"Youth Sports: Innocence Lost”
Dr. John Ferguson

By

Daniel Frankl, Ph.D., Professor
California State University, Los Angeles
School of Kinesiology and Nutritional Science

 
 
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The purpose of this article is to provide information about, and evidence of, the relationship between exercise and cognitive performance. This body of knowledge is divided into three sections that are related to research in this area. The three major areas addressed are 1) definitions of exercise, cognitive performance, and academic (class) performance, 2) trends of daily exercise participation in society and physical education, and 3) exercise and cognitive research in specific age groups.

2. Is There a Connection?.

  Years of examination of exercise research have provided contrasting evidence of a link between exercise and cognitive performance (Bills, 1927; Kirkendall, 1985; Tomporowski & Ellis, 1986; Weingarten, 1973). It is even less clear how exercise affects the cognitive performance in general, or the classroom performance in particular, of a diversified college student population in health/fitness physical education classes. In an attempt to address these issues, the need exists to examine the relationship between exercise and cognitive performance of college students in health/fitness physical education classes.

 The American College of Sports Medicine (ACSM, 2000) has indicated that substantial research literature supports the fact that exercise can improve physiological function, enhance psychological well being, and increase physical fitness. A limited amount of research has been conducted to explain how exercise relates to the classroom cognitive performance of college students, and mixed results exist in the exercise/cognitive performance research literature in the few studies that have used college-aged individuals as participants (Gliner, Matsen-Twisdale, Horvath, & Maron, 1979; Kubitz & Mott, 1996; Lybrand, Andrews, & Ross, 1954; Plunk & Bowden, 2001; Sullum, Clark, & King, 2000; Tomporowski, Ellis, & Stephens, 1987; Weingarten & Alexander, 1970). Although research has focused on the relationship between exercise and cognitive performance in general, there has been little investigation specific to the relationship between exercise as measured by caloric expenditure and cognitive performance as measured by class exam scores. More studies are needed to supplement the few that currently exist in an attempt to gain insight into this relationship.

 Cognitive performance measurements include memory recall , perceptual skills, and reaction time. Dillon and Schmeck (1983) defined cognitive performance as a function of critical thinking that requires the processing of information that can be perceived by the individual and placed in memory or retrieved from memory. An associated measure of cognitive performance is academic performance.

 Cambridge (2001) defines academic performance as the act of studying and thinking, especially at schools and universities, with measures expressed as letter grades or point grades for specific classroom work and grade point averages (GPA) for semester and/or academic year results. The research literature has presented mixed results from the influence of exercise on classroom performance, as some results (Lueptow & Kayser, 1973) have shown no association between these variables, while other research results (Shephard, 1997) indicated that a positive relationship does exist. Etnier et al. (1997) indicated that the general inconclusiveness of exercise/cognition research is partly because there are many influences on cognitive performance other than exercise and no single, specific variable has been proven to explain the variation in cognitive performance among individuals.


3. Exercise, Cognitive Performance, and Academic (Class) Performance Defined.

Exercise.

The American College of Sports Medicine (ACSM) defines physical activity as bodily movement produced by the contraction of striated muscle that substantially increases energy expenditure (ACSM, 2000). According to the ACSM, exercise is defined as a subset of physical activity that involves planned, structured, and repetitive bodily movement performed to improve or maintain one or more components of physical fitness. The components of physical fitness, which are objective and measurable, are 1) flexibility, 2) cardiovascular endurance, 3) muscular strength, 4) muscular endurance and 5) body composition. Exercise can thus be considered a method of achieving physical fitness.

Cognitive and academic (class) performance.

Dillon and Schmeck (1983) defined cognitive performance as a function of critical thinking that requires the processing of information that can be perceived by the individual and placed in memory or retrieved from memory. Cambridge (2001) states that a more specific measure of cognitive performance is academic performance, which is defined as the act of studying and thinking at schools, especially colleges and universities, with measures expressed as letter or point grades for specific class work, and grade point averages (GPA) for semester and academic year results. Although research has explored the possibility of a relationship between exercise and class performance, the mechanisms by which regular exercise may improve this measure of cognition are not well understood.

