decrease in “off-task behavior.” A fourth control participant did not
demonstrate the same positive results.

Using a similar research design, Patrick and Hrycaiko (1998) found a PST
package of goal-setting, relaxation, imagery and self-talk to enhance endurance
performance. All three experimental participants showed an immediate enhanced
performance effect following an introduction to the skills. In addition, there was a
positive relationship between the “participants’ level of mental skills usage and running
performance.” Furthermore, participants reported that using all of the skills in the
package aided each single mental skill. The authors argued that the interrelatedness of
the skills provides a more powerful intervention because the skills are used in

combination. Further research by Thewell and Greenless (2001) provided support for the

49

use of goal-setting, relaxation, imagery, and self-talk in a PST package in relation to
endurance performance. All ﬁve “recreational” gymnasium triathlon participants
experienced an immediate performance effect when introduced to the skills and all ﬁve
participants demonstrated an increased usage of the mental skills throughout the
intervention. The authors pointed out, however, that the performance measures were not
taken in a competitive environment and suggest that “future research is required to
demonstrate the beneﬁts of psychological skills training on competitive athletic
performance.”

Fewer studies have looked at psychological skills training packages and
subsequent effects on self-conﬁdence and/or anxiety, in addition to performance. Hughes
( 1988), however, found a PST package of goal-setting and imagery (to be practiced “in a
state of relaxed attention,” Martens, 1987) to increase self-conﬁdence as well as enhance
the sport skills of male high school athletes. His investigation was unique in that an
instructor at the secondary school level implemented the PST program. In a more recent
study of mental skills training and novice scuba divers, Terry, Mayer, and Howe (1998)
found the intervention group to show lower respiration rates and better performance than
the control groups. In addition, particularly signiﬁcant to scuba diving, as panic (extreme
anxiety) may be fatal, the intervention group also reported higher self-conﬁdence and
lower cognitive anxiety. The mental skills training program included relaxation, mental
practice, and “affirmations” (positive self-talk).

Hanton and Jones (1999b) used an intervention package of goal-setting, imagery,
and positive self-talk/thinking with competitive swimmers who were “debilitated by

anxiety.” As for the exclusion of relaxation, the authors argued that because anxiety has

50

been reported to be facilitative as well as debilitative (Jones & Swain, 1995), it may not
be appropriate or possible to reduce the symptoms of anxiety, in certain sports, through
relaxation techniques. It may be more appropriate to help athletes interpret anxiety
symptoms as facilitative. Previous research (Hanton & Jones 1999a) showed goal-
setting, imagery and self-talk to be a particularly important means of maintaining
facilitative interpretations of anxiety and was, therefore, integral in the intervention
package. Swimmers who completed the intervention reported more facilitative
interpretations of anxiety. In addition, subjects showed a “considerable increase in
conﬁdence levels” as well as evident performance improvements across ten races. The
authors concluded that the ﬁndings provide evidence that the intervention was successful
when working with athletes in the “real world” of competitive sport.

In all, researchers have shown PST programs to result in improved performance
(often immediate), increased responsibility and commitment on the athletes part,
increased attentional focus, decreased off-task behavior, increased practice intensity,
increased self-conﬁdence, decreased anxiety, and directional changes in the interpretation
of anxiety from debilitative to facilitative. In addition, intervention participants have
reported “signiﬁcantly greater pleasure and enjoyment” (Beauchamp, Halliwell, Fournier,
& Koestner 1996). The sum of these positive attributes suggest that it is only logical to

address the need of ﬁnding further answers in relation to PST and competitive sport.

51

CHAPTER III
METHODS
Participants

The participants were 43 female softball players belonging to Michigan Class A
High School teams from three suburban communities. The experimental team competed
in an eight-team league of all Class A schools including four inter-city schools. Most
players came from middle socioeconomic families. The control teams were teams
competing in the same conference and were chosen for similarities in community size and
atmosphere (very supportive), team achievements, socioeconomic background, and
conference experiences. The numbers on each team were as follows: Experimental, n =
12; Control #1, n = 16; Control #2, n = 15. Midway through the season, the coach of a
control team decided to no longer participate in the study; therefore, the study concluded
with one control team. Two players from the remaining control team quit midway
through the season to reduce the total number of participants to 14. The following were
the demographics of the experimental team and the remaining control team.

Along with the preseason measures, players of both the experimental team and the
control team responded to a demographic information questionnaire (see Appendix A).
The purpose of this questionnaire was to better understand the make-up of the two teams
and differences between the two teams. The information gained through the demographic
questionnaire is displayed in Table 2. Overall, the experimental team was a younger, less
experienced team. The average grade for the experimental team was 10.83,

SD = .72, while the average grade for the control team is 11.51, SD = .65. In terms of

“senior leadership,” the control team bettered the experimental team by seven seniors. As

52

for the experience factor, the experimental team had less overall varsity sport experience
(2.50 years/player versus 3.71 years/player), less varsity softball experience (1.58
years/player versus 1.86 years/player) and less summer softball experience (2.17
years/player versus 4.79 years/player). Although the differences in age and experience
were not initially known when the control team was selected, they are important to keep

in mind to fully understand the implications of the results of this study.

 

Table 2
Demographic Information

Experimental Team Control Team
Year in School Sr. 2 Sr. 9

Jr. 6 Jr. 4

So. 4 So. 1

M= 10.83 M= 11.51

SD, .72 SD, .65

Seasons of Varsity Total, 30 Total, 52
Sport Experience M = 2.5 M = 3.71

2 players at 4 years 8 players at 4 years+
Seasons of Varsity Total, 19 Total, 26
Softball Experience M = 1.58, SD .70 M = 1.86, SD .86

lat3 years 4at3years

5 at2years 4at2years
Seasons of Summer Total, 26 Total, 67
Softball Experience M = 2.17 M = 4.79

3 at 4 years+ 8 at 4 years+

2at7years+ 6at7years+

 

The experimental team’s season consisted of 14 conference games, 13 non-
conference games, and one state tournament district game for a total of 28 games. The

control team’s season consisted of 14 conference games (the same conference), 18 non-

53

conference games, and one state tournament district game for a total of 33 games. The
game-by—game outcomes for the season are listed in Table 3.
Table 3

Game by Game Summary of Runs Scored (RS) and Runs Against (RA)

 

 

 

Experimental Team Control Team

Game RS RA Difference RS RA Difference
1 16 17 -1 12 0 +12
2 10 3 +7 9 11 -2
3 17 15 +2 1 10 -9
4 19 3 +16 14 6 +8
5 10 18 -8 l4 4 +10
6 11 10 +1 13 10 +3
7 11 8 +3 3 4 -1
8 9 19 -10 l 11 -10
9 18 7 +11 3 2 +1
10 **15 7 +8 0 9 -9
11 **7 12 -5 12 11 +1
12 *7 5 +2 8 3 +5
13 *14 12 +2 0 3 -3
14 *9 7 +2 **7 15 -8
15 *10 9 +1 ”12 7 +5
16 **10 0 +10 *12 6 +6
17 **ll 10 +1 *6 5 +1
18 4 14 -10 *4 2 +2
19 ***9 19 -10 *4 2 +2
20 *7 12 -5 *11 1 +10
21 *1 18 -17 *12 4 +8
22 *13 20 -7 5 4 +1
23 *15 9 +6 8 6 +2
24 13 22 -9 *4 6 -2
25 4 16 -12 *3 1 +2
26 *18 20 -2 7 14 -7
27 *16 4 +12 1 8 -7
28 l 6 -5 **9 4 +5
29 "22 0 +22
30 0 8 -8
31 *14 4 +10
32 *25 3 +22
33 "*2 12 -10

 

*Conference games; "Measures taken; ***District game

54

The control team ﬁnished the season with a higher overall winning-percentage
(20-13; 60.6%) than the experimental team (15-13; 53.5%), and ﬁnished ahead of the
experimental team in the conference standings (1 1-3, 2nd place; 9-5, 3rd place,
respectively). Also, an analysis of the outcome differences indicated that the control team
did better than the experimental team defensively. The control team gave up 293 season
(67 conference) runs compared to the experimental teams’ 322 season (145 conference)
runs. Subjective knowledge of the individual pitchers gave the control team a distinct
edge in pitching ability and experience. This edge largely accounted for the difference in
the "runs against" column.

The game of softball is structured such that the pitcher plays a central role in the
teams defensive “success.” For this reason, a more realistic indication of overall
individual contributions may be gained through an offensive analysis (Table 4). Looking
at outcome only, the “runs scored” totals show that the experimental team had the
offensive advantage. The experimental team scored 305 season (153 conference) runs
while the control team scored 259 season (146 conference) runs. Although it is not
speciﬁcally indicated, it is interesting to note that the most runs given up in a single game
by the control team (15) were to the experimental team.

The Michigan High School Athletic Association sponsored an annual State
Tournament for which every member school was eligible. This tournament began toward
the conclusion of the regular season with district then regional, quarterﬁnal, semiﬁnal,
and ﬁnal competitions and was a single elimination format. Only one team per class
(Class A) made it through the tournament without being eliminated and was thus

declared State Champion. Although teams may have had a few games following the

55

Table 4

Offensive Team Totals for the Experimental and Control Teams

 

ExperimentaiTeam Tog
Overall - 28 games:
Runs Scored 305
Runs Against 322

Average runs/game
Runs Scored 10.89
Runs Against 11.50
Difference -.61

Conference — 14 games:

Runs Scored 153
Runs Against 145

Average runs/game
Runs Scored 10.92
Runs Against 10.35

Control Team Totaﬁ
Overall — 33 games:
Runs Scored 259
Runs Against 293

Average runs/ game
Runs Scored 7.85
Runs Against 8.88
Difference -l .04

Conference - 14
Runs Scored 146
Runs Against 67

Average runs/ game
Runs Scored 10.43
Runs Against 4.79

Difference +.57 Difference +5.04

 

district game, a loss in a district game was commonly viewed as the “end” of the season.
Success in the district tournament ultimately dictated the length of the season. The
district game therefore, was a highly signiﬁcant game for both the experimental team and
the control team. Understanding this signiﬁcance and viewing this game more closely is
necessary to aid in the interpretation of results. The district game summaries are
presented in Table 5.

By district draw, both teams were placed in the same bracket with the control
team drawing a ﬁrst round "bye." The ﬁrst round bye for the control team along with a
ﬁrst round loss for the experimental team resulted in a common opponent for both teams.
Although both teams lost by ten runs in six innings, the experimental team demonstrated

greater offensive production with 9 runs and 12 hits compared to 2 rims and 5 hits for the

56

Table 5

District Game Summary for the Experimental and Control Teams, Score by Inning,
Offensive Totals

 

 

 

 

 

 

Experimental Tea_m_ Control Team

Score: 9-19 Score: 2-12
Inning: 1234567 Inning: 1234567
Team: 220320- Team: 100001-
Opponent: 8 3 0 2 0 6 - game Opponent: 4 0 1 4 0 3 game
Team Totals

9 runs, 12 hits, 4 errors 2 runs, 5 hits, 15 errors

5 BB (2 scored) 0 BB
Opponent Totals

19 runs, 9 hits, I error 12 runs, 11 hits, 6 errors

16 BB (11 scored) 8 BB (4 scored)

 

control team. Both teams faced the same "All-District" pitcher for the opponents. The 16
walks given up to the opponent, ll of which resulted in runs, was evidence of the
inexperienced pitching staff of the experimental team. The experimental team also
committed four errors. The same junior varsity player who replaced an injured varsity
starter, however, committed three of those errors. The junior varsity player had not been
a part of the experimental intervention. A varsity player committed the fourth error after
moving from ﬁrst base to shortstop following an injury to the shortstop. The 15 errors
committed by the control team cannot be accounted for but it was apparent that this was
not a typical defensive effort.
Instrumentation

Demographic Survey. Titled “background information,” (see Appendix A) the
demographic survey was a 5-item questionnaire used to determine initial differences

among players on the experimental team and the control teams.

57

State Sport-Conﬁdence Inventory (SSCI). The SSCI (see Appendix B) is a 13-
item self-report inventory designed to measure self-conﬁdence in speciﬁc sport situations.
The inventory uses a 9-point Likert scale in which athletes are to rate items from low (1)
to high (9) based on the “most conﬁdent” athlete they know. The SSCI has demonstrated
adequate validity, positive contributions to alpha, item-total correlation coefficients
greater than .50 and acceptable item discrimination coefficients. Internal consistency
estimates resulted in an alpha coefficient of .95 (V ealey, 1986).

Competitive State Anxiety Inventory - 2 (CSAI-2). Within the 27-item scale of the
C SAI-2 are three 9-item subscales that measure cognitive anxiety, somatic anxiety and
self-conﬁdence (see Appendix C). The CSAI-2 is a revised version of the original
Competitive State Anxiety Inventory (Martens, Burton, Rivkin, & Simon, 1980) and was
initially designed to separately measure the cognitive and somatic components of anxiety.
Factor analysis of the initial scale, however, unexpectedly revealed a third component,
self-conﬁdence (Martens et al., 1990). Internal consistency was demonstrated with alpha
reliability estimates for each of the three subscales exceeding .80 in three separate
samples (Burton, 1983) and concurrent validity was established by supporting predicted
relationships between the CSAI-2 and a variety of other trait anxiety measures (Gould,
Petlichkoff, & Weinberg, 1984). Also, the authors found evidence to support construct
validity through a “systematic progression of research studies” (Martens et al., 1990).

Performance Data. Two offensive statistics typically calculated for softball
players, on—base average and batting average, were selected as indicators of performance.

On-base average for each player was calculated by dividing the total number of times on

58

base by the total number of times at bat. Batting average was calculated by dividing the
total number of hits by the total number of official times at bat (all at-bats except walks,
hit by a pitch, and catcher interference).

Procedures

Approval for this study was received from the University Committee on Research
Involving Human Subjects (U CRIHS). See Appendix D. Control teams were selected on
the basis of experiences similar to those of the experimental team, within their own
respective communities, and within the same conference of play. Coaches (also friends
and colleagues) of the teams were approached with the idea of participating in this study
and both agreed. Prior to the administration of any instrumentation, players of all teams
were asked to participate in the study and, thus, signed participant consent forms. The
PST program was administered by the researcher and coach, a graduate student at a mid-
westem university, under the direction of an accomplished sport psychologist from the
same university.

