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In the Mind's Eye: Enhancing Human Performance (1991)

Chapter:11 Optimizing Individual Performance

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Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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11

Optimizing Individual Performance

One of the long-standing concerns of sports psychology has been an understanding of performance under pressure. Unlike the military, the “pressure” in a sport is not usually intended to put someone at risk of life and limb. Although fear of injury may create pressure in some sports, more frequently competitive pressure is associated with a threat to one's self-esteem.

Since the mid-1970s there has been interest among psychologists to use sports as a naturalistic laboratory in which to conduct research on performance under pressure. In this chapter we review the rather expansive sports literature in four areas: the relationship between the mental health model, mood, and motor performance; cognitive-behavioral interventions for sport and motor performance; preperformance routines (i.e., preparation rituals), sports performance and electrophysiological correlates associated with these routines; and the effect of exercise on reactivity to psychosocial stressors. In the last section, we turn to a different area of research, neuroscience, to consider broader issues of the brain and performance.

THE MENTAL HEALTH MODEL OF SPORTS PERFORMANCE

A recent mental health model of athletic performance (Morgan, 1985) posits that success in sports is negatively correlated with psychopathology: that is, anxious, depressed, hysterical, neurotic, introverted, withdrawn, confused, fatigued, or schizoid athletes do not perform as well in sports as athletes with more positive mental health profiles. Scientifi-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

cally speaking, Morgan's model may not seem very provocative, but its common sense and intuitive appeal has advantages in its gaining acceptance among the public (see Morgan, 1980).

Morgan maintains that his model has an intermediate level of complexity: that is, that the model can specify relationships [e.g., y = f(x)]. Morgan implies that the flow of causality is from psychological states to success in sports, not the other way around. However, he does not provide evidence for this flow, and it could be argued that the flow is in the opposite direction: that self-protective mechanisms may operate for athletes believing that they will not make a team or place first, which subsequently affects psychological states.

Morgan (1985:71) further maintains that this type of model “also predicts specific responses will be dependent upon specific stimulus conditions.” Although the model does not clearly spell out all of the stimulus conditions, its empirical basis suggests that it may be limited to certain types of sports. With few exceptions (LeUnes et al., 1986; Morgan, 1981), most of the evidence has come from sports that emphasize muscular or cardiorespiratory endurance —body building, cycling, karate, wrestling, speedskating, soccer, rowing, distance running, and swimming. The model has been applied to other types of performance tasks. (In considering the use of this model for military settings, it seems most appropriate for dynamic, large-muscle activities or cardiorespiratory endurance tasks that involve intense aerobic/anaerobic training over a period of months.)

The basic model is a between-subjects static model, consisting of predictions of desirable psychological states for optimal performance. It has also been extended to a within-subjects dynamic model consisting of monitoring athletes throughout different stimulus conditions associated with intense training. Morgan (1985) believes the evolving dynamic model will ultimately prove to be superior to the static model in understanding changes in athletic performance. We first present the static model to better understand its features, which are also incorporated into the dynamic model.

Static Model: The “Iceberg Profile”

Although Morgan's work is admittedly pretheoretical, the measuring instruments used to test the static model represent existing psychological theory applied to sports (e.g., Eysenck et al., 1982). Specifically, Morgan 's research has primarily focused on several standard psychological instruments: the State-Trait Anxiety Inventory (STAI) (Spielberger et al., 1970); the Profile of Mood States (POMS) (McNair et al., 1971/ 1981); the Eysenck Personality Inventory (EPI) (Eysenck and Eysenck,

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

1968, which measures extroversion, neuroticism, and conformity; the Somatic Perception Questionnaire (SPQ) (Landy and Stern, 1971); and the Depression Adjective Checklist (DACL) (Lubin, 1967). The conformity measure (i.e., lie scale) of the EPI was used throughout Morgan' s research to infer the validity of subjects' self-report responses. In some studies (Morgan, 1981; Morgan and Johnson, 1978), the Minnesota Multiphasic Personality Inventory (MMPI) was used in place of the other instruments.

To test the model, Morgan defined psychopathology as higher scores relative to college student norms on introversion, neuroticism, trait anxiety, tension, depression, anger, fatigue, and confusion, as well as on the MMPI clinical scales used to diagnose problems dealing with psychological adjustment. Thus, Morgan predicted that athletes displaying psychopathology—defined as one standard deviation above the 50th percentile on the scales—would have lower levels of performance compared with athletes displaying a more “positive mood profile.”

In a review of seven of his own empirical studies testing the static mental health model with pre-elite and elite athletes, he found a consistent pattern, relative to college student norms (McNair et al., 1971/ 1981): higher than average vigor and extroversion scores (i.e., positive characteristics for performance) and lower than average scores on the scales indicative of potential psychopathology. For example, on the POMS inventory, which has become most associated with tests of Morgan's mental health model (see LeUnes et al., 1988, for an annotated bibliography), the positive mood profile has become known as the “iceberg profile.” This term refers to the shape of the curve relative to 1967 college student norms when raw scores on the six scales are plotted on the POMS profile sheet; see Figure 2. Since vigor happened to appear on these scoring forms in a middle position among the other moods and since athletes typically score above the population average on vigor, the plot looked like an iceberg. 1

In all this research, the measured relationship of mental health to performance has been somewhat indirect. In no case were actual performances compared with athletes' responses on psychological inventories at the time the inventories were completed. Instead, they were inferred from final placement in competitions (e.g., 1st or 2nd) whether they made or did not make a team, or from expert ratings of elite runners within a 2-year period (Morgan et al., 1987a). In most studies the time span between athletes' completing the psychological inventories and the performance outcome was less than a week. In other studies in which trait measures (e.g., MMPI) were used, this time span was either much longer (as much as 4 years), or the response set used for the POMS (i.e., “past week including today”) did not necessarily include the time in

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

FIGURE 2 Comparison of profile of mood states of athletes and college student norms.

which the performances occurred (Morgan et al., 1987a). In spite of the rather crude performance measures, the findings have been remarkably consistent in showing that better athletes displayed a more positive mental health profile than athletes who were slightly worse (Morgan, 1985). The robust pattern generalized across several muscular and cardiorespiratory endurance-type sports and several samples of athletes. (Morgan also concluded that the findings were not likely due to response distortion since scores on the EPI lie scales were not correlated with any of the psychometric variables or performance.) The accuracy of the prediction was high but less than perfect. Using an a priori clinical analysis as the prediction basis, Morgan (1985) concluded that the accuracy of the prediction was between 70 and 80 percent and always exceeded base-rate or chance expectancies.2 Although Morgan's model suggests a high degree of predictive accuracy, he maintains that this level of precision is not acceptable for selection purposes.

Considering that in Morgan's (1985) early research the mental health model was capable of making fine-grain differentiations with reasonable accuracy among high-level performers, an important question is whether the findings have held up in more contemporary research studies by other investigators. Although several of the studies cited in the annotated bibliography of LeUnes et al. (1988) claim to support Morgan's iceberg profile, many of these studies made no statistical comparisons to

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

a control group. Instead, these studies simply plotted the means of a single group of athletes and contrasted them to the normative sample reported in the POMS test manual (McNair et al., 1971/1981). The unusually consistent findings relative to the test norms are likely due to an inappropriate comparison group; the norms were obtained from participants in psychological tests and students in psychology courses and “should be considered as very tentative” (McNair et al., 1971/1981:19). More recent studies of undergraduate college nonathletes (Boyle, 1987; Dyer and Crouch, 1987) demonstrate that the mean scores for tension, depression, and vigor have decreased over the past 20 years. This instability over time, which represents from 2-7 points on the various POMS subscales, and the current controversy surrounding the factor structure of the POMS (Boyle, 1987; Norcross et al., 1984; Reddon et al., 1985), suggests that the normative sample reported in the POMS manual is an inappropriate comparison group. Thus, studies of this type offer no convincing support for the iceberg profile and the mental health model.

A better test of the replicability of Morgan's findings for the mental health model are studies that provide comparison groups similar to those reported by Morgan (1985). We found 14 such studies that compared the POMS scores of two groups of athletes representing two levels of performance outcome (13 in LeUnes et al., 1988; Morgan et al., 1987b). Of the 148 total comparisons made with the six scales, only 27 (18 percent) were statistically significant and 24 (16 percent) in the predicted direction. The pattern predicted by the mental health model may have been present in these studies, but the power of the statistical tests may not have been sufficient to detect differences because of the small number of subjects. To examine this possibility, the directions of the 148 comparisons were examined relative to the predictions of the mental health model. As shown in Table 1, the percentage of supportive versus nonsupportive findings was calculated for each study. Compared to chance expectations of 50 percent supportive, these 14 studies yield an unimpressive overall average percentage of 53 percent supportive findings. As a whole, the findings from other investigators, as well as Morgan's studies (Morgan and Pollock, 1977; Morgan et al., 1987b), fail to clearly support the predictions of the mental health model.

In the face of these more recent findings, it is highly questionable that the POMS instrument, which is primarily used to test the mental health model, is sensitive enough to reliably differentiate among athletes who are already highly proficient. In addition to small samples and performance measures that have been indirect and often distally linked in time with psychological measures, the susceptibility of the POMS to distorting influences may also contribute to the lack of sensitivity in differentiating among athletes. For instance, Boyle (1987) has noted that

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

TABLE 1 Comparisons of the Outcomes and Directions of Performance Changes Predicted by the Mental Health Model

       

Comparisons in Predicted Direction

Study and Year

Sport

Na

Total Comparisons

Number

Percent

Craighead et al., 1986

Basketball

61

6

2

33

Daiss et al., 1986

Football

60

4b

1

25

DeMers, 1983

Diving

60

18

8

44

Dyer and Crouch, 1987

Running

40

12c

8

66

Guttman et al., 1984

Skating

11

18

14

77

LeUnes and Nation, 1982

Football

180

18

14

77

Miller and Miller, 1985

Netball

20

6

3

50

Morgan and Pollack, 1977

Running

19

6d

1

16

Morgan et al., 1987b

Running

27

6

0

0

Riddick, 1984

Swimming

79

18

9

50

Silva et al., 1981

Wrestling

15

6

4

67

Silva et al., 1985

Wrestling

86

6

6

100

Tharion et al., 1988

Running

34

6

3

50

Wilson et al., 1980

Running

30

18

18

100

a Number of athletes.

b Data not reported for two subscales.

c Comparisons between beginning runners and advanced runners at 3 hours and at 10 minutes prior to performance.

d Comparisons between world-class middle long distance runners and college middle distance runners.

social desirability and other response sets, inadequate self-insight, and item transparency affect POMS scores. Miller and Edgington (1984) have demonstrated the susceptibility of the POMS to response distortion or “faking good” when physical education students were led to believe the test results might influence team selection. The resulting extreme iceberg profile prompts considerable concern that the strong situational demands of team selection and placement in athletic competition may produce distorting influences that override instructions to subjects to answer the POMS as honestly as they can and that may be unique to the POMS and, thus, not detectable by the conformity scale of the EPI. Overall in fact, the static model has had limited success in predicting levels of athletic performance.

Dynamic Model: Measuring Overtraining

A more viable and methodologically sound approach of the mental health model may be to use measures of mood to monitor athletes across

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

different conditions of situationally induced pressure brought about by manipulating the training stimulus. This section reviews studies examining this dynamic mental health model.

