Abstract
    The purpose of this study was to explore the relationship between attributional style, anxiety, and athletic performance. Seligman’s (1984) Attributional Style Questionnaire (ASQ) was used to assess general attributional style. Martens’ (1977) Sport Competition Anxiety Inventory (SCAT) was used to assess trait anxiety while state anxiety was measured by the Competitive State Anxiety Inventory (CSAI-2; Martens et al., 1982). Twenty-two male and female long-distance runners from high school, adult, and casual teams completed the ASQ and SCAT during the week of a race. During the competitive setting, subjects completed the CSAI-2 approximately 3 hours before the start of the race. A finding unique to this study was that the high school runners experienced the greatest amount of Cognitive A-state anxiety, previous to the race. Findings also suggested support for a relationship between attributional style and state anxiety. No relationship was found based on trait anxiety or perceived performance. Thus, it is suggested that in attempting to understand the relationship between anxiety and performance, the manifestations of anxiety should be studied in the context of the competitive setting, not at the trait level.
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  Introduction
    The relationship between anxiety-related emotional states and performance outcome has been a topic of interest among sport psychologists over the past twenty years (Gould, Tuffey, Hardy, & Lochbaum 1993). Of particular importance to sport psychologists is the question of whether there is a way in which the effect of anxiety, on performance, could be predicted. If antecedents could be determined, sport psychologists could further their understanding of the mental preparation that occurs, resulting in the level of athletic performance.

    One particular field of research, which is increasing interest, is that of attributional style. Attributional style plays a large role in the way in which an individual will react to the anxiety that is present at the competitive level (Santamaria, & Furst, 1990). Attributional style may also be indicative of the way in which the individual will perceive his or her performance outcome, as portrayed through their pre-race anxiety levels. It is the intricate relationship between an athlete’s style of attributions, his or her pre- race anxiety levels, as well as performance outcome,that requires further investigation.

Research of the Anxiety-Performance Relationship
    In examining the relationship between anxiety-related emotional states and performance outcome, various approaches have been taken. These include general arousal-based approaches, general anxiety-based approaches, and multidimensional anxiety-based approaches.

General Arousal-Based Approaches
    Until recently, all of the literature has been dominated by general arousal-based explanations (Jones, 1995). These explanations include drive theory and the Inverted-U hypothesis. The most popular, the Inverted-U hypothesis has dominated for the past 20 years (Landers, & Boutcher, 1986).  This theory, developed by Yerkes and Dodson (1908), is based upon the notion that all individuals have a unique optimal arousal level. For each of our behaviors, maximum performance can only occur if we have reached a moderate level of arousal. Any levels of arousal that are above or below this amount will result in a decreased level of performance. Also, as the complexity of the performance increases, the optimum moderate level of arousal must decrease (Jones, 1995).

    Until recently, this hypothesis was considered to be a valid predictor of sports performance. However, various problems have been found with the validity behind this hypothesis. One of the major criticisms of this theory is found in its failure to explain why performance is impaired at arousal levels above and below the optimum (Eysenck, 1984; Landers, 1980). Also, Eysenck (1984) claims the theory ignores the various specific effects upon information-processing efficiency.

    Another theory, evolved from the inverted-U hypothesis, is reversal theory (Apter, 1982). This theory states each individual has meta-motivational states that exist together in opposite pairs. One state seeks seriousness, while the other seeks arousal. Depending on which state the athlete exists, they will either experience an aroused or a calming effect (Jones, 1995).This theory is criticized for looking at anxiety and arousal from a unidimensional approach. This approach is out-dated, in it’s failure to account for the highly differentiated pattern of arousal among individuals (Jones, 1995).

General Anxiety-Based Approaches
    General anxiety-based approaches began with the state-trait approach. Speilberger’s state-trait approach was developed in 1966, along with his State-Trait Anxiety Inventory (1966). According to Speilberger, "State anxiety refers to an existing or immediate emotional state characterized by apprehension and tension. Trait anxiety is a predisposition to perceive certain situations as threatening, and to respond to these situations with varying levels of state anxiety" (Martens, Vealey, Burton, 1990, p.5).

    Speilberger’s conclusions were that both high and low levels of anxiety would interfere with performance. Therefore, a moderate level of anxiety arousal would promote optimum performance. This theory actually supported the Inverted-U hypothesis.  The research in this area looks at optimal anxiety states, and is very similar to optimal arousal theory. Some research has even gone so far as to explore the hypothesis that the level of anxiety, which is present at the competitive level, has psychological benefits which non-competitive exercise does not produce (Clingman, & Hilliard, 1989).

    Clingman and Hilliard (1989) studied the relationship between competition and anxiety in adult athletes. Clingman and Hilliard looked at the effects of performance results on the athlete’s anxiety. This differs from most other research, which has examined how the precompetition anxiety level effects performance, rather than the other way around.  Clingman and Hilliard (1989) found a significant relationship between a successful race subsequent of anxiety reduction. They also found that a decrease in anxiety level only resulted if the runner performed as well, or better, than their expected successful performance. If they performed unsuccessfully, an anxiety reduction did not occur.  Clingman and Hilliard (1989) believe the decrease in anxiety from trait levels, for the successful runners, shows the post-race reductions in anxiety were not just a function of an elevated pre-race anxiety level, but were an actual departure from the runners’ usual arousal state. Thus, this study suggests that a successful competition may be beneficial to one’s psychological health.

    Another attempt, at explaining the anxiety-performance relationship, was performed by the Russian sport psychologist, Yuri Hanin (1980). Hanin found the optimal level of pre-competition anxiety, needed for best performance, differed substantially between individuals. He noted that either high arousal, moderate arousal, or a complete relaxation state would affect each individual differently (Hanin, 1980, 1986).