All measures were administered to the experimental team and the control teams
prior to the season for pre-season measures (see Appendix E for season schedule).
Following the completion of the pre-season measures, the coaches and players of the
control teams were instructed to proceed with their normal preseason activities while the
experimental team was introduced to Psychological Skills Training. All players of the
experimental team participated in the PST as this was a scheduled part of the training for
the team. The intensity of participation for each individual, however, could not be
controlled. The ﬁrst three days of practice were an adjustment period during which

players learned the routine of practice and got to know each other better. The initial PST

59

session for the experimental team occurred on the fourth day of practice and included
detailed discussions on self-talk, social reinforcement, the attentional demands of softball,
and goal-setting. Players were given goal-setting guides and competition reﬂection
guides (Orlick, 1986; see Appendix F1& F2 respectively) that were to be completed for
practice the next day. Players were asked to keep written evaluations for each pre-season
practice from this day forward in terms of daily goals and psychological skills applied.
The skills introduced in this practice were continually emphasized and reinforced as they
came up in physical skills practice.

Session two took place four days later when relaxation and mental imagery were
introduced. The session took place at the beginning of practice to help provide a more
concentrated effort throughout practice. Prior to any discussion, players were instructed
to read Chapter 6, Mental Rehearsal, of the Athletes ' Guide to Mental Training (N ideffer,
1985). Imagery and relaxation were discussed, after which players participated in a
relaxation/imagery session. In a relaxed state, players observed a skilled model
demonstrate correct hitting mechanics then imaged themselves duplicating the action.
Player attention was directed to several key elements of hitting mechanics.

Players were then asked to practice relaxation and imagery on an individual basis
in addition to the team sessions. Suggested times for individual practice included at night
when preparing to sleep, or prior to anxious situations such as test taking, speech giving,
etc. Players were also asked to use relaxation and imagery on their own in team practices
at times such as just prior to a turn in the batting cage, between defense repetitions, or
while practicing pitching. Further team sessions were conducted approximately once a

week throughout the season (see season schedule) and became progressively shorter in

60

length as skill increased. Also, players were asked to evaluate their own progress in the
development of their ability to relax and image.

A detailed discussion of the effects of anxiety on performance took place at the
start of the third week of practice. Players were asked to look back through practice
evaluations and develop their own individual pre-competition plan (Orlick, 1986; see
Appendix F 3), according to what they felt would work best for them. Individual plans
were continually evaluated and adjusted by each player, often with the help of the coach,
throughout the season. In addition, once games began, players were asked to evaluate
competitions using the competition evaluation form as a guide (Orlick, 1986; see
Appendix F4). Continued psychological skills practice took place through the remainder
of the season. The focus was on trying to make the skills automatic and, thus, available
to the athlete when needed.

During competition, players were instructed to use the practiced positive self-talk,
relaxation, and imagery skills to help recover more quickly from mistakes. In that
softball is essentially a game of failure (i.e., a “good” hitter in high school softball still
fails six of ten times), these skills have the potential to be called upon often. For
example, following a swing and a miss, players were to: step out of the batter’s box,
brieﬂy relax, then image the bat making contact with the center of the ball, on a pitch
within the strike zone. With practice, this routine took only seconds! Also,
communication between players was worded positively. “Don’t worry about it” was not
considered a positively worded statement! Players instead would give each other verbal
cues (not instruction) on performance execution to prepare for the next play. For

example, following a defensive error where the player looked to the base for the throw

61

before securing the ball, one would say “head down,” or “stay on it,” both of which were
understood by everyone on the team.

As the season progressed and situations came up, various additions were made to
practices. For example, following the experimental team’s second game loss to a control
team, most players talked about being distracted by verbalizations from a “fan.” They
agreed that as anxiety increased over what was being said, they were unable to regain the
necessary attentional focus. The next day’s practice included a position play drill with
nine players on defense. The remaining players plus the assistant coach were instructed
to “laugh,” “make fun of,” and, in general, be “obnoxious” to the players on the ﬁeld,
(without their knowledge). The result was instant disaster; all nine players fell apart, just
as in the game the previous day. Even after the players on defense ﬁgured out what was
going on, they were unable to recover. However, following only a few sessions such as
this, not only in defensive practice but also in hitting practice, players had greatly
improved their attentional control.

Regarding instrumentation administration, the SSCI post-game and the CSAI-2
pre-garne measures were administered on the days of the contests between the
experimental and the control teams, the day of the contest between the control teams, and
again before the start of the State District Tournament. Each coach assumed the
responsibility of distributing and collecting measures for her/his own team immediately
following the completion of the games. The researcher administered post-season
measures for all teams after the completion of the season. At this time, all of the in-
season measures were also collected. Players and coaches were thanked for their

participation!

62

Data Analysis

Group means and standard deviations on the pre-tests and post-tests were
calculated and compared. Because some of the players of the experimental group had
already been exposed to an informal psychological skills program, initial differences
between the experimental group and the control groups were expected. For this reason,
an analysis of covariance was done to reduce the effects of the initial group differences
statistically by making adjustments to the post-test means of the two groups.

Performance data were taken from the season scorebooks.

63

CHAPTER IV
RESULTS

Pre-season

Both the State Sport-Conﬁdence Inventory (SSCI) and Competitive State Anxiety
Inventory (CSAI-2) were administered at the beginning of the pre-season to determine
any initial signiﬁcant differences in state sport-conﬁdence and competitive state anxiety
between the experimental team and the control team. T-tests on the pre-season means of
the SSCI measures showed no signiﬁcant difference between teams in sport-conﬁdence.
t(24) =-.48, p >.05. T-tests on the pre-season means of the CSAl-2 subscales of cognitive
anxiety, t(24) = -.64, p >.05; somatic anxiety, t(24) = -.31, p >.05; and conﬁdence, t(24) =
.47, p >.05, also showed no signiﬁcant differences between teams. The means and
standard deviations of each measure are given in Table 6. Hypothesis 1 was supported.
Table 6

Pre-season Means and Standard Deviations for State Sport-Conﬁdence Inventory and
Competitive State Anxiety Inventory-2

 

 

Experimental Control Total Group
(N= 12) (N= 14) (N=26)
M SD M SD M SD
State Sport-Conﬁdence 84.92 16.88 87.93 15.39 86.54 15.84
Cognitive Anxiety 19.08 2.35 20.14 5.26 19.65 4.14
Somatic Anxiety 16.83 5 20 17.43 4.52 17.15 4.76
Conﬁdence 23.67 4.72 22.86 4.04 23.23 4.29

 

State Sport-Conﬁdence

In addition to the preseason measure, the State Sport-Conﬁdence Inventory

64

(SSCI) was administered following (post game) three pre-selected competitive situations.
The ﬁrst situation was a conference doubleheader between the experimental team and the
control team, the second situation was after a doubleheader with a common conference
opponent, and the third situation was after a single district game with what turned out to
be a common non-conference opponent.

It was hypothesized that the experimental team would remain more consistent in
state sport-conﬁdence as measured by the SSCI in these three selected situations. To test
for any signiﬁcant differences between the experimental and the control teams on the
SSCI post game measures, a 2 x 3 (team by game) multivariate analysis of variance
(MANOVA) was used on the data. The analysis of post game means showed that
although the experimental team mean was higher than the control team mean (89.26 and
82.06 respectively), the difference was not signiﬁcant, F(l,l7) = 1.21, p > .05. In other
words, there was no signiﬁcant difference between the average of the means of the
experimental team and of the control team. There was, however, a signiﬁcant game
effect, F (2,16) = 4.03, p < .05; and a signiﬁcant interaction, team by game effect, F(2,16)
= 9.09, p < .01. Means and standard deviations are presented in Table 7. The signiﬁcant
game effect revealed by the MAN OVA suggests the combined mean scores of the two
teams are signiﬁcantly different from game to game. Further post hoc analysis revealed
the signiﬁcant difference to be from game 2 (95.00) to game 3 (74.15). Also, the team by
game interaction effect showed the difference between the experimental team means and
the control team means to be signiﬁcantly different given the game.

To understand exactly which of the mean scores created the signiﬁcant difference,

Tukey’s post hoc test was employed. The results showed the experimental

65

Table 7

Post Game Means and Standard Deviations for State Sport-Conﬁdence Inventory

 

 

 

 

N M SD

M

Experimental (EXP) 9 89.26 20.05

Control (CTL) 10 82. 06 14.75
Postjame trial total ggoup

Po-game 1 (exp/ctl) 19 87.23 17.11

Po-game 2 (common opp.) 19 95.00 13.69

Po-game 3 (district) 19 74.15 23.87
T_e_arm by Post game trial

1 EXP Po-game 1 9 84.11 21.36

2 CTL Po-g 1 10 90.10 12.71

3 EXP Po-g 2 9 98.56 12.15

4 CTL Po-g 2 10 91.80 14.82

5 EXP Po-g 3 9 85.11 26.15

6 CTL Po-g 3 10 64.30 16.73

 

team game 3 mean (85.1 1) to be signiﬁcantly higher than the control team game 3 mean
(64.30), and the experimental team game 2 mean (98.56) to be signiﬁcantly higher than
the control team game 3 mean (64.30). Otherwise stated, the mean score for the control
team post game 3, (64.30), was signiﬁcantly lower than the mean score for the
experimental team post game 2, (98.56), and 3 (85.11). Also, the Tukey test revealed no
signiﬁcant difference from game to game for the experimental team but a signiﬁcant
difference from game 1 (90.10) to game 3 (64.30) and from game 2 (91 .80) to game 3
(64.30) for the control team. The game means for the two teams are illustrated in
Figure 1.

The results of the MAN OVA along with the results of the Tukey test support the

second hypothesis; the experimental team did remain more constant in sport-conﬁdence

66

State Sport-Conﬁdence

 

 

100 -
_ X = experimental team
_ X 0 = control team
95 -
' O
90 - O
85 -
_ x x
80 P
75 b
70 -
65 -
- 0
ﬂ
2 i t i
po-gl po-gZ 130-33
Game

Figure 1. Post Game Means for State Sport-Conﬁdence Inventory.

67

over selected games as measured by the SSCI. The experimental team showed a beneﬁt
from the treatment intervention.

The SSCI was administered again at the conclusion of the season, after all games
had been played. A 2 X 4 (team by game) multivariate analysis of variance including all
post game measures plus the post season measure was performed to test for a signiﬁcant
increase in sport-conﬁdence over the season by the experimental team. Although this
analysis revealed no signiﬁcant team effect, F (1,14) = .49, p >.05, the experimental team
again had the higher team mean (90.00 and 85.40 respectively). Also, there was no team
by game interaction effect F (3,12) = 1.76, p > .05. There was, however, a signiﬁcant
game effect, F (3,22) = 4.80, p < .05. A Scheffe post hoc test showed the signiﬁcance to
be between game 2 (95.75) and game 3 (76.13). Means and standard deviations are
presented in Table 8.

In a comparison of means, the experimental team mean is lower than the control
team mean on the initial post game measure (83.63 and 91.00 respectively) and is higher
than the control team mean on the post season measure (93.75 and 89.63 respectively).
The experimental team concluded the season higher than the initial post game measure
(83.63 initial, 93.75 post) while the control team concluded the season lower than the
initial post game measure (91.00 initial, 89.63 post) as illustrated in Figure la, Appendix
G. These differences, although positive for the experimental team, did not prove to be
signiﬁcant. Hypothesis 3, the experimental team would signiﬁcantly increase sport-

conﬁdence over the season, was not supported.

68

Table 8

Post game, Post Season Means and Standard Deviations for State Sport-Conﬁdence

 

 

 

 

Inventory
N M SD
Lean.
Experimental (EXP) 8 90.00 18.90
Control (CTL) 8 85.40 1 1.69
Post game trial total group
Po-game l (exp/ctl) 16 87.31 18.08
Po-game 2 (common opp.) 16 95.75 13.86
Po-game 3 (district) 16 76.13 23. 18
Po-season 16 91 .69 8.92
Ie_am by Post gag trial
EXP Po-game 1 8 83.63 22.78
CTL Po-g l 8 91.00 12.28
EXP Po-g 2 8 98.50 12.98
CTL Po-g 2 8 93.00 15.02
EXP Po-g 3 8 84.13 28.32
CTL Po-g 3 8 68.13 14.25
EXP Po-S 8 93.75 11.75
CTL Po-S 8 89.63 5.24

 

Competitive State Anxiety

Competitive state anxiety was measured with the Competitive State Anxiety
Inventory-2 (CSAI-2). In addition to the pre-season measure, the CSAI-2 was
administered before and after three selected games (experimental vs. control,
experimental/control vs. common opponent, experimental/control vs. common district
opponent) then again at the conclusion of the season. In an attempt to answer speciﬁc
questions concerning competitive state anxiety, the measures were analyzed as: (1) pre-
game measures only, (2) pre-game plus post season measures, and (3) post game

measures only. Within the CSAI-2 are the three subscales: cognitive anxiety, somatic

69

anxiety, and conﬁdence. These subscales will be discussed individually in the following
presentation of results.
Pre-Game Competitive State Anxiety

Cognitive Anxiety Because cognitive anxiety is likely to inﬂuence performance,
the pre-game CSAI-2 cognitive anxiety subscales were exclusively analyzed for
statistically signiﬁcant differences. A 2 x 3 (team by game) multivariate analysis of
variance (MANOVA) showed differences between the experimental and the control team
to be signiﬁcant. Means and standard deviations are presented in Table 9. The
MANOVA showed a signiﬁcant team effect, F (1,19) = 31.27, p < .001; the experimental
team mean for cognitive anxiety (17.58) was signiﬁcantly lower than the control team
mean (23.14). There was a signiﬁcant game effect, F(2,18) = 6.91, p < .01. A Scheffe
Table 9

Pre-Game Cognitive Anxiety Means and Standard Deviations for Competitive State
Anxiety Inventory-2

 

 

 

 

N M SD

learn.