An interesting extension of the mental health model has been in the area of overtraining and staleness. Staleness is an undesirable or pathological condition that, in a sports context, often results when one is not able to fully recover from the acute fatigue caused by overtraining (Morgan et al., 1987a). (Overtraining should not be confused with overlearning, in which the physical demands of the task do not interfere with successful performance.) The most obvious symptoms of staleness include “physiological and psychomotor retardation, chronic fatigue, depressed appetite, weight loss, insomnia, decreased libido, muscle soreness and elevated depression and tension” (Morgan et al., 1987a:110).

In most endurance sports, coaches plan times during the year or season when they can increase the volume of training by altering the intensity (i.e., time at a fixed distance) or duration (i.e., constant pace but varied distance). Intensity and duration of training increases nearly four-fold during several weeks or months prior to important competitions. Most coaches believe that with the proper training stimulus, the process of overtraining can lead to enhanced athletic performance as long as the athlete is allowed sufficient time to recover from the acute fatigue brought on by the intense training. Often, however, the training stimulus is not appropriate, and athletes are unable to recuperate fully within 12-24 hours following an intense workout. As the intense training continues, chronic levels of fatigue develop and performance deteriorates.

The undesirable effects of overtraining are sometimes checked by monitoring resting heart rate, blood pressure, lactate, creatine kinase, cortisol, or catecholamine levels. If values on these measures deviate from normal, then the training stimulus can be cut back in a dose-response manner. Just as these physiological manifestations of overtraining can be monitored to prevent staleness, Morgan et al. (1987a) argue that staleness can also be prevented by systematically monitoring changes in mood. By examining mood states (e.g., with POMS) during training cycles consisting of light training, intense or overtraining, and tapering phases, staleness can be diagnosed early and prevented by reducing the training stimulus until the athlete once again displays a mood profile conducive to optimal performance (i.e., the iceberg profile). Without physiological or psychological markers to prevent staleness, the only known treatment is a dramatic reduction or change in training or, in extreme cases, complete rest by discontinuance of training.

With the exception of one study conducted with wrestlers,3 most of the longitudinal studies by Morgan et al. (1987a) have been with collegiate swimmers. In these studies, varsity swimmers were given the

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

POMS scale at 1-month intervals from September (training load at approximately 3,000 yards/day) to the peak training load in January (11,000 yards/day) until just before the conference championship in February (peak training load was tapered to 5,000 yards/day). In this research, global mood disturbance was measured with the response set of “how you have been feeling during the past week including today.” Global mood disturbance was calculated by summing the negative mood scales (anger, confusion, depression, fatigue, and tension), subtracting the “vigor” score from this total, and then adding a constant of 100 to prevent the occurrence of negative values.

During the 10 years that Morgan and his colleagues monitored mood scores on approximately 200 female and 200 male competitive swimmers, the greatest global mood disturbance typically occurred in late January when athletes were training twice a day to accomplish the peak training load. This increase in global mood disturbance usually resulted from a statistically significant increase in fatigue and a significant reduction in vigor. During this time about 5-10 percent of the swimmers experienced what was considered as staleness: the swimmers' performances had deteriorated, and they were unable to train at customary levels. They were referred to counseling psychology and outpatient psychiatric services, and approximately 80 percent of them “were judged to possess depression of clinical significance” (Morgan et al., 1987a:108).

Of the eight studies summarized by Morgan et al. (1987a), only one study controlled for nonathletic stressors—social, economic, and academic—in the life of college students. Throughout the semester (September through early December), 44 collegiate swimmers and 86 nonathletic college students (controls) completed the POMS bimonthly from week 3 to week 13 of the semester. As shown in Figure 3, the swimmers scored significantly lower than the controls at the beginning of the semester. However, as the training volume increased during the ensuing weeks (weeks 5 to 11), the swimmers experienced a significant global mood change; the controls did not change significantly at any point throughout the 13-week period. The swimmers had significantly higher mood disturbance than the controls during weeks 9 through 13. As the swimmers were not yet into the taper phase, there was no support for the findings of other studies (see Morgan et al., 1987a) that a return to normal mood levels occurs once the training stimulus was lowered.

In several of the research reports of the static and dynamic mental health models, Morgan has argued that psychobiological tests of the models would provide greater understanding than does a purely psychological approach. Illustrative of this is a recent psychobiological study (O'Connor et al., 1989) conducted with 14 female collegiate swimmers and 8 active college females who served as controls. As in other swim-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

FIGURE 3 Moods of student athletes and nonathletes.

ming studies, the training volume of the swimmers increased from 2,000 yards/day in September (baseline) to a peak of 12,000 yards/day in January (overtraining), followed by a reduction in training to 4,500 yards/ day by February (taper). The swimmers had more global mood disturbance in comparison with the controls during overtraining followed by a reduction in global mood disturbance after the taper period. The salivary cortisol levels of the controls did not change across time periods, while the swimmers had higher cortisol levels than controls during the baseline and overtraining periods. The swimmers had cortisol levels similar to the control subjects during the taper phase. 4

In this study the team's coach (who was not given the mood and cortisol data) classified three swimmers as being stale because they had a performance decrement of 5-10 percent for 2 weeks or longer. For each of these women, the period of staleness coincided with the end of the overtraining period. Using a nonparametric test to examine the 3 stale and 11 normal swimmers, the results showed that the stale group had significantly higher global mood disturbance and salivary cortisol levels than the normal group. This finding is merely suggestive since the stale athletes may also have had more mood disturbance during the baseline period.

The results of this study (O'Connor et al., 1989) are consistent with other studies (Morgan et al., 1988) showing a convergence of physiological and psychometric measures of distress in swimmers during a

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

period of increased training. The fact that tension remained elevated following the taper period may have been due to anxiety associated with an impending conference championship. The differences in salivary cortisol levels during the baseline are also problematic. This difference may have been due to limitations associated with only collecting one cortisol sample for each training phase and the time frame in relation to training in which these samples were obtained (O'Connor et al., 1989). Although no subjects in this study possessed negative affective states of clinical significance (i.e., one standard deviation of the population average of college females), three subjects had prolonged performance decrements that resulted in their being diagnosed as stale.

Global mood disturbance has recently been shown to be related to athletes' running economy (Williams and Krahenbuhl, in press) and mood state following a rapid 6 percent weight loss (Horswill et al., 1990). For example, it has been noted for some time that even in elite runners there is considerable day-to-day variability in ventilation measures, which exercise physiologists use to infer how economically one runs at a constant workload. Comparing the POMS to daily ventilation measures showed a surprisingly high association, r = .80. It appears that these within-subject comparisons of mood state over days or months can detect when athletes may feel undue pressure in their lives that can slightly (e.g., running economy, weight loss) or dramatically (e.g., staleness) affect their performance. The implications of the dynamic model are far-reaching.

Summary

There are a number of shortcomings in the studies testing the static and dynamic mental health models. These shortcomings include the use of a single-group design in several studies, which greatly limits their internal validity; most of these studies were cross-sectional, exploratory, descriptive, or retrospective in nature. Many of the studies only used comparisons to college norms established more than 20 years ago, and it is possible that these norms are not stable over time and are no longer still representative of college students today. Most of the studies had very small numbers of subjects, which greatly restricted the use of multivariate statistics for testing the predictions of the model and for determining the strength of the predicted relationships. The studies were limited in scope to endurance sports for which the training stimulus was easily quantifiable. Finally, there is meager physiological validation for the predictions of the mental health model.

In addition to these shortcomings, another major problem in the series of studies testing the static model has been in the quantification of

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

performance. The performance measure employed represented an outcome, such as won or lost, made or didn't make the team; but an athlete might have performed very well relative to his or her past performance (e.g., personal best), but still failed to win. Yet Morgan would label the performance as unsuccessful. If, instead, the performance measure was actual swimming times and distances, a ratio scale of measurement could be developed to detect small group differences and enable future investigators to determine if athletes having the greatest performance decrements actually have more global mood disturbance. 5

The results of studies using control groups to test the static model have produced inconsistent results. It may be too much to expect that a self-report measure of mood can be sensitive enough to reliably discriminate among levels of athletic proficiency, let alone predict which athletes will make a team or place first in a given contest. With the use of within-subjects designs with control groups (Morgan et al., 1987a:Study 7; O'Connor et al., 1989), the studies testing the dynamic mental health model have had more internal validity and have shown a greater degree of consistency in supporting the predictions of the model. The dynamic model also has the distinct advantage of being able to specify the situational variables (e.g., training intensity) that lead to predictable mood changes characteristic of what is known as staleness.

COGNITIVE-BEHAVIORAL INTERVENTIONS

Sports psychologists have studied cognitive-behavioral interventions as a means of facilitating sports performance since the late 1970s. The general assumption is that cognitive-behavioral interventions can help performers achieve greater control of their precompetitive arousal states and maintain attentional focus on the task at hand. The studies reported in this section do not measure arousal/attentional processes directly; rather, they infer these processes from performance changes. Improvements in arousal and attention, which can be achieved by practice in cognitive-behavioral intervention techniques, is believed to result in higher levels of motor performance. As defined by Greenspan and Feltz (1989), “interventions” consist of actions, initiated by someone other than the performer, that focus on psychological skills in an attempt to improve performance.

For this review, the interventions typically reported in the sports psychology literature have been put into five categories: (1) relaxation with no attempt to alter cognitions (e.g., progressive muscle relaxation, autogenic training, biofeedback, and hypnotherapy); (2) imagery (including “mental practice”); (3) mental preparation strategies (e.g., association-disassociation strategies and goal setting); (4) skill development

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

strategies (e.g., modeling); and (5) cognitive restructuring-coping strategies (i.e., when a clear and deliberate attempt is made to alter cognitions) (see Greenspan and Feltz, 1989; Whelan et al., 1989). Before turning to recent reviews of cognitive-behavioral interventions in a sports performance context, we consider the motor performance literature on imagery and mental practice; this material represents an update on the topic in the committee's first report (Druckman and Swets, 1988:Chapter 5).

Mental Practice and Motor Performance

Although there are a few studies that show that mental practice can enhance retention (Annett, 1979), most of the research literature deals with mental practice and motor performance. According to Richardson (1967:95): “mental practice refers to the symbolic rehearsal of a physical activity in the absence of any gross muscular movements. ” Meta-analytic reviews show that, across many types of motor tasks, mental practice groups performed significantly better than control groups. This is the case whether one examines group differences at the posttest (effect size = 0.48; Feltz and Landers, 1983) or pretest-posttest change scores (effect size = 0.47; Feltz et al., 1988). The motor performance studies contained in these meta-analytic reviews usually have greater internal validity than the sports studies, but less external validity (see Campbell and Stanley, 1963). The motor performance studies are more often laboratory studies, in which subjects have been randomly assigned to treatment conditions. An even more important difference is that the motor performance tasks are typically novel tasks that control for the effect of prior experience and also minimize practice of the task during the intervention period.

Although those meta-analytic and narrative reviews (Richardson, 1967; Singer, 1972; Weinberg, 1982) have concluded that mental practice is better than no practice at all, a more interesting question is whether mental practice can be as good as or better than physical practice. To investigate this question, subjects in the mental practice, physical practice, and control groups (no practice) receive the same number of practice trials. In addition, many of the motor performance studies have included an additional condition of combined practice. In this case, the ratio of physical to mental practice has been 50:50 so that subjects receive half the number of trials of the 100 percent physical and half the number of trials of the 100 percent mental practice groups. Although some reviewers (Richardson, 1967; Singer, 1972; Weinberg, 1982) have suggested that mental practice or a combination of mental and physical practice can be as effective or more effective in improving performance than 100 percent physical practice, the meta-analytic review by Feltz et

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

al. (1988) found otherwise. For pretest-posttest change scores, it showed effect sizes of 0.79 for physical practice, 0.62 for the 50:50 combined practice, 0.47 for mental practice, and 0.22 for no practice (control group).