    This approach differed from the inverted-U theory in that it argued that optimal performance could occur at various levels of anxiety, for a given individual, rather then at one specific level for all athletes (Hanin, 1980). Thus, Hanin took an individualistic approach in order to determine the optimal anxiety-performance relationship. Hanin believed that no relationship could be found between anxiety and performance, for groups of athletes. Instead, the pre-competition anxiety zone must be determined for each individual athlete (Hanin, 1980).  Hanin’s Zone of Optimal Functioning Approach (ZOF) claims a person’s ZOF can be obtained by determining a performer’s mean pre-competition state anxiety score plus or minus four points, on Speilberger’s State-Trait Anxiety Inventory (Gould et al.,1993).   It presumes an athlete will always perform their best when they reach their individual optimal zone of functioning. One of the major limitations of this theory was the fact that the central measuring instrument, The State-Trait Anxiety Inventory, was non sport-specific; it failed to measure sport-specific multidimensional anxiety (Gould et al., 1993).

Multidimensional Anxiety-Based Approaches
    Research in the multidimensional anxiety ?based approaches began in the late 1960’s and early 1970’s, with a focus on the actual source of stress on the athlete (Jones, 1995). Recent studies, taking the multidimensional approach, focus on the source of cognitive and somatic state anxiety, as well as self-confidence, as being those factors that would influence the athlete’s expectations of his or her performance.

    Martens (1977) felt that a sport-specific competitive trait anxiety scale would better predict competitive state anxiety and behavior than would a general trait scale. Thus, he developed the Sport Competition Anxiety Test (SCAT).  Trait anxiety is defined as being "A predisposition to perceive certain environmental stimuli as threatening or non-threatening, and to respond to these stimuli with varying levels of A-state"(Martens, Vealey, Burton, 1990).  Martens went on to refer to trait anxiety as ‘A-Trait’; believing it described an individual’s difference in either perception of threat, A-State response to perceived threat, or both (Martens, Vealey, Burtons, 1990). Thus, SCAT was developed in order to provide a reliable and valid measure of competitive A-trait.

    A sport-specific competitive anxiety scale was soon found to be needed. Martens modified Speilberger’s State Anxiety Inventory (SAI), and went on to develop the Competitive State Anxiety Inventory(CSAI) ( Martens, Vealey, Burtons, 1990). Through ongoing research, other components of anxiety were identified to play an important role in predicting and explaining behavior.  These components ? cognitive and somatic anxiety; and self-confidence- were found by Martens to be highly relevent to competitive sport. Thus, Martens, now joined by Robin Vealey and Damon Burton, developed a second version of the CSAI. This updated version was made to assess these three components within the realm of competitive sport. This new test was named the Competitive State Anxiety Inventory ? II (CSAI-2) (Martens, Vealey, Burton, 1990).

    The authors of the CSAI-2 focused on distinguishing between cognitive and somatic A-state in understanding competitive activity. Cognitive A-state was defined by Martens, Vealey, and Burton (1990) as "being associated with worry" (p.120). They stated "In sport, it is most commonly manifested in negative expectations about performance, and thus negative self-evaluation; both of which precipitate worry, disturbing visual images or both"(p.120).
They went on to define somatic A-state as "referring to the physiological and effective elements of the anxiety experience that develops directly from autonomic arousal. Somatic A-state is reflected in such responses as rapid heart rate, shortness of breath, clammy hands, butterflies in stomach, and tense muscles"(p. 120).

    In a study conducted by Gould et al. (1993), it was attempted to test the utility of Hanin’s ZOF hypothesis by using the CSAI-2; a sport-specific multidimensional state anxiety measure. The study consisted of a sample of 11 middle distance and long distance runners from a Division I university track team. The mean age of the runners was 20.5, and there was a range of 1-5 years of collegiate competition. First, their optimal state anxiety was assessed by the CSAI-2, in which they were asked to assess how they felt prior to their best performance within the last 2 years. Next, the individual state anxiety levels of each athlete were measured prior to each competition throughout the season. Each athlete was asked to complete the 27-item CSAI-2 form within 24 hours after competiton, based on how they felt immediately prior to the race. Finally, both subjective and objective performance measures were obtained for each of the runners, for every meet. The objective measure of performance was calculated by subtracting the actual race time from the runner’s goal time, and then dividing by actual race time. The subjective measure of performance was taken based on how the athlete felt that he or she performed, due to the weather; illness; competition; or time of season, for example. These feelings were rated on a 0-10 point Likert-type scale that ranged from poor to excellent performance (Gould et al., 1993).

    The results of this study found support for Hanin’s notion of a zone of optimal functioning. The results showed a relationship between each runner’s CSAI-2 distance and his or her ZOF and subjective performance. Thus, the greater the distance from the runner’s ZOF, the worse that he or she performed (Gould et al., 1993). This study was helpful in extending Hanin’s ZOF principles to the CSAI-2, which is a sport specific multidimensional measure of anxiety. Thus, ZOF can be connected to cognitive and somatic anxiety (Gould & Tuffey, 1993). In order to better examine the specific nature of the competitive anxiety response, and its relationship to performance, understanding multidimensional anxiety-based approaches is pertinent to further research.

Comparing Cognitive vs. Somatic Anxiety
    Another major influence on performance may include one’s own personal perception of their ability to succeed (Jones, 1995). According to Jones (1995), further research into anxiety antecedents, as being determinants of performance, is greatly needed in order to further enhance the mental preparation of sports performers.  Lazarus and Folkman (1984), suggested further investigation on anxiety antecedents, would enable sport psychologists to gain a broader perspective on stress management strategies, and most importantly, help to further our understanding of problem-focused coping styles. By understanding those factors, which are antecedents to both somatic and cognitive anxiety, researchers could come to a better understanding of how anxiety affects the athlete’s performance.

    Various environmental factors, which are related to the athlete’s expectations of success, are hypothesized to be antecedents of cognitive anxiety and self-confidence. These factors include one’s perceptions of his or her ability, as well as an opponent’s ability.  Those antecedents of somatic anxiety are considered to be of shorter duration, mostly consisting of conditioned responses to stimuli (Gould, Petlichkoff, & Weinberg, 1989). Antecedents of somatic anxiety are thought to be non-evaluative, of shorter duration and consist mainly of conditioned responses to stimuli, such as changing room preparation and pre-competition warm-up routines. Perhaps through understanding how individual differences can influence the frequency of cognitive intrusions, psychologists can get a better picture of how these intrusions affect the athlete’s performance.

