Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 193
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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sports is negatively correlated with psychopathology: that is, anxious, depressed, hysterical, neurotic, introverted, withdrawn, confused, fatigued, or schizoid athletes do not perform as well in sports as athletes with more positive mental health profiles.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-
OCR for page 194
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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,
OCR for page 195
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 196
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 197
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 198
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 199
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 200
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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-
OCR for page 201
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 202
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 203
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE 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
OCR for page 236
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Annett, J. 1979Memory for skill. Pp. 233-247 in M.M. Gruneberg and P.E. Morris, eds., Applied Problems in Memory. New York: Academic Press. Anshel, M.H. 1988 The effect of mood and pleasant versus unpleasant information feedback on performing a motor skill. Journal of General Psychology 115:117-129. Bandura, A. 1982 Self-efficacy mechanism in human agency. American Psychologist 37:122-147. Bedford, T.G., and C.M. Tipton 1987Exercise training and arterial baroreflex. Journal of Applied Physiology 63:1926-1932. Bettelheim, B. 1960 The Informed Heart. New York: Free Press. Bloom, B. 1985 Developing Talent in Young People. New York: Ballentine Books. Blumenthal, J.A. 1989Letter to the editor: response to Abbott and Peters. Psychosomatic Medicine 51:219-221. Bohlin, G., and A. Kjellberg 1979 Orienting activity in two stimulus paradigms as reflected in heart rate. Pp. 169-197 in H.D. Kimmel, E.H. van Olst, and E.F. Orlebeke, eds., The Orienting Reflex in Humans. Hillsdale, N.J.: Erlbaum. Borkovec, T.D., and J.K. Sides 1979 Critical procedural variables related to the physiological effects of progressive relaxation: a review. Behavioral Research and Therapy 17:119-125. Boutcher, S.H., and D.J. Crews 1987The effect of a preshot attentional routine on a well-learned skill . International Journal of Sport Psychology 18:30-39. Boutcher, S.H., and N.W. Zinsser 1990 Cardiac deceleration of elite and beginning golfers during putting . Journal of Sport and Exercise Psychology 12:37-47. Boyle, G.P. 1987 A cross-validation of the factor structure of the profile of mood states: were the factors correctly identified in the first instance? Psychological Reports 60:343-354. Campbell, D.T., and J.C. Stanley 1963 Experimental and Quasi-Experimental Designs for Research. Chicago: Rand McNally. Carroll, D., and P. Anastasiades 1978 The behavioral significance of heart rate: the Laceys' hypothesis. Biological Psychology 7:249-275. Chollet, F., V. DiPiero, R. Wise, D. Brooks, R. Dolan, and R. Frackowiak 1991 The functional anatomy of recovery after stroke in humans: a study with positron emission tomography. Annals of Neurology 29:63-71. Christina, R.W. 1987Motor learning: future lines of research. The Academy Papers 20:26-41. Cohn, P.J., R.J. Rotella, and J.W. Lloyd 1990 Effects of a cognitive-behavioral intervention on the preshot routine and performance in golf. The Sport Psychologist 4:33-47. Coles, M.G.H. 1984 Heart rate and attention: the intake-rejection hypothesis and beyond . Pp. 276-294 in M.G.H. Coles, J.R. Jennings, and J.A. Stern, eds., Psychophysiological Perspectives: Festschrift for Beatrice and John Lacey. Stroudburg, Pa.: Hutchinson and Ross.