Experimental (EXP) 12 17.58 2.93

Control (CTL) 9 23.14 3 .05
Pre-game trimotal group

Pre-game l (exp/ctl) 21 18.71 3.39

Pre-game 2 (common opp.) 21 20. 10 4.17

Pre-game 3 (district) 21 21.43 5.03
Team by Pre-game trial

EXP Pre-garnel 12 17.08 3.29

CTL Pre-g 1 9 20.89 2.15

EXP Pre-g 2 12 17.50 2.78

CTL Pre-g 2 9 23.56 3.05

EXP Pre-g 3 12 18.17 2.72

CTL Pre-g 3 9 25.78 3.96

 

70

post hoc analysis showed the signiﬁcance to be between game 1 (18.71) and game 3
(21.43). There was, however, a non-signiﬁcant team by game interaction effect, F(2,18)
= 2.90, p > .05. These ﬁndings indicated that the experimental team had more consistent
levels of cognitive anxiety than the control team across the season, as seen by the
signiﬁcant team effect. Additionally, all players reported higher levels of pre-game
anxiety between games 1 and 3 as the stakes rose for game 3, the district game.

Somatic Anxiety. As with cognitive anxiety, somatic anxiety uniquely inﬂuences
performance and was therefore, analyzed separately for statistical differences. In general,
the control team reported a higher level of somatic anxiety than the experimental team. A
2 X 3 (team by game) MANOVA revealed the game effect to be non-signiﬁcant, F (2,18)
= .145, p > .05.; however, the team effect was signiﬁcant, F(l,l9 ) = 36.04, p < .001.
The experimental team reported a signiﬁcantly lower level of somatic anxiety (12.61)
than the control team (16.78).

The MANOVA also showed the team by trial interaction effect to be signiﬁcant,
F (2, 18) = 3.61, p < .05. Tukey’s post hoc test revealed the experimental team mean to
be signiﬁcantly lower than the control team mean on game 1 (12 .83 and 16.78
respectively), game 2 (11.75 and 15.78 respectively), and game 3 (13.25 and 17.78
respectively). In addition, the control team mean for game 3 (17.78) was signiﬁcantly
higher than the experimental team mean for game 1 (12.83), game 2 (11.75) and game 3
(13.25). The experimental team did not at any time approach the level of somatic anxiety
reported by the control team for game 3. Furthermore, the control team mean for game 1
(16.78) was signiﬁcantly higher than the experimental team mean for game 1 (12.83),

game 2 (11.75) and game 3 (13.25). Finally, the control team mean for game 2 (15.78)

71

was signiﬁcantly higher than the experimental team mean for game 2 (11.75) and also for
game 1 (12.83) at the .05 level.

Means and standard deviations are presented in Table 10. Somatic anxiety mean
scores are illustrated in Figure 2. It is interesting to note that the pattern of the means
from game to game is the same; however, the experimental team reported a lower level of

pre-game somatic anxiety than the control team for each of the three games.

Table 10

Pre-Game Somatic Anxiety Means and Standard Deviations for Competitive State
Anxiety Inventory-2

 

 

 

N M SD

Iii!!!

Experimental (EXP) 12 12.61 2.51

Control (CTL) 9 16.78 2.35
Pre-game trial total ggoup

Pre-game 1 (exp./ctl) 21 14.52 3.20

Pre-game 2 (common opp.) 21 13.48 3.42

Pre-game 3 (district) 21 15.19 3.00
Iaam by Pre-game trig

EXP Pre-game 1 12 12.83 2.90

CTL Pre-g 1 9 16.78 2.11

EXP Pre-g 2 12 11.75 2.73

CTL Pro-g 2 9 15.78 2.90

EXP Pre-g 3 12 13.25 1.91

CTL Pre-g 3 9 17.78 2.05

 

72

Somatic Anxiety

 

 

18 : O
17 L /

_ O
16 1. \ O

- X = experimental team

- O = control team
15 -
14 - )(
13 b }L\\\‘\\\\\\\\‘\\\\\\\\ ////////////////////////
12 - X
11 L
10 l

5

L l l 1.

pre-gl pre-g2 pre-g3

Game

Figure 2. Pre-Game Somatic Anxiety Means for Competitive State Anxiety

Inventory-2.

73

Confidence. As opposed to the SSCI, which measured conﬁdence post game, this
CSAI-Z measure of conﬁdence was pre-game. A 2 x 3 (team by trial) MANOVA showed
a signiﬁcant team effect, F(l,l9) = 11.87, p < .01; the experimental team mean of 26.83
was signiﬁcantly higher than the control team mean of 22.44. There was, however, no
game effect F (2,18) = .548, p > .05. Means and standard deviations of the conﬁdence
subscale are presented in Table 1 1.

Table 11

Pre-Game Conﬁdence Means and Standard Deviations for Competitive State Anxiety
Inventory-2

 

 

 

N M SD

Tiara

Experimental (EXP) 12 26.83 4.20

Control (CTL) 9 22.44 3.60
Pre-game trial total gzoup

Pre-game 1 (exp/ctl) 21 25.19 4.36

Pre-game 2 (common opp.) 21 25.29 4.29

Pre-game 3 (district) 21 24.38 4.90
T_eam by Pre;game tria_l

EXP Pre-gamel 12 26.50 4.08

CTL Pre-g 1 9 23.44 4.30

EXP Pre-g 2 12 27.58 3.38

CTL Pre-g 2 9 22.22 3.42

EXP Pre-g 3 12 26.41 5.13

CTL Pre-g 3 9 21.67 3.08

 

The MANOVA results showed a deﬁnite team effect in all three subscales. The
experimental team means were consistently higher on the conﬁdence subscale and lower

on the anxiety subscales prior to each game. The consistent team effects along with the

74

positive experimental team means, therefore, give support to hypothesis 4. The
experimental team did show signiﬁcantly higher conﬁdence and lower cognitive and
somatic anxiety on all pre-game measures.
Pre-Game, Post Season Competitive State Anxiety

A CSAI-2 Post season measure was added to the pre-game measures to test for
anxiety and conﬁdence “over the season.” It is important to note that not all participants
were available for post season measures, which may reduce the power of these results.

Cognitive Anxiety. A 2 x 4 (team by trial) MANOVA of the pre-game measures
and the additional post season measure again showed a signiﬁcant team effect, F (l ,14) =
15.10, p < .01, for cognitive anxiety; the experimental team mean (17.22) was
signiﬁcantly lower than the control team mean (22.29). The MANOVA also showed a
signiﬁcant game effect, F (3,12) = 9.97, p = .001. The means and standard deviations are
presented in table 12 and illustrated in Figure 3. Scheffe’s post hoc test showed the
means from game 1 (18.19) to game 3 (21.61) and game 3 (21.61) to the post season
(18.00) to be signiﬁcantly different. Finally, the MANOVA showed a signiﬁcant team by
game interaction effect, F (3,12) = 5.11, p < .05. Tukey’s post hoc analysis revealed
some interesting signiﬁcant mean differences. For instance, the control team game 2
mean (22.86) and game 3 mean (26.57) were signiﬁcantly higher than all of the
experimental team pre-game means and the post season mean (16.44, 17.56, 17.89, and
17.0, respectively). The control team game 3 mean (26.57) was also signiﬁcantly higher
than the control team game 1 mean (20.43) and the control team post season mean

(19.29).

75

Table 12

Pre-Game, Post Season Cognitive Anxiety Means and Standard Deviations for
Competitive State Anxiety Inventory-2

 

 

 

 

N M SD
m
Experimental team (EXP) 9 17.22 2.98
Control team (CTL) 7 22.29 3.62
Pre-game trial total group
Pre-game 1 (exp/ctl) 16 18.19 3.45
Pre-game 2 (common opp.) 16 19.88 4.05
Pre-game 3 (district) 16 21.69 5.47
Po-season 16 18.00 4.03
Team by Pre-game trial
EXP Pre-gamel 9 16.44 3.28
CTL Pre-gl 7 20.43 2.23
EXP Pre-g2 9 17.56 3.09
CTL Pre-g2 7 22.86 3.13
EXP Pre-g3 9 17.89 2.62
CTL Pre-g3 7 26.57 4.04
EXP Po-S 9 17.00 2.92
CTL Po-S 7 19.29 5.09

 

76

Cognitive Anxiety

0

' X = experimental team
26 l' O=control team
25 -
24 _
23 -

_ O
22 -
21 b

' O
20 L

O

19.
13-
17t /
16-

15b

 

L 1 1 1
T I l 1

pre-gl pre-g2 pre-g3 po-S

Game

Figure 3. Pre-Game, Post Season Cognitive Anxiety Means for Competitive State
Anxiety Inventory-2.

77

Somatic Anxiety. A 2 x 4 (team by trial) MAN OVA also showed the difference in
somatic anxiety team means to be signiﬁcant, F (l, 14) = 10.30, p < .01, and the difference
in games to be signiﬁcant, F(3, 12) = 10.33, p = .001. There is however, no team by trial
interaction effect, F (3,12) = 1.42, p >.05. Means and standard deviations are presented in
Table 13. A further contrast of trials was done to test for constancy over the season.
Scheffe’s post hoc test showed the difference between game 3 (15.62) and the post season
measure (12.13) to approach signiﬁcance. No other differences were found.

Table 13

Pre-Game, Post Season Somatic Anxiety Means and Standard Deviations for Competitive
State Anxiety Inventory Inventory-2

 

 

N M SD
Tm
Experimental (EXP) 9 12.47 2.39
Control (CTL) 7 15.54 2.93
Pre-game trial total ggoup
Pre-game 1 (exp/ctl) 16 14.06 2.86
Pre-game 2 (common opp.) 16 13.44 2.99
Pre-game 3 (district) 16 15.62 2.78
Po-season 16 12.13 4.06
Team by Pre-game trial
EXP Pre-game l 9 12.44 2.40
CTL Pre-g l 7 16.14 1.95
EXP Pre-g 2 9 12.33 2.96
CTL Pre-g 2 7 14.86 2.55
EXP Pre-g 3 9 13.67 1.58
CTL Pre-g 3 7 18.14 1.68
EXP Po-S 9 11.44 2.60
CTL Po-S 7 13.00 5.53

 

78

Conﬁdence. For the conﬁdence subscale, a 2 x 4 (team by trial) MAN OVA
revealed a signiﬁcant team effect, F (1, 14) = 5.20, p < .05; the experimental team mean
of the four trials (27.47) was signiﬁcantly higher than the control team mean of the four
trials (24.14). The MANOVA also revealed a signiﬁcant game effect, F (3,12) = 5.98, p
=.01. Tukey’s post hoc test showed a signiﬁcant difference between the garnelmean
(23.94) and the post season mean (28.31) and a difference that approached signiﬁcance
between the game 3 mean (24.25) and the post season mean (28.31). The MANOVA,
however, showed no interaction effect, F (3, 12) = 1.72, p > .05. Means and standard
deviations are presented in Table 14.

Table 14

Pre-Game, Post Season Conﬁdence Means and Standard Deviations for Competitive

State Anxiety Inventory-2

 

 

 

N M SD
Lain
Experimental (EXP) 9 27.47 4.64
Control (CTL) 7 24.14 3.94
Pre-nge trial total ggoup
Pre-game 1 (exp/ctl) 16 23.94 4.46
Pre-game 2 (common opp.) 16 25.56 4.10
Pre-game 3 (district) 16 24.25 5.12
Po-season 16 28.31 4. 80
Team by Pre-game trial
EXP Pre-gamel 9 27.00 4.58
CTL Pre-g 1 7 24.57 4.24
EXP Pre-g 2 9 27.44 3.75
CTL Pre-g 2 7 23.14 3.34
EXP Pre-g 3 9 26.56 5.18
CTL Pre-g 3 7 21.29 3.40
EXP Po-S 9 28.29 5.04
CTL Po-S 7 27.57 4.76

 

79

Again, the MANOVA results show a team effect in all three subscales. The
experimental team mean of the four trials was signiﬁcantly higher on the conﬁdence
subscale and lower on the anxiety subscales than the control team mean. Therefore,
hypothesis 5, the experimental team will remain constant or report higher conﬁdence and
lower cognitive and somatic anxiety at the conclusion of the season, was supported.

Post Game Competitive State Anxiety

Cognitive Anxiety. A 2 x 3 (team by game) multivariate analysis of variance
(MANOVA) showed differences between the experimental team and the control team to
be signiﬁcant. Means and standard deviations are presented in Table 15. The MANOVA
showed a signiﬁcant team effect, F (1,17) = 7.91, p < .05, and a signiﬁcant game effect,
F(2,16) = 10.33, p = .001. There was however, no signiﬁcant team by game interaction
Table 15

Post Game Cognitive Anxiety Means and Standard Deviations for Competitive State
Anxiety Inventory-2

 

 

N M SD

Lam

Experimental (EXP) 10 1 7.93 3 .94

Control (CTL) 9 21.26 4.27
Post game trial total gmup

PO-game 1 (exp/ctl) 19 20.42 4.33

PO-game 2 (common opp.) 19 16.26 4.01

PO-game 3 (district) 19 21.84 4.96
Team by Post game trial

EXP Po-game 1 10 19. 40 4.30

CTL Po-g 1 9 21.56 4.30

EXP Po-g 2 10 15. 30 3.20

CTL Po-g 2 9 17.33 4.72

EXP Po-g 3 10 19. 10 4.33

CTL Po-g 3 9 24.89 4.96

 

80

effect, F (2,16) = .95, p > .05. The signiﬁcant team effect showed the experimental team
mean (17.93) to be signiﬁcantly lower than the control team mean (21.26). A Sheffe post
hoc test showed the signiﬁcant game effect to occur between game 1 (20.42) and game 2
(16.26) and also between game 2 (16.26) and the “season ending” game 3 (21.84). The
difference between game 1 and game 3 was not signiﬁcantly different.