Research of Self-Confidence
    Recently, researchers have begun to look more at how the individual actually interprets his or her anxiety symptoms. According to Jones(1990), the role that self-confidence plays in the anxiety response, and also in the anxiety-performance relationship has been an ever-increasing topic of debate. Bandura (1977) believed change in one’s behavior was due to their individual efficacy expectations. He argued that one’s own cognitive thoughts concerning their self-efficacy could result in reducing their anxiety. Thus, Bandura (1977) suggested self-efficacy as mediating the relationship between control and coping behavior.  In examining competitive state anxiety, it was proposed that self-confidence and cognitive anxiety are at two polar extremes of a cognitive evaluation continuum (Martens, Burton, Vealey, Bump, & Smith, 1990).  Also, recent studies that looked at antecedents of cognitive anxiety and self-confidence contribute to the belief that these two factors are very independent from one another.

    The work by Jones, Swain, & Hardy, (1993) proposed that self-confidence may have the ability to protect against potential debilitating anxiety effects. If this is the case, then it would be helpful to further examine the ways in which athletes view their self-confidence levels, and whether or not these beliefs can lead to a debilitating or facilitating effect on the anxiety-performance relationship.  Donzelli and Dugoni (1990), found facilitative and debilitative effects of anxiety may be due to the particular type of competition the athlete is involved in. The study distinguished between open-skill sports, which don’t require forming to a particular pattern, and closed-skill sports that are highly routinized.

    The study found higher levels of anxiety may be facilitative in performance of closed-skill sports (such as gymnastics, diving, or running), whereas anxiety was found to be debilitating to the performance of open-skilled sports (such as wrestling or racquetball). This was thought to be because open-skilled performances require more split-second decisions, which can be altered with anxiety (Donzelli & Dugoni, 1990).
We have seen that one way to examine how an individual functions, according to their own self-confidence effects, is to look at what the individual attributes to be the cause for his or her own success or failure. Thus, it is important to look at their individual attributional style.

Research on Attributional style
    The effect of one’s attributional style, in determining their performance outcome, has become a new focus of investigation among sport psychology research.  Causal Attribution Theory was founded by Fritz Heider, and was later refined by the efforts of Weiner in 1979 (Weiner, 1985). According to Santamaria & Furst (1990), attribution theory attempts to "Explore the intricate processes that we go through in order to identify the causes for our behaviors, the behaviors of others, and for various life events"  (p.43).  Weiner (1985) developed an attribution categorization system that incorporated the three causal dimensions of locus of causality, controllability, and stability.

    Santamaria and Furst (1990), attempted to investigate causal attributions for successful and unsuccessful sport performances, along Weiner’s (1979) 3 causal dimensions of locus of causality, stability, and controllability.  The study began by having subjects examine attributions for successful and unsuccessful performances, immediately following their performance. It was hypothesized that those attributions, which were given for most successful and least successful performances, would differ from other successful or unsuccessful performances.  The subjects completed the revised Causal Dimension Scale, used to assess the causal dimensions of locus of causality, stability, and controllability for the open-ended causal attributions that subjects assign to a particular outcome (Santamaria & Furst 1990). Subjects were then asked to reflect back upon their most successful and least successful races in their careers. Finally, they were asked to complete two Causal Dimension Scales, one for the causal attribution given for their most successful race, and one for the causal attribution of the least successful race (Santamaria, & Furst 1990).

    Results found that runners gave more internal attributions for their most successful races than for their least successful races. These findings suggest that a self-serving bias may have been present, since athletes were examining those performances that were MOST or LEAST successful.  This self-serving bias may cause the athlete to attribute more internal causes for success in order to feel as though they have more control over their performance. The study also hinted at a difference in causal attributions for an athlete’s most and least successful performances. This type of information could lead to further implications for enhancing performances (Santamaria, & Furst 1990).

    More recent studies have begun to examine the effects which trait and situational self-handicapping can have on an athlete’s performance. Jones and Berglas (1998) report that "Self-handicapping has come to represent the proactive use of strategic behavior in the forms of reduced effort or self-reported excuses in order to protect one’s self-esteem and sense of personal competence from threat" (p.202). Thus, an athlete is able to control the causal attribution of a potential success or failure in order to minimize the loss of any perceived self-esteem, along with the emotional distress that this may cause.

Self-Handicapping Effects on Anxiety
    Snyder (1990) suggests that athletes who develop self-handicapping strategies may perceive an event as less threatening, and thus they would respond with lowered levels of state anxiety.  Ryska, Yin, & Cooley (1998), however, note that no psychological research has been done to evaluate the role of self-handicapping behavior on the pre-competition effect  (i.e., state anxiety), among a sport population. His study sought to look at this effect.

    The study began by giving a sample of 239 cross-country runners the Sport Competition Anxiety Test. This was used to measure the way in which they tended to respond to competitive sport situations, with varying levels of state anxiety.  In order to measure pre-competitive anxiety, athletes were given the Competitive State Anxiety Inventory-2 (CSAI-2). Next, the individual ability of each runner to utilize self-handicapping behavior, was assessed by using the Self-Handicapping Scale (SHS). Finally, the actual self-handicapping strategies, themselves, were assessed through an open-ended response format.

    The study hypothesized "Competitive anxiety among high trait and situational self-handicapping athletes would be significantly lower compared to that reported by their low situational-handicapping counterparts" (Ryska et al., 1998, p.53). However, it was found that those athletes who were high trait-handicappers lacked the buffering effect of situational self-handicapping, but that both trait and situational self-handicapping were associated with greater cognitive and somatic state anxiety.  Ryska et al.’s (1998) explanation for these findings was that "levels of state anxiety reported by athletes may not merely reflect their pre-competitive cognitions and affect, but are, at least in part, presented as a self-protective strategy (i.e., self-handicap) in the anticipation of competitive failure" (p. 53).  Higgins and Snyder (1989) suggest that various factors ? including competitive level, athlete’s psychological skills, and sport type- may influence the actual degree to which state anxiety would be used as a self-handicap. It is important to note, an increase in the actual anxiety symptoms could produce debilitating effects upon the athlete’s performance. However, an increase in the perception of anxiety may actually prove to be a facilitating motivator (Greenberg, Pyszcynsk, & Paisley, 1985).