OCR for page 237
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Craighead, D.J., G. Privette, F. Vallianos, and D. Byrkit 1986 Personality characteristics of basketball players, starters and non-starters . International Journal of Sport Psychology 17:110-119. Crews, D.J. 1989 The Influence of Attentive States on Golf Putting as Indicated by Cardiac and Electrocortical Activity. Unpublished doctoral dissertation, Arizona State University. Crews, D.J., and S.H. Boutcher 1986a An exploratory observational analysis of professional golfers during competition. Journal of Sport Behavior 9:51-58. 1986b Effects of structured preshot behaviors on beginning golf performance . Perceptual and Motor Skills 62:291-294. Crews, D.J., and D.M. Landers 1987 A meta-analytic review of aerobic fitness and reactivity to psychosocial stressors. Medicine and Science in Sport and Exercise 19(5):114-120. 1991 Cardiac Pattern as an Indicator of Attention: A Test of Two Hypotheses . Unpublished manuscript, Department of Exercise Science and Physical Education, Arizona State University, Tempe. Csikszentmihalyi, M. 1990Flow: The Psychology of Optimal Experience. New York: Harper and Row. Csikszentmihalyi, M., and R. Larson 1987 Validity and reliability of the Experience Sampling Method. Journal of Nervous and Mental Disease 175:526-536. Daiss, S., A. LeUnes, and J. Nation 1986 Mood and locus of control of a sample of college and professional football players. Perceptual and Motor Skills 63:733-734. Davidson, R.J., G.E. Schwartz, and L. Rothman 1976 Attentional style and self-regulation of mode specific attention: an EEG study. Journal of Abnormal Psychology 85:611-621. Deijen, J., M. Heemstra, and J. Orlebeke 1989 Dietary effects on mood and performance. Journal of Psychiatric Research 23:275-283. DeMers, G.E. 1983 Emotional states of high-caliber divers. Swimming Technique May-July:33-35. Diamond, M., E. Greer, A. York, D. Lewis, T. Barton, and J. Lin 1987 Rat cortical morphology following crowded-enriched living conditions . Experimental Neurology 96:241-247. Dishman, R.K. 1982 Contemporary sport psychology. Exercise and Sport Sciences Reviews 10:120-143. Druckman, D., and J. Lacey, eds. 1989 Brain and Cognition: Some New Technologies. Committee on New Techniques in Cognitive Psychophysiology, Commission on Behavioral and Social Sciences and Education, National Research Council. Washington, D.C.: National Academy Press. Druckman, D., and J.A. Swets, eds. 1988 Enhancing Human Performance: Issues, Theories, and Techniques. Committee on Techniques for the Enhancement of Human Performance, Commission on Behavioral and Social Sciences and Education, National Research Council. Washington, D.C.: National Academy Press. Dyer, J.B., III, and J.G. Crouch 1987 Effects of running on moods: a time series study. Perceptual and Motor Skills 64:783-789.
OCR for page 238
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Elliott, R. 1972 The significance of heart rate for behavior: a critique of Lacey's hypothesis. Journal of Personality and Social Psychology 22:398-409. Eysenck, H.J., and S.B.G. Eysenck 1968 Manual for the Eysenck Personality Inventory. San Diego, Calif.: Educational and Industrial Testing Service. Eysenck, H.J., D.K.B. Nias, and D.N. Cox 1982Sport and personality. Advances in Behavior Research and Therapy 4(2):1-56. Feltz, D.L., and D.M. Landers 1983The effects of mental practice on motor skill learning and performance: a metaanalysis. Journal of Sport Psychology 5:25-57. Feltz, D.L., and C.A. Riessinger 1990 Effects of in vivo emotive imagery and performance feedback on self-efficacy and muscular endurance. Journal of Sport and Exercise Psychology 12:132-143. Feltz, D.L., D.M. Landers, and U. Raeder 1979 Enhancing self-efficacy in high-avoidance motor tasks: a comparison of modeling techniques. Journal of Sport Psychology 1:112-122. Feltz, D.L., D.M. Landers, and B.J. Becker 1988 A revised meta-analysis of the mental practice literature on motor skill learning. Pp. 1-65 in D. Druckman and J.A. Swets, eds., Enhancing Human Performance: Issues, Theories and Techniques. Background Papers. Committee on Techniques for the Enhancement of Human Performance, Commission on Behavioral and Social Sciences and Education, National Research Council. Washington, D.C.: National Academy Press. Frankl, V. 1963 From Death Camp to Existentialism. Boston: Beacon Press. Gal, R., and R.S. Lazarus 1975 The role of activity in anticipating and confronting stressful situations . Journal of Human Stress December:4-20. Gale, A., and J.A. Edwards 1983 The EEG and human behavior. Pp. 99-127 in A. Gale and J.A. Edwards, eds., Psychological Correlates of Human Behavior. New York: Academic Press. Gallwey, W.T. 1981 The Inner Game of Golf. New York: Random House. Garfield, C. 1978 Peak Performance. Los Angeles, Calif.: Tarcher Press. Gasser, T., P. Bacher, and H. Steinberg 1985 Test-retest reliability of spectral parameters of the EEG. Electroencephalography and Clinical Neurophysiology 60:312-319. Gevins, A.S., N.H. Morgan, S.L. Bressler, B.A. Cutillo, R.M. White, J. Illes, D.S. Greer, J.C. Doyle, and G.M. Zeitlin 1987Human neuroelectric patterns predict performance accuracy. Science235:580-585. Gevins, A.S., B.A. Cutillo, S.L. Bressler, N.H. Morgan, R.M. White, J. Illes, and D.S. Greer 1989 Event-related covariances during a dimanual visuomotor task. II. Preparation and feedback. Electroencephalography and Clinical Neurophysiology 74:147-160. Gould, D., R. Weinberg, and A. Jackson 1980 Mental preparation strategies, cognitions and strength performance . Journal of Sport Psychology 2:329-339. Graham, F.K. 1979 Distinguishing among orienting, defense and startle reflexes. Pp. 137-167 in H.D. Kimmel, E.H. van Olst, and J.F. Orlebeke, eds., The Orienting Reflex in Humans. Hillsdale, N.J.: Erlbaum.
OCR for page 239
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Greenspan, M.J., and D.L. Feltz 1989 Psychological interventions with athletes in competitive situations: a review. The Sport Psychologist 3(3):219-236. Guttman, M.C., M.L. Pollack, C. Foster, and D. Schmidt 1984 Training stress in Olympic speed skaters: a psychological perspective . The Physician and Sports Medicine 12:45-57. Hahn, W.W. 1973 Attention and heart rate: a critical appraisal of the hypothesis of Lacey and Lacey. Psychological Bulletin 79:59-70. Hall, E., and E. Erffmeyer 1983 The effect of visuo-motor behavior rehearsal with video-taped modeling on free-throw accuracy of intercollegiate female basketball players . Journal of Sport Psychology 5:343-346. Hamilton, S., and W. Fremouw 1985 Cognitive-behavioral training for college free-throw performance. Cognitive Therapy and Research 9:479-483. Hatfield, B.D., and D.M. Landers 1987 Psychophysiology in exercise and sport research: an overview. Exercise and Sport Sciences Reviews15:351-387. Hatfield, B.D., D.M. Landers, and W.J. Ray 1984 Cognitive processes during self-paced motor performance: an electro-encephalographic profile of skilled marksmen. Journal of Sport Psychology 6:42-59. 1987 Cardiovascular-CNS interactions during a self-paced, intentional attentive state: elite marksmanship performance. Psychophysiology 24:542-549. Hatze, H. 1976 Biomechanical aspects of a successful motion optimization. Pp. 5-12 in P.V. Komi, ed., Biomechanics V-B. Baltimore, Md.: University Park Press. Hedges, L.V., and I. Olkin 1985 Statistical Methods for Meta-Analysis. Orlando, Fla.: Academic Press. Heward, W. 1978 The effects of reinforcement on the offensive efficiency of a barn-storming baseball team. Behavior Modification 2(1):25-59. Heyman, S.R. 1987 Research and interventions in sport psychology: issues encountered in working with an amateur boxer. The Sport Psychologist 1:208-223. Hird, J.S., D.M. Landers, J.R. Thomas, and J.J. Horan 1991Physical practice is superior to mental practice in enhancing cognitive and motor performance. Journal of Sports Exercise Psychology. In press. Horswill, C.A., R.C. Hickner, J.R. Scott, D.L. Costill, and D. Gould 1990 Weight loss, dietary carbohydrate modifications, and high intensity physical performance. Medicine and Science in Sports and Exercise 22:470-476. Howell, M.L. 1956Use of force-time graphs for performance analysis in facilitating motor learning. Research Quarterly 27:12-22. Jennings, J.R., B.E. Lawrence, and P. Kasper 1978 Changes in alertness and processing capacity in a serial learning task. Psychophysiology 17:37-46. Kahneman, D. 1973 Attention and Effort. Englewood Cliffs, N.J.: Prentice-Hall. Kendall, G., D. Hrycaiko, G.L. Martin, and T. Kendall 1990 The effects of imagery rehearsal, relaxation, and self-talk package on basketball game performance. Journal of Sport and Exercise Psychology 12:157-166.