Somatic Anxiety. A 2 x 3 (team by game) MANOVA revealed a signiﬁcant game
effect, F (2,16) = 7.04, p < .01, and a signiﬁcant team by game interaction, F(2,16) = 9.19,
p < .01. There was, however, no team effect, F(1 ,17) = .50, p > .05. Somatic anxiety
mean scores and standard deviations are presented in Table 16. Mean scores are
illustrated in Figure 4. The post hoc analysis revealed that the signiﬁcant game difference
occurred between game 1 (12.68) and game 3 (15.79) and also between game
Table 16

Post Game Somatic Anxiety Means and Standard Deviations for Competitive State
Anxiety Inventory-2

 

 

 

N M SD

Team

Experimental (EXP) 10 13.07 5.42

Control (CTL) 9 14.17 3.62
Post game trial total ggoup

Po-game 1 19 12.68 3.43

Po-game2 19 12.31 6.10

Po-game 3 19 15.79 5.71
13m by Post game trial_

EXP Po-game 1 10 12.20 3.49

CTL Po-g 1 9 13.22 3.49

EXP Po-g 2 10 14.00 7.93

CTL Po-g 2 9 10.44 2:30

EXP Po-g 3 10 13.00 4.92

CTL Po-g 3 9 18.89 5.06

 

81

X = experimental team

1 8 _ O = control team

17'-

16-

15-

14-

Somatic Anxiety

13

12

ll

10

 

5
I

l l l

l 1 1
190-31 po-gZ po-g3

Game

Figure 4. Post Game Somatic Anxiety Means for Competitive State Anxiety Inventory-2

82

2 (12.31) and game 3 (15.79) at the .05 level. As for the signiﬁcant interaction effect, a
Tukey test revealed that the control team game 3 mean (18.89) was signiﬁcantly higher
than the control team game 2 mean (10.44) at the .01 level of signiﬁcance. The control
team game 3 mean (18.89) was also signiﬁcantly higher than the experimental team game
1 mean (12.20), the experimental game 3 mean (13.00), and the control team game 1
mean (13.22), at the .05 level of signiﬁcance.

Confidence, A 2 x 3 (team by game) MAN OVA revealed a signiﬁcant team
effect, F(l,l7) = 6.14, p < .05, for the post game conﬁdence subscale. Means and
standard deviations of the conﬁdence subscale are presented in Table 17. The
experimental team mean (25.93) was signiﬁcantly higher than the control team mean
(22.70). Also, there was a signiﬁcant game effect, F(2,16) = 9.13, p <.01. A Scheffe post
Table 17

Post Game Conﬁdence Means and Standard Deviations for Competitive State Anxiety
Inventory-2

 

 

 

 

N M SD

T_eam.

Experimental (EXP) 10 25.93 5.41

Control (CTL) 9 22.70 3.97
Post ga_me trial total ggoup

Po-game 1 19 24.53 5.14

Po-game 2 19 27.78 4.87

Po-game 3 19 21.21 5.80
Team by Post gag trig

EXP Po-game 1 10 25.90 5.61

CTL Po-g 1 9 23. 00 4.36

EXP Po-g 2 10 28. 00 4.40

CTL Po-g 2 9 27.56 5.62

EXP Po-g 3 10 24.50 6.22

CTL Po-g 3 9 17.56 1.94

 

83

hoc test showed the difference between the game 2 mean (27.78) and the game 3 mean
(21.21) to be signiﬁcant. There was, however, no interaction effect, F (2,16) = 2.26, p >
.05.

The MAN OVA results showed a team effect on two of the three subscales of the
CSAI-2. The experimental team demonstrated signiﬁcantly lower cognitive anxiety and
signiﬁcantly higher conﬁdence than the control team on all post game measures. The
experimental team mean for somatic anxiety, although lower, was not signiﬁcantly lower
than the control team. Therefore, hypothesis 6, the experimental team will have
signiﬁcantly higher conﬁdence and lower cognitive and somatic anxiety on all post game
measures of the CSAI-2, was only partially supported.

Performance

On-Base Average. On-base average is detemiined by the number of times a batter
reaches ﬁrst base safely divided by the batter’s total times at bat. As well as at-bats that
result in hits, on-base average also includes “unofficial” at-bats, which are those at-bats
when a base is reached through walks, hit by a pitch, catcher interference, etc. On-base
average also includes reaching base as a result of an error, it does not, however, include
reaching base as a result of a ﬁelder’s choice. On-base averages for the experimental
team and the control team are presented in Table 18.

T-tests showed the on-base average difference to be non-signiﬁcant, t(l3) = 1.25,
p > .05. However, the t-test compares only the average of the averages and not the actual
times on base/times at bat average. For example, the average of the averages as shown by

the t-tests was .517, SD = .084 and .487, SD = .073, for the experimental and the control

84

teams respectively, a difference of .030. The total times on base/total times at bat average
is .542 and .495 respectively, a difference of .047. Although this difference is also not
likely statistically signiﬁcant, an analysis of the actual number of times on-base/times-at-
bat that make up the averages shows the experimental team to have had 29 more
baserunners than the control team with 36 fewer times at bat. It should also be pointed
out that the 29 more baserunners occurred in 5 fewer games. An additional 5 games for
the experimental team at an average of 19.57 baserunners/game would total to nearly 127
more baserunners than the control team. Further analysis of the total runs scored (see
Chapter 3, Table 4) and the total number of baserunners (see Table 18), shows the
experimental team not only had more baserunners, but also had a higher percentage of
those baserunners score (55.7% of 548) as compared to the control team (50.0% of 519).
This would indicate greater offensive efficiency as well. From a coach’s perspective, I
would argue that these numbers are signiﬁcant!

Batting Average. Batting average is deﬁned as the number of times a batter
reaches ﬁrst base safely as a result of a hit and is determined by dividing the number of
hits by the number of “ofﬁcial” at-bats. Batting averages are typically lower than on-base
averages as base on balls, hit by a pitch or catcher interference are not included as ofﬁcial
at-bats and, thus, do not ﬁgure in the average. A base on an error, however, is considered
an official at-bat and counts the same as an out. Batting averages for the experimental
team and the control team are presented in Table 18.

Again, t-tests showed the batting average difference to be non-signiﬁcant, t(1 3) =
1.01 , p > .05. However, the t-test compares only the average of the averages and not the

actual hits/official times at bat average. The average of the averages as shown by the t-

85

tests was .298, SD = .074 for the experimental team and .258, SD = .081 for the control
team, a difference of .040. The actual hits/official times at bat average is .305 for the
experimental team and .285 for the control team, a difference of .020. Initially, this
difference appears to be relatively small but a closer look shows the experimental team
with only 2 fewer hits but 63 fewer official at bats. The 2 fewer hits occurred in 5 fewer
games. An additional 5 games for the experimental team at the team’s average of 8.7
hits/ game would total to approximately 41 more hits than the control team. From a
coach’s perspective, I would, again, argue that these numbers are signiﬁcant!

Table 18

Season On-Base Averages and Batting Averages

 

T_tgm On-Base Averaga
Experimental 548 for 1012 = .542 (28 games)
Control 519 for 1048 = .495 (33 games)

Team Batting Avegge
Experimental 245 for 804 = .305

Control 247 for 867 = .285

 

Runs Scored. The experimental team scored 305 runs in 28 games (Chapter 3,
Table 4) and the control team scored 259 runs in 33 games for a difference of +46 runs
for the experimental team. Based on averages, 19.57 baserunners/game in 5 more games
would result in approximately 97 more baserunners for the experimental team. If 55.7%
of those additional baserunners score, it would result in an another 54 runs. Had the
experimental team played as many games as the control team, the experimental team,
theoretically, would have out-scored the control team by 100 runs. Once again, from a

coach’s perspective, I would argue that these numbers are signiﬁcant.

86

The above statistics clearly show that the experimental team bettered the control
team in each offensive category analyzed. Although the control team ﬁnished the season
with good offensive statistics (i.e., what coach would complain of an average of nearly 16
base runners per garnel), the experimental team ﬁnished the season with better offensive
statistics (i.e., nearly 20 base runners per game). The season statistical differences
combined with experience differences indicated in the demographic information provided
by the players (see introduction), indicates a positive effect of PST on offensive softball

performance.

87

 

CHAPTER V
DISCUSSION

The overall results of this study suggest that PST, under the direction of a coach,
can have a positive effect on the cognitions and performance of high school softball
players. The experimental team was a younger, less experienced team yet had
consistently higher self-conﬁdence, lower anxiety and better offensive performance
statistics than the control team.

As hypothesized, there was no signiﬁcant difference between the experimental
team and the control team prior to the season in terms of competitive anxiety and self-
conﬁdence. Because both teams were not different on this initial measure, it can be
expected that any signiﬁcant differences on subsequent measures are a result of the PST
intervention. However, demographic information provided by the players showed there
were age and experience differences. Although unknown initially, the control team was
an older, more experienced team (see Chapter 3, Table 2) with nine seniors, seven more
than the experimental team. The control team exceeded the experimental team in varsity
softball experience, total varsity sport experience (all sports), and summer softball
experience. With these differences in mind, the most important implication of this study
is that through PST it is possible to teach younger, less experienced players to “think” and
play like veterans. In all, the experimental team achieved and maintained higher levels of
self-conﬁdence, lower levels of competitive anxiety, and completed the season with
greater offensive performance.

In regard to self-conﬁdence, as hypothesized, the experimental team remained

more constant across selected situations than the control team. The experimental team’s

88

initial in-season sport conﬁdence scores were slightly lower than the control team’s
scores. However, by the second measure the experimental teams’ sport conﬁdence scores
exceeded those of the control team and then remained more constant through the
remainder of the season. These results are consistent with previous research (Hanton &
Jones, 1996a; Hughes, 1988; Terry et al., 1998) that reported increases in self-conﬁdence
to coincide with PST.

As successful experiences have been shown to be important in developing and
maintaining self-conﬁdence (Feltz, 1982; F eltz & Mungo, 1983; George, 1994; Vealey,
1986), the increased self-conﬁdence of the experimental team indicates that the players
were able to learn to evaluate ability based on performance versus outcome. An analysis
of the “winning percentage” is one means through which this conclusion can be drawn.
The winning percentage of the experimental team was just 53.5% as compared to 60.6%
for the control team. Included in the winning percentage of the experimental team were
losses in nine of the ﬁnal eleven games (see Chapter 3, Table 3). Yet, the experimental
team demonstrated higher levels of self-conﬁdence.

As suggested by Vealey (1986), focusing on performing well (versus winning and
losing) is related to higher levels of sport-conﬁdence. Along with this performance
orientation, Vealey found the interaction of an individual’s deﬁnition of success with
their perception of ability to also be related to self-conﬁdence. These two ﬁndings in
Vealey’s research were key to the PST intervention in the present study and were
subsequently supported. First, a main goal of this PST program was to get players to
understand and develop a performance orientation. From the beginning, players readily

agreed that winning was a given, as “everyone wants to win;” however, improved

89

 

performance would ultimately result in more wins. That being decided, throughout the
season, improved performance, and not winning, was the primary focus for the
experimental team.

Through goal-setting players were focused on performing well as each individual
was responsible for setting and evaluating challenging but realistic long term “dream”
goals, and season goals as well as short term daily practice or competition goals (Orlick,
1986; Orlick & Partington, 1988). A key part of the process of goal-setting for this high
school age group was learning the controllable and uncontrollable aspects of softball and
then setting goals and evaluating success accordingly (Burton, 1989b). For example,
“readiness” in the batter’s box, and swing execution are controllable aspects of hitting. A
pitcher’s effectiveness or an umpire’s strike zone are not controllable aspects. A batters’
focus and subsequent goal evaluation would then be on readiness in the box and/or swing
execution (depending on the individuals’ hitting goals) and not on the opposing pitcher or
the umpire. A focus on the controllable aspects of softball increased the opportunity for
perceived success and each perceived success increased the expectation that future
performances were also likely to be successful (Bandura, 1977). As a result, self-
conﬁdence was enhanced.

Second, redeﬁning success in a failure-oriented game such as softball (a
“successful” batting average of .400 means failing six of ten times) became an essential
part of this PST program. Conventional wisdom tells us that a ball that “drops in” for a
hit is a success and one that is caught for an out is a failure. However, with the nature of
the game of softball, it is entirely possible for a poorly hit ball to result in a hit and a well

hit ball to be caught. Therefore, as pitching effectiveness and/or defensive positioning are

90

not controllable factors of the game, “hitting .400,” often viewed as a performance goal
was considered an outcome goal.

Players instead set goals to focus on aspects of swing execution and contact. A
well hit ball achieved through correct swing execution, whether resulting in a hit or an
out, was considered success. Likewise, a poorly hit ball due to a mechanical error was
considered something to improve upon; again regardless of whether it resulted in a hit or
an out. Also, a strike out as a result of a questionable umpire call was considered bad
luck (not related to ability, F eltz, 1984) and was not dwelled upon! Going a step further,
each player had her own individual goals of swing execution depending on stage of
learning, strengths, and weaknesses, and evaluated success accordingly. If, for example,
the batter achieved her performance goal (i.e., correct head position throughout the at bat)
yet struck out, the batter was successful, and one step closer to developing a total swing.
Using this deﬁnition of success, a .400 batting average did not effectively represent
performance, as perceived success would actually be much higher. Ultimately, successful
experiences were increased and self-conﬁdence again was enhanced.

As an example of the effectiveness of this strategy, at one point during the season,
a player (the #4 “power hitter”) on the experimental team was waiting to bat in the last
inning of a game where the opponent was ahead by 3 runs. After going “0-3” her
previous at bats, she was reminded that although these at-bats did not result in “bits,” she
was, in fact, hitting the ball very hard. With bases loaded, and the conﬁdence that she
was having a good day at the plate, she hit a three run triple to tie the game. Keeping in
mind that this was a learning experience; it should be noted that this player was very

upset about her previous at-bats (with an outcome focus) until she was reminded about

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how hard she was hitting the ball (a performance focus). Because of her understanding of
PST to this point in the season, upon being reminded, her immediate response was, with a
smile; “I have hit the ball hard.”

Although we considered goals based on hitting mechanics, ﬁelding mechanics,
and pitching mechanics to be performance goals, the current literature considers these
types of goals to be “process goals” (Gould, 2001). At the time of this study, process
goals had yet to be identiﬁed. However, it seemed only logical that this type of goal
would be most effective as the realization of the high number of uncontrollable factors in
the game of softball became apparent, especially as they relate to performance measures
such as batting averages, ﬁelding averages, and earned run averages.

Because the skills in this PST program were presented as a package, it is not
possible to know the exact effect of each skill in regard to these results. It could very
well be that each skill meant something different to each player and, therefore, played a
different role in each individual’s success. It is known, however, that the PST package
resulted in positive results for the experimental team. Goal-setting was an integral part of
PST because, as mentioned previously, it helped develop and maintain a primary focus on
performance. Beyond that, relaxation, imagery, and self-talk played a role in the
successful accomplishment of the performance goals for each player. A brief description
of the likely contribution of each skill, in regard to self-conﬁdence, follows.

Although relaxation is usually associated with reducing anxiety, relaxation in this
study was also used to reduce the muscle tension that can occur through simply “trying
too hard,” with or without the presence of anxiety. Muscle tension, regardless of its’

source, can create coordination difficulties and as a result, interfere with skill execution

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(N ideffer, 1985). Tension free muscles in the game of softball can result in stronger,
more accurate throws by the defense, greater arm speed and pitch accuracy for the pitcher.
and a stronger, quicker more accurate swing for the batter.

In relation to hitting, for example, tension can create slight differences in swing
execution and/or bat path (mechanical accuracy), which can result in much larger
differences in the subsequent ball contact (or non-contact). Tension can also interfere
with bat speed as muscle groups work against each other. A reduction in tension,
therefore, results in a quicker, more accurate swing. A quicker, more accurate swing has
many implications for success in hitting. Among them, the quicker the swing, the greater
the force exerted on the ball (force = mass x acceleration, mass being equal, i.e. the same
bat). Also, the quicker the swing, the longer the batter can wait to initiate the swing and
thus, have more time to decide if the pitch is “good” (Elliott, 1992). In addition, the more
accurate the swing, the better the ball contact and thus, fewer strike outs, weak ground
balls or pop-ups (low percentage “on base” contact) and more hard hit ground balls or
line-drives (higher percentage “on base” contact).

Players worked to understand the speciﬁc muscles required for a particular skill
and then worked to use only those muscles while all other muscles remained relaxed.
Relaxation practice started with progressive relaxation group sessions that initially lasted
15-20 minutes and became progressively shorter throughout the season. Understanding
the difference between tension and relaxation and then being able to achieve a state of
relaxation in a progressively shorter time period, ultimately a few seconds, was a goal of
this PST program. As a result of the reduction of tension that occurred through

relaxation, players experienced increased success, which again, is associated with higher

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levels of self-conﬁdence. The results in this study are consistent with the previous but
somewhat limited research that found improvements in performance and ﬁne motor
coordination to be associated with progressive relaxation (Kukla, 1976; Lanning &
Hisanaga, 1983; Owen & Lanning, 1982).

Also, as suggested by previous research, imagery was used in conjunction with
relaxation (Greenspan & Feltz, 1989). Imagery is related to self-conﬁdence in that
individuals are able to “see” themselves demonstrating mastery. The visualization of
demonstrated mastery can be perceived by the athlete as a performance accomplishment,
a form of persuasion, and/or a vicarious experience to the imager, all of which are
theorized to be sources of information that inﬂuence self-conﬁdence. Imagery, as it
relates to self-conﬁdence in this study, played a role in visualizing the successful
accomplishment of performance goals, in duplicating demonstrations of correct skill
execution, and in preparing for game situations.

In relation to hitting, for example, players, in a relaxed state, used imagery to learn
correct hitting mechanics. Following a demonstration by a live, skilled model (versus
videotaped, Hall & Erffrneyer, 1983) players would imagine themselves duplicating the
correct mechanics. Key points were emphasized, visualized then physically practiced in
various drills. Not only were key points duplicated quickly, but ﬁner details of the swing
were duplicated as well, with little or no further instruction. This strategy had to be
carefully monitored, however, as sometimes non-desirable details could also be
duplicated. For instance, during the preseason, players would practice hitting in rotating
groups of two, since there was an even number of players on the team, hitting partners

were always the same. One player in particular was working on her hands and

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subsequent bat path, yet had a somewhat quirky stride. As her goal was to work on her
hands, I did not give feedback on her stride. Before long, I noticed her hitting partner had
picked up the same quirky stride. The situation provided a great opportunity to illustrate
to them, and to the rest of the team, the effectiveness of modeling/imagery! Both players
momentarily altered their hitting goals and easily corrected the stride.

Imagery was also used in hitting strategy. Players would visualize their individual
strike zone and the relation of pitches to that zone. Then, in game situations, players
would “look” for speciﬁc pitch locations depending on the count. If, for example, the
count was 3 balls, 0 strikes, the players’ “best pitch” to hit would be visualized prior to
stepping in the batter’s box. Once in the box, the player would swing only if the real
pitch matched the visualized pitch. Where most teams would “take” the 3-0 pitch, the
experimental team would swing at the pitch, but only if it matched the “best pitch”
previously visualized. As most 3-0 pitches are thrown for strikes, it became a high
percentage pitch to hit. If, however, a player had a 2 strike count, the whole strike zone.
plus a little more to account for umpire perception, would be visualized and the batter
would “see” pitches in that zone then prepare to hit any pitch that matched the
visualization.

Consistent with previous research (Orlick & Partington, 1988; Vadocz et al.,
1997) players reported improvement in imagery ability, with practice. In addition, several
players reported learning to “slow” the pitch down and make it “look” bigger when facing
an exceptional pitcher. This ability may be illustrated in the hitting performance of the
district game (the third measure, toward the end of the season). Facing the same “all-

state” pitcher as the control team, the experimental team produced 12 hits and 9 runs

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versus the control team’s 5 hits and 2 runs. Following the experimental team’s game, the
opposing coach commented that his pitcher had not been hit that hard all season. Also, it
is interesting to note that SSCI measures taken following these games showed the
experimental team to have signiﬁcantly higher sport-conﬁdence than the control team,
even though both teams lost by 10 runs in 6 innings. Indicating, again, that a
performance orientation and the subsequent perception of success, is related to self-
conﬁdence. Although success in this situation cannot be totally attributed to imagery, it
is consistent with previous research that found increases in self-conﬁdence to coincide
with imagery (Feltz & Ressinger, 1990; Vadocz et al., 1997).

Finally, self-talk is associated with increases in self-conﬁdence (Landin & Hebert,
1999). In the realm of self-talk, the experimental team focused on positive
communication between players, cue words and/or task-relevant statements, and positive
thoughts (that often went along with positive/successful mental images). In relation to
positive communication, for example, players - and coaches, on the experimental team
worked to eliminate the word “don’t,” in any communication. “Don’t” not only has a
negative connotation, it also has the potential to produce the action to be avoided (Carton.
1984). Phrases such as “don’t worry about it,” and “don’t swing at the high ones,” (two
very common phrases in high school softball) were replaced with “you’ve got the next
one,” and simply, “strikes.” A visual image of the top (or bottom) of the strike zone
would accompany the word “strikes.”

Cue words and task-relevant statements played a role in skill acquisition and

execution. Statements such as “head down,” “hands to the ball,” “glove down,” and “two

hands,” helped players focus on the desired action in learning or performing a skill.

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Although the teaching of physical skills would occur in practice, verbal cues also served
as reminders of key points and aided player focus and performance in game situations. In
terms of error correction, a key strategy for every player on the experimental team
following an error was, to momentarily relax, imagine the skill performed correctly and
repeat a word or phrase to reinforce the correction. For example, if a defensive player
incorrectly anticipated a bounce which brought her hands up early and led to the ball
going between her legs, every player on the team was to relax, “see” the hands stay low to
make the play correctly, and repeat the phrase “glove down.” Immediately following,
would be a positive communication to the player who made the error. As a result,
consecutive errors, which often lead to the “bad inning,” were rare. Also, with practice
the whole process took only seconds, outside observers would probably not notice
anything different.

Self-talk also included positive self-statements (Rushall et al., 1988). “The Little
Engine That Could” (Piper, 1976) was a team role model. Rather than “I can’t”
statements, players said, “I can!” “I CAN hit that pitcher” creates a whole different
approach to hitting than “I can’t hit that pitcher.” Sounding repetitive, self-talk
contributed to performance success which is associated with increased levels of self-
conﬁdence and coincides with previous self-talk and PST research (Hanton & Jones,
1999b; Landin & Hebert, 1999; Terry et al., 1998).

A possible limitation of this study in regard to sport-conﬁdence was that the sport-
conﬁdence measures were taken post competition. However, post competition for
“game” 1 and 2 was actually post doubleheader, only game 3 was a single game. In that

performance has been found to more strongly predict self-conﬁdence, than self-

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conﬁdence predicts performance, the SSCI scores may have been more strongly
inﬂuenced by the performance of the second game versus the combination of the two
games. In relation to the ﬁrst measure, between the experimental team and the control
team, the measure was taken following a second game win by the control team. More
important however, in the same game, members of the experimental team acknowledged
(in post-game discussion) an attentional disruption (created by a “fan”) which
subsequently resulted in performances below expectations. As this doubleheader
occurred relatively early in the season (the ﬁrst conference games), players were still
learning to focus on the controllable factors of softball and “block out” the uncontrollable
factors (i.e., crowd noise). It would have been interesting to also have a post ﬁrst game
measure to see how the performance in each game inﬂuenced sport-conﬁdence. The
SSCI scores of this ﬁrst measure were the only conﬁdence scores throughout the season
where the control team’s mean was higher than the experimental team’s mean.

Although there was no support for the hypothesis that the experimental team
would have signiﬁcantly increased sport-conﬁdence at the conclusion of the season, it is
interesting to note the differences in the control team and the experimental team from the
beginning of the season to the post season. The experimental team’s post season measure
of sport-conﬁdence was more than 10 points higher than the initial in-season measure of
sport-conﬁdence which was taken immediately following the second game loss to the
control team (see Chapter 4, Table 8, or Appendix G). On the other hand, the control
team’s post season measure of sport-conﬁdence was almost 2 points lower than the initial

measure taken immediately following the second game win over the experimental team.

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A closer analysis shows that the control team concluded the season with a higher
winning percentage (60.6%), a higher, second place ﬁnish in the conference standings,
and a better record in the ﬁnal 11 games (6-5 with a +36 run differential). Yet, they were
unable to completely return to that initial level of sport-conﬁdence. The experimental
team concluded the season with a lower winning percentage (53.5%), and a lower, third
place ﬁnish in the conference standings. In addition, the experimental team faced some
of their toughest opponents near the end of the season to go 2-9 with a -59 run differential
in the ﬁnal 11 games. Yet, they exceeded the post season level of sport-conﬁdence for
the control team, and their own initial level of sport-conﬁdence, by more than 10 points!
Although these measures are not statistically different, this would indicate an effect of
PST at the conclusion of the season.

Readers should not misinterpret these results as indicating that through PST, the
experimental team no longer cared about winning. On the contrary, this was a very
competitive team from a very competitive community where winning is important. The
fact that this team was able to have increased conﬁdence following an absolutely tough
conclusion to the season only reinforces the power of PST, as the experimental team was
still able to understand and focus on success! It may be noted here, that with the
knowledge, leadership and conﬁdence of the players who returned (all but three), the
experimental season was followed with a conference championship season.

In regard to competitive anxiety, the experimental team was hypothesized to have
signiﬁcantly lower cognitive and somatic anxiety than the control team on all pre-game
measures of the CSAI-Z. Along with this, pre-game conﬁdence as measured by the

CSAI-2 was predicted to be signiﬁcantly higher for the experimental team than for the

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control team. Results showed support for the hypothesized direction on all three
subscales of the CSAI-2.

The experimental team was consistently lower in cognitive anxiety than the
control team for all three games in which the measures were taken (see Chapter 4, Table
9). In addition, there was a signiﬁcant difference between the means of game one and the
means of game three as both teams experienced an increase in cognitive anxiety prior to
game three. However, it is important to note that this highest measure of cognitive
anxiety for the experimental team, prior to game three, was still not as high as the lowest
measure of cognitive anxiety for the control team. The experimental team did not
experience the level of cognitive anxiety that the control team experienced prior to any of
the games in which measures were taken, not even the season determining district game.
These results are consistent with previous research that shows individual psychological
skills and/or PST to lower cognitive anxiety (Burton, 1983, 1989b; Lanning & Hisanaga,
1983;Terry et a1, 1998).

Results were similar for somatic anxiety and again, for conﬁdence. The
experimental team reported signiﬁcantly lower levels of pre-game somatic anxiety than
the control team for all three measures. And, as with cognitive anxiety, the experimental
team’s highest somatic anxiety score (again, prior to game three) did not approach the
control team’s lowest somatic anxiety score. Prior research has not exclusively
represented somatic anxiety as it relates to PST, however, these results are consistent with
research that has cited the use of psychological skills to control arousal levels (Feltz &

Landers, 1983; Hardy et al. 2001; Vadocz et al. 1997).

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As for the conﬁdence sub-scale, the experimental team reported signiﬁcantly
higher levels of conﬁdence than the control team on all three pre-game measures and,
again, the experimental team’s lowest conﬁdence score was not as low as the control
team’s highest score. The control team did not experience the level of conﬁdence that the
experimental team experienced prior to any of the games in which measures were taken.
The positive conﬁdence results for the experimental team, however, should be expected,
as the authors of the CSAI-2 report the sub-scale to measure conﬁdence as the opposite of
cognitive anxiety (Martens et al., 1990).

Again, because the psychological skills used in this study were presented as a PST
package, it cannot be determined exactly which skills, or combination of skills,
contributed to lower levels of pre-game competitive anxiety for each individual.
However, as a package, PST did produce positive results for the experimental team.
Although anxiety was not dwelled upon during the season, it was initially important for
the players to understand the arousal/performance relationship and the negative effects
that anxiety can have on performance. Once understood, each player then worked to ﬁnd
her own optimal level of arousal, and to understand and recognize her own unique
response to anxiety. It was also important, as a coach, to learn about each player and give
feedback accordingly. To help coincide with the positive atmosphere created by PST, the
season focus was on replicating optimal levels of arousal rather than dwelling on negative
responses to anxiety.

Goal-setting and subsequent goal evaluation was an integral part of each player’s
understanding of the relationship between arousal and performance. Practice or

competition goals were recorded and evaluated on a daily basis in player journals and/or

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competition evaluation forms (Orlick, 1986). In the evaluation process, players looked
for patterns of what may have interfered with, and most important, what may have
contributed to goal accomplishment, in terms of arousal control. From there, an effort
was made to duplicate the positive and eliminate the negative. It is important to note that
under-arousal was a concern as well as over-arousal as both are negatively related to
attentional focus (Easterbrook, 1959). Less than optimal attentional focus is not only
associated with lower performance, but just as important, reduced practice intensity and
efficiency. Practice intensity is necessary for goals and goal evaluations to contribute to
the understanding of arousal control.

Relaxation, imagery, and self-talk played a role in arousal/anxiety control as well.
Relaxation helped to reduce the negative effects of anxiety by reducing unnecessary
muscle tension. In addition, relaxation played a role in attentional redirection as “athletes
cannot simultaneously concentrate on relaxation and worry” (N ideffer, 1985).

Imagery and self-talk worked in much the same way. Imagery used as previously
mentioned, helped to direct attention to task relevant cues, away from worry. Players,
however, were also encouraged to use imagery to set appropriate arousal levels prior to
practice repetitions and competitions (Feltz & Landers, 1983). Prior to games, for
example, players would “see” themselves warming up for the game and during that
warm-up, imagine their focus changing from the day at school to the demands of the
game. Players would “feel” their muscles getting warm, their throwing arms getting

loose, they would “hear” the noise of the crowd, and as they imagined the game was

 

ready to start, “feel” they were ready to have their “best game ever.” From there they

would imagine mastery performance; throwing the ﬁrst pitch for a strike, hitting the ball

102

hard, making the tough play, etc. Self-talk would accompany the imagery and relaxation
to help reach and regulate the appropriate arousal level (Hardy et al., 2001 ).

Players eventually learned that the optimal level of arousal was for the most part,
a controllable factor and then worked to attain that control. Of course, attaining control
was not always easy as new situations often presented new reactions with which players
had to learn to deal. Two such situations stand out; both involved the anxiety producing
invitation and subsequent playing in the local “Softball Classic” tournament.

The Softball Classic is a prestigious, late season, single-elimination, invitational
tournament with the invitation based on a team’s win/loss record during the ﬁrst part of
the season. As the tournament selection time approached, the experimental team was a
borderline team, however, two wins in an upcoming non-conference, weekend
doubleheader would most likely guarantee an invitation. As the signiﬁcance of these two
games emerged, the team’s focus changed from performance to outcome; we had to win!
The result: instant disaster. Not only did the team lose the ﬁrst game; it was a 10-run/5-
inning mercy rule loss (see Chapter 3, table 3, game 8). Between games we talked about
the change to an outcome focus (the idea initiated by the players), reviewed controllable
versus non-controllable factors, and agreed to go back to what had worked to that point in
the season, a performance focus. The second game was a 10-run/5-inning mercy rule win
for the experimental team (see game 9). The difference in play was amazing!

Despite the doubleheader split, the experimental team received an invitation to
play in the Softball Classic, a Friday night game, under the lights. The invitation was
huge for this young team. In the days leading up to the tournament it became apparent to

the players that the support from peers, teachers, and the whole community was also

103

 

huge. “Everyone” was going to be at the game. From my perspective, with the growing
anticipation and excitement, we would do well, especially because we had PST! Ha!

My concern started on the bus ride to the tournament site as player energy and
emotion was high — really high! However, the plan was to get to the ﬁeld, warm-up (run
and throw), then provide time for individual relaxation and imagery, just as we had done
to this point in the season. I was conﬁdent that everyone knew what to do. Following the
warm-up I told the team that they had the next ﬁve minutes to themselves and I
suggested, based on their outward behavior, that they concentrate on relaxing, and then
“see” themselves performing well, their “best game!” The response I got was
unexpected. A senior captain said something to the effect of; “We don’t have time for
that stuff here, this is a real game." Huh? A “real” game, what? The team was choosing
to disregard what we had worked on since the beginning of the season. I was unprepared.

The previous game ended, the stands were full, and it was our turn to take the
ﬁeld. As the game started and then progressed, the effect of over-arousal/extreme anxiety
was very apparent. A “catastrophe” ensued. But it was a short game, only 5 innings (10
run mercy rule, game 18). Players mishandled bunts, dropped throws, “froze” on line
drives that were a step away, outﬁelders ran in on ﬂy balls that were hit deep; it was not
good! And, it all took place in front of what quite literally appeared to be the whole
community. A community (especially teachers and peers) that would not let them soon
forget their performance that night. The players were devastated.

An explanation for this situation may well lie in the cusp catastrophe model of
anxiety and performance (Hardy & Fazey, 1987). There was indeed a dramatic decrease

in performance and there was no recovery; not even to a moderate level. Also, it was

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rather evident that players were experiencing cognitive anxiety as well as increasing
physiological arousal. Given the unexpected levels of cognitive anxiety/physiological
arousal and the lack of experience in dealing with those levels, a simultaneous reduction
in both, as suggested by Hardy ( 1996) would not have happened easily.

In hindsight, it would have been very interesting to have conﬁdence and anxiety
measures from that night. What happened? When did it happen? What were they
thinking? What were they feeling? Could pre-game anxiety scores have predicted the
impending poor performance? And, in hindsight, it would have been interesting to see
how different the performance result would have been had we prepared for the extreme
anxious reactions. On the other hand, the situation provided a great learning opportunity.
We learned for sure that anxiety can have dramatic negative effects on performance and
we learned for sure that PST is for “r ” games too.

Following this tournament game, we had only the weekend to recover and prepare
for the next, very important district game. Conﬁdence and anxiety scores as well as
performance statistics from the district game, just three days later, indicate that the
devastation from that night was short-lived. Because of PST, the players readily
understood what happened and rebounded very quickly. Through the rest of the season
players chose to continue to work on and use PST and although, as previously mentioned,
the end of the season was tough, conﬁdence remained high, anxiety remained low and
performance continued to improve.

The inclusion of the post season CSAI-2 scores provides support for the
hypothesis that the experimental team would remain constant or increase conﬁdence and

report lower cognitive and somatic anxiety at the conclusion of the season, signiﬁcantly

105

 

more than the control team. The greatest support for this hypothesis comes from the
signiﬁcant team effect on all three subscales of the CSAI-2. The experimental team
reported signiﬁcantly lower cognitive and somatic anxiety and signiﬁcantly higher
conﬁdence with all four measures taken into consideration. Although the experimental
team did not signiﬁcantly lower cognitive or somatic anxiety from the ﬁrst, pre-game
measure to the last, post season measure they did remain more constant than the control
team. The same is true for conﬁdence; the experimental team remained more constant.
In relation to cognitive anxiety, it is interesting to note that the post season measure for
the control team, a measure that did not involve an impending competition but rather a
general approach to competition, still did not produce scores as low as any pre-
competition measure for the experimental team. These results, again, support previous
research that found PST to lower anxiety and increase conﬁdence (Terry et al., 1998).

The hypothesis that the experimental team would have signiﬁcantly higher
conﬁdence and lower cognitive and somatic anxiety than the control team on all post
game measures of the CSAI-2 was only partially supported as results showed a team
effect on only two of the three subscales. The experimental team reported signiﬁcantly
lower cognitive anxiety and signiﬁcantly higher confidence across all three measures,
however, in regard to somatic anxiety, while the experimental team mean was lower than
the control team mean across the measures, it was not signiﬁcantly lower. The fact that
these were post-game measures as opposed to pre-game measures provides speculation as
to the lack of a team effect for somatic anxiety.

Somatic anxiety results show the post game (post doubleheader) 2 measure to

oppose the consistency of results so far (see Chapter 4, Table 16). A closer look at the

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outcomes of the doubleheader (against a common opponent) shows the control team to
have been involved in a lopsided victory, winning their second game by 22 ms. The
experimental team, however, escaped with a one run second game victory. It is logical
that a one run game would create more somatic anxiety than a 5 inning, 22 run game and
therefore, explains the difference in somatic anxiety levels between the teams on the
second measure. It is also logical that this one run game would create more somatic
anxiety than either the ﬁrst experimental team post game measure (a second game 5 run
loss) or the third experimental team post game measure (a 10 rtm loss).

Although this second CSAI-2 measure shows the experimental team to have
reported its’ highest level of post game somatic anxiety (14.00), it is interesting to note
that the scores also reﬂect the teams lowest level of post game cognitive anxiety (15.30)
and the highest level of post game conﬁdence (28.00). This provides support for the
multidimensional nature of competitive state anxiety (Martens, 1977). It might also
provide insight as to why the experimental team was able to successfully stop the
opponents comeback attempt in the late innings of the game.

When considered in relation to the catastrophe model, although somatic anxiety
and physiological arousal are considered to be slightly different constructs, the model
predicts that under conditions of low cognitive anxiety, physiological arousal should have
small effects on performance (Hardy, 1996). Therefore, although the players reported
experiencing their highest level of somatic anxiety, the cognitive anxiety scores indicate
that it would not effect performance. In addition, relative to self-efﬁcacy theory (Feltz,
1982) performing well enough under intense conditions to win a one run game would

enhance perceptions of success and thereby increase self-conﬁdence, as reﬂected in the

107

 

post game CSAI-Z conﬁdence scores. This second game in which measures were
administered also reﬂects the experimental team’s highest level of reported self-
conﬁdence as measured by the SSCI (also a post game measure).

Also interesting with this second measure, is a comparison of the experimental
team’s pre-game cognitive and somatic anxiety scores with their post game scores
(cognitive pre-game, 17.50, cognitive post game, 15.30; somatic pre-game 11.75, somatic
post game 14.00). From pre-game to post game, cognitive anxiety decreased while
somatic anxiety increased. This is consistent with multidimensional anxiety theory,
which theorizes that the two components of anxiety change differently during
performance evaluation (Gould et al., 1984).

The hypothesis that the experimental team would have signiﬁcantly higher on-
base averages and batting averages than the control team was not supported statistically.
However, the case was made for the experimental team having out performed the control
team relative to these averages. In addition, the experimental team out performed the
control team in terms of total runs scored. Because this PST program was presented as a
package, it is not known to what extent each psychological skill contributed to
performance success for each individual player. However, that PST or components of
PST would result in increased performance is consistent with previous research (Hall &
Erffrneyer, 1983; Kendall et al., 1990; Landin & Hebert, 1999; Patrick & Hrycaiko, 1998;
Seabourne et al., 1985).

Goal-setting contributed to increased performance by giving players both focus
and direction. In addition, setting goals based on redeﬁned success (performance/process

versus outcome) contributed to greater perceptions of success. At the same time, as

108

 

players became aware of, and internalized, controllable versus uncontrollable factors of
the game, they were not distracted by what may have previously been perceived as
“failure,” such as a well-hit line drive resulting in an out. Although the experimental
team knew they would likely give up runs (largely due to inexperienced pitching, an
uncontrollable factor) they were conﬁdent in their ability to put the bat on the ball and
score runs. Players were able to enter the batter’s box in a positive, relaxed state and
focus on the pitch. A review of the previous discussion on conﬁdence and anxiety may
provide a greater understanding of the possible contribution of each psychological skill to
the performance results as they relate to this study.

The inter-relatedness of the constructs involved in producing positive results
makes it hard to separate and discuss each one individually. Self-conﬁdence increases
because of successful performances, the negative effects of anxiety decrease because of
the conﬁdence gained through successful performances and performance increases
because self-conﬁdence is high and anxiety is low. In addition, as supported by research,
the present study included, psychological skills contribute to increased self-conﬁdence,
decreased anxiety, and increased performance. However, as stated by Martens (198 7),
PST is not magic. Effort is required to attain (and retain) psychological skills as well as
physical skills. And, as evidenced in this study, both require a learning process, and
practice. Also, PST will not allow an individual to perform beyond her/his ability level
(as demonstrated by the experimental team’s pitchers), PST can only help an individual

strive to perform to her/his potential, and hopefully make the experience more enjoyable

 

along the way.

109

In general, players on the experimental team responded positively to the
implementation of PST. The players tended to be academically oriented and appreciated
the added information regarding the practical application of psychological concepts.
Although some were not sure that PST would make a difference, all were willing to try.
However, so that PST would have a true chance to make a difference, it was important for
players to understand that they could talk freely about perceptions and evaluations and
know that their status on the team would not change as a result. Parent feedback and
support was positive as well. As a matter of fact, in the summer league, following this
spring season, there was more than one game when a parent informed me that a player
was momentarily off by herself preparing mentally so that she would be ready to compete.
I believe 1 was instructed to “let her do her thing.” Teachers and other coaches were not
as supportive as they really did not understand what we were doing or trying to
accomplish.

Implications. There are three important implications resulting from this study.
First, athletes of high school age and ability will beneﬁt from a PST program. Most
importantly, with the age and experience differences between the experimental and
control teams in mind, this study demonstrates that it is possible to teach younger, less
experienced players to “think” and play beyond that of veterans. Overall, the younger,

less experienced experimental team was more conﬁdent, less anxious, and had better

 

performance. In general, the addition of PST to the daily practice schedule was a logical
addition. In that PST contributed to practice efﬁciency, learning PST did not add to the

total practice time. Subj ectively, players were more focused, they advanced physical

llO

skills more quickly, and they learned game strategies more easily than previous non-PST
teams.

A second implication is that, as with physical skills, PST requires a learning
process. Players need to learn not only what psychological skills are, but also, to learn
how to use the skills effectively. In addition, and apparently as important, players must
learn to trust that the skills will work, even in “real games.” In this study, learning PST
was a continual process. Players were introduced to the skills; they practiced the skills,
evaluated the skills and then adjusted and eventually reﬁned the skills. And then they
practiced them again. The consistent reinforcement, practice and evaluation of
psychological skills throughout the season was key to PST effectiveness. As with
physical skills, psychological skills improved with practice and experience.

A third implication is that a coach can effectively teach PST. Key to this coach
effectively teaching PST, however, is a thorough understanding of basic psychological
principles, an understanding gained through some rather impressive graduate classes.
Also unique to this PST program were my own perceptions of what I had learned in those
classes combined with what I had learned through my previous coaching experiences.
Interestingly, those perceptions were altered following a summer softball playing
experience of my own (the ﬁrst in 10 years). I believe my teaching of PST was more
effective the following season after personally learning to use the same skills
competitively. 1 was reminded that the game is quite different inside the foul lines.