In the committee's first report (Druckman and Swets, 1988:65), the possibility was raised that a combination of mental and physical practice might approach or exceed improvement of the 100 percent physical practice group if the ratio included a majority of physical practice trials, for example, 70:30. With tasks like pursuit rotor (a spinning disc with a quarter-sized target that a person tries to track and that records “time on target” [Oxendine, 1969]), standing broad jump and hand dynamometer (a device used to measure grip strength [Wills, 1966]), combined practice groups (75:25 and 50:50) have not been found to be significantly different from physical practice groups. However, the results of these studies are far from conclusive. Not only were these effects not found for other tasks examined in these studies—soccer kick, modified free-throw, and hand dynamometer—but these studies also lacked necessary control groups to clearly interpret the influence of physical and mental practice on motor performance.

A more complete test of the hypothesis that combinations of physical and mental practice can affect motor performance as much as physical practice alone was recently conducted (Hird et al., 1991). This study compared different ratios of physical to mental practice for performance on a cognitive task (peg board), which requires perceptual and symbolic task elements, and on a motor task (pursuit rotor). Subjects (36 males and 36 females) were randomly assigned to one of six groups: control (practice on a lateral balancing task); physical practice; mental practice; or one of three combined physical and mental practice groups, 75:25, 50:50, and 25:75. There were seven practice sessions, consisting of four trials per session for the peg board and eight trials per session for the pursuit rotor. The results showed that all treatment conditions significantly improved performance from pre- to posttest, except for the control group for the peg board task. Consistent with the Feltz and Landers (1983) meta-analysis, effect size calculations indicate that mental practice was more effective for the peg board than for the pursuit rotor. Also, effect sizes and significant linear trends for the posttest scores for both tasks show that as the relative proportion of physical practice increased, performance was enhanced (see Table 2). These findings indicate that reducing or replacing physical practice with mental practice would be counterproductive if performance enhancement was the only consideration. However, for conditions under which physical practice may be expensive, time consuming, fatiguing, or injurious, combined mental and physical practice or mental practice alone is clearly more effective than no practice.

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

TABLE 2 Comparative Effects of Physical and Mental Practice

 

Hird et al. (1991)

   

Group

Peg Board

Pursuit Rotor

Feltz and Landers (1983)

Feltz et al. (1988)

Physical Practice

2.05

1.52

0.79

75:25 Combined

1.54

1.32

50:50 Combined

1.36

1.10

0.62

25:75 Combined

1.07

0.95

Mental Practice

1.06

0.50

0.48

0.47

Control (no practice)

0.22

NOTE: All numbers are effect sizes.

Although physical practice was better than combined mental and physical practice and mental practice alone in these studies, in real-life settings mental practice is not always used as a replacement or trade-off for physical practice. Rather, mental practice is often used as a supplement to physical practice. There has been a paucity of motor performance research that has examined the performance effects that occur when varying amounts or types of mental practice are systematically added to a constant amount of physical practice. This question has been addressed in sports, when the regular training and competitive schedule of athletes is supplemented (although not systematically) with cognitive-behavioral techniques. These field experimental studies are presented in the next section.

Sports Performance

The generalizability of the motor performance findings has been questioned, primarily because athletes' participating in real-world sports tasks were not the central focus of the studies. Recently, the emphasis in sports psychology studies has been to broaden the scope to include a number of strategies that emphasize cognitions, thoughts, or mental activities as mediational processes and/or as the central change mechanisms (Whelan et al., 1989). Collectively these strategies have been called cognitive-behavioral interventions and include such “psychological skills” as imagery, relaxation, biofeedback, hypnotherapy, cognitive restructuring, systematic desensitization, self-monitoring, performance-contingent rewards, and goal-setting. At the same time, reviewers have narrowed their focus to the sports context. Thus, they selected for their reviews only those studies that used athletes who competed on a regular and

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

organized basis, and in which performance (the dependent variable) was measured in a noncontrived competitive situation in the sport in which the athletes regularly competed.6 The overall results of these reviews provides strong support for a relationship between cognitive-behavioral interventions and an enhancement of sports performance. For instance, Whelan et al. (1989) found that the average effect size (0.62) represented more than one-half a standard deviation advantage in the performances of the athletes receiving cognitive-behavioral interventions compared with control groups who were denied this supplemental mental training. Likewise, Greenspan and Feltz (1989) observed the same facilitation of sports performance in 87 percent of the studies in their review.7

The effects of cognitive-behavioral techniques were robust with respect to four factors (Whalen et al., 1989): type of control group used (no treatment, attentional, placebo, etc.); team or individual sport; open or closed skills; 8 and performance measured in competition or practice conditions. Effect sizes were higher (0.62) in studies using appropriate motivational control groups to infer causality. In addition, in the studies of athletes' performing in conditions of competitive pressure (competing directly with others), training in cognitive-behavioral techniques significantly enhanced performance (effect size of 0.31, p < .05); this effect size, however, was less than half of what it was when no competition was present (0.75, p < .01). The type of outcome measure was also an important moderating variable. Studies that used objectively determined performance, physiological, or self-report measures all showed significant effect sizes (> 0.49, p < .05). In contrast, when the outcome measure was based on the ratings of judges or trained observers, the effect size was not statistically significant (0.29, p > .05).

The type of skill and the skill level of the performer were also rated by Whelan et al. (1989). Significant effect sizes were found for tasks primarily involving accuracy, endurance, and strength; significant effect sizes were not found for tasks that emphasized balance or speed. In terms of skill level, the effect sizes were significant for both novice and proficient performers. However, with so few intervention studies being conducted with elite athletes (usually defined as national team, Olympic, or professional level), no meta-analytic information on the effectiveness of interventions could be provided for this level of competitor.

The issue of whether cognitive-behavioral interventions actually work with elite level athletes was the topic of discussion on the 1988 pre-Olympic games telecast on the ABC television program Nightline. William P. Morgan, a prominent sports psychologist from the University of Wisconsin at Madison, mentioned that there is no scientific evidence that the intervention techniques used with athletes actually improve performance. Since the topic of the Nightline program dealt with the psy-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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chological preparation of Olympic athletes, it later became clear that Morgan's remarks were being addressed to the dearth of intervention studies on elite athletes. But of four studies with elite athletes, 75 percent show positive effects of cognitive-behavioral interventions on sports performance. For example, semiprofessional baseball players improved batting efficiency average as a result of performance that was contingent on monetary rewards (Heward, 1978) and an Olympic pommel-horse athlete, who received stress-inoculation training, improved performance in a number of meets more than other gymnasts (Mace et al., 1987).

In studies with comparison groups, the results are mixed. For instance, Mumford and Hall (1985) found that sectional and national level figure skaters given four 50-minute sessions of various kinds of imagery were not rated any differently by judges than figure skaters who watched films related to, but not of, skating figures. In another study involving elite athletes, Kim (1989) obtained the complete cooperation of Korean sports administrators to randomly assign Olympic rifle shooters to treatment conditions. The 48 subjects (aged 18-30) were assigned in equal numbers to four groups: a relaxation/imagery group, a meditation/imagery group, a combined relaxation/imagery/meditation group, and a no-treatment control group. The subjects in the first two groups listened to either a relaxation/imagery or a meditation/imagery audio-cassette tape in a private room two times a day over a 6-week period for a total of 13 hours of treatment. Subjects in the combined group listened to the meditation/imagery tape for 3 weeks and then listened to the relaxation/ imagery tape for 3 weeks. The subjects in the control group listened to a tape that contained classical music without any instruction.

The results of Kim's (1989) study showed no pretest differences among groups, but there were significant pretest-posttest differences for anxiety and performance. Although no differences were found for the relaxation/imagery and control groups, the meditation/imagery and combined meditation/relaxation/imagery groups showed both significant posttest reductions in self-reported anxiety and better shooting performance. Analysis of posttest scores only revealed a significant difference among groups for shooting performance (p < .05), and Scheffe post hoc tests showed this was due to the combined group performing better than the control group.9 Kim (1989) concluded that his findings support Suinn's (1983) and Smith's (1980) contention that combining treatment components is an effective clinical technique for enhancing performance.

These studies suggest that the effects of interventions used with elite athletes may be more beneficial if multiple component treatments are used. This finding is consistent with Greenspan and Feltz's (1989) review: where using a multiple component treatment (e.g., relaxation

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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combined with imagery or modeling), three of the five studies (Hall and Erffmeyer, 1983; Lee and Hewitt, 1987; Weinberg et al., 1981) showed better performance in competitive conditions than studies using a single component treatment (e.g., only imagery). In comparison to Mumford and Hall's (1985) findings, Kim's results are consistent with Whelan et al.'s (1989) observations that greater intervention effects are found with tasks that are more objectively scored than those by judges' ratings. Moreover, they are in accord with the general progressive relaxation literature (reviewed by Borkovec and Sides, 1979), in which more treatment sessions were shown to produce changes in physiological measures of arousal than fewer sessions.

There are also data from some single-subject design studies in which the interventions were remedial in nature (reviewed by Greenspan and Feltz, 1989). Six cognitive restructuring studies involved an athlete or coach seeking help for an anxiety or concentration problem, and the author of the study then evaluated the problem, developed an intervention, applied it, and then assessed it (Hamilton and Fremouw, 1985; Heward, 1978; Heyman, 1987; Kirschenbaum and Bale, 1980:Study 2; Komaki and Barnett, 1977; Meyers et al., 1982).10 Five of the studies showed significant improvements in performance. This success rate was higher than the control-group studies reviewed by Greenspan and Feltz (1989). These findings are also consistent with the general clinical literature that shows patients who are given progressive muscle relaxation by a therapist have stronger effects than nonpatients. In addition, subjects receiving instructions directly from a therapist showed a greater relaxation response than did subjects receiving standardized taped instructions with no opportunity to control their training progress (Borkovec and Sides, 1979). Thus, the reviews of the sports literature generally support Borkovec and Sides' (1979:119) conclusion:

The likelihood of producing significant physiological reductions via progressive relaxation appears to be greater when multi-session, subject-controlled training is conducted with subjects for whom physiological activity contributes to a presenting, clinical problem.

At first glance the reviews of the sports literature appear to show rather consistent findings; however, Greenspan and Feltz (1989) also acknowledge several cautions in interpreting this literature. Most of this literature is based on collegiate samples, with very few studies examining cognitive-behavioral interventions with elite or young athletes. According to Greenspan and Feltz (1989), future research needs to emphasize: the use of appropriate single-subject or treatment group designs sufficient to infer causality; comparison of different interventions; the development of more treatment manuals so that future re-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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search can become more standardized; assessment of nontargeted areas (e.g., cognitive changes) in addition to the targeted performance components; and follow-up assessments to determine the long-term effects of different psychological interventions on athletes performing in competitive situations.

Furthermore, although the meta-analyses of mental practice and cognitive-behavioral interventions in general have consistently shown that these techniques can enhance motor performance and sports skills, there are individual studies that have not shown positive effects. Since the 1989 reviews of Greenspan and Feltz and Whelan et al., there have been studies showing enhanced performance (Feltz and Riessinger, 1990; Kendall et al., 1990) and studies showing no effects of cognitive-behavioral interventions (Lawrence et al., 1990; McCullagh et al., 1990a, 1990b; Morrison and Walker, 1990). Some of the studies showing nonsignificant effects have been conducted in military settings; all of them are directly relevant to issues raised in the committee's first book (Druckman and Swets, 1988). In the next two sections, we compare these studies with previous reviews on cognitive-behavioral techniques in order to gain insight into why some studies show positive effects and others do not. This comparison is divided into the two primary types of cognitive-behavioral technique used, modeling and imagery or mental practice.