OCR for page 240
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Kim, G.B. 1989 Relative effectiveness of anxiety reduction techniques on levels of competitive anxiety and shooting performance. Pp. 61-74 in Commemorative Volume Dedicated to Professor Hong-Dae Kim, Young-Nam University. Dae-Ku, Republic of Korea: Hong-ik Publishing Co. Kirschenbaum, D., and R. Bale 1980 Cognitive-behavioral skills in golf: brain power golf. Pp. 275-287 in R. Suinn, ed., Psychology in Sports: Methods and Applications. Minneapolis. Minn.: Burgess. Komaki, J., and F. Barnett 1977 A behavioral approach to coaching football: improving the play execution of the offensive backfield on a youth football team. Journal of Applied Behavior Analysis 10:657-664. Kubitz, K.A., D.M. Landers, W. Salazar, and S.J. Petruzzello 1991A Meta-Analytic Review of the Effects of Acute Exercise on Selected Aspects of Sleep. Unpublished manuscript, Department of Exercise Science and Physical Education, Arizona State University. Lacey, B.C., and J.I. Lacey 1964 Cardiac Deceleration and Simple Visual Reaction Time in a Fixed Foreperiod Experiment. Paper presented at the October meeting of the Society for Psychophysiological Research, Washington, D.C. 1966 Change in Cardiac Response and Reaction Time as a Function of Motivation . Paper presented at the October meeting of the Society for Psychophysiological Research, Denver, Colo. 1970 Some autonomic-central nervous system interrelationships. Pp. 205-261 in P. Black, ed., Physiological Correlates of Emotion. New York: Academic Press. 1974 Studies of heart rate and other bodily processes in sensorimotor behavior. Pp. 538-564 in P.A. Obrist, A.H. Lack, J. Brener, and L.V. DiCara, eds., Cardiovascular Psychophysiology. Chicago: Aldine. 1980Sensorimotor behavior and cardiac activity. Pp. 170-179 in I. Martin and P.H. Venables, eds., Techniques in Psychophysiology. New York: Wiley. Lacey, J.I. 1967 Somatic response patterning and stress: some revisions of activation theory. Pp. 14-37 in M.H. Appley and R. Trumbull, eds., Psychological Stress: Issues in Research. New York: Appleton-Century-Crofts. Lacey, J.I., J. Kagan, B.C. Lacey, and H.A. Moss 1963 The visceral level: situational determinants and behavioral correlates of autonomic response patterns. Pp. 161-196 in P.H. Knapp, ed., Expression of the Emotions in Man. New York: International Universities Press. Landers, D.M. 1985 Psychophysiological assessment and biofeedback: applications for athletes in closed skill sports. Pp. 63-105 in J.H. Sandweis and S. Wolf, eds., Biofeedback and Sports Science. New York: Plenum Press. Landers, D.M., M.Q. Wang, and P. Courtet 1985 Peripheral narrowing among experienced and inexperienced rifle shooters under low-and high-time stress conditions. Research Quarterly for Exercise and Sport 56:122-130. Landers, D.M., M.W. Han, W. Salazar, S.H. Petruzzello, K.A. Kubitz, and T.L. Gannon 1991aThe effects of learning on electroencephalographic and electrocardiographic patterns in novice archers. International Journal of Sport Psychology. In press.
