Throughout the centuries, dietary intake has been a source of concern to athletes in search of an ergogenic edge over opponents.

It wasn’t until 1866 that it was demonstrated that there was insignificant, if any use of protein as a fuel during exercise. Since that time, innumerable studies have refuted the notion that a high protein intake will enhance athletic performance.

Since the conclusion of the Kraus-Weber Tests in the 1950s, there has been ever- increasing awareness and concern for cardiopulmonary fitness and health in Americans. Endurance type activities such as Nordic skiing, cycling, running, triathalons, and swimming have become in vogue, and as a result, more intense attention has been devoted to dietary manipulations which may provide an ergogenic effect, thus prolonging time to exhaustion, or delaying the onset of blood lactate accumulation (OBLA) in an attempt to compete at a higher intensity, longer.

The classic study by Christensen and Hansen in 1939 established the effect of a high carbohydrate diet upon endurance time, and that pre-exercise glycogen levels exerted an influence in time to exhaustion. Subsequently, it was discovered that if an athlete, after depleting glycogen reserves, consumed a high carbohydrate diet for two to three days prior to an athletic event, there would in fact be higher glycogen levels than prior to exercise. This “supercompensation” effect became the basis for carbohydrate loading undertaken by endurance athletes.

Therefore, the concentration of muscle and liver glycogen prior to exercise plays an important role in endurance exercise capacity. In exhaustive exercise many studies have observed significant depletion of both liver and muscle glycogen. It is interesting to recognize that the point of exhaustion seems to occur upon the depletion of liver glycogen. Conversely, muscle glycogen reserves, though significantly lower are only 65-85% depleted, versus the 85-95% depletion exhibited for liver glycogen. This should make it readily apparent that liver glycogen is an integral determining factor in an athlete’s time to exhaustion. It follows that endurance athletes who maintain a daily regimen of endurance training without glycogen repletion may severely deplete their glycogen reserves.

Glycogen, the major reservoir of carbohydrate in the body, is comprised of long chain polymers of glucose molecules. The body stores approximately 450-550 grams of glycogen within the muscle and liver for use during exercise. At higher exercise intensities, glycogen becomes the main fuel utilized. Depletion of liver glycogen has the consequence of diminishing liver glucose output, and blood glucose concentrations accordingly. Because glucose is the fundamental energy source for the nervous system, a substantial decline in blood glucose results in volitional exhaustion, due to glucose deficiency to the brain. It appears that the evidence presented in the literature universally supports the concept that the greater the depletion of skeletal muscle glycogen, then the stronger the stimulus to replenish stores upon the cessation of exercise, provided adequate carbohydrate is supplied.

Though most of the evidence presented on glycogen is related to prolonged aerobic exercise, there is evidence that exercise mode may play a role in glycogen replenishment, with eccentric exercise exhibiting significantly longer recovery periods, up to four days post-exercise. Muscle fiber type is another factor implicated in the replenishment of glycogen in athletes, due to the enzymatic capacity of the muscle fiber, with red fiber appearing to be subjected to a greater depletion, but also undergoing repletion at a significantly grater rate.

Though early literature appeared to indicate that the time course of glycogen replenishment after exercise-induced depletion was 48 hours or more, more recent data have controverted this thought. One study reported that a carbohydrate intake totaling up to 550-625 grams per day was found to restore muscle glycogen stores to pre-exercise levels within the 22 hours between exercise sessions. The findings of this study were supported by second study in which a carbohydrate intake of 3100 kcal resulted in complete resynthesis of glycogen within 24 hours.

There also appears to be a two-hour optimal window immediately after the cessation of exercise for the administration of carbohydrates. Simple carbohydrates appear to be the preferred replacement during this replenishment period.

Normally, 2% of glycogen is resynthesized per hour after the initial 2 hours immediately after exercise. With administration of 50 grams of carbohydrate every 2 hours, the rate rose to 5% per hour, but did not rise when additional carbohydrate was administered. Administration of .7grams per kg body weight every two hours is another strategy that appears to maximize the rate of glycogen resynthesis. There is also some evidence that even smaller loads (28 grams every 15 minutes) may induce even greater repletion rates.

Therefore, at least 20 hours are required to recover muscle glycogen stores, even when the diet is optimal. So, athletes working out two times per day should complete one workout at a diminished workload to relieve the reliance on glycogen reserves.

The principle of glycogen resynthesis and supercompensation has great practical implications, not only in athletics, but also within industry for workers who consistently undergo depletion of glycogen stores due to prolonged bouts of exertion, or extended lifting tasks which would be glycolytic in nature; due to the duration, and also the myofibrillar ischemia induced by static contractions.

ABSTRACT

Changes in cognitive strategies can improve performances and lessen perceived fatigue during distance activities (Padget & Hill, 1989). However, such changes may be difficult and annoying for participants (Masters & Lambert, 1989). This study identified subjects’ preferred cognitive strategies and examined the effects of a complementary cognitive strategy. Twenty-five subjects performed an 800 meter free-style swim while being timed and assessed for heart rate. One week later, subjects read a Behavioral Instruction Sheet (BIS), appropriate for their style in the first swim and followed it during the second swim. Results showed that associative thinking was used more frequently than dissociative thinking by 73%, t(21) = 6.68, p<.05. No significant differences were found from the first to the second swim in performance times, RPE and heart rates with the exception of more muscular fatigue in the second swim t (16) = -2.17, p<.05. This study suggests that cognitive strategy training can not be completely associative or dissociative.

INTRODUCTION

Various forms of cognitive self-control strategies have long been used for optimizing endurance performance. In some instances, individuals use distracting forms of thinking to endure longer sustained performance perceive less fatigue and perform faster than those strategies focusing on the task (Gill & Strom, 1985; Padget & Hill, 1989;). Yet these results are not without controversial findings (Masters & Lambert, 1989; Schomer, 1987). World-class marathoners tend to apply focusing techniques almost invariably during marathon races to maintain an accurate awareness of their bodily function, tension, pain and discomfort (Morgan, 1978). However, when training, runners tend to prefer a dissociative strategy (Pennebaker & Lightner, 1980).

A developing body of research supports the notion that some distance runners can mentally separate themselves from the inherent pain and fatigue resulting from marathon running. Morgan and Pollock (1977) suggest that two cognitive strategies are frequently used by runners; “association” and “dissociation”. They theorize that dissociation is more pleasurable as it enables individuals to reduce “anxiety, effort sense and general discomfort” (Morgan, 1978, p. 46). It is also thought that dissociation strategies allow marathon runners to persevere through temporary zones of boredom (Schomer, 1986). However, Morgan and Pollock (1977) found that world-class marathoners tend to apply associative techniques almost invariably during marathon races to maintain an accurate awareness of their bodily function, tension, pain and discomfort (Morgan, 1978). Morgan and Pollock (1977) describe runners’ associative strategies as: scanning their body to identify painful or tense areas and thus remember to lessen muscle tension while implementing feelings of relaxation; and thinking of their pace and race strategy (Morgan, 1978).

Rushall and Shewchuk (1989) examined the effects of thought content instructions on swimming performance. Using three types of thought instructions on training performances, swimmers completed two 400-meter effort swims and one set of 8 x 100- meter swims. Such types of strategies like positive thinking and mood word conditions made all swimmers improve their workout performance in at least two of the three conditions during the 100-meter repeat task. Such findings in thought manipulations are encouraging yet Weinberg, Smith, Jackson and Gould (1984) suggest that some athletes find it difficult to change their cognitive strategies (from dissociative thoughts to associative thinking or vice versa). In fact, some subjects find it bothersome and annoying to change their existing cognitive strategies (Masters & Lambert, 1989; Weinberg, Smith, Jackson & Gould, 1984).