Measurements of cognitive performance include memory recall (Bills, 1927), perceptual skill (Krus, Wapner, & Werner, 1958; Weingarten, 1973; Young, 1979), reaction time (Chodzko-Zajko et al., 1992; Madden, Blumenthal, Allen, & Emery, 1989), and class performance (Sallis et al., 1999; Shephard & Lavallee, 1994). Research has shown that exercise has also been associated with changes in other psychological parameters such as a decrease in stress (Brown, 1991; Dua & Hargreaves, 1992; Kagan & Berg, 1988), and an increase in self-esteem (Daley & Buchanan, 1999; Walters and Martin, 2000). Wilmore and Costill (1999) reported that a cause-and-effect relationship exists between consistent, moderate exercise and physiological variables, and that as structured and consistent physical exercise also has numerous psychological effects on the human body.


4. Trends of Daily Exercise Participation.

Society.

Pate, Heath, Dowda, and Trost (1996) conducted the Youth Risk Behavior Survey of 11,631 high school students that provided information on exercise and other health behaviors, such as diet and substance use. A subset of 2,652 highly active students and a subset of 1,641 low-activity students were used to examine the relationship between exercise and other health behaviors. Logistic regression analysis results showed that low exercise levels were associated with cigarette smoking, marijuana use, lower fruit and vegetable consumption, greater television watching, and low perception of academic performance. The authors concluded that low exercise level was linked to several negative health behaviors and that interventions to increase exercise participation may be effective in reducing such behaviors.

According to Mokdad et al. (1999), obesity (defined as being over 30% above ideal body weight) in the overall population of the United States increased from 12% in 1991 to 18% in 1998. The greatest increase occurred between the ages of 18 to 29 years. By region, the largest increases in weight were seen in the South with a 67% increase in the number of obese people. The North Carolina Institute of Medicine (1999) reported that, in North Carolina , children and adults rank among the least physically fit of all states (49 th overall) and the state received a D+ grade on physical activity in 1998. The North Carolina Institute of Medicine also reported that, based on 1999 data from a national health initiative called Healthy People 2000, only 29% percent of students in grades 9-12 participated in daily physical education, down from 42% in 1991.

Statistics from the National Center for Health Statistics (2000) show that participation in regular physical exercise is not as prevalent as in the past, especially in school-aged individuals. Nearly half of all young people in the United States (12-21 years) are not vigorously active on a regular basis and the number of overweight children has more than doubled in the past decade. The United States Department of Health and Human Services (2000) reported that physical exercise is listed as one of the 10 leading health indicators for Healthy People 2010, a continuation of Healthy People 2000 directed by U.S. Surgeon General David Satcher. In an attempt to slow the decline of America 's physical health, physical inactivity has been placed as the second national priority for public health concerns in the new millennium. The Surgeon General has established a target goal of 85% of adolescents in grades 9-12 that engage in 20 minutes of vigorous exercise three or more days per week, up from the present level of 65%. Currently, only 15% of adults aged 18 years and older engage in 30 minutes of moderate physical exercise five or more days per week. Healthy People 2010 has a goal target of 30% for this age group.

Physical education.

Hanson and McKenzie (1989) reported that public school systems in the United States have often viewed physical education from a negative standpoint so that physical educators are forced to fight to preserve the existing curricular investment in physical education. Godin and Shephard (1990) stated that the likelihood of sustaining a regular exercise program during adult life depends, in part, on the individual's past experience of physical exercise and that the importance of conveying the benefits of regular exercise is paramount during a person's formative years.

Almond and McGeorge (1998) reported that within the past 30 years in the United States , required physical education participation from grade school through college has been reduced in an attempt to streamline curriculums and save money. Hensley (2000) surveyed 600 four-year colleges and universities in the United States to determine how many schools had a required basic instruction program (BIP) in physical education for all students. Results from 386 schools (64% return rate) showed that 63% had a BIP in physical education, with a two-hour requirement being the most common. Hensley noted that the BIP in physical education requirement for four-year colleges and universities was over 90% prior to 1960.

Daily physical education.

Shephard and Lavallee (1994) directed the Quebec Trois Rivieres study, a longitudinal experiment that involved 546 primary school students in grades one through six. The study compared experiment participants who received an additional hour per day of physical education taught by a physical education specialist (for a total of one hour and forty minutes) to control participants who received only the standard 40-minute physical education program, taught by a non-specialist. This curricular discrepancy allowed the control subjects 13% to 14% more academic instruction time than the experimental group. Each participant's cognitive performance in five areas (French, English, mathematics, natural science and conduct) was computed. Repeated measures analysis of variance results showed that experimental students outperformed the control participants by significant levels in grades two, three, five and six. The authors concluded that cognitive performance is maintained or enhanced by an increase in a student's level of physical activity even when accompanied by a reduction in curricular time for the study of academic material.