OCR for page 241
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Landers, D.M., S.H. Petruzzello, W. Salazar, D.J. Crews, K.A. Kubitz, T.L. Gannon, and M.W. Han 1991b The influence of electrocortical biofeedback on performance in pre-elite archers. Medicine and Science in Sports and Exercise 23:123-129. Landy, F.J., and R.M. Stern 1971 Factor analysis of a somatic perception questionnaire. Journal of Psychosomatic Research 15:179-181. Larson, R., and M. Csikszentmihalyi 1983 The experience sampling method. In H. Reis, ed., Naturalistic Approaches to Studying Social Interactions. San Francisco, Calif.: Jossey Bass. Lawrence, G., D. Druckman, and D.M. Landers 1990 Mental practice for solderers. Unpublished manuscript, U.S. Army Research Institute, Alexandria, Va. Lee, A.B., and J. Hewitt 1987 Using visual imagery in a flotation tank to improve gymnastic performance and reduce physical symptoms. International Journal of Sport Psychology 18:223-230. LeUnes, A., and J.R. Nation 1982 Saturday's heroes: a psychological portrait of college football players. Journal of Sport Behavior5:139-149. LeUnes, A., S. Daiss, and J.R. Nation 1986 Some psychological predictors of continuation in a collegiate football program. Journal of Applied Research in Coaching and Athletics 1:1-8. LeUnes, A., S.A. Hayward, and S. Daiss 1988 Annotated bibliography on the profile of mood states in sport, 1975-1988 . Journal of Sport Behavior 11(4):213-240. Light, K.C. 1982 Cardiovascular responses to effortful active coping. Psychophysiology 18:216-225. Lobmeyer, D.L., and E.A. Wasserman 1986 Preliminaries to free throw shooting: superstitious behavior? Journal of Sport Behavior 9:70-78. Loehr, J. 1989 Mental Toughness. Videotape. Available from Grand Slam Communications, 5150 Linton Blvd., Suite 420, Delray Beach, Florida 33484. Lubin, B. 1967 Manual for the Depression Adjective Checklist. San Diego, Calif.: Educational and Industrial Testing Service. Mace, R., C. Eastman, and D. Carroll 1987 The effects of stress-inoculation training on gymnastics performance on the pommelled horse: a case study. Behavioral Psychotherapy 15:272-279. Maddi, S. 1965 Motivational aspects of creativity. Journal of Personality 33:330-347. Mahoney, M.J., and M. Avener 1977 Psychology of the elite athlete: an exploratory study. Cognitive Therapy and Research 1:135-141. Maslow, A. 1971 The Farther Reaches of Human Nature. New York: Viking Press. Massimini, F., and P. Inghilleri 1987 L'esperienza Quotidiana. Milano: Franco Angeli Libri. Massimini, F., M. Csikszentmihalyi, and M. Carli 1987 The monitoring of optimal experience: a tool for psychiatric rehabilitation . Journal of Nervous and Mental Disease 175:545-549.