While some studies have examined the effects of both cognitive strategies, few if any studies have ever considered identifying the subjects’ preferred choice of cognitive strategy and complementing their current predominant strategy. The purpose of this study was two-fold: to identify subjects’ preferred cognitive strategies during distance swimming and to examine the effects of using a cognitive strategy that is complimentary to the one being used by swimmers.

METHODOLOGY
Subjects

A total of 22 subjects (11 males and 11 females) from a University Masters Swim Club volunteered to swim two 800 meter free-style swims, one week apart. Subjects varied in age from 19 to 45 years old (m=27) and normally swam between 500 m and 12,500 m per week (m= 4,490 metres).

Measurements

Pre-Swim Questionnaire
The pre-swim questionnaire consisted of gathering general and demographic information (i.e., why do they swim distances? preferred cognitive thought patterns when swimming, etc.).

Timed Performance
Swimmers’ performances were timed during both swims with stopwatches, accurate to 1/100th of a second. Timers were briefed on the proper procedures and were familiarized with the stopwatches prior to the study. Subjects were told that this was not a race and that they should swim their normal speed.

Heart Rate
Before swimming, the subjects were fitted with a Vantage XL Sport Tester transmitter and receiver that recorded time and heart rate every 15 seconds from the moment they started the swim to the end. This modality has been used extensively to train and measure athletes (Daniels & Landers, 1981). The data was then down-loaded via an interface unit to a computer for processing.

Subjective Appraisal of Cognitive Thoughts
(SACT; Schomer, 1986) The SACT consists of 10 categories, in which each descriptor relates to a specific cognitive attentional style (associative or dissociative). Subjects were asked to circle all those descriptors that came to mind while swimming. Depending on the number of associative or dissociative descriptors the subject was identified as preferring a particular style of cognitive thinking. Schomer (1986) established the reliability and validity of the statements by examining 109 recordings taken from marathoners, four times per month. After transcribing runners’ personal conversations, Schomer inspected the scripts for “recurrent thoughts on task-related and task-unrelated material”. Categories were proposed and rationalized based on a “pronounced attentional focus”. The reliability and validity of 10 sub-classifications emerged (Schomer, 1986).

A pilot study with 20 swimmers was conducted by the present investigators to examine the construct validity of the categories as outlined by Schomer. For the swimmers, it indicated that comprehension of the sub-classification titles was poor. Consequently, the titles were re-worded in a general context while using the same content and examples employed by Schomer (1986) in his description of the subcategories.

Perceived Fatigue Questionnaire
(PFQ; Pennebaker and Lightner, 1980) The PFQ measures changes in perceived fatigue. It contains 10 physiological symptoms related to fatigue (dizziness, sore eyes, headache, etc.) which are measured on a scale from 1 to 100. For each symptom, subjects mark with a slash how they feel (e.g., 0 = not at all dizzy to 100 = the worst feeling of dizziness ever). All scores are summed to provide a total symptom index of fatigue. The scalar properties of these symptoms are found in Pennebaker & Skelton (1978).

Rate of Perceived Exertion
(RPE; Borg, 1982) The RPE scale is a 15-point instrument ranging from 6 to 20. The instrument has several identifiers at every uneven number (e.g., 7 “very very light” and 19 “very very heavy”). It has been found to correlate linearly with heart rate. Because of its positive relationship with heart rate, the RPE scale was an appropriate measurement for this study. In the present study, the RPE was printed on a large cardboard and shown to the swimmers after each swim.

Post-Swim Questionnaire
Following the second swim, swimmers in the associative and dissociative groups were asked to evaluate the effectiveness of the strategies. This questionnaire identified the extent to which the assigned strategy was used during the swim.

Procedure

After signing a consent form and being informed of the results’ confidentiality, the subjects prepared for the swim. Prior to entering into the pool, subjects answered a short Pre-Swim Questionnaire. Subjects were cautioned that this was not a race. All swimmers wore a waterproof wrist-mounted heart rate receiver and a transmitter around the chest. A total of eight swimmers (one swimmer per lane) swam at any one time. Staggered starts (one minute apart) were used to lessen the “motivation” variable of competition against peers. This enabled the swimmers to use dissociative strategies if they so wished in the first swim. All swimmers stopped at the end of 800 meters when they saw a red flutter board being waved underwater as they approached the end of the pool. This procedure was chosen to minimize potential disruptions with swimmers who were not finished their swim. Swimmers’ times were taken by trained individuals who were supervised by the researchers.

RESULTS

Subjects in this study generally commented that they swam for fitness (65.6%) and relaxation (19.4%). The pre-swim questionnaire revealed the swimmer’s preference for a certain type of strategy; either associative (78.1%), dissociative (9.6%) or a mixture of both (12.3%). Following the swim, results showed that swimmers preferred association thinking by 73%, a significant difference t(21)=6.68, p<.05 from dissociative thinking. Associative thinking was found to occur significantly more in the middle of the swim than near the end F(2,24)=3.87; p<.035.

Table 1: Impressions of the Behavioral Instruction Sheet According to Their Cognitive Strategy

Note. Scores are based on a 100 point scale.

Though a number of descriptors were offered in the Perceived Fatigue Questionnaire, subjects generally commented of more muscular fatigue in the second swim t (16) = -2.17, p<.05. No statistical changes were found in subjects’ swimming time, RPE and heart rates from the first to the second swim.

Subjects rated the BIS to be easy to use (m=71), helpful (m=69) and effective (m=63), on a 100 point scale. Boredom (m=60) and pain (m=51) were also reduced.

Subjective Appraisal of their Cognitive Strategy during the Second Swim

Generally, 57% of subjects found the second swim easier (86% associative and 14% dissociative). The associative thinkers generally commented that their second swim was faster “There must be a mistake in timing. I found it much easier this time even though I took longer”. Swims also felt more comfortable “Generally I felt better all around.” Comments from the disassociators implied that the second swim was more enjoyable. The BIS “gave me other things to think about. I was not as mentally drained prior to the swim as I was in the first swim”. Subjects favoring the first swim (100% associative) attributed it to physical and mental factors. For instance, one subject suffered from a headache during the second swim and another blamed it on exhaustion because of work-out before the second swim. Also, one swimmer commented on “feeling more relaxed” and being less stressed during the first swim.

DISCUSSION

These results suggest that distance swimmers prefer associative thinking when swimming. Similar results were found in other studies with marathon runners during races (Masters and Lambert, 1989; Morgan and Pollock, 1977). Elite distance runners were found to be mostly associative thinkers throughout important races. Their results encouraged researchers to consider the notion of “the better the associative thinking the better the performance” (Schomer, 1987). Yet in this study, swimmers did not significantly improve their swimming times even after having read the BIS for an associative strategy. The strong preference for swimmers’ associative thinking was reflected mostly in the middle of the swim rather than throughout the entire swim. In comparison to distance runners during important races, the participants did not perceive the swim to be a race. Interestingly, a difference was found in muscular fatigue after the second swim despite the similar timed performances, RPE and heart rates between both swims. Three recommendations are suggested. Different results were found by Rushall and Shewchuk (1989). They found that thought content instructions improved swimming workout performance in at least two of the three thought conditions. In future studies, the extent to conformity of the BIS should be examined. Secondly, an 800 meter swim may not have been far enough for distance swimmers to use dissociative strategies especially since the groups’ average swimming per week was 4,490 m. Finally, the 800 m swims may have been too familiar for the participants, knowing their pace and the approximate time required. Perhaps, time could be a better independent variable than distance.

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Correspondence concerning this article should be addressed to Dr. Roger T. Couture, School of Human Kinetics, Laurentian University, Sudbury, Ontario, Canada, P3E 2C6; Tel.# (705) 675-1151, ext. 1023.E-Mail: Rcouture@NICKEL.LAURENTIAN.CA

This study was supported by a grant from the Laurentian University Research Fund, Sudbury, Ontario, Canada.