Dwyer, Blizzard, and Dean (1996) used fifth grade students as participants in a study designed to examine the relationship of exercise and cognitive performance. Three activity groups (control, skill, or fitness) participated in a 14-week intervention. The control group exercised for a half hour three times per week in physical education class; the skill group had similar content as the control group but exercised for 75 minutes daily; the fitness group followed the same routine as the skill group but exercised at higher intensities. Results showed that cognitive performance was similar in the three groups despite less classroom time in the two exercise groups. The authors suggested that these results indicate indirect support for the beneficial role of exercise on cognitive performance.

Sallis et al. (1999) conducted a two-year study of fourth and fifth grade students in a single public school district (12 schools) in Southern California to examine the relationship of exercise and cognitive achievement. Participating schools were randomly assigned to one of three conditions. In the specialist condition, certified physical education specialists implemented the Sports, Play, and Active Recreation for Kids (SPARK) program (Sallis et al., 1997). In the experimental condition, classroom teachers were trained by research staff to implement the SPARK program. In the control condition, classroom teachers implemented the usual physical education program. Results showed that achievement test scores for students involved in the SPARK program greatly exceeded the national average at baseline. The authors concluded that these results reinforced previous findings (Shephard, 1997) that spending more time on physical education does not interfere with cognitive performance.


5. Exercise and Performance in Specific Age Groups

Adolescents.

Daley and Buchanan (1999) examined changes in self-perception related to participation in extracurricular aerobics. Females aged 15 to 16 years from a single-sex secondary school in southeast England were recruited into either an aerobics plus physical education group (n = 43) or a physical education only group (n = 70). The physical education only group took part in compulsory class activity once per week for one hour and did not participate in any form of aerobics throughout the duration of the study. Participants in the aerobics group took part in compulsory class activity and additionally attended an aerobics class once per week after school for five weeks. All participants completed a physical self-perception questionnaire one week prior to commencing the aerobics intervention and again five weeks later. All participants also completed a physical activity participation questionnaire at the conclusion of the study. A series of 2 x 2 analyses of variance (ANOVA) with repeated measures for time were conducted. Results showed significant changes in adolescent girls' physical self-perceptions as a result of participation in five weeks of aerobics in addition to a one-hour physical education class.

Daley and Ryan (2000) examined the cognitive performance of adolescent boys and girls attending a mixed Catholic comprehensive school in southwest England . Three classes were randomly selected from each of grades 8, 9, 10 and 11. Each class consisted of 21 to 25 pupils for a total of 232 participants between the ages of 13 and 16 years. Previous examination results for common core topics (English, mathematics, and science) were used as measures of cognitive performance and each grade was rated as follows: A=5, B=4, C=3, D=2, E=1, F=0. Participants completed a modified version of a physical activity participation questionnaire and were asked to list all sports-based physical activities normally participated in during a typical week and to indicate the frequency and duration of each activity. Correlations between exercise participation and cognitive performance were not statistically significant. The authors suggested that external factors, such as age and family background, may influence the exercise/cognitive performance relationship.

College-aged adults .

Lybrand et al. (1954) used college students to measure the effects on perceptual organization after a five-mile march while carrying a 40-pound backpack. Cognitive scores for participants were higher than both non-exercisers and subjects in sleep-deprived conditions. Weingarten and Alexander (1970) studied the effects of exercise on cognitive performance of college males of different physical fitness level. Two cognitive tests of odd and even-numbered matrices were given to physically “fit” (n = 13) and “less fit” (n = 9) male participants. During test one, all participants performed a physiologically moderate work level on a treadmill (zero grade) with speed kept constant at 3.5 mph for 10 minutes, plus the time added to complete the cognitive matrices. During test two, given five days later, all participants performed a physiologically heavy work level with speed kept constant at 3.5 mph but with grade levels beginning at 5% for the first four minutes, 10% for the next four minutes, and 15% for minutes 8-10. The “less fit” group showed a significantly higher cardiovascular exertion level during test two. No differences were seen between test scores and time taken for test completion on test one for either group, though in test two the “fit” group scored higher and took a longer completion time than the “less fit” group. The authors speculated that the “less fit” participants completed test two in less time (as compared to test one) in an effort to escape physical pain from an increased workload and thus rushed their answers and consequently made more errors.

Gliner et al. (1979) gave college-aged adult men detection tasks for several hours after a marathon race. When compared to pre-test results, fewer false-positive responses suggested that participants' cognitive sensitivity increased as a result of endurance exercise. Counter to these findings are results from a study by Tomporowski et al. (1987) which compared 12 elite college-aged track athletes (mean VO 2 max = 66.09 ml / kg / min) to 12 average-fit participants (mean VO 2 max = 41.11 ml / kg /min). Participants were given a test of cardiovascular fitness approximately five weeks prior to attending a laboratory test session in which they performed free-recall test of memory. During the laboratory session, each participant ran on the treadmill at 80% VO 2 max until voluntary exhaustion or until a total treadmill run time of 50 minutes elapsed. The free-recall test of memory was administered immediately upon completion of the run. The authors hypothesized that highly trained runners would be able to withstand the physical stress of the exercise intervention more efficiently than average fitness group participants and would consequently perform better on the free-recall memory task. Although none of the high-fitness participants reported the exercise demands to be fatiguing, suggesting that the treadmill run produced different physiological effects on the two groups of participants, no significant differences on free-recall cognitive memory tasks were reported between groups.

Kubitz and Mott (1996) had 34 Kansas State University students participate in an experiment designed to determine the effect of aerobic exercise on brain function measured by electroencephalographic (EEG) monitoring during and after exercise. A group of 14 women and 20 men participated as exercisers (n = 18) or as controls (n = 16). Those in the exercise group exercised on a cycle ergometer for three 5-minute stages while wearing an electrode cap to monitor EEG readings. Those in the control group followed the same protocol (without the exercise) and watched a 15-minute fitness video. Results showed that aerobic exercise decreased the alpha level of EEG activity and increased the beta level in the exercise group participants. This reaction was an indicator of increased brain activity, although the level of activation returned to its normal state after exercise. The non-exercise group that watched videotapes showed EEG responses that indicated a deactivation of brain activity.

Herholz et al. (1987) suggested that a plausible explanation for the varied results in endurance-type exercise studies may be derived from theory that long-duration aerobic exercise causes an arousal of the central nervous system (CNS) that may have an effect on cognition. However, Tomporowski et al. (1987) argued that endurance-type exercise also causes physical fatigue of the musculoskeletal system and that these changes may increase or decrease cognitive performance depending on when the subject is tested and the physical fitness level of the participant.

Sullum et al. (2000) utilized college-aged participants to measure the processes of change for exercise, self-efficacy, and decision-making ability. Undergraduate male and female students (n = 52) participated in a semester-length aerobic conditioning class. Questionnaires were given in an eight-week follow-up to identify those who continued to exercise and those who had stopped (relapsers). Results showed that relapsers had lower self-efficacy scores and higher perceived negative views of exercise as compared to non-relapsers. The authors concluded that continuous exercise routines have more enduring value as compared to intermittent exercise routines and that consistent exercise may promote cognitive success in college students.

Plunk and Bowden (2001) determined the physical fitness level of college-aged males (n = 28) and females (n = 47) by using the Cooper 1.5-mile run and compared scores to grade point average. Each participant's estimated submaximal oxygen uptake was determined by his/her time on the 1.5-mile run. These values were used to place each participant into one of five categories of fitness (1 = poor; 2 = fair; 3 = average; 4 = good; 5 = excellent). An insignificant correlation coefficient (r = .28) was reported for all participants; males had a correlation coefficient of (r = .14) and females had a correlation coefficient of (r = .46). The authors suggested that the discrepancy in the correlation coefficients between males and females may be because the GPA of college-aged females were positively affected by physical fitness as compared to males. However, it is more likely that these differences were seen as a result of performing statistical analysis on a relatively small and uneven population size.

Older adults.

Bills (1927) measured the effect of high muscle tension (grip strength) on a cognitive task of addition and perception memory that was given during the performance of the hand dynamometer strength test. Results showed that participants performing mental tasks during conditions of increased muscular tension demonstrated more rapid acquisition and recall of nonsense syllables, faster learning of a paired-associate memorization task, greater accuracy on simple mathematical problems, and superior efficiency on a color-naming perception test than those participants who performed the same tasks under normal conditions. A different result was seen in a study by Krus et al. (1958). Participants performed 20-second upper body isometric contractions followed by a test of perceptual sensitivity. Results showed a decreased performance in pre-post sensitivity tests among participants. This study suggested that individuals' psychological functioning immediately after anaerobic exercise may be different from their ability to process information during anaerobic exercise. These anaerobic muscle-tension exercise studies were done to test the inverted-U theory of arousal, which states that as physical arousal increases, performance will increase up to a point and will then decrease as further arousal continues (Martens, 1974). Data from such studies indicate that moderate levels of muscular exertion may elicit the greatest performance increase as compared to extremely low or high levels of muscular tension.

Blomquist and Danner (1987) reported mixed results after investigating changes in information-processing efficiency that occur when exercise improves physical fitness. Adult volunteers (n = 66) between the ages of 18 – 48 years were recruited as study participants from adult fitness programs, educational classes, and the community. Predicted maximum oxygen uptake (VO 2 max) via bicycle ergometry was used as the measure of physical fitness. Participants were divided into two groups based on an increase in predicted VO 2 max from pretest to posttest; a 15% improvement was the criterion for participant inclusion into the Improved Group and improvement of less than 5% placed participants into the Stable Group. Twelve participants whose physiological change was 5% to 15% were eliminated from the study. Four information-processing measures (memory-scan task, same-different name retrieval task, timed pictoral subtest, word list memory) were given individually to each participant at the beginning and end of the 12-week study period. A significant interaction was found for the Posner name retrieval task (Posner & Mitchell, 1967) as the time required to access letter names from long-term memory decreased more from pretest to posttest in the Improved Group than in the Stable Group. The time required to scan immediate memory for numbers tended to become shorter for Improvement Group participants as compared to Stable Group participants, but the difference was nonsignificant. Timed pictoral subtests and word list memory tasks showed improvement for both groups without a significant difference between groups. The authors noted that although improvements in information-processing were not dramatic, these changes did occur in healthy adults who made modest gains in physical fitness.

Madden et al. (1989) conducted a study at Duke University that showed no improvement in cognitive performance on reaction time and attention tests. A group of 85 older adults (age 65+) were randomly assigned to either an aerobic exercise group, a non-aerobic exercise group (yoga), or a control group. Baseline fitness levels were measured as were baseline reaction-times. After 16 weeks of training, there was improvement in aerobic capacity in the exercise group, but there was no improvement on the reaction-time tests. The authors concluded that improvements in such cognitive tests are independent of improved aerobic capacity. By comparison, Van Boxtel et al. (1997) examined aerobic fitness and its interaction with age to predict cognitive performance on measures known to be affected by chronological age. Participants (males and females, 24-76 years of age) were subjected to submaximal bicycle ergometry tests and extensive neurocognitive examinations (tests of intellect, memory, simple and complex cognitive speed). Results showed that aerobic capacity accounted for up to five percent of the variance in the examination scores. The authors concluded that aerobic fitness may selectively and age-dependently act on attentional cognitive processes.

Park and Schwarz (2000) reported that if participants aged 20 to 75 are given a cognitive task to perform, reasons for the differing results can be partitioned into categories. Some of the variance will be attributed to the participants' education level, their experience with the cognitive task, and their age. Park and Schwarz identified four mechanisms that have been hypothesized to account for age differences in cognitive functioning. These mechanisms are 1) the speed at which information is processed, 2) working memory function, 3) inhibitory function (i.e., inhibiting attention to irrelevant material), and 4) sensory function (i.e., visual/auditory acuity).


6. Where Do We Go Now?

The literature is somewhat inconclusive as to how exercise may affect cognitive performance and the college-aged student. There have been numerous studies conducted but noticeable variations exist among them. Studies have varied by design issues, subject selection, performance measures, and the timing of tests. Such variance makes it difficult to associate one particular independent variable with a specific cognitive result. Several non-exercise variables are also present that affect the cognitive performance of the college-aged student. The question of how exercise could improve the classroom cognitive performance of college students in health/fitness physical education classes has not been fully answered. According to the literature, a gap exists in the research that is specific to exercise and cognitive performance, especially of college-aged individuals. Further research that is specific to the area of cognitive performance, exercise, and the college-aged student is needed.


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