OCR for page 242
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Mazziotta, J., and M. Phelps 1984 Positron computed tomography studies of cerebral metabolic responses to complex motor tasks. Neurology 34:116. McCullagh, P., M.R. Weiss, and D. Ross 1989 Modeling considerations in motor skill acquisition and performance: an integrated approach. Exercise and Sport Science Reviews 17:475-513. McCullagh, P., K.J. Evans, K.M. Morrison, and K.M. Petersen 1990a The Use of Videotapes and Imagery to Enhance Skilled Performance. Unpublished manuscript, Department of Kinesiology, University of Colorado, Boulder. McCullagh, P., A. Meriweather, and D.I. Siegel 1990b The Effectiveness of Sybervision as an Observational Learning Tool for the Tennis Serve. Unpublished manuscript, Department of Kinesiology, University of Colorado, Boulder. McNair, D.M., M. Lorr, and L.F. Droppleman 1971/81 Profile of Mood States Manual. San Diego, Calif.: Educational and Industrial Testing Service. Meyers, A., R. Schleser, and T. Okwumabua 1982 A cognitive behavioral intervention for improving basketball performance . Research Quarterly for Exercise and Sport 53(4):344-347. Miller, B.P., and G.P. Edgington 1984 Psychological mood state distortion in a sporting context. Journal of Sport Behavior7(3):91-94. Miller, B.P., and A.J. Miller 1985 Psychological correlates of success in elite sportswomen. International Journal of Sport Psychology 16:289-295. Molander, B., and L. Backman 1989 Age differences in heart rate patterns during concentration in a precision sport: implications for attentional functioning. Journal of Gerontology: Psychological Sciences 44:80-87. Morgan, W.P. 1979 Anxiety reduction following acute physical activity. Psychiatric Annals 9:141-147. 1980 Test of champions. Psychology Today July:92-99. 1981Psychophysiology of self-awareness during vigorous physical activity . Research Quarterly for Exercise and Sport 52:385-427. 1985 Selected psychological factors limiting performance: a mental health model. Pp. 70-80 in D.H. Clarke and H.M. Eckert, eds., Limits of Human Performance. Champaign, Ill.: Human Kinetics. Morgan, W.P., and R.W. Johnson 1978 Personality characteristics of successful and unsuccessful oarsmen . International Journal of Sport Psychology 9:119-133. Morgan, W.P., and M.L. Pollock 1977 Psychologic characterization of the elite distance runner. Annals of the New York Academy of Sciences 301:383-403. Morgan, W.P., D.R. Brown, J.S. Raglin, P.J. O'Connor, and K.A. Ellickson 1987a Psychological monitoring of overtraining and staleness. British Journal of Sports Medicine21:107-114. Morgan, W.P., P.J. O'Connor, P.B. Sparling, and R.R. Pate 1987b Psychological characterization of the elite female distance runner . International Journal of Sports Medicine 8(Supplement):124-131. Morgan, W.P., D.L. Costill, M.G. Flynn, J.S. Raglin, and P.J. O'Connor 1988 Mood disturbance following increased training in swimmers. Medicine and Science in Sports and Exercise 20:408-414.
OCR for page 243
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Morrison, J.E., and S.A. Walker 1990 Effects of Mental Practice on Tank Gunnery Performance. Technical report no. 873. U.S. Army Research Institute for the Behavioral and Social Sciences , Alexandria, Va. Mumford, B., and C. Hall 1985 The effects of internal and external imagery on performing figures in figure skating. Canadian Journal of Applied Sport Sciences 10(4):171-177. Neiss, R. 1990 Expectancy in motor behavior: a crucial element of the psychobiological states that affect performance. Human Performance 2:273-300. Newell, K.M., J.T. Quinn, Jr., W.A. Sparrow, and C.B. Walter 1983 Kinematic information feedback for learning a rapid arm movement. Human Movement Science 2:255-269. Newell, K.M., W.A. Sparrow, and J.T. Quinn, Jr. 1985 Kinetic information feedback for learning isometric skills. Journal of Human Movement Studies 11:113-123. Nisbett, R.E., and T.D. Wilson 1977 Telling more than we can know: verbal reports on mental processes . Psychological Review 84:231-259. Norcross, J.C., E. Guadagnoli, and J.O. Prochaska 1984 Factor structure of the profile of mood states (POMS): two partial replications. Journal of Clinical Psychology 40:1270-1277. North, T.C., P. McCullagh, and Z.V. Tran 1990 Effect of exercise on depression. Exercise and Sport Sciences Reviews 18:379-415. Obrist, P.A. 1981 Cardiovascular Psychophysiology: A Perspective. New York: Plenum Obrist, P.A., R.A. Webb, J.R. Sutterer, and J.L. Howard 1970 Cardiac deceleration and reaction time: an evolution of two hypotheses . Psychophysiology 6:695-706. O'Connor, K.P. 1981The intentional paradigm and cognitive psychophysiology. Psychophysiology18:121-128. O'Connor, P.J., W.P. Morgan, J,S. Raglin, C.M. Barksdale, and N.H. Kalin 1989 Mood state and salivary cortisol levels following overtraining in female swimmers. Psychoneuroendocrinology 14:303-310. Orwin, R.G. 1983 A fail-safe N for effect size. Journal of Educational Statistics 8:157-159. Oxendine, J.B. 1969 Effect of mental and physical practice on the learning of three motor skills. Research Quarterly 40(4):744-763. Pahl, J. 1990 Positron emission tomography in the study of higher cognitive functions . In A. Schiebel and A. Wechsler, eds., Neurobiology of Higher Cognitive Function. New York: Guilford. Petruzzello, S.J., D.M. Landers, B.D. Hatfield, K.A. Kubitz, and W. Salazar 1991 A meta-analysis on the anxiety reducing effects of acute and chronic exercise: outcomes and mechanisms. Sports Medicine 11:143-182. Pirozzolo, F.J. 1991 A developmental neuropsychological model of human performance. Developmental Neuropsychology 7:377-391. Pirozzolo, F.J., and M. Csikszentmihalyi 1991 Preparation to Perform Under Pressure. Unpublished manuscript, Department of Neurology, Baylor College of Medicine.