The experimental team continued to work on, and implement PST the following
season. Although there were no measures taken that season, the returning players’

psychological skills and the subsequent effectiveness of the skills seemed to improve

111

 

 

even more with the continued practice. The team appeared to play every game with
conﬁdence and there were no “catastrophe” performances. Also important, the returning
players became advocates of PST and effective models for the new players. Season
statistics reﬂected a continued improvement in team performance as on-base average,
batting average, and the total runs scored, all increased from the experimental year. The
team ﬁnished the following season with a 20 — 8 win/loss season record and a 12 — 2
conference record. Most impressive, 11 of the 12 conference wins were 5 inning/ 10 run
mercy rule wins. This was a considerable improvement fi'om the experimental year.

Also interesting, following graduation, several players reported continued use of
PST. For example, one player reported using PST prior to a surprise test in a college
class. She said that she was about to panic along with the rest of the students in the class
but then remembered to relax and focus. She continued with positive self-talk, telling
herself that she had listened in class and had taken good notes and there was no reason to
doubt her ability to answer the questions. She later called to say she had received the
only “A” on the test. This would support the claim that PST also results in better
participation in any achievement endeavor outside the athletic setting (Martens, 1987;
Weinberg & Williams, 2001).

There are several probabilities regarding the results of this study. First, it may be
that the scores on the measures were a reﬂection of what the players on the experimental
team learned throughout the season and therefore, players may have responded according

to what was believed to be desirable. To be sure, the experimental team did learn a lot

 

about psychological concepts. However, very little attention was paid to the measures,

except for the time it took to ﬁll them out. Also, prior to the season, players were asked

112

to answer honestly. They were told that there were no wrong answers and that individual
scores would not be known. Based on the open communication that existed between the
players and coaches, I believe the scores to be an honest reﬂection of what each player
felt at the time.

Second, as mentioned previously, two of the post game measures were actually
post doubleheader. The performance/outcome of the second game most likely had the
greater inﬂuence on the scores. It may have been more accurate to have measures
following each game; however, this would have been more time consuming and more
intrusive. Third, one might wonder if maybe my coaching style alone would affect the
results of this study. However, I believe the control team coach had a coaching style
similar to my own. She provided opportunities for many repetitions and gave generally
positive feedback. It should be noted that the control team’s post season cognitive
(19.29) and somatic (13.00) anxiety scores were also below, and the post season
conﬁdence scores (27.5 7) were also above the norms established for the CSAI-2 (Martens
et al., 1990; Table 1, Chapter 2). Finally, maybe the experimental team just had better
athletes. Better athletes might result in better performance, and subsequently, lower
anxiety and higher self-conﬁdence. However, the control team had some great athletes!
If only they were on my team...

Many questions remain in regard to PST and provide a basis for future research.

To begin with, this PST program provided a focus on both self-conﬁdence and anxiety.

 

However, is it necessary for a PST program to focus on both self-conﬁdence and anxiety?
Would the results also be positive with a focus on one and the exclusion of the other?

For example, it has been suggested that self-conﬁdence may be one of the most powerful

113

qualities that elite performers possess, more powerful than anxiety management skills
(Hardy et al., 1996). It has also been suggested that anxiety and self-conﬁdence are at
opposite ends of a continuum (Martens et al., 1990). Both of these suggestions would
lead one to conclude that a PST program could focus exclusively on increasing self-
conﬁdence. However, would a focus on self-conﬁdence be enough to improve
performance and decrease the negative effects of anxiety?

In addition, the catastrophe model (Hardy & Fazey, 1987) suggests that cognitive
anxiety and self-conﬁdence can be experienced at the same time and predicts that
cognitive anxiety can sometimes be facilitative. Research has indeed shown cognitive
anxiety to be facilitative (Jones & Swain, 1995). If a PST program were to focus
exclusively on increasing self-conﬁdence, would cognitive anxiety be more easily
perceived as facilitative? Or, would it still be necessary to address responses to anxiety.
On the other hand, how would a focus on just anxiety management inﬂuence self-
conﬁdence and performance?

Furthermore, the players on the experimental team learned PST the ﬁrst
season, however it seems they began to internalize PST the following season. In addition,
the experimental team experienced a great improvement in both performance and
outcome the following season. Was the improvement from the ﬁrst season to the second
season a result of PST or simply a result of maturity? A multi-year study along the same
lines as the present study may help to answer these questions.

Finally, there is a need to better understand PST from the athlete’s perspective,
to investigate PST from “inside” the athlete’s mind. It would be interesting to ﬁnd out,

for example, if athletes are aware of increases in conﬁdence and decreases in anxiety as

114

 

they learn and implement psychological skills. In relation to this study, it would be
interesting to know if the experimental team was aware that, although the outcomes were
less than what they expected, they still had high levels of conﬁdence and low levels of
anxiety, especially as compared to the higher ranked control team. If athletes were indeed
aware of such results, would this knowledge further reinforce conﬁdence in otherwise
anxiety producing situations? Also, it is important to try to understand the athlete’s initial
reactions to PST and what it takes for the athlete to buy-in to PST. It is important to
know if certain psychological skills are relied on more that others in relation to certain
situations for a certain type of athlete. In relation to the younger athlete, it is important to
ﬁnd out if and how a parent’s support, or lack of support, affects PST. A greater
understanding from the athlete’s perspective would contribute to more efficient teaching
and subsequent learning and implementation of skills.

In conclusion, a psychological skills training program that was implemented by a
coach did effectively increase self-conﬁdence, decrease anxiety and increase
performance, especially as compared to an older, more experienced control team. Key to
effectively teaching PST was an understanding of the psychological skills used in the
program and how they relate to the game of softball. Also key to effectively teaching
PST, was the consistent reinforcement of psychological skills throughout the season. Just
as with physical skills, players were consistently reminded and given opportunities to
practice psychological skills. As it was not enough to just tell players to “watch the ball,”
it was not enough to just tell them to “relax and imagine success.” Learning PST was a
continual process that required effort on the part of the coach and the players, and needed

to be evaluated often to assure success.

115

 

APPENDIX A

Demographic Survey

116

 

Background Information

ID NUMBER: (to be assigned):

 

Age: Grade in school:

 

 

Years of Varsity experience in all sports:
Years of Varsity experience in softball:

Years of Varsity experience in Summer softball:

Rate your ability to play softball compared to other softball players in the league:

Battin

1 2 3 4 5

below average average above average
Basean

1 2 3 4 5

below average average above average
Team Play

1 2 3 4 5

below average average above average
Concentration
1 2 3 4 5

below average average above average

117

 

1
below average

1
below average

1
below average

1
below average

1
below average

Covering bases

3 4 5
average above average

Fielding

3 4 5
average above average

Situation play

3 4 5
average above average
Pitching
(if you’re a pitcher)
3 4 5
average above average

Visualize the play before it happans

(Imagery)
3 4 5
average above average

118

 

APPENDIX B

State Sport-Conﬁdence Inventory (SSCI)

ll9

 

STATE SPORT-CONFIDENCE INVENTORY

Think about how conﬁdent you feel right now about performing successfully in the
upcoming competition.

Answer the question below based on how conﬁdent you feel right now about competing
in the upcoming contest. Compare your self-conﬁdence to the most self-conﬁdt:n_t,2__1thlete
you know.

Please answer as you really feel, not how you would like to feel. Your answers will be
kept completely conﬁdential.

HOW CONFIDENT ARE YOU RIGHT NOW ABOUT COMPETING IN THE

UPCOMING CONTEST? (circle number)

1.

Compare the conﬁdence you feel ﬁght
m in YOUR ABILITY TO EXECUTE
THE SKILLS NECESSARY TO BE
SUCCESSFUL to the most conﬁdent
athlete you know.

Compare the conﬁdence you feel gigm
no__w in YOUR ABILITY TO MAKE
CRITICAL DECISIONS DURING
COMPETITION to the most conﬁdent
athlete you know.

Compare the conﬁdence you feel $8M
ao_w in YOUR ABILITY TO
PERFORM UNDER PRESSURE to
the most conﬁdent athlete you know.

Compare the conﬁdence you feel Ligm
r_ro_w in YOUR ABILITY TO
EXECUTE SUCCESSFUL STRATEGY
to the most conﬁdent athlete you know.

Compare the conﬁdence you feel right

Low

Low

no_w in YOUR ABILITY TO CONCENTRATE

WELL ENOUGH TO BE SUCCESSFUL
to the most conﬁdent athlete you know.

Compare the conﬁdence you feel Ligh_t
gay in YOUR ABILITY TO ADAPT
TO DIFFERENT COMPETITIVE
SITUATIONS AND STILL BE
SUCCESSFUL to the most conﬁdent
athlete you know.

120

Low
1

Low

2

Medium
4 5

Medium

4 5

Medium

4 5

Medium

4 5

Medium
4 5

Medium

4 5

High
9

High

High
9

High
9

High
9

High

 

HOW CONFIDENT ARE YOU RIGHT NOW
ABOUT COMPETING IN THE UPCOMING
CONTEST? (circle number)

10.

ll.

12.

13.

Compare the conﬁdence you feel ﬁgm
m in YOUR ABILITY TO ACHIEVE
YOUR COMPETITIVE GOALS to

the most conﬁdent athlete you know.

Compare the conﬁdence you feel [1:th
gay in YOUR ABILITY TO BE
SUCCESSFUL to the most conﬁdent
athlete you know.

Compare the conﬁdence you feel right
m in YOUR ABILITY TO THINK
AND RESPOND SUCCESSFULLY
DURING COMPETITION to the
most conﬁdent athlete you know.

Compare the conﬁdence you feel ﬁgh;
r_ro_w in YOUR ABILITY TO MEET
THE CHALLENGE OF COMPETITION
to the most conﬁdent athlete you know.

Compare the conﬁdence you feel [1th
no_w in YOUR ABILITY TO BE
SUCCESSFUL BASED ON YOUR
PREPARATION FOR THIS EVENT
to the most conﬁdent athlete you know.

Compare the conﬁdence you feel mt
m in YOUR ABILITY TO
PERFORM CONSISTENTLY
ENOUGH TO BE SUCCESSFUL to
the most conﬁdent athlete you know.

Compare the conﬁdence you feel ﬁght
any in YOUR ABILITY TO
BOUNCE BACK FROM
PERFORMING POORLY AND BE
SUCCESSFUL to the most conﬁdent
athlete you know.

121

Low

Medium
4 5 6

Medium
4 5 6

Medium
4 5 6

Medium
4 5 6

Medium
4 5 6

Medium
4 5 6

Medium
4 5 6

 

 

 

 

APPENDIX C

Competitive State Anxiety Inventory-2 (CSAI-2)

122

 

COMPETITIVE STATE ANXIETY INVENTORY — 2
ILLINOIS SELF-EVALUATION QUESTIONNAIRE (5)

Name: Sex: M F Date:

Directions: A number of statements which athletes have used to describe their feelings before competition are given below. Read
each statement and then circle the appropriate number to the right of the statement to indicate how you feel right now - at this moment.
There are no right or wrong answers. Do not spend too much time on any one statement. but choose the answer which describes your
feelings right now

 

 

Not At All Somewhat Moderately So Very Much So
1. I am concerned about this competition ___________________________ 1_ _____________________ 2 ______________________ 3 _____________________ 4

2. I feel nervous ______________________________________________________ 1 _____________________ _2 ______________________ 3 _____________________ 4

3. I feel at ease _______________________________________________________ 1 _____________________ _2 ...................... 3 ..................... 4

4. l have self doubts __________________________________________________ 1 _____________________ _2 ______________________ 3 _____________________ 4

5. I feel jittery ________________________________________________________ 1 _____________________ _2 ______________________ 3 ..................... 4

6. I feel comfortable ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, I. ..................... .2 ...................... 3. ..................... 4
7. 1 am concerned that 1 may not do as well in

thiscompetitionaslcould ________________________________________ 1 ______________________ 2 3 ______________________ 4
8. May body feels tense ______________________________________________ 1 ,,,,,,,,,,,,,,,,,,,,, 2 ______________________ 3 _____________________ 4

9. I feel self-conﬁdent _______________________________________________ 1 _____________________ 2 ...................... 3 _____________________ 4

10. 1 am concerned about losing _____________________________________ l_ _____________________ 2 ...................... 3 _____________________ 4

1 1. I feel tense in my stomach ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 1_ ..................... _2 ______________________ 3 _____________________ 4 ,

12. I feel secure ________________________________________________________ 1_ _____________________ _2 ______________________ 3 _____________________ 4

13. 1 am concerned about choking under pressure ,,,,,,,,,,,,,,,,,,, l. ..................... .2 ...................... 3. ..................... 4

14. My body feels relaxed ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 1 _____________________ 2 ______________________ 3 _____________________ 4

15. I’m confident I can meet the challenge ,,,,,,,,,,,,,,,,,,,,,,,,,, 1_ _____________________ 2 ______________________ 3 _____________________ 4

16. I‘m concerned about performing poorly ,,,,,,,,,,,,,,,,,,,,,,,,, 1 _____________________ 2 ______________________ 3 ..................... 4

17. My heart is racing ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 1_ _____________________ 2 ...................... 3 _____________________ 4

18. I ‘m confident about performing well _____________________________ l _____________________ 2 ______________________ 3 _____________________ 4

19. I’m worried about reaching my goal ,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 1 ,,,,,,,,,,,,,,,,,,,,, _2 ,,,,,,,,,,,,,,,,,,,,,, 3 _____________________ 4

20. I feel my stomach sinking ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 1 _____________________ 2 ______________________ 3 _____________________ 4

21. I feel mentally relaxed ____________________________________________ l _____________________ 2 ______________________ 3 ,,,,,,,,,,,,,,,,,,,,, 4
22. I’m concerned that others will be disappointed

withmyperfonnance ______________________________________________ 1 ,,,,,,,,,,,,,,,,,,,,,, 2 3 ______________________ 4
23. My hands are clarnmy _____________________________________________ 1 _____________________ ,2 ,,,,,,,,,,,,,,,,,,,,,, 3 _____________________ 4
24. I‘m confident because 1 mentally picture

myself reaching my goal __________________________________________ 1 ______________________ 2 _____________________ 3 ______________________ 4
25. I’mconcernedlwon’tbeabletoconoentrate ___________________ l _____________________ 23 _____________________ 4
26. I’mcontidentofcomingthroughunderpressure ________________ l_ _____________________ 23 ..................... 4
27. My body feels tight _______________________________________________ 1 _____________________ _2 ______________________ 3 _____________________ 4

123

 

APPENDIX D

University Committee on Research Involving Human Subjects (UCRHIS) Approval

124

 

MICHIGAN STATE UNIVERSITY

 

unrvnsrnr corom'm on men nwomno 1m memo . marrow . tum-mt
HUIIAN sonnets mania)

:06 3mm HALL

(9m ass-9130

April 25, 1988

Jill Elliott
1105 N. Waverly Rd.
Lansing, MI 48917

Dear Ms. Elliott:

Subject: "THE EFFECTS OF PSYCHOLOGICAL SKILLS TRAINING ON
HIGH SCHOOL SOFTBALL PERFORMANCE W"

The above project is exempt from full UCRIHS review. This project has been reviewed by
another committee member and approval is granted for conduct of this project.

You are reminded that UCRIHS approval is valid for one calendar gear. If you plan to
continue this project beyond one year, lease make provisions for o taining appropriate
UCRIHS approval prior to April 25, l 89.

Any changes in rocedures involvin human sub'ects must be reviewed by UCRIHS prior
to initiation of t e change. UCR S must also notiﬁed promptly of any tEmblems
(:nexpefted side effects, complaints, etc.) involving human subjects during e course of
t e wor .

Thank on for bringing this project to my attention. I“ can be of any future help, please
do not esitate to let me know.

Sincerely,

    
 

JKH/sar

cc: M. Ewing

MSU is on Afﬁrmative Action/Ind may Institution
1 2 5

 

 

APPENDIX E

Psychological Skills Season Schedule

126

 

PSYCHOLOGICAL SKILLS SEASON SCHEDULE

 

 

 

 

 

 

 

 

 

____-.____M°nday .. - Triggers-.. :._-,..._.Wedneegex- i.,,,-,--,..T.h9tsdax_ Friday..,.,_ _. Sat. 1,
a 1 - 4 5
; TRYOUTS
‘ (through D
- the 15 ) 1
7 8 Q 9 1 10 11 12
14 15 - 16 ; 17 § 18 19
( 1“ DAY AS PHYSICAL ‘ CONTINUE
? ATEAM. . SKILLS FROM
PRACTICE - YESTERDAY
p Learning the i
i routine-
conditioning,
3 defensive skill
i; drills, game
i situations,
‘ 3 hitting ; , y
;21 ;22 ,23 $24 125 :26
; EXPERIMENTAL ; I ; 1"IMAGERY '
TEAM. PR5: More on i Reinforcement g SESSION!
SEASON Goal- of Continue from ; EVALUATION
gﬁiﬁﬁgﬁm “ setting, I psychological f yesterday 1) Read ch. 6.
: Demo 11‘ ' Examples I skills E ; Nideffer.
, grap Ic , . . . . .
. survey, SSCI. of effective I prevrously 2) Watch Came
* CSAI-2 vs. : discussed j bat for
i DISCUSSION or: a ineffective 1 during understanding of
, PST—goal- goals 1 physical skills j key points.
setting. self-talk. , practice i 3) Relaxation and
? 390‘3' 1. imagery prior to
; reInforcement. i batting practice
i “mm" 3 3 4) Batting practice
23 : 29 I 30 a 31
Reinforcement ' 1 Assignment: { 1) Attention
of all i I write own control drills
psychological i Continue I defensive , 2) hitting
f skills previously from I responsibilitie ; demonstration,
I discussed yesterday F s for each ? emphasis on
during physical ‘ I possible I imagery to
1 skills practice g situation and reinforce key
i use imagery

g to practice
ii them

3‘ points

 

 

 

127

 

 

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128

2
ADMINSTRATION
OF PRE-SEASON
MEASURES TO
CONTROL TEAMS
4 5 7 8 9
Spring Break : ; P '
f Got 12 j “vacation” ? Individual skills practice
, players on
11 . 12 i 13 14 15 16
Detailed Game , Pre- 2 GAMES, Game Review
discussion of : situationsl . competition ‘ NON-
. arousal/anxiety ' strategy 2 plan i Conference : Reinforcement of
effects on i ; adjustments 1 Post- . PST
performance, Formal competition
preparing for ' relaxation/ evaluation - 9 Pre-plan
competition - ; imagery E Orlick (1986) adjustments
: pre-competition i sessions as a guide
plan, Orlick Z
g (1986), ; Imagery ? Goal
j Competition evaluation evaluations
' goals—within 5 (ending ;
. control . ? practice)
18 F 19 20 i 21 , 22 23
? Reinforcement Relaxation] 2 GAMES, Game review ' Discussion of
of PST during imagery NON- . psychological 2
physical skills session- E Conference l 1 skills becoming gamesl .
. practice i evaluation ' f individual eval-
(end of Post 7 responsibility
; practice) competition . f
‘5 evaluations : Relaxation/
[Relaxation ‘ : imagery to be
becoming i » done on own
4 ; easier] , outside of practice ‘
: 25 26 g 27 28 29 . 30
2 NON- Game Reinforce- : ‘ ;
3 CONFERENCE review, ment 2
‘ GAMES Start of continued gamesl
individual Ethrough all . eval-
l Evaluations psychologi games and + ~
3 cal skill practices
:; evaluations
(3 players! 3
practice)

A

 

 

May

 

 

 

 

 

 

 

 

 

Monday Tuesday wgqegay Thursday -- Friday _W ___S_at._ _
2 3‘ 3 . 4 , 5 » 6 7
» Pre-competition % 2 GAMES, 7 Game review I 2 GAMES, : Game '
plan Conference 1 1 Conference ' Review
adjustments — w/control 1 .
. team Game 1 Review PST
Relaxation/ SSCI post evaluations (especially if
. imagery ; game, ‘ changes are .
' (positive self- . CSAI-2 , necessary or
. talk) pre/post 1 something
i game new comes
i i I up)
I Competitio -
: n L
._ ? ,EYﬁlllﬁlQDi- -- __ .. WEE-.. WW-
9 g 10 I 11 i 12 3 13 14
1 GAME, NON- i 2 GAMES, I Game Review I 2 GAMES. . Game
CONFERENCE , Conference 3 Imagery on 1 Conference , review
. 5 ; own/evaluate ' (second ‘
_ Game 2 Game 3 measures) SSCI ‘- .
evaluations Evaluations ! Game F post game, CSAI- =1 1
‘ I situations I 2 pre/post game ' l
3 under LOUD l i
i conditions to I Game
l prepare for I evaluations
, g next opponent E . ' -w
€16 ;17 :18 119 g20 521
; Players should j 2 GAMES, I Game review I 2 GAMES. Game :
i be internalizing Conference ; 1 Conference review , 2 3
. skills that work é Group : (control team1 ; , gamesl :
i by now. Game I relaxation! : vs. control team 2 9““-
1 continued evaluations imagery, if 1 measures)
% reinforcement necessary 1 Game
: and evaluation (if not, on own) I evaluations,
' Evaluate l adjustments,
I reinforcement . ’
Z 23 124 25 i 26 1 27 : 28
; Game Review I 2 GAMES, 1 GAME, ; Focus on district Tentative
; I Conference NON- 1 tournament Pre-district
1 Game Conference : preparations, f game
I evaluations I Game I relaxation/ — (*State .
i I evaluations ’ imagery Q Tournament) .
i l 4 Evaluate Measures for I
; l 1 j i all teams .
‘30 731 : 6/1 7.6/2 6/3 . DIST.
. . . . FINALS ,

 

*Some teams are drawn to have a qualifying game before the 27‘”. If any of the three teams are selected

to play the qualifying game, measures will be on that day.

129

 

 

APPENDIX F

Psychological Tools

 

130

 

F1

Goals

 

1. Dream Goal (long-term)—What is your long term goal?
What is potentially possible in the long term if you stretch all your limits?

2. Dream Goal (this year)——What is your dream goal for this year?
What is potentially possible if all your limits are stretched this year?

3. Realistic Performance Goal (this year)—What do you feel is a realistic performance
goal that you can achieve this year(based on your present skill level, on your potential
for improvement, and on your current motivation)?

4a. Goal of Self-Acceptance—Can you make a commitment to accept yourself and to
learn from the experience regardless of whether you achieve your ultimate
performance goal this year?

4b. If you do not meet your desired performance goal, to what extent will you still be able
to accept yourself as a worthy human being?

Complete self- 0 1 2 3 4 5 6 7 8 9 10 Complete and full
rejection self-acceptance

5. Can you set an on-site goal of best effort (giving everything you have that day) and be
satisﬁed with achieving that single goal?

6. Focused Psychological Goal (this year)—What do you feel is an important goal for
you to focus on this year in terms of your psychological preparation or mental control
(e.g. a speciﬁc goal related to psychological readiness for the event, focus control
within the event, distraction control, conﬁdence, coping with hassles or setbacks, and
improving interpersonal harmony or relationships)?

7. Daily Goal—(A) Set a personal goal for tomorrow’s training session. Write down
one thing you would like to do, or accomplish, or approach with special focus or
intensity. (B) Can you set a personal goal before going to each training session this
year?

8. What do you think others could do to increase the harmony among team members
this year?

131

 

F2

Competition Reﬂections

 

These questions are designed to help you reﬂect upon your personal competitive
history and to help you develop or reﬁne a precompetition plan and competition focus
plan.

Knowing your competitive self

1. Think of your all-time best performance(s) and respond to the following questions
keeping that event(s) in mind:

How did you feel just before that event?

 

No Activation 0 l 2 3 4 5 6 7 8 9 10 Highly activated . -
(mentally and (mentally and 1 !
physically ﬂat) physically charged)

Notworried O 1 2 3 4 5 6 7 8 9 10 Extremely

or scared at all worried or scared

2. What were you saying to yourself or thinking shortly before the start of the event(s)?

3. How were you focused during the event (i.e., what were you aware of or paying
attention to while actively engaged in the performance)?

4. Now think of your worst competitive performance(s) and respond to the following
questions keeping that event in mind:

How did you feel before that event?

No activation 0 1 2 3 4 S 6 7 8 9 10 Highly activated

 

 

(mentally and (mentally and
physically ﬂat) physically charged)
Not worried 0 1 2 3 4 5 6 7 8 9 10 Extremely
or scared at all worried or scared
(Cont.)

132

Competition Reﬂections (Cont. )

 

5. What were you saying to yourself or thinking shortly before the start of that event?

6. How were you focused during the event (i.e., what were you aware of or paying
attention to while actively engaged in the performance)?

7. What were the major differences between your thinking (or feelings) prior to these
two performances (i.e., best and worst)?

8. What were the major differences in your focus of attention during these performances
(i.e., best and not-so-best)?

9. How would you prefer to feel just before an important performance?

No activation 0 1 2 3 4 5 6 7 8 9 10 Highly activated
(mentally and (mentally and
physically ﬂat) physically charged)

Notworried O l 2 3 4 5 6 7 8 9 10 Extremely
or scared at all worried or scared

10. How would you prefer to focus your attention during an important performance?

11. Is there anything you would like to change about the way you approach a
competition? or training?

12. Is there anything you would prefer to change about the way the coach approaches you
during training or competitions?

133

 

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134

F4

Competition Evaluation—Form B

 

 

 

 

Name: Event:
Date: Results
Event/Site Your Placing'

 

 

1. Did you have a performance outcome goal for this event?
2. If so, to what degree did you achieve this performance outcome goal?

Did not achieve 0 1 2 3 4 5 6 7 8 9 10 Achieved goal
goal at all completely

3. What was your on-site goal(s) for this event (e.g., what focus did you want to carry
into this event)?

4. To what degree did you achieve this on-site goal(s)?

Did not achieve 0 l 2 3 4 5 6 7 8 9 10 Achieved goal
goal at all completely

5. Circle your feeling going into this competition.

No determination O 1 2 3 4 5 6 7 8 9 10 Completely determined

No conﬁdence 0 l 2 3 4 5 6 7 8 9 10 Completely conﬁdent

Noworries O l 2 3 4 5 6 7 8 910 Veryworried

No physical 0 1 2 3 4 S 6 7 8 9 10 Highly physically

activation (ﬂat) activated (positively
charged

6. How did your precompetition plan go?
Terrible 0 l 2 3 4 5 6 7 8 9 10 Felt really good

Were you feeling the way you wanted to feel?

 

(Cont.)

135

 

 

Competition Evaluation Form B

7.

10.

11.

What were your thoughts as you approached the start of the event?

How did your competition focus plan go?

Went poorly/ O 1 2 3 4 5 6 7 8 9 10 Went really well/
lack of focus/ completely focused/
off plan followed plan

Comments (e. g., What was on, what was off, what needs work or adjustment?)

When you were going best, where was your focus?

Were you able to fully extend yourself during the event (how much did you push)?
Did not extend O l 2 3 4 S 6 7 8 9 10 Completely extended
myself at all myself (to the limit)

Did you have occasion to draw upon a refocusing plan at any time of this
competition (before, during, or after)?

Yes No

 

If yes, comment brieﬂy (e.g., were you able to call upon a plan, did it work?)

 

(Cont.)

136

 

 

 

Competition Evaluation Plan Form B (Cont. )

12. Did you experience any communication or interpersonal problems surrounding this
event?

Yes No

 

If so comment brieﬂy (i.e., What was the problem and were you able to deal with it
adequately?)

137

u“

 

APPENDIX G

Figure 1a. Post Game, Post Season Means for State Sport-Conﬁdence Inventory

138

 

State Sport-Conﬁdence

 

 

100 - X = experimental team
' O = control team
- X
95 ~
' O X
: 0
9O -
_ O
85 -
- X X
80 r-
75 -
7O -
' O
65 -
é
I l l 1 1
po-gl po-gZ pO-g3 po-S

Game

Figure la. Post Game, Post Season Means for State Sport-Conﬁdence Inventory.

139

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