Individual Attributional Factors Affecting Anxiety
    An athlete’s perception of his or her anxiety can have extremely various effects from person to person. Another way researchers have begun to explore these different effects is by looking at the how they determine Learned Helplessness (LH), and empowerment, among individuals. LH is defined as "A debilitating cognitive state in which individuals often possess the requisite skills and abilities to perform their jobs, but exhibit sub-optimal performance because they attribute prior failures to causes which they cannot change, even though it is possible in the current environment" (Constance, Martinko, 1998; p. 173).

    Empowerment is defined as "A cognitive state that results in increased intrinsic task motivation" (Constance, Martinko, 1998; p.1). Although empowerment and LH are complete polar opposites, they both affect the way in which a person is motivated to behave.  The concepts of empowerment and Learned Helplessness are similar to Rotter’s (1966) ideas concerning locus of control. Rotter believed that a person with an internal LOC attributed events as being caused by their own personal behavior, or beliefs. If a person had an external LOC, they would tend to attribute the cause of events to be due to environmental factors which they couldn’t control (Rotter, 1966).  The reformulation of learned helplessness theory, by Abramson, Seligman, and Teasedale (1978), presents four dimensions along which a person’s attributions can be characterized. These include locus of causality, stability, globality, and controllability.

    Locus of causality refers to whether or not the event was caused by an internal or external location, to the self. Stability refers to how long the cause is expected to last. A stable attribution expects a cause of long duration, whereas an unstable attribution expects a cause of a shorter duration.
Globality refers to how significantly the cause will effect other situations. A global attribution refers to a far-reaching cause, whereas a specific attribution is a cause of narrow-range. Controllability refers to whether or not the cause is controllable, by the person who is experiencing it (Abramson, Seligman, & Teasedale, 1978).  Controllability becomes an important issue with people who experience LH. These individuals believe they do not have control over the outcome of a particular experience. (Greenberger & Strasser, 1986).  According to Constance and Martinko (1998), a person will use the cues that they obtain from the environment, coupled with their own individual differences, in order to determine their attitudes regarding their performance.  Thus, a person’s attributional style, coupled with their global assessments from past experiences, will have a major impact on the way in which they behave (Constance, Martinko, 1998).

    The two attributional style measures, which are currently being examined, are the Attributional Style Questionnaire (ASQ), and the Reformulated Attributional Model of Learned Helplessness (RAM).  The ASQ measures a person’s causal explanations for a particular event (Seligman, Abramson, Semmel, & von Baeyer, 1979). RAM is used to measure the way in which a person will attribute their reactions from past events, in order to determine future performance responses, in achievement and health-related situations (Hale, 1993).  Thus, if a person consistently fails to reach a certain level of performance, he or she will begin to believe that they cannot improve, and thus will reduce their efforts (Hale, 1993). RAM attributes a person’s causal explanations according to the dimensions of internal-external; stable-unstable; and global-specific (Hale, 1993). Thus, with further research, sport psychologists are looking at the RAM and ASQ tools to reliably determine what the athlete attributes to be the cause of his or her performance outcome. Depending on how the athlete makes attributions, they may be either helping to improve or hinder their performance outcome.

Research of Attributional Style as an Antecedent to the Anxiety-Performance Relationship
    The previously mentioned research, which examines the effects of one’s individual attributional style on his or her performance outcome, can also be connected with other personality traits.  Archer (1979) found that a person’s general expectation of his or her own level of control can influence their behavior outcome only if there are inadequate clues indicating the level to which the behavior can actually be controlled. Archer went on to find, in an experiment in which participants were examined to see how much control they could exercise over a shock, participants who had high trait anxiety, as well as those who had low trait anxiety showed no difference in their expectation of control. However, when the situation was ambiguous, it was found that trait anxiety could influence their expectations (Archer, 1979).

    The effect of one’s attributional style, on his or her ability to control their anxiety levels, is very applicable to the area of athletic competition.
In accordance with the ideas of Rotter (1966), it has been found that a decrease in anxiety level usually results at the noncompetitive level. On the other hand, competitive physical activity can alter anxiety levels, according to the expected level of performance (Clingman, Hilliard, 1994).
Rotter (1966) suggested that a person would exhibit attributional styles in order to determine their level of control over a situation, only when he or she is unable to gain sufficient cues about the level of possible control over the situation. In conjunction with this idea, Clingman & Hilliard (1994) found that performance at the competitive level may cause the athlete to rely upon their own attribution styles in determining their level of success.  Thus, depending on the beliefs of the athlete about the level of control he or she has over their performance, their anxiety levels may be affected. Depending on the way in which they are affected by their anxiety, their performance outcome may either be facilitated or debilitated (Clingman, & Hilliard, 1994).

    In a recent study, Cingman and Hilliard (1994) examined a group of adult 5-km runners. A significant decrease was found in the levels of state anxiety from pre- to post-race, with the successful runners. Also, there was a significantly lower post-race state anxiety for the successful runners compared to the unsuccessful runners (Clingman, Hilliard, 1994). Thus, perhaps the athlete’s expected level of perceived performance could have been a determinant of the anxiety that he or she experienced in this competitive environment.

The Present Study
    The current study is designed to explore the relationship between a competitive athlete’s attributional style; multidimensional state anxiety; and his or her perceived performance outcome. Competitive running yields the possibility for many factors to effect the athlete’s level of performance outcome. These factors may include time of day, the level of competition against a fellow runner, the difficulty of the course, or the general over all health perception of the runner. Thus, it is difficult to know how much control an athlete can have over his or her level of performance results. This makes it necessary for the athlete to make attributions, based on past performances, in determining how successful or unsuccessful they believe their performance will be.

    Within the realm of competition, a runner may experience a certain level of trait anxiety. Trait anxiety is indicative of the level at which state anxiety may affect the runner, once they are faced with the actual competition. As cited above, numerous studies have shown this level of anxiety to become either debilitating or facilitating to the athlete’s performance outcome. Investigating an athlete’s individual attributional style may help to determine the way in which his or her anxiety levels will affect their perceived performance outcome. Since the athlete is also making causal attributions, based upon how they believe that they will perform in the race, the athlete may be affecting the level of anxiety they are experiencing.

    Thus, a three-part relationship may be present. The athlete’s attribution style may be indicative of the amount of pre-competition state anxiety they are experiencing, as portrayed through their perceived race performance time. Thus, an athlete’s individual attributional style may acts as an antecedent in interpreting whether their pre-race state anxiety symptoms will have a more facilitative or debilitative effect upon their perceived performance outcome.
My hypothesis being, an athlete who experiences a more positive attributional style will exhibit a positive expectation of the level of his or her race success. This will also relate to the level of Cognitive A-state anxiety which the athlete is experiencing during pre-race conditions.
Thus, the way in which an athlete makes attributions, coupled with his or her global assessments from past experiences, will have an impact upon their level of pre-race Cognitive A-state anxiety, in accordance with the athlete’s expected level of performance.
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Method
    Participants.
    A total of 22 competitive long-distance runners (15 men and 7 women, mean age= 35) volunteered to participate. The participants were divided among three individual groups. The first group was consisted of six high school cross-country team runners, ages 15-18. This group was tested during the week of a class qualifier, 5-K race. The second group consisted of eight adult runners, ages 41-73. The group was tested during the week of a competitive 5-mile road race. The third group consisted of five casual runners, ages 19-38. This group was tested during the week of a competitive 10-mile trail race.
All participants were treated in accordance with The American Psychological Association strict ethical principles, while all research was conducted in full compliance with the federal law.

    Materials.
    Within this study, an athlete’s attributional style is operationally defined as being the level of positive versus negative responses on the Attributional Style Questionnaire(ASQ) (Seligman, Abramson, Semmel, & vonBaeyer, 1979).  Trait anxiety is operationally defined as the total sum score measured by the Sport Competition Anxiety Inventory (SCAT) (Martens, 1977).  State anxiety is operationally defined based upon the total scores obtained on each of the three sub-scales of the Competitive State Anxiety Inventory-II (CSAI-2) (Martens, Vealey, Burton, 1990) ? Somatic A-state; Cognitive A-state; self-confidence.  Goal time is operationally defined as the measure, given by each individual athlete, as the time which he or she expects to complete the race in. Race time is operationally defined as the official time during which he or she completed the race.

    Three pen and pencil surveys were used. The Attributional Style Questionnaire (ASQ) was administered in order to determine the runner’s general causal explanations within everyday life situations (Seligman, Abramson, Semmel, &vonBaeyer, 1979). The ASQ is composed of 12 different hypothetical situations, consisting of six good events and six bad events. Each situation is followed by a series of four questions, used to measure the participant’s responses on the basis increasing internality, stability, and globality. Composite scores measure how positively the individual reacts to good situations, bad situations, and all situations.

    According to validity and reliability measures, Composit Positive minus Composit Negative (CPCN); Composite Negative (CoNeg); and Composite Positive (CoPos) scores were found to be the most valid & reliable (Seligman, Abramson, Semmel, & vonBaeyer, 1979). Therefore, the current study focuses on the composite scores rather than the individual dimension scores. The Sport Competition Anxiety Test (SCAT) was used in order to measure the athlete’s predisposition to respond with varying levels of A-state in competitive sport settings (Martens, 1977). The SCAT-A version was used, for persons aged 15 and older. The survey consisted of 15 statements, with which respondents had to indicate the level at which they agreed with each statement.

    Because face validity was very apparent among the 10 anxiety items, 5 simulation statements were added to reduce response bias (Martens, 1077). Validity of the SCAT was determined through the evidence gathered from 11 experimental and field studies. These studies supported the construct validity of SCAT as a valid measure of competitive A-trait. Evidence for reliability and internal consistency of SCAT was obtained using test-retest, ANOVA, & KR-20 analyses (Martens, 1977).

    The Competitive State Anxiety Inventory-II (CSAI-2) was used to measure the athlete’s level of existing states of cognitive A-state, somatic A-state, and state self-confidence in competitive situations (Martens, 1977).  The CSAI-2 is constructed of 27 statements, with which the respondent must indicate their level of agreeableness with, on a 4 point Likert-Type scale. According to Martens, Vealey, and Burton (1990), evidence has been found to support the construct validity of CSAI-2 as "a measure of sport ?specific A-state, somatic A-state, and state self-confidence, provided through a systematic progression of research studies" (p. 172).  Martens, Vealey, and Burton (1990) also acknowledged the fact that "Evidence for the reliability and concurrent validity for the independent subscales was accumulated and was consistent with the theoretical literature" (p. 140).

    Scoring.
    The ASQ was scored on three attributional dimensions ? internality, stability, and globality. The scales were scored so that positive situations received a high of 7 and a low of 1. On the other hand, negative situations received a high of 1 and a low of 7. The anchored scores(external, unstable, and specific attributions) were scored as optimistic. The unanchored scores (internal, stable, and global) were scored as pessimistic. Composite scores, composite positive (CoPos) and composite negative (CoNeg), were created through summing the positive, and then the negative scores on each of the three dimensions of attributional style. CoNeg is the sum of all of the negative scores, on each dimension. CoPos is the sum of all of the positive scores on each dimension.  Composite Positive minus Composite Negative (CPCN) was found by subtracting the CoPos minus CoNeg. The range of scores for CPCN is ?18 to 18; this score reflects how positively or negatively a person reacts to all events (Seligman, 1984).

    The Sport Competition Anxiety test (SCAT)(Martens, 1977), was used to obtain each individual’s trait anxiety measure. For each of the 15 items, three responses were possible; given SCAT scores a range from 10 to 30. The Competitive State Anxiety Inventory-II (CSAI-2)(Martens, Vealey,& Burton, 1990), was scored by computing a total for each of the three individual sub-scales. These scores ranged from a low of 9 to a high of 36.
The higher the individual’s score, the greater the cognitive or somatic A-state, or self-confidence. Each group was then separated into their individual categories ? the casual runners; the high-school cross-country team; and the competitive adult runners.

    Design and Procedure.
    Testing occurred in two sessions during the week of the competitive race, for each of the three groups. During the first session, the athlete’s were first asked to consent to participation through the signing of an agreement. Next, the Attributional Style Questionnaire was administered (Seligman, Abramson, Semmel, &vonBaeyer, 1979). After completion of the ASQ, participants were administered the Sport Competition Anxiety Test (SCAT).  On the day of the competitive race, each group was tested within two hours of the start of the race. The athlete’s were administered the Competitive State Anxiety Inventory-II (CSAI-2), and were asked to write down their goal race time at the top of their paper. Finally, each participant was debriefed by being given a summary of the study. For each of the pen and pencil surveys, during the two testing meetings, participants were given as much time as they wanted, in order to complete each survey. At the end of the race, I obtained each athlete’s official race time. This procedure was followed for each of the three groups.
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Results

    SPSS version 10.0 was used to statistically analyze all data. The mean, range, and standard deviation of each participant was calculated (see Table 1).
 
 

 
 
 
 

	N	Minimum	Maximum	Mean	Std. Deviation
Act. Time Age  Cog. A-state CoNeg CoPos CPCN Goal Time SCAT Self-confidence Som.A-state Valid N (listwise)	18 22 20 22 22 22 19 22 20 20 18	17.46 17.00 13.00 8.80 11.00 -1.50 17.40 13.00 1 1	122.00 73.00 34.00 17.80 20.20 6.00 120.00 29.00 14 13	55.4961 34.5455 19.9000 13.8636 15.7091 1.8455 53.8621 21.7727 7.70 6.05	41.8701 18.1284 6.5365 2.1652 1.8779 2.3468 40.8972 4.4286 3.92 3.35

    Each group was separated according to the level at which they competed ? high school cross-country team; casual runners; and adult competitive road race. Bivariate correlations were run for each of the three groups, in order to examine the relationships among the following variables: goal time, actual time, self-confidence, cognitive A-state, somatic A-state, CPCN, CoNeg, CoPos, and SCAT. An alpha level of .05 was used for all statistical tests.

    The results of the Pearson product-r correlations for the high-school cross country team runners suggested significant positive correlations between cognitive A-state anxiety and CoNeg attributional style (p=.854*). Significant positive correlations were also suggested between Self-Confidence and CoNeg (p=.902*). Actual time and goal times were found to negatively correlate with Somatic A-State anxiety, and Cognitive A-State anxiety levels (see Table 2).
 
 

High School Runners(n=7)

1.CPCN	1.00	-.949**	--	--	--	--	-.976**	--	-.912*
2.CoNeg	-.949**	1.00	--	--	--	--	--	--	--
3.CoPos	--	--	1.00	--	--	--	--	--	--
4.SCAT	--	--	--	1.00	--	--	--	--	--
5.GoalTime	--	--	--	--	1.00	.997**	-.955**	-.861**	--
6.Act.Time	--	--	--	--	.977**	1.00	-.962**	-.877**	--
7.Cog.ASt	-.976**	.854*	--	--	-.955**	-.962**	1.00	.894**	.624*
8.Som.ASt	--	--	--	--	-.861**	-.877**	.605*	1.00	.781*
9.Self Conf	-.912*	.902*	--	--	--	--	.624*	.781*	1.00

Note. All nonsignificant bivariate correlations were omitted.
* Correlation is significant at p<.05 (two-tailed)
** Correlation is significant at p<.05 (two-tailed)

    The correlations performed on the group of casual runners were found to suggest positive relationships between Cognitive A-State and CoNeg 9p=.854*). Significant positive correlation was also suggested between Self-Confidence and CoNeg (p=.902*). Negative correlations were suggested of actual time and goal time related with Cognitive A-State and Somatic A-state (see Table 3).
 
 

 
 
 
 

Subscale	1	2	3	4	5	6	7	8	9
1. CPCN	1.00	-.946*	--	--	--	--	-.976**	--	.912*
2.CoNeg	-.946*	1.00	--	--	--	--	--	--	.902*
3.CoPos	--	--	1.00	--	--	--	--	--	--
4.SCAT	--	--	--	1.00	--	--	--	--	--
5.GoalTime	--	--	--	--	1.00	.997*	-.955**	-.861**	--
6.Act.Time	--	--	--	--	.997*	1.00	-.962**	-.877**	--
7.Cog.ASt	-.976*	.854*	--	--	-.955**	-.962**	1.00	.894**	.895*
8.Som.ASt	--	--	--	--	-.861**	-.877**	--	1.00	--
9.Self Conf	-.912	.902*	--	--	--	--	.895*	.781*	1.00

Note. All nonsignificant bivariate correlations were omitted.
* Correlation is significant at p<.05
** Correlation is significant at p< .01
 

    For the group of competitive adult runners, positive correlations were suggested between Cognitive A-State anxiety and CoNeg (p=.854*). Self-Confidence and CoNeg were suggested to have positive correlation (p=.902*). Goal time and actual times were suggested to negatively correlate with both Cognitive A-State and Somatic A-State (see Table 4). For all correlations, alpha was set at the .05 level.