OCR for page 244
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Raven, P.B., D. Rohm-Young, and C.G. Blomquist 1984 Physical fitness and cardiovascular response to lower body negative pressure. Journal of Applied Physiology 56:138-144. Ray, W.J., and H.W. Cole 1985 EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes. Science 228:750-752. Ray, R.L., and H.D. Kimmel 1979 Utilization of psychophysiological indices in behavioral assessment: some methodological issues. Journal of Behavioral Assessment 1:107-122. Reddon, J.R., R. Marceau, and R.R. Holden 1985 A confirmatory evaluation of the Profile of Mood States: convergent and discriminant item validity. Journal of Psychopathology and Behavioral Assessment 7:243-259. Richardson, A. 1967 Mental practice: a review and discussion. Part 1. Research Quarterly 38(1):95-107. Riddick, C.C. 1984 Comparative psychological profiles of three groups of female collegians: competitive swimmers, recreational swimmers, and inactive swimmers . Journal of Sport Behavior 7:160-174. Robinson, R. 1990 The Iron Horse. New York: Harper and Row. Roland, P., E. Meyer, T. Shibasaki, Y. Yamamoto, and C. Thompson 1982 Regional cerebral blood flow changes in cortex and basal ganglia during voluntary movements in normal human volunteers. Journal of Neurophysiology 48:467-480. Roland, P., L. Eriksson, S. Stone-Elander, and L. Widen 1987 Does mental activity change the oxidative metabolism of the brain? Journal of Neuroscience 1:2373-2389. Rose, D., and R.W. Christina 1990 Attentional demands of precision pistol-shooting as a function of skill level. Research Quarterly for Exercise and Sport 61:111-113. Rothstein, A.L., and R.K. Arnold 1976 Bridging the gap: application of research on videotape feedback and bowling. Motor Skills: Theory Into Practice 1:35-62. Ryan, A.J. 1983 Exercise is medicine. The Physician and Sports Medicine 11:10. Salazar, W., D.M. Landers, S.J. Petruzzello, D.J. Crews, K.A. Kubitz, and M.W. Han 1990 Hemispheric asymmetry, cardiac response, and performance in elite archers. Research Quarterly for Exercise and Sport 61:351-359. Sandman, C.A., and B.B. Walker 1985 Cardiovascular relationship to attention and thinking. Pp. 95-122 in V.M. Rental, S.A. Corson, and B.R. Dunn, eds., Psychophysiological Aspects of Reading and Learning. New York: Gordon & Breach. Schmid, W.D. 1989 Heart rate patterns of archers while shooting. Fiziologiya Cheloveka 15:64-68. Shulhan, D., H. Scher, and J. Furedy 1986 Phasic cardiac reactivity to psychological stress as a function of aerobic fitness level. Psychophysiology 23:562-566. Silva, J.M., III, B.B. Schultz, R.W. Haslam, and D. Murray 1981 A psychophysiological assessment of elite wrestlers. Research Quarterly for Exercise and Sport 52:348-358. Silva, J.M., III, B.B. Shultz, R.W. Haslam, T.P. Martin, and D.F. Murray 1985 Discriminating characteristics of contestants at the United States Olympic wrestling trials. International Journal of Sport Psychology 16:79-102.