Modeling

Although there is an extensive amount of research on modeling of social skills, modeling or observational learning of motor or sports skills has not received prolonged and systematic study. A recent review (McCullagh et al., 1989) proposed an integrative model that attempts to consolidate several aspects of various motor behavior disciplines—motor learning and control, sports psychology, motor development, etc. It is clear from this review that there are many factors associated with the observer, the observer's perception of the action, the demonstration, rehearsal strategies, behavioral responses, and feedback that are influential in how modeling can affect skill acquisition and performance. In general, studies examining attentional, retentional, and motivational aspects of modeling have shown enhanced performance of people who are exposed in comparison with control groups that are not exposed to such demonstrations. This section covers research that examined modeling through the use of commercially available videotapes (theoretical and practical issues dealing with modeling are presented in Chapter 4).

In two studies supported by the United States Tennis Association, McCullagh et al. (1990b) examined the effectiveness of using Sybervision sports training videotapes as a learning tool for the tennis serve. Col-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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lege students with limited tennis playing experience were compared in a pretest-posttest design on their form and accuracy in the tennis serve. In the first experiment, there were the following four groups: a Sybervision tape of Stan Smith (12 subjects), physical practice of 20 serves per session (13 subjects), Sybervision plus physical practice (10 subjects), and physical activity instruction unrelated to tennis (i.e., motivational control, 9 subjects). As recommended in the Sybervision instructions, the treatment of seven sessions extended over 4 weeks. In addition to assigning points (0 to 5) for accuracy of the serve, the subjects' performances were filmed and later evaluated by two experienced tennis instructors for their form in executing the proper stance, grip, toss, backswing, and point of contact and follow-through; with 0-5 points for each of these technical elements, the form scores for each of the 10 pretest and 10 posttest serves ranged from 0 to 25. The results showed only that all groups made a significant improvement in form scores from pretest to posttest. There were no effects for accuracy, and neither measure showed differences among the groups.

With the small sample size used in this study, there may not have been sufficient statistical power to detect differential improvement made by the treatment groups. Unfortunately, McCullagh et al. (1990b) did not give information on the relative strength of the performance gains. Although the interaction was not statistically significant, inspection of the effect sizes for each group revealed that the combined group of Sybervision and physical practice had the largest effect size (0.42), followed by Sybervision only (0.30), control (0.17) and physical practice (0.13).

A second study by McCullagh et al. (1990a) attempted to add additional components to the Sybervision tennis serving demonstrations to see if this would facilitate the performance (accuracy and form) as well as subjects' ability to recognize errors in another player's serves. Following the pretest of 10 serves, the 46 subjects were randomly assigned to either the Sybervision only group, Sybervision plus physical practice group (20 serves per session), Sybervision plus mental rehearsal group (Sybervision audiotape at end of each session accompanied by imagery), and Sybervision plus verbal cues (videotape with audiotape overlay of brief verbal cues directing subject's attention to racquet position, weight shifts, form and height of ball toss, fluid motion, backswing, point of contact, and follow-through). The results revealed that all groups significantly increased in form but decreased in accuracy from pretest to posttest. These results were attributed to the emphasis in the Sybervision instructions on Stan Smith's form. This emphasis may have carried over to the posttest and resulted in subjects' concentrating on form to the detriment of accuracy. (No meaningful information was derived

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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from the error recognition data since, with the measure used, even the judges had trouble identifying errors.) Finally, no one group had significantly better form than any other group, although the effect sizes for the Sybervision plus imagery group (1.48) and Sybervision plus verbal cues group (1.30) were considerably higher than the Sybervision only group (0.66) and the Sybervision plus physical practice group (0.64). Compared to the earlier study (McCullagh et al., 1990b), the larger effect sizes for the Sybervision group were likely due to subjects' in the second study (McCullagh et al., 1990a) seeing the videotape twice as many times within the same time and number of sessions.

Two modeling studies—one of diving and one of basketball foul shooting (cited in Whelan et al., 1989)—showed statistically significant group effects (Feltz et al., 1979; Hall and Erffmeyer, 1983). These studies did not examine Sybervision, but both contained a videotape of a model that was combined with other treatments: for example, relaxation/imagery, focus on sensory cues, physical practice, informational feedback, or repetition of important steps (cues) in the model's demonstration. These conditions yielded a 20 percent improvement in number of correct dives (Feltz et al., 1979) and a 9 percent improvement in basketball foul shooting (Hall and Erffmeyer, 1983).

The subjects in Hall and Erffmeyer's (1983) study were highly experienced female basketball players. This study also had more pretest and posttest performance trials (100 each) than the Sybervision studies. These factors may have helped to produce more stable performance scores. In addition, due to greater experience on the task, the subjects may have been able to gain more information from the model. In a study of bowling, Rothstein and Arnold (1976) concluded that experienced subjects benefited more from videotapes of bowlers than did novice performers. This finding suggests that having a background in the sport may be an important prerequisite for deriving knowledge from a videotape of an expert model.

An important differentiating factor in the Feltz et al. (1979) study of diving, but not in the McCullagh et al. studies of tennis serving, was the provision of informational feedback following each trial. Feedback on the correctness of the subject's performance, combined with having the subjects verbally repeat the steps in the dive that the model demonstrated, may have been important in the videotape group's achievement of a 20 percent increase in correct dives. McCullagh et al. (1990b:16) recognized the importance of knowledge of results or knowledge of performance and suggested that the Sybervision program would “never really be effective unless it is supplemented with personalized instruction.”

The potency of providing feedback for motor skill acquisition is well

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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recognized. In sports, simple as well as complex techniques that provide feedback about one's own performance are becoming increasingly more popular. For example, at Vic Braden's Tennis Academy feedback techniques include wall markings to provide information on the consistency of the ball toss for the tennis serve and slow motion films of performers ' tennis techniques. With the use of computer technology, subjects can also be provided with knowledge of outcomes (e.g., with the laser rifle system at the U.S. Olympic Training Center or the shooting system at Ft. Benning) or sophisticated knowledge of technique (Peak Performance or SelSpot Systems). For example, subjects can be given, in real time, kinematic information about their movement such as force/time curves (Howell, 1956), position/time graphs (Hatze, 1976), or kinematic feedback (Newell et al., 1983, 1985). Although there is now a wealth of biomechanical technology to quantify movement and present this information in more sophisticated ways, the implementation of this technology in providing systematic feedback to facilitate learning of physical skills is in its infancy. The basic problem that needs to be addressed is “what information feedback to use and how to use it to optimize learning for beginners and to help advanced performers make corrections in their well-learned techniques” (Christina, 1987:35). More research needs to be conducted to determine, for real-world tasks, the ways in which task conditions should be structured and feedback given (i.e., by type, amount, scheduling, etc.) to those learning new skills or effecting changes in well-learned skills.

Imagery and Mental Practice in Military Settings

Although the sports and motor performance literature has generally shown that imagery and mental practice are effective in enhancing performance, there are some recent applications to military settings that have failed to find this relationship. One study examined various measures of soldering performance in groups that were either trained in imagery rehearsal, relaxation, or received no training (control) (Lawrence et al., 1990). Another study examined tank gunnery performance for subjects in a no-treatment control group and a mental practice group (Morrison and Walker, 1990). A close examination of these studies revealed several limitations in the design and methodological procedures. Those limitations render these studies virtually useless in determining if these cognitive-behavioral techniques are effective in military settings, but they are instructive in identifying methodological procedures that may mask imagery and mental practice effects in operational military environments.

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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Unlike most of the motor performance laboratory studies on mental practice, in which subjects are randomly assigned to experimental and control conditions, the military studies used intact groups. The use of intact groups raises a risk that variables other than the one of interest (i.e., independent variable) may affect the dependent performance measures, and this may have been a problem in these military studies. The disparities among or between groups could be due to any number of factors associated with the characteristics of the groups. For instance, in the Lawrence et al. (1990) study, there was more variability among the three intact groups in each treatment condition than there was between the mental rehearsal, relaxation, and control groups. Likewise, in the Morrison and Walker (1990) study, there was a substantial difference between the mental practice and control groups at the pretest.11 These problems are not uncommon when intact groups are used. The mental practice group happened to have higher general technical (GT) scores (i.e., word knowledge, paragraph comprehension, and arithmetic reasoning) than the control subjects. This led the researchers to suggest that this may have influenced the significantly higher pretest tank gunnery scores of the mental practice group.

There are other methodological problems in the military studies. The study by Lawrence et al. (1990) used judges' ratings which have been shown to be associated with the weakest sports performance effects (Whelan et al. 1989). In addition, subjects in this study may not have been sufficiently motivated since their soldering performances were voluntary and were not being graded.

Methodological problems could have masked the effects of mental practice on tank gunnery performance in the Morrison and Walker (1990) study. A mental rehearsal briefing given before, instead of after, the pretest could have affected the superior pretest performance of the mental practice group. In addition, while waiting their turn, control subjects watched their partners perform on the simulator; thus, modeling effects for control subjects, combined with the possible use of mental practice, may have offset the mental practice effects for the experimental subjects. Morrison and Walker were aware of these potential confounding variables, but dismissed them as unavoidable in operational military conditions. Like many psychological variables, the small to moderate performance effects produced by cognitive-behavioral interventions are unlikely to be evident when operational routines place major methodological restrictions on the study. These problems are also present in sports settings, but as the Kim (1989) study has shown, they can be overcome. By gaining the cooperation of coaches or sports administrators, some routine procedures may be changed in order to permit a study to detect group differences in performance. Once the effect has been

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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scientifically demonstrated under altered operational conditions, it can then be decided whether the effect is beneficial enough to suggest incorporation into the operational routine.

Summary

The sports psychology literature convincingly shows that cognitive-behavioral techniques can produce small to moderate improvements in various types of motor performance. Most of the studies illustrating these effects have used novice or proficient performers, and there are a few studies that have even shown these effects in elite athletes. Although few individual studies have been designed to examine variables that may moderate these small to moderate improvements, the narrative and meta-analytic reviews suggest that the performance gains accruing from cognitive-behavioral interventions and their measurement can be enhanced if they include: multiple components, imagery, relaxation, feedback, modeling, cognitive restructuring, etc.; direct administration of the treatment rather than indirect administration by audiotape, particularly in the case of progressive muscle relaxation; the use of many sessions, particularly for tasks with more motor and fewer cognitive components; and behavioral, self-report, or physiological performance measures rather than judges' ratings. In addition, the interventions show stronger results for subjects who have problems with precompetitive anxiety or concentration. Even if some of these factors are not present, cognitive-behavioral interventions can still improve performance. However, the effects may be less or they may take longer to achieve. In operational environments in which intact groups are typically used and strict adherence to methodological procedures are often not possible, the effectiveness of cognitive-behavioral interventions may be difficult to discern. Recently, investigators have attempted to tie cognitive-behavioral techniques more closely to actual sports performance by building these techniques into the preperformance routines of the athletes. The popular and scientific literature dealing with the use of cognitive-behavioral techniques in the preperformance routines of athletes are presented in the next section.

PREPERFORMANCE ROUTINES, SPORTS PERFORMANCE, AND PHYSIOLOGICAL MEASURES

One recent concern among sports psychologists is that cognitive-behavioral techniques taught to athletes in noncompetitive settings may not generalize to performance in settings characterized by intense competitive pressure. The basic premise in this type of research is that the

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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few seconds preceding the execution of a motor skill are critical for successful performance (Gould et al., 1980; Mahoney and Avener, 1977; Suinn, 1977). Whether athletes have good mental control the day before or an hour before competition may have little to do with the control they exhibit immediately prior to performance. By training athletes to incorporate cognitive-behavioral techniques at the time of actual performance, it is believed that their levels of concentration will be enhanced and thus their performance will be improved. The varied literature on preperformance routines is presented in this section in two parts: performance effects of preperformance routines and electrophysiological correlates associated with these routines.

Preperformance Routines and Sports Performance

Structured preperformance routines have typically been used by experienced performers executing skill activities when the environment is static (e.g., tennis serve, golf putt, archery, gun shooting). According to Crews and Boutcher (1986b:291), a preperformance routine consists of “a set pattern of cue thoughts, actions, and images consistently carried out before performance of the skill.” They suggest that athletes have learned a preperformance routine “to divert attention away from negative, irrelevant information, to stop attention focusing on a well-learned skill (e.g., disruption of automatic processing), and to establish the appropriate physical and mental state for the ensuing task” (Crews and Boutcher, 1986b:291). If athletes do not have a well-established preperformance routine, they say one should be developed for them. Before it is developed, an athlete should have some proficiency in a variety of cognitive-behavioral techniques.

An example of a commercially available preperformance routine is Loehr's (1989) mental toughness training program. To improve a person 's tennis games, this videotape teaches tennis players a series of steps to be followed during the time between points. As director of sports science for the U.S. Tennis Association and consultant to the Nick Bolletieri Tennis Academy, Loehr has observed the between-point behaviors of numerous expert tennis players and has interviewed them about their between-point cognitions. He has concluded that there is a four-part pattern exhibited by the top players that reveals more about their mental toughness than can be ascertained during point play. Loehr believes that his unique player development system will produce a more confident, mentally tough athlete—the “challenge attitude ”12 who will perform at a high level more consistently.

The mental toughness training program has four stages: positive physical response, relaxation response, preparation response, and rituals re-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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sponse. The positive physical response stage begins immediately following the scoring of a point and lasts 3-5 seconds. According to Loehr, mentally tough athletes maintain their composure and display a strong, fighting, positive physical image. They may clap for opponents, clinch their fists for a good shot, or simply walk away from a mistake. They typically place the racquet in their opposite hand, carried by the throat at the balance point, as they walk briskly back to the baseline. Their eyes are forward and down and the shoulders are back.

The second stage, the relaxation response, lasts 6-15 seconds, depending on the stress associated with the previous point and the amount of preparation needed for the next point. During this stage, a player 's eyes are directed toward the racquet strings and the physical image they present continues to be strong and competitive. The high energy walk back to the baseline continues as athletes walk back and forth until breathing and heart rate stabilize. It is also common for expert tennis players to relax the arms and hands, do stretches, or take deep breaths during this stage.

The third stage is the preparation response, which begins as players move toward the baseline to serve or receive the serve, and also lasts about 6-15 seconds. Players typically lift and direct their eyes to the opposite side of the court and make a strong statement with their bodies: for example, “I will win this point.” Following this there may be a momentary pause while the players covertly go over the score and their intentions for the next point.

The last stage is the ritual response, which lasts 5-8 seconds and begins as soon as a player steps to the baseline. The purpose of this stage is to adjust arousal levels and deepen concentration. The two components characterizing this stage are bouncing the ball two or more times and pausing after the last bounce to help slow the service motion under the pressure of competition. When returning a serve, players' rituals typically consist of stimulation of the feet or making a physical gesture (such as jumping up and down on their toes or swaying back and forth). During this stage, top tennis players only think about the serve (if they are serving) or the return (if they are returning the serve). They do not think about technical aspects of tennis, such as the grip, strokes, or stance: this type of cognitive elaboration in the moments prior to response execution is believed to interfere with athletes' ability to play instinctively and automatically.

Although this is a preset routine, Loehr suggests that after it is taught, athletes can individualize the content making up the various stages of the preperformance routine. The observations that led to Loehr's model of the between-point behavioral and mental routines of expert tennis players was not experimental research. Although Loehr's preperformance

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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routine has been used, there are no scientific studies that have examined its effectiveness. The crucial question is whether those using structured preperformance routines perform better than those who do not use them. Fortunately, there is an emerging sports science literature that has addressed this question.

Observational analyses of professional golfers also reveal the use of well-defined, consistent routines for both putts and full swings (Crews and Boutcher, 1986a). The cognitive-behavioral strategies incorporate such mental functions as choosing a target, visualizing the flight of the ball to the target, kinesthetically feeling a perfect shot, and using cue words. Juxtaposed with the mental routine, the preshot routine incorporates taking a practice swing that simulates the desired swing, aligning the feet in relation to the target, “waggling” the club, and glancing at the hole.

Using cognitive and behavioral elements like these, Crews and Boutcher (1986b) assigned 15 golfers from a beginning golf class to an experimental, preshot routine group and 15 to a control group (no preshot routine). Following an 8-week preshot routine training program, Crews and Boutcher found that the performance of the preshot routine group improved only for the better male golfers, and they concluded that preshot routine training improved performance when physical skills were well learned. In another study of 12 collegiate golfers (Boutcher and Crews, 1987), both males and females improved the consistency of the preshot routine behaviors following a 6-week training period, but only the females improved in task performance.

Preshot routines have also been effective in improving basketball free-throw shooting performance (Lobmeyer and Wasserman, 1986) and novel motor task performance (Singer et al., 1989). Following a preshot training program, subjects improved 7 percent in performance when using their preshot routine than when not using the routine (Lobmeyer and Wasserman, 1986). In a laboratory environment, ten subjects were taught a five-step learning strategy that sequentially consisted of readying, imaging, focusing, executing, and evaluating. Following four practice trials, subjects in the “learning strategy group” performed significantly faster —and not at the expense of greater number of errors—than did a control group and the group that previewed the location of the six targets.

Preperformance routines have generally been effective in improving motor or sports performance of beginning level performers, but their effects have yet to be demonstrated in elite performers. Although the introduction of a preshot routine resulted in a more consistent preperformance routine and led golfers to report that the intervention had a positive effect on their concentration, Cohn et al. (1990) failed to find immediate

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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improvements in performance for three subjects. This study, however, used very few observations (2-8 rounds of nine-hole play) following the introduction of the preshot routine. With elite performers, it is possible that much more practice in using a preshot routine is necessary to improve par-level golf performance.

Interview data from athletes and the general assumptions of investigators support the idea that a preperformance routine increases a performer 's concentration and facilitates performance. Although athletes given training in a preperformance routine report better concentration, retrospective reports of cognitive processes are known to be unreliable (Nisbett and Wilson, 1977); retrospective reports are often based on implicit, a priori assumptions of the cause of subsequent behavior. Furthermore, athletes' inability to describe their preperformance state is consistent with descriptions of the cognitive state associated with “peak performance” as being characterized by (Gallwey, 1981): body/brain integration; allowing things to happen rather than trying to force a particular performance outcome; total absorption in the activity while maintaining unconscious awareness of process cues (relevant feelings, balance and weight distribution, etc.); lack of recall due to the mind being “blank” immediately prior to the response; and obvious difficulty in putting the cognitive and behavioral actions of the preperformance period into words. Trying to obtain self-reports during the preperformance routine is counter-productive since it will interfere with the desired state of automatic processing in the moments before response execution. Thus, several investigators have examined electrophysiological indicators of attention while athletes are in a preperformance routine prior to the performance of a discrete, closed skill that involves minimal movement. This literature, which has dealt with measures of heart rate and electroencephalographic (EEG) activity, is reviewed in the next section.

Physiological Correlates of Preparation to Perform

The experimental psychology literature offers several research techniques with which to measure attention (e.g., a dual-task paradigm to divide attention, readiness potentials, and averaged evoked potential of the EEG). Although these techniques have been used with shooters (Landers et al., 1985; Rose and Christina, 1990), the manipulations involved disrupt performance on self-paced tasks (and sports) and thus decrease the ecological validity. An alternate approach has been to use continuous psychophysiological measures (previously used in laboratory studies of attention) to examine the performance of archers, shooters, and golfers (Hatfield and Landers, 1987; Landers, 1985). Although several psychophysiological measures have been used in this research,

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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the ones that have produced the most consistent results during athletes ' preperformance routines in the sports of archery, rifle shooting, and golf putting have been measures of cardiac deceleration and spontaneous EEG activity.

Cardiac Deceleration

Stimuli of various types produce a pattern of beat-by-beat cardiac acceleration or deceleration in the 3-5 seconds prior to a response. The direction and magnitude of change has been related to performance and is suggested to be an indicator of an individual's attentive state. This cardiac pattern prior to initiating a response has been subject to varying explanations (see Coles, 1984; Graham, 1979; Jennings et al., 1978; Kahneman, 1973; Lacey et al., 1963; Obrist et al., 1970; van der Molen et al., 1985).

Lacey's intake-rejection hypothesis (Lacey, 1967; Lacey et al., 1963) is one hypothesis that attempts to explain the cardiac pattern that occurs prior to a response. According to this hypothesis, as a person focuses on the external environment and attempts to take in external stimuli, the heart decelerates; then, as the person focuses internally and rejects external stimuli, the heart accelerates. Tasks requiring internal cognitive elaboration of a problem-solving sort (e.g., mental arithmetic, reversed spelling, sentence structure) produce cardiac acceleration (Lacey et al., 1963). Cardiac deceleration has typically been found in a motor response paradigm, a reaction-time (RT) task (Lacey and Lacey, 1964, 1966, 1970). Using a 4-second RT foreperiod, Lacey and Lacey found a pattern of deceleration three or four beats prior to the stimulus; this pattern terminated with the onset of the stimulus light.13 Performance on the RT task was associated with greater cardiac deceleration, although the correlations were low (Lacey and Lacey, 1964, 1966, 1970).

The intake-rejection hypothesis has been criticized for being too general. Several investigators have suggested that task specificity might be responsible for disagreements in interpreting cardiac patterning associated with information processing (Bohlin and Kjellberg, 1979; Carroll and Anastasiades, 1978; Coles, 1984; Elliott, 1972; Graham, 1979; Hahn, 1973; Jennings et al., 1978). The original work by Lacey et al. (1963) stated that cardiac deceleration was an indication of the intention to note and detect external events. In examining the nature of the tasks, it is apparent that there are actually two components occurring simultaneously that comprise the intake-rejection hypothesis. One is the intake of the external stimuli (warning and imperative stimulus) created in the foreperiod of the RT task and the rejection of the external environment to solve the problems in the math task. The second component is the type of cogni-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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tive task used to create the intake-rejection situation. In 1963, Lacey et al. referred to the RT task as one that increases sensory awareness, while the math task increases cognitive elaboration and processing within the brain. The name of the hypothesis stresses the intake and rejection component; however, it is possible that it is the processing component required that determines cardiac pattern.

Other investigators have questioned that cardiac deceleration is simply an indication to note and detect external events. The Laceys (1974), for example, suggested that anticipatory deceleration may also be associated with intention to respond. Coles (1984) has argued that these two intentions are confounded and that cardiac deceleration primarily reflects motor readiness, not anticipatory sensory input. Contrary to Coles (1984), Graham (1979) believes that stimulus input is reflected by cardiac deceleration and preparation for output produces cardiac acceleration.

Regardless of whether cardiac deceleration is indicative of intake of sensory information, preparation for output, or sensory awareness, it is hypothesized that experienced athletes with a consistent preperformance routine have better attentional skills and would thus show a pattern of cardiac deceleration prior to performance. Several studies have investigated the relationship between cardiac deceleration and attention in the few seconds before response execution in sports (with minimal potential for movement artifact in the cardiac measure). For example, Stern (1976) used the sequence of “get set,” 5 seconds, “go” commands and found that subjects preparing for either a sprint up a flight of stairs or a bicycle sprint showed a phasic cardiac change of acceleration until 1 second before the “go” signal and then showed a deceleration from 1 second to the “go” command. Hatfield et al. (1987) found a trend for cardiac deceleration in elite rifle marksmen in the 2.5 seconds prior to the execution of the shot. Among highly skilled golfers, significant cardiac decelerations of 4-11 beats per minute have been found within 3-7 seconds of a putt (Boutcher and Zinsser, 1990; Crews, 1989; Molander and Backman, 1989). Only Salazar et al. (1990) reported cardiac acceleration in elite archers immediately prior to arrow release. This may have been due to the physical demands of overcoming the 31-50 pound bowstring tension. When archers have used lower bowstring tensions (20-25 pounds) (Landers et al., 1991a) or shot at shorter distances (Schmid, 1989), cardiac deceleration has been clearly evident.

There is also evidence in these cross-sectional studies that cardiac acceleration is associated with poorer performance (Molander and Backman, 1989) with novice performers (Schmid, 1989) and that greater degrees of cardiac deceleration are associated with better performance (Boutcher and Zinsser, 1990; Crews, 1989). Schmid (1989) found that “subcon-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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scious shooters” had greater cardiac deceleration than “cognitive shooters”14 The degree to which cardiac deceleration differences noted between novice and experienced performers are associated with learning the task has been investigated in archers. The archers experienced a 62 percent increase in performance over a 12-week period in which they had received 27 sessions of archery training (35 hours total) from the 1988 Olympic coach of the U.S. National Archery Team (Landers et al., 1991a).15 In contrast to studies conducted with laboratory RT tasks (Hahn, 1973) or sports tasks with novice performers (Stern, 1976), the studies investigating sports tasks with experienced athletes have generally shown greater deceleration.

Hemispheric Asymmetries in the Brain

In addition to examining cardiac deceleration during athletes' preperformance routines, Hatfield et al. (1984, 1987) also investigated associated time-locked EEG asymmetries between the hemispheres of the brain. The use of EEG measures was prompted by their promotion as a more direct measure of attentional states (Gale and Edwards, 1983; Obrist, 1981), their success in differentiating varying states of attentional focus (Davidson et al., 1976; Ray and Cole, 1985; Ray and Kimmel, 1979), and their stability and reliability over time (Gasser et al., 1985; Wheeler et al., 1989). The use of this measure was partly based on Walker and Sandman's findings (1979, 1982) that cardiovascular changes differentially influence the left and right sides of the brain. More recently, Sandman and Walker (1985) have pointed out that cardiovascular influences on the activity in the right and left hemispheres may vary from moment to moment and that the ability of an organism to detect and react to the environment may be intimately linked to hemispheric asymmetry. Although cardiovascular changes have been shown to be related to hemispheric changes (Walker and Sandman, 1979, 1982; Sandman and Walker, 1985) and hemispheric asymmetries have been predictive of performance accuracy (Gevins et al., 1987, 1989), these studies have neither investigated experienced athletes during their preperformance routines nor have they used spontaneous EEG measures.

By using skilled individuals to reduce response variability in EEGs (O'Connor, 1981), Hatfield et al. (1984, 1987) examined spontaneous EEGs during the preparatory period within 7.5 seconds prior to the trigger pull by elite rifle shooters. They found that left temporal (T3) and left occipital (O1) EEG alpha activity (8-12 Hz) significantly increased during that period. This suggests that the activation level in the left hemisphere was declining. Further examination of the relationship between heart rate and EEG revealed that, within 2.5 seconds prior to

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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the shot, cardiac deceleration was associated with increased alpha activity in the left hemisphere while right alpha remained constant. Hatfield et al. interpreted these findings as indicative of cognitive changes (reducing the covert verbalizations of the left hemisphere and increasing the visual-spatial processes dominant in the right hemisphere), which allow dominance of the right hemisphere at the time of the shot.

In subsequent EEG studies with archers and golfers, second-to-second changes in EEGs prior to the response and multiple EEG bands have been examined. During the preparatory period (3-5 seconds), which is characterized by intense concentration, experienced athletes have shown greater increases in left hemisphere alpha activity than in right hemisphere activity (Crews, 1989; Landers et al., 1991a; Salazar et al., 1990). The asymmetry was greatest at 1 second before the response (shot or putt) and was not evident earlier (up to 5 seconds) or immediately following the response (Wang and Landers, 1987). This effect was independent of minor bodily movements (e.g., eye blinks) (Crews, 1989; Landers et al., 1991a; Salazar et al., 1990). Furthermore, Salazar et al. (1990) have shown that even when the physical exertion of drawing a 40-50 pound bow was controlled, the hemispheric differences were still evident.

Although left hemispheric activity increases more than right hemispheric activity (particularly in the alpha range), better performance has been found to be associated with a moderate increase in left hemisphere EEG activity at the time of the shot or putt (Crews, 1989; Landers et al., 1991a; Salazar et al., 1990). Comparisons of best and worst shots revealed no significant right hemisphere spectral power differences, but there were significant left hemisphere differences (Landers et al., 1991a; Salazar et al., 1990). (The muscular forces and handedness were the same for best and worst shots, so the differences in EEG activity could not be attributed to muscular contaminants.) Although reliable EEG asymmetries have been observed in highly experienced performers, the above-mentioned studies do not provide information on whether these EEG patterns are developed through training in the skill. Recent studies by Landers et al. (1991a) and Landers et al. (1991b) suggest that these EEG patterns are trainable. For example, in rank beginners, the EEG asymmetries were not evident 2 weeks into training, but were evident at a time (14th week) when archery performance had improved 62 percent (Landers et al., 1991a). In Landers et al. 's study (1991b), the moderate increase in left hemispheric EEG activity immediately before the motor response was used as a model of “correct performance” in a biofeedback training study. A group of 24 pre-elite archers were randomly assigned in equal numbers to three groups: a correct feedback group (i.e., greater left hemisphere low-frequency activity), an incorrect feedback group

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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(i.e., greater right hemisphere low-frequency activity), and a no feedback control group. The pretest and posttest consisted of 27 shots with EEG data collected for the left and right temporal hemispheres. Analyses indicated that the correct feedback group significantly improved performance, while the incorrect feedback group showed a significant performance decrement from pretest to posttest. The control group showed no significant pretest-posttest differences in performance. EEG analyses showed differences that were consistent with the training given to the incorrect, but not the correct, feedback group. Overall, these training studies demonstrate that the EEG patterns observed during athletes' preperformance routines become more similar to the patterns observed in elite athletes with increased training or specific EEG feedback known to be associated with better performance.

Summary

The studies examining preperformance routines show that they are used by better performers, and people trained in the use of these routines generally show better performance. Preperformance routines teach athletes to habitually use cognitive-behavioral techniques at strategic times in their sports performances. Most of the sports studies have been conducted in practice settings, and more research is needed to compare the benefits of preperformance routines in practice with their benefits in competitive settings. The consistent patterns in EEG hemispheric asymmetries and cardiac deceleration during the latter stages of the preperformance routine suggest that they are learned responses that are indicative of better attentional focus and that result in overall better performance. These psychophysiological measures can assist in determining the efficiency of preperformance routines.

From questionnaire responses of best and worst performers (Crews and Landers, 1991), it appears that those patterns may be indexing a state of automatic processing: best performers are focused on overall bodily awareness and relevant external cues (e.g., hole or target); worst performers, who failed to consistently display the asymmetric EEG pattern, were more often focused on what might be called cognitive elaboration of specific cues (e.g., backswing, club head, etc.). Crews and Landers (1991) have noted that by increasing total awareness, the best golfers were perhaps adopting a “let it happen,” automatic approach, while the worst performers were perhaps trying to “make it happen” and cognitively control the putt (Gallwey, 1981). Further research is necessary to substantiate the value of a preperformance routine in fostering a state of automatic processing.

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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EXERCISE AND STRESS

The relationship between aerobic fitness and psychological well-being is an area within the field of exercise and sports psychology that has received considerable attention in the last 5 years. Research interest among exercise scientists on such topics as depression, anxiety, sleep, and reactivity to psychosocial stressors has intensified with the recognition that the life-styles of millions of Americans are disrupted due to anxiety and depression (Dishman, 1982; Morgan, 1979) and that primary care physicians routinely prescribe exercise for these and other emotional disorders (Ryan, 1983). Recent meta-analytic reviews have shown that aerobic exercise can have a small but reliable effect in reducing state (acute) and trait (chronic) anxiety (Petruzzello et al., 1991), increasing slow wave (i.e., stages 3 & 4) and total sleep time (Kubitz et al., 1991), and decreasing depression (North et al., 1990). Although these reviews fail to show that exercise is psychologically more beneficial than the more conventional psychological techniques—relaxation, imagery, group therapy, cognitive restructuring, etc.—it is known that carefully prescribed exercise can have additional health benefits (weight loss, enhanced cardiorespiratory efficiency and muscle tone, reduced risk of heart attack, etc.), and this may help to promote adherence to a psychological intervention program involving exercise.

Related to the topic of performance under pressure is whether or not exercise contributes to the reduction of psychosocial stress. As of 1987, Crews and Landers had identified 34 studies that had attempted to determine if the magnitude of the psychosocial stress response was lower among exercisers, or if recovery from psychosocial stress was more rapid among exercisers. Since 1987, there have been approximately 20 additional studies on this topic. Typically, these studies have included four laboratory stressors: (1) cognitive performance tasks, such as solving timed arithmetic problems; (2) passive response tasks, such as viewing films of industrial accidents or medical operations; (3) active physical performance tasks, such as exercise; and (4) passive physical performance tasks, such as holding an immersed limb in ice water (Crews and Landers, 1987). Although these stressor tasks are quite different from operational tasks which create stress reactions —such as those in everyday life or those in more pressured settings such as in the military—they do produce sizable elevations in heart rate and therefore may be relevant for other settings. For example, Crews and Landers (1987) calculated heart-rate response above initial values and found that the 34 studies could be categorized into high (> 30 beats/minute) or low (< 30 beats/ minute) stress response. Other measures of stress less frequently exam-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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ined in these studies included systolic and diastolic blood pressure, skin response, hormonal, muscle activity, and psychological self-report.

For the 1,449 subjects, the meta-analytic results showed an overall effect size of 0.48 (Crews and Landers, 1987). This result indicates that, regardless of the type of physiological or psychological measure used, aerobically fit subjects had a reduced stress response. (The magnitude of the effect represented nearly a one-half standard deviation gain in stress reactivity relative to control conditions.) The underlying assumption of this laboratory paradigm is that reduced physiological response to stress or faster physiological recovery results in less total time spent in stress at perhaps a lower level of stress. In other words, “exercise either acts as a coping strategy or serves as an ‘inoculator' to more effectively respond to the intrusion of psychosocial stress” (Crews and Landers, 1987:S118).

The moderator variables examined in the Crews and Landers meta-analysis included: study and subject characteristics, such as published or unpublished studies, acute or chronic exercise, and male or female subjects; methodological characteristics, such as initial or baseline values of stress, whether statistically controlled, and correlational versus training designs; and stressor characteristics, such as low or high stress response, stress reactivity versus recovery from stress, and types of stress measures. A meta-analytic procedure (described by Hedges and Olkin, 1985) was used to determine if the measures were homogeneous across studies. The chi-square test did not reject the hypothesis of homogeneity of effect sizes: that is, the effect-sizes were not related to specific moderating variables, and so no further breakdown into moderating variables was warranted (Hedges and Olkin, 1985). Thus, the results suggest that all of the studies could be represented by the mean effect size, 0.48.16

Although some investigators (Abbott and Peters, 1989) have argued that the Crews and Landers' (1987) meta-analytic review has precluded conducting further studies in this area, Blumenthal (1989) has pointed out that there is a need for more experimental (i.e., training) studies. There is also a need for more studies that examine: whether anaerobic exercise produces the same buffer to psychosocial stressors as is found with aerobic exercise, and whether individuals experiencing more long-term, chronic levels of high stress (e.g., air traffic controllers) derive psychological benefits from exercise training (Crews and Landers, 1987).

Many authors have suggested various mechanisms to explain the effects of exercise on the psychosocial stress response. Earlier explanations focused on physical activity rather than aerobic exercise. For example, Gal and Lazarus (1975) suggested that physical activity can reduce stress reactions in four ways: (1) heightening feelings of control

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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and mastery; (2) serving as a defense mechanism to help people forget about their distress so as to decrease anxiety; (3) providing an attention diversion; and (4) producing a means of energy discharge allowing for reasonably rapid body mobilization or arousal. Recently, other investigators (Light, 1982; Shulhan et al., 1986) have focused more on mechanisms that are directly tied to changes in aerobic fitness, such as changes in the release of endogenous opiates, baroreceptor function, release of insulin, sensitivity to beta-adrenergic stimulation, and stimulation of brain metabolism or levels of serotonin. As emphasized by Crews and Landers (1987), more research that examines these underlying mechanisms is necessary to determine how these changes in fitness actually reduce stress response or time spent in stress. In military settings, with the exception of orthostatic intolerance for those undergoing high “g” forces (e.g., fighter pilots) (Bedford and Tipton, 1987; Raven et al., 1984), aerobic conditioning may help alleviate psychological reactions in most operational conditions. As physical training is compatible with military training, it should not be too difficult to design studies in military settings to explore both the psychological and physiological effects of aerobic exercise.

In summary, several research studies have shown that aerobic exercise can help people to cope better with psychosocial stressors. The measures of coping ability used in the studies included physiological and psychological measures of reactivity to the laboratory stressor and of recovery to baseline levels following termination of the stressor. These effects are of a moderate size and are consistent across many studies, but the mechanisms for the effects are unknown.

BROADER VIEWS: NEUROSCIENCE AND PEAK PERFORMANCE

The foregoing review evaluates the research on techniques that may enhance the preparation to perform. It is also important to monitor research for potential breakthroughs in theory and methodology that may provide general guidelines for evaluating proposed techniques and their potential applications. Particularly in this “Decade of the Brain,” it is instructive to ask whether advances in understanding of the human brain and how it controls behavior have aided in the search for methods that could potentially enhance human performance. In this section, we review these advances and discuss which lines of scientific inquiry are likely to provide a better understanding of human performance. In addition, ecological studies of individuals who achieve extraordinary high performance are reviewed in order to determine the validity of an “ideal performance state model.”

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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One conclusion that is supported by considerable empirical data is that significant behavioral and performance enhancements can be achieved under certain conditions. While this conclusion may seem obvious to most readers, it should be remembered that behavioral constructs earlier in this century maintained that many behavioral properties were “fixed” entities, resulting from static physiological features. More recently, neurobiological studies revealed that enriched and impoverished environments have differential effects on numerous aspects of cortical structure (e.g., Diamond et al., 1987). Animals raised in enriched environments have an enlarged cortex and manifest performance superiorities (e.g., in maze running). Parallel behavioral research has identified some of the growth-promoting family, training, and other environmental conditions that may enhance performance (e.g., Bloom, 1985). Both the neurobiological and behavioral lines of research strongly support the idea that the innate characteristics of individuals are less important in performance than the encouragement, nurturance, education, and training they receive. The implications of these studies are unequivocal in their suggestion that, given the proper conditions, most individuals are capable of remarkable performance excellence. The challenge for researchers, as well as for institutions such as the Army, is to define the training techniques and environmental characteristics that enhance human performance.

Models of the Brain

In the previous section, and more extensively in the committee's first book (Druckman and Swets, 1988), we delineate some of the serious shortcomings in attempts to understand sports performance in the context of any simplified, metaphysical model of the brain. Sports performance is a quintessential problem in complex motor, cognitive, affective, and attentional processes, and it depends on functions that are widely distributed throughout both cerebral hemispheres. Studies that characterize the cognitive, attentional, or motor components of sports as “left hemisphere abilities” or “right hemisphere abilities” are fatally flawed. Not only is it inherently insupportable to characterize sports abilities by brain hemisphere, it is also methodologically and logically flawed to narrowly localize these complex processes.

Recent neuroscientific studies using imaging techniques have revealed that even simple motor processes, such as unilateral ballistic finger movements, have complex neuroanatomical and neurophysiological correlates (Roland et al., 1982; Druckman and Lacy, 1989); using a regional cerebral blood flow technique, the researchers found bilateral increases in blood flow during unilateral ballistic finger movements in the supple-

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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mentary motor cortex, premotor cortex, parietal opercula, paracentral cortex, putamen, caudate, and thalamus. Using position emission tomography, regional cerebral blood flow, and other oxygen and glucose metabolic imaging methods, numerous studies show that even heavily overlearned tasks, such as handwriting, result in bilateral metabolic increases in many subcortical regions, especially in the striatum (Mazziotta and Phelps, 1984). When one considers the cognitive and other mental components of sports techniques, the picture is even more complicated. Mental imagery alone is known to increase oxidative metabolic values in 25 separate cortical areas (Roland et al., 1987).

When researchers attempt to localize mental or motor tasks in brain areas, the reliability of their results should be carefully considered. These studies must be considered preliminary in the context of the poor test-retest reliability, the biological variability between subjects, and the notoriously poor geographical resolution (i.e., the discrimination of one brain subregion from another) of these methods (Pahl, 1990). Any study attempting to localize a specific mental event that uses methods with a resolution of more than 5-7 millimeters is limited in its reliability. And experiments that use many subjects and average across subjects and trials may not provide any useful information since the geographical variability in certain localizable functions (such as language) is already so large that some information is probably lost of averaging across subjects.

Nevertheless, we encourage the use of novel neuroimaging techniques in the study of human performance. The application of techniques that are especially reliable in geographical resolution (e.g., positron emission tomography) in combination with techniques that are especially reliable in temporal resolution (e.g., endogenous evoked potentials) may be important in future human performance research. Careful application of the most sensitive techniques for the particular skill and purpose being considered will lead to the better understanding of brain-behavior relationships (Chollet et al., 1991; Druckman and Lacey, 1989).

“Ideal Performance State”

Psychological science has long been intrigued with mental states associated with an individual's “peak performance.” The “virtues” or qualities that enhance human performance were major themes of Aristotle's Nicomachean Ethics, written more than 23 centuries ago. The empirical study of peak performances in modern times began less than two decades ago, however, with the work of Maslow (1971) and other existential psychologists. Using idiographic methods, Maslow characterized those performances —“peak experiences”—both by the character traits

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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of the individuals who possessed the virtues or qualities of the self-actualizing personality and by the states these individuals recalled during their best moments. The concept of peak performance in sports was popularized in the self-help work of Garfield (1978).

The focus of a large portion of psychological research—as demonstrated in the review above—has been on the role of behavioral states and how they influence performance. Indeed, nearly all the commercial efforts in this domain suggest that achievement of these states is possible (“anyone can do it”) and, thus, that such issues as character traits do not affect the attitudinal states. In fact, however, ideal performance state may not be easy to achieve: current clinical research suggest complex correlational relationships between high performance character traits and peak performance attitudes (Pirozzolo, 1991); at the same time, it is also likely that these traits and states are learnable (Loehr, 1989; Bandura, 1982) through a variety of “training” experiences.

In the rest of this section we review research that used mainly idiographic methods to characterize the behavioral state variously known as the flow state (Csikszentmihalyi, 1990), the peak experience state (Maslow, 1971), the ideal performance state, the zone, etc. Most of the empirical data collected for analysis in these studies come from naturalistic studies of everyday work and play. It is noteworthy, however, that these experiences and studies do not appear to differ from life-or-death alternatives experienced in the military: that is, intense battlefield experiences also seem to be associated with the same behavioral states (Csikszentmihalyi, 1990). Clinical experience with Vietnam veterans in Veterans Administration hospitals are consistent with other data suggesting that flow experiences occur with surprising frequency and intensity. Csikszentmihalyi (1990:69) states that war experiences can be “more exhilarating than anything encountered in civilian life. ”

As an early worker in the field, Maslow conducted hundreds of structured interviews that resulted in descriptions of common features of peak experiences: a temporary distortion of time perception; an overwhelming feeling of peacefulness, relaxation, wonder, and happiness; a total loss of fear and other negative emotions, including immature defensive strategies; and a complete absorption in the task at hand. These phenomenological observations were rooted in mysticism, but they nevertheless contributed to the study of metamotivational states, which are defined as higher needs for creativity and challenge.

Cross-national, cross-cultural, and other studies of the ideal performance state have documented an extraordinary concurrence in behavioral descriptions of the flow state (Csikszentmihalyi, 1990; Massimini and Inghilleri, 1987). Subjects report many, if not all, of the following affective, attentional, and cognitive states: a clearly focused “mind's

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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eye” of task requirements; an unself-conscious absorption in the task at hand; an uncommon intrinsic motivation, which is an absence of goal states in which the subject is performing for external rewards, trophies, financial rewards, or even social approval; a strong sense of purpose (appropriate striving); a total commitment of the “project ” in which the subject controls the contents of his or her consciousness and allows no room for distraction; a feeling of exercising control; a stretching of talents to match environmental challenges; a time transformational experience, which is most often characterized by time being slowed down but also can include a sense of accelerated temporal distortion; a sense of order in cognitive and motor set schemata; no wasted psychic or physical energy (or entropy); and the use of “higher” coping strategies (“transformational”) rather than emotion-focused or regressive coping strategies.

A promising method for studying mental characteristics of high performance behavior is the experience sampling method (ESM), developed by Csikszentmihalyi and colleagues (e.g., Csikszentmihalyi and Larson, 1987). The ESM is a naturalistic method for assessing temporal and contextual fluctuations in mood and performance. It has been used in healthy normal people as well as clinical populations and in Western and non-Western countries, and it has shown good validity and reliability (Larson and Csikszentmihalyi, 1983; Massimini et al., 1987; Csikszentmihalyi, 1990). Subjects in studies employing the ESM are signaled by means of an electronic pager worn on the wrist which is activated several times a day at random intervals. When they are signaled, subjects stop and describe their thoughts and emotions. The ESM is a highly reliable technique for measuring the mood of the moment; it does not suffer from reconstructive memorial and affective biases. The experience of flow can be linked to what the subject is thinking and feeling at that moment; motivational or goal states; contextual variables, such as the people he or she is with at the time; and the “work” he or she is doing at the moment. The ESM has the limitation of terminating the unself-conscious flow state when it exists, however, since the subject must evaluate the contents of his or her consciousness. The ESM has been recently used in efforts to increase awareness of the contextual and psychological variables that promote peak performance (Pirozzolo, 1991; Pirozzolo and Csikszentmihalyi, 1991), although larger scale studies are clearly needed before firm conclusions can be drawn about the utility of the ESM and its efficacy in behavior change.

This kind of intervention technique clearly depends on a mental health model of sports performance. As intuitively appealing as the mental health model is, it is not without serious deficiencies, some of which are detailed above. Most important are the countless case examples of

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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individuals who have succeeded in spite of hostile internal and external psychological environments, such as in the examples of Bettelheim (1960) and Frankl (1963), whose works focused on the severe psychological and physical adversities in concentration camps. Similarly, John Bunyan's Pilgrim's Progress was written in the humiliating environment of a prison (Maddi, 1965). The lives of Jesus Christ, Seneca, Galileo, Mill, Van Gogh, Dante, Freud, and Toulouse-Latrec, among numerous others, were characterized by physical pain, depression, and a variety of other indignities and suboptimal circumstances. A recent biography documents that one of the greatest baseball players of all time, Lou Gehrig, was riddled with self-doubt and low confidence and lived in a hostile family environment (Robinson, 1990).

Another possible explanation for the failure of the mental health model to predict performance is inattention to complex subject factors, including but not limited to subject self-schema. A recent study suggests that elated and depressed subjects respond differentially to positive and negative feedback (Anshel, 1988). Other neuroendocrinologic and neuropsychological factors undoubtedly play a role in this complex relationship between mood and performance. Future research should control for such potential artifacts, including the growing agreement of neuroscientists on the role of dietary factors on mood and performance (e.g., Deijen et al., 1989; Wurtman, 1982).

Two of the most popular interventions used by sports psychologists that require further research are the cognitive-behavioral technique of teaching preshot and preperformance preparatory routines and the use of psychological tests as motivational devices. As discussed above, there is no doubt that preperformance preparatory strategies exert influences on sports performance, but the nature and cause of the effects are by no means completely understood. The mechanisms of action that have been proposed include outcome or performance expectancies; improved sense of self-efficacy; improved attention control; reduction of unfocused arousal (off-target, entropic, physiologic efforts); more efficient cognitive strategies; and diminution of potentially destructive self-monitoring behaviors. A recent review argues that expectancy has a robust effect on motor performance (Neiss, 1990). Preperformance strategies and expectancies may control the path of cognitive events such that subjects rehearse overlearned motor sequences, channeling their attention and energies into an on-target, challenged approach to the task at hand, which, in turn, may interfere with off-target, unfocused-aroused perceptions of threat that inevitably leads to choking under pressure.

The additional considerations raised in this section suggest themes largely overlooked by contemporary research on human performance.

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
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They contribute to the development of a broader framework to guide the research.

CONCLUSIONS

Mental Health and Athletic Success The mental health model has produced inconsistent results in differentiating successful athletes from less successful athletes in terms of individual mood scales. However, measures of global mood have been effective in identifying when individual athletes are experiencing a psychologically unhealthy, overtrained state. Thus, the use of global mood measures may be useful for monitoring the potential psychopathology associated with intense physical training.

Physical Versus Mental Practice If the goal is to maximize performance in the shortest possible amount of time, physical practice is superior to mental practice. However, if nonphysical practice time is available or if a person cannot physically practice, then the small effects due to mental practice can be useful for facilitating performance and for better retention.

Cognitive-Behavioral Interventions The overall effects of cognitive-behavioral interventions are small to moderate. These effects will be enhanced if treatments emphasize: multiple components, (relaxation, modeling, imagery, cognitive restructuring, etc.); direct administration of the treatment by an investigator, rather than an audiotape); many sessions; people who have problems with precompetitive anxiety or concentration; and tasks that are objectively scored.

Preperformance Preparation In closed skills (the environment is unchanging), an individually designed preperformance routine, “preparation ritual” with multiple components has been shown to facilitate performance. In closed skill sports that involve aiming (e.g., rifle shooting), better performers have a greater cardiac deceleration within 3.5 seconds of executing a motor response. In addition, better performances are associated with a moderate increase (above baseline rates) alpha activity in the left hemisphere of the brain and little or no change in activity in the right hemisphere. However, too great an increase in left hemispheric alpha activity is associated with worse shots. Electrophysiological patterns like heart-rate deceleration and EEG asymmetries that are related to performance can be used during the preparatory period (i.e., 3-5 seconds before response execution) to assist in determining the efficacy of preperformance routines.

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

Exercise and Stress Aerobic exercise is related to reduced physiological and psychological response and quicker recovery from psychosocial stressors.

Neuroscience and Peak Performance Further understanding of the bases for performance is likely to come from ongoing research in neuroscience and on “peak performance. ” Recent neuroscientific studies using imaging techniques have shown that even simple motor processes have complex neurophysiological correlates. Research on high performance behavior has made progress in identifying the affective, attentional, and cognitive states associated with such behavior.

NOTES

1. The iceberg profile does not convey a relationship in a true scientific sense; it is more an artifact resulting from connecting unrelated points with lines rather than representing mean values with a bar graph.

2. The 70-80 percent prediction accuracy may be inflated since in at least one study (Study 4) 7 of the 16 athletes did not have profiles that were “sufficiently remarkable to permit application of the clinical prediction model” (Morgan, 1985:74). Thus, they were eliminated and the prediction analysis was only carried out on the remaining nine athletes, and all nine predictions (100 percent) proved to be correct (Morgan, 1985). It is unclear why the seven athletes were “sufficiently remarkable” in this study. In other studies, it appears that all were included in the clinical prediction analysis, even though approximately 10 percent of the nonhospitalized population would have mental health problems of clinical significance (Morgan et al., 1987b).

3. The study of 40 members of the University of Wisconsin wrestling team did not show significant changes in their mood states over a 5-month period. Although 10 percent of the wrestlers developed mood disturbance, the failure of the group data to show significant changes in mood disturbance as a function of training stimulus may be due to the greater difficulty in calculating peak work loads in wrestling in comparison with swimming.

4. The only phase in which salivary cortisol was correlated with depressed mood was in the overtraining phase (r = .50; p < .05).

5. To provide a common metric and thereby equate times for various swimming distances, T scores can be calculated in much the same way as in the decathlon competition in track and field.

6. Most of the studies covered in these reviews were published between 1970 and 1989. The narrative review by Greenspan and Feltz (1989) dealt with 19 published articles (23 interventions) and the Whelan et al. (1989) meta-analytic review contained 49 published articles (121 comparisons across 333 outcome measures). The differences in the numbers of studies is because Whelan et al. included studies with a greater variety of interventions (e.g., goal setting, modeling, association/disassociation strategies, and hypnotherapy). In neither review were there unpublished studies (e.g., dissertations, government reports, papers presented at meetings). This led Greenspan and Feltz (1989) and Whelan et al. (1989) to suggest the possibility of a “file drawer” problem or publication bias. For example, either researchers obtaining nonsignificant results are not submitting their research for publication or journal reviewers are less likely to publish articles showing nonsignificant results than those showing significant results. This is certainly possible since Feltz and Landers' (1983) review of the motor performance literature showed that the effect size for unpublished studies was significantly smaller (0.32) than the effect size for published studies (0.74).

Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

7. Although these findings could be overestimated without unpublished studies, the likelihood of unpublished studies substantially reducing an effect size of 0.62 is not great. According to Orwin's (1983) fail-safe formula, it would take nearly 120 studies showing very small effect sizes (e.g., 0.20) to reduce this moderate effect size to a small one. Since previous reviewers (Greenspan and Feltz, 1989) could not find many unpublished studies, it does not appear that missing studies would greatly influence the strength of this relationship. Thus, the effects appear to be real and are very robust in that they generalize across studies using very diverse interventions, research designs, subject characteristics, and sports.

8. “Open” skills, like those in basketball, football, and soccer, involve constantly changing environmental conditions such as blocking and faking. “Closed” skills, like those in bowling, archery, and free-throw shooting in basketball, involve stable environmental conditions.

9. Using the data in Kim's (1989) Table 1, we calculated pretest-posttest effect sizes for each group with the same formula used by Feltz et al. (1988). This secondary analysis revealed that the combined relaxation/meditation/imagery group was more effective in reducing anxiety (ES = 0.93) and improving performance (ES = 0.80) than the meditation/imagery group (ESs = 0.48 and 0.24, respectively), the relaxation/imagery group (ESs = 0.30 and −0.14, respectively), and the control group (ESs = −0.04 and 0.04, respectively).

10. These studies used an appropriate A-B-A-B single-subject design.

11. Although the mental practice group performed at an initially higher level than the control subjects, they made smaller pretest-posttest gains than did the control subjects. For example, the effect sizes for the pretest-posttest gains for the mental practice and control groups were 0.35 and 0.75, respectively, for firing rate; 0.76 and 1.26 for hit probability; and 0.66 and 1.04 for hit rate.

12. A challenge attitude is described by Loehr (1989) as involving 100 percent effort without fear. A player with this attitude feels free and aggressive and won't give up or become angry. Although a person can substantially improve the amount of time he or she displays a challenge attitude, one can never really master it.

13. As in the Lacey and Lacey (1980) laboratory research, cardiac deceleration patterns observed in sports are unrelated to sinus arrhythmia since decelerations have occurred with a variety of respiratory patterns (Boutcher and Zinsser, 1990; Crews, 1989).

14. In addition to a greater amount of cardiac deceleration prior to a shot, Schmid (1989) noted that elite archers exhibited a postshot delay in cardiac acceleration.

15. A planned comparison t test between epoch 1 (0.5 second before arrow release) and epoch 5 (2.5 seconds before arrow release) during the pre- and posttest revealed that cardiac deceleration was significant only during the posttest. The means for the posttest were 85.1 beats per minute at epoch 1 and 91.5 beats per minute at epoch 5. The heart rates for pre- and posttest at epoch 1 were not significantly different.

16. There is debate as to whether the Hedges and Olkin (1985) meta-analytic procedures are appropriate for studies like Crews and Landers (1987) in which a whole population of studies is considered. Hedges and Olkin's analysis of variance (ANOVA) analogue involves statistical assumptions of a sample derived from a population. When dealing with the entire population, the rather stringent procedures of the ANOVA analogue may not be necessary or even recommended. For example, they may conceal real differences between moderator variables. In the case of the Crews and Landers (1987) meta-analysis, subsequent investigation may reveal that effect sizes are greater for published studies that use chronic exercise and that use random assignment.

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×

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×

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Suggested Citation:"11 Optimizing Individual Performance." National Research Council. 1991. In the Mind's Eye: Enhancing Human Performance. Washington, DC: The National Academies Press. doi: 10.17226/1580.
×

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The archer stands and pulls back the bow, visualizing the path of the arrow to the target. Does this mental exercise enhance performance? Can we all use such techniques to improve performance in our daily lives?

In the Mind's Eye addresses these and other intriguing questions. This volume considers basic issues of performance, exploring how techniques for quick learning affect long-term retention, whether an expert's behavior can serve as a model for beginners, if team performance is the sum of individual members' performances, and whether subliminal learning has a basis in science.

The book also considers meditation and some other pain control techniques. Deceit and the ability to detect deception are explored in detail. In the area of self-assessment techniques for career development, the volume evaluates the widely used Myers-Briggs Type Indicator.

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