Adult Competitive Runners (n=11)

Subscale	1	2	3	4	5	6	7	8	9
1.CPCN	1.00	--	--	--	--	--	-.976**	--	-.912*
2.CoNeg	-.949**	1.00	--	--	--	--	.854*	--	.902*
3.CoPos	--	--	1.00	--	--	--	--	--	--
4.SCAT	--	--	--	1.00	--	--	--	--	--
5.GoalTime	--	--	--	--	1.00	.956**	-.955**	-.861**	--
6.Act.Time	--	--	--	--	.956**	1.00	-.962**	-.877**	--
7.Cog.ASt	-.976*	.854*	--	--	-.955*	-.962**	1.00	.894**	--
8.Som.ASt	--	--	--	--	.795	-.877**	.894**	1.00	--
9.Self.Conf	-.912*	.902*	--	--	--	--	--	.781*	1.00

Note. All nonsignificant bivariate correlations were omitted.
* Correlation is significant at p<.05
** Correlation is significant at p<.01

    Three Univariate Analyses of Variance (ANOVA) were calculated in order to test between-subjects effects. The first one-way ANOVA was calculated with “Total New”(the total sum of all three subscales of CSAI-2, for state anxiety) as the dependent variable. Independent variables were based on each Runner Type (casual, adult, and high-school). Degrees of freedom (1,20); F (5.779); Mean squares(318.706); and significance (p=.012) were calculated.
    Post-Hoc testing revealed the mean difference between Runner Type groups, for Total New, was most significant with the high school runners. As shown in Table 5, a Tukey HSD reveals significance (at the .05 level) was found based on observed means for Runner Type.
 
 

 
 
 

(I)Run Type	(J) Run Type	Mean	Std.	Sig.	95% Conf. Int	95% Conf. Int
		Diff. (I-J)	Error		Lower	Upper
Casual	Adult	-3.622	4.142	.633	-14.249	7.004
	High School	-14.233*	4.497	.015	-25.770	-2.697
Adult	Casual	3.622	4.142	.663	-7.004	14.249
	High School	-10.611*	3.914	.037	-20.652	-.5700
High School	Casual	14.233*	4.497	.015	2.697	25.770
	Adult	10.611*	3.914	.037	.570	20.652

  Note. The mean is significant at the .05 level

    The estimated marginal means of Total New, for Runner Type revealed a significant increase in state anxiety levels of the high school runners, pre-race, as opposed to the amount of increase seen in both the adult and casual runners (see Figure 2). The marginal means of the runners were based on mean scores for the total of each of the three subscales of the CSAI-2. These means were based on an N of 5, 9, and 6 for the casual, adult and high school runners, respectively.
 

Figure 2
 
 

    A second univariate ANOVA testing cognitive A-state anxiety, based upon Runner Type, revealed significance at .001 (based upon alpha .05).Post Hoc testing (see Table 6) revealed the high school runners as indicating the highest levels of cognitive A-state anxiety, based on observed means.

(I) Run Type	(J) Run Type	Mean	Std	Sig.	95% Conf. Int	95% Conf. Int
		Diff. (I-J)	Error		Lower	Upper
Casual	Adult	-1.56	1.54	.579	-5.50	2.39
	High School	-6.83*	1.67	.002	-11.11	-2.55
Adult	Casual	1.56	1.54	.597	-2.39	5.50
	High School	-5.28*	1.45	.006	-9.00	-1.55
High School	Casual	6.83*	1.67	.002	2.55	11.11
	Adult	5.28*	1.45	.006	1.55	9.00

Note. The mean difference is significant at the .05 level.

    The mean differences (seen in Figure 3) represent the estimated marginal means of cognitive-A state anxiety, as seen among each of the three Runner Type groups.

Figure 3
 
 

    One way ANOVA’s were also calculated for somatic A-state anxiety, as well as for self-confidence, based upon Runner Type. Significance was .000 (df = 1,20; F = 14.354; MS = 66.875). Analysis of Variance calculated for variance in self-confidence, based upon Runner Type, revealed insignificance at .631 (df = 2; F = .473; MS = 7.700).
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Discussion

     Support For Hypothesis. The results of the bivariate correlations indicate that significance was suggested between Cognitive A-State anxiety and Composite Negative attributional style, for all three Runner Types. This suggestive correlation is supportive of the original hypothesis, being that an athlete’s attributional style will relate to the level of Cognitive A-state anxiety that the athlete is experiencing during pre-race conditions. Significance was also suggested for a significant correlation between Self-Confidence and Composite Negative attributional style. This was found only in the adult competitive runners. This finding supports the hypothesized notion of attributional style relating to State anxiety.

    Non-significance was suggested between goal times and race times, in conjunction with attributional styles or anxiety levels. Thus, an athlete’s perceived-performance was not suggested to be related to his or her explanatory style, or to the anxiety experienced previous to competition. The results of the univariate ANOVA’s suggested a significant difference in pre-race State anxiety levels among the three Race Types. When subscales were examined, it was the Cognitive A-State anxiety that was suggested as having the most variance between each group.

    The high school cross-country runners displayed the highest levels of pre-race State anxiety levels, with Cognitive A-State  indicating the highest subscale mean sum. This report of variance, based upon State anxiety, was small, yet, significant. This is indicative of the small sample size of each group. (casual N=5; adult N=9; high school N=6).
However, support for the original hypothesis was illustrated with Cognitive A-State varying the most, between groups, of the three subscales on the State anxiety measure.

    Reasons For Non-Significance. Non-significant correlations were reported between each runners’ goal and race times, along with his or her individual measures of attributional style, as well as pre-race anxiety. However, goal race times and actual race times were significantly correlated with one another. This suggests that a relationship does not exist between an individual’s causal explanations for uncontrollable events, and the time in which they perceive they will complete their race. This also suggests a non-correlation between State or Trait pre-race anxiety levels, with the amount of time in which the athlete perceives he or she will finish the race. Small sample size could have had an effect upon the significance of race times correlated with either attributional style, or anxiety. However, all bivariate correlations were performed within groups, thus having an N of 20.

Review of the Literature. According to Martens, Vealey, and Burton (1990), it is important to measure  Cognitive and Somatic A-State anxiety separately. The conceptual arguments, and empirical evidence, show that these two components are derived from different antecedents. Therefore they both have different impacts on behavior.

    Our results suggest support for this claim. Between the three groups of runners, Cognitive A-State anxiety showed the highest level of variance, when compared with both Somatic A-State anxiety and Self-Confidence levels. Morris, Davis, and Hutchings (1981), suggested that cognitive anxiety is more resistant to change than is somatic anxiety. Therefore, it could be suggested, an athlete’s level of Somatic A-State anxiety and Self-Confidence anxiety will not vary, between groups, in a competitive setting, as much as the athletes’ Cognitive A-State anxiety levels. Because an athlete’s Cognitive A-State is indicative of negative expectations about success in performance, (Bandura, 1977; Feltz, Landers, & Raeder, 1979; Rosenthal, 1968; Weinberg, Gould, & Jackson, 1979), it is interesting to note that the high school runners showed the highest estimated means of Cognitive A-State anxiety.

    The significant correlations suggested of Cognitive A-State anxiety, and Composite Negative attributional style, further emphasizes the relationship between Cognitive A-State and negative expectations.  Composite Negative scores reflect the level at which an athlete positively, or optimistically, reacts to negative situations. Thus, the finding, Cognitive A-State and Composite Negative scores are related, supports the initial hypothesis that an athlete’s explanatory style may impact the level of anxiety which he or she experiences pre-competition.

    This raises the question of why the difference lies so heavily with high school runners, as compared to both the casual runners and adult competitive runners. Perhaps the level of competition was much higher for the high school runners, thus having a significant effect upon their cognitive anxiety levels.  Further research in this area may help to specifically examine the relationship between Cognitive A-State anxiety and performance, through analyzing more closely those factors that influence one’s expectations of performance.

    Influence of Trait Anxiety. Levels of Trait anxiety were not found to elicit a relationship with any other variables. Thus, SCAT measures did not correlate with any other variables. According to the interactional anxiety paradigm, state responses should be the best predictors in determining performance, because performance is the product of both person and situational factors (Martens, Vealey, & Burton, 1990). Therefore, trait responses do not have much of an impact on performance.
Because state responses were suggested to have the greatest impact upon runners, CSAI-2 state anxiety levels revealed the greatest variance between groups. As previously stated, Cognitive A-State suggested the greatest levels of variance, with Somatic A-State being next in line. Self-Confidence did not suggest significant levels of variance, within A-State. These findings reinforce previous demonstrations (Martens et al., 1982),that Cognitive A-State and Somatic A-State are more strongly correlated than Self-Confidence.

    Future Directions. Further research in the area of anxiety and performance may want to focus more specifically upon the aspect of performance. The evidence, suggested in the given study, found non-significant relationships between race times with the athletes’ anxiety levels and attributional style.  Future anxiety research is also crucial to understanding the discrimination between the emergence of Somatic A-State versus Cognitive A-State anxiety. Future research in this particular area would be helpful in relating these A-State components to an athlete’s causal explanations, through the understanding of their discriminating manifestation factors.
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References
 

Abramson, L.Y., Seligman. M.E.P., & Teasedale, J.D., (1978) Learned-helplessness in humans: Critique and reformulation, Journal of Abnormal Psychology, 87 (1): 49-74

Archer,R.P., (1979). Relationships between locus of control, trait anxiety and state anxiety: An interactionist perspective, Journal of Personality, 47, 305-316.

Apter,M.J., (1982). The experience of motivation: The theory of psychological reversals. London and New York, Academic Press

Bandura, A., (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191-215

Clingman, J.M.; Hilliard, D.V., (1994). Succeed and Relax, Journal of Sport Behavior, 17, 120-129

Clingman, J.M.; Hilliard, D.V, (1989) Anxiety reduction in competitive running as a function of success, Journal of Sport Behavior, 17(2), 120-129

 Eysenck, M.W. (1984). A handbook of cognitive psychology. London: Erlbaum

Feltz,D.L., Landers, D.M., & Raeder, U. (1979).Enhancing self-efficacy in high-avoidance motor tasks: A comparison of modeling techniques. Journal of Sport Psychology, 1, 112-122.

Gould, D.,et al.(1993). Multidimensional state anxiety and middle distance running performance: An exploratory examination of Hanin’s zones of optimal functioning hypothesis, Journal of Applied Sport Psychology, 5, 85-89

Gould, D., Petlichkoff, L., & Weinberg, R.S., (1984). Antecedents of temporal changes and relationships between CSAI-2 components. Journal of Sport Psychology, 6, 289-304.

Greenberg, J., Pyszczynski, T., & Paisley, C., (1985). Effects of intrinsic incentives on the use of test anxiety as an anticipatory attributional defense: Playing it cool when the stakes are high. Journal of Personality and Social Psychology, 47, 1136-1145.

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Consent Form

    The Runner study is divided into three parts. During the first part, I will be giving you two brief pen and pencil surveys. These will be given before the day of the competitive race. The first survey will be evaluating your individual attributional style. The second pen and pencil survey will briefly evaluate your general mood state. On the day of the race I will be asking you to fill out another brief survey, evaluating your mood state, before the start of the race. At this time I will also ask for you to write down your goal time, for that day’s race. Following the race, I will also need to aquire your official race time.
     Your completion of this study is fully voluntary. Should you decide not to participate at any time, please let me know and the procedure will be discontinued. If you have questions about this study, please feel free to contact me at : cneely@anselm.edu.
 After reading this description/informed consent form, I (sign here):

---------------------------------------------------- agree to participate in this study. I agree to let you access my race results for this specific race.

Date___/___/___
Please print your name:____________________  Date of Birth: ___/___/___
Parent’s Signature (If under 18)__________________________
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Debriefing Form
 
 

     Thank you for your participation in this study. Past research has shown an athlete’s attributional style, coupled with their global assessments from past experiences, can have a major impact on the way in which they perform. Further, competitive physical activity can alter anxiety levels, according to the expected level of performance. Thus, this study was designed to study the effect one’s attributional style may have on his or her ability to control pre-race anxiety levels, while controlling for expected level of performance. Thus, the relationship between attributional style, pre-race anxiety levels, and anticipated performance outcome are being examined in order to gain further insight into the mental preparation that occurs before a competitive athlete’s performance.
     Please sign the debriefing form to indicate your knowledge and understanding of this study. Should you have any further questions, please feel free to contact me.

Today’s Date:___/___/___              Signature_______________________

Thank you again for your kind assistance in my research project. Again, if you have any questions about this study, please feel free to contact me.

Christine Neely   (cneely@anselm.edu; phone: 1-603-656-6253)
Senior Psychology Major, Saint Anselm College
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