OCR for page 245
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Singer, R.N., L.A. Flora, and T.L. Abpirezl 1989 The effect of a five-step cognitive learning strategy on the acquisition of a complex motor task. Journal of Applied Sport Psychology 1:98-108. Singer, R.S. 1972 The Psychomotor Domain: Movement Behavior. Philadelphia, Pa.: Lea & Febiger. Smith, R.E. 1980 A cognitive-affective approach to stress management training for athletes. Pp. 54-72 in C.H. Nadeau, W.R. Halliwell, K.M. Newell, and G.C. Roberts, eds., Psychology of Motor Behavior and Sport—1979. Champaign, Ill.: Human Kinetics. Spielberger, C.D., R.L. Gorsuch, and R.E. Lushene 1970 Manual for the State-Trait Anxiety Inventory. Palo Alto, Calif.: Consulting Psychologists Press. Stern, R.M. 1976 Reaction time and heart rate between the GET SET and GO of simulated races. Psychophysiology 13:149-154. Suinn, R.M. 1977 Behavioral methods at the winter games. Behavioral Therapy 8:283-284. 1983 Imagery and sports. Pp. 507-534 in A.A. Sheikh, ed., Imagery: Current Theory, Research, and Application. New York: Wiley. Tharion, W.J., S.R. Strowman, and T.M. Rauch 1988 Profile and changes in moods of ultramarathoners. Journal of Sport and Exercise Psychology 10:229-235. van der Molen, M.W., R.J.M. Somsen, and J.F. Orlebeke 1985 The rhythm of the heart beat in information processing. Pp. 1-88 in P.K. Ackles, J.R. Jennings, and M.G.H. Coles, eds., Advances in Psychophysiology. Greenwich, Conn.: JAI Press. Walker, B.B., and C.A. Sandman 1979 Human visual evoked responses are related to heart rate. Journal of Comparative and Physiological Psychology 93:717-729. 1982 Visual evoked potentials change as heart rate and carotid pressure change. Psychophysiology 19:520-527. Wang, M.Q., and D.M. Landers 1987A psychophysiological investigation of attention during archery performance . Psychophysiology 23:449. Weinberg, R.S. 1982 The relationship between mental preparation strategies and motor performance: a review and critique. Quest 33(2):195-213. Weinberg, R., T. Seabourne, and A. Jackson 1981 Effects of visuo-motor behavior rehearsal, relaxation, and imagery on karate performance. Journal of Sport Psychology 3:228-238. Wheeler, R.E., A.J. Tomarken, L.M. Kinney, A.M. Straus, R.C. Doss, and R.J. Davidson 1989 EEG Activation Asymmetries Are Stable Over Time. Paper presented at the annual meeting of the Society for Psychophysiological Research, New Orleans, October. Whelan, J.P., A.W. Meyers, and J.S. Berman 1989 Cognitive-behavioral interventions for athletic performance enhancement . Paper presented at the annual meeting of the American Psychological Association, New Orleans. Williams, T., and G. Krahenbuhl 1991 Mood state and running economy in moderately trained male runners . Medicine and Science in Sports and Exercise 23(6):727-731. Wills, B.J. 1966 Mental Practice as a Factor in the Performance of Two Motor Tasks . Unpublished doctoral dissertation, University of Wisconsin, Madison.
OCR for page 246
IN THE MIND'S EYE: ENHANCING HUMAN PERFORMANCE Wilson, V.E., N.C. Morley, and E.I. Bird 1980 Mood profiles of marathon runners, joggers and non-exercisers. Perceptual and Motor Skills 50:117-118. Wurtman, R. 1982 Nutrients that modify brain function. Scientific American 246:42-51.
Representative terms from entire chapter: