Mood and Cycling Performance in Response to Three Weeks of High-Intensity, Short-Duration Overtraining, and a Two-Week Taper

Transcription

1 444 Berger, Motl, Owen, et al. The Sport Psychologist, 1999, 13, Human Kinetics Publishers, Inc. Mood and Cycling Performance in Response to Three Weeks of High-Intensity, Short-Duration Overtraining, and a Two-Week Taper Bonnie G. Berger, Robert W. Motl, Brian D. Butki, David T. Martin, and John G. Wilkinson University of Wyoming David R. Owen Brooklyn College, City University of New York This study examined changes in mood and performance in response to highintensity, short-duration overtraining and a subsequent taper. Pursuit cyclists (N = 8) at the United States Olympic Training Center completed the POMS and simulated 4-km pursuit performance tests throughout a six-week period. The six-week period included a baseline week, three weeks of overtraining that consisted primarily of high-intensity interval training, and a two-week taper. Total Mood Disturbance (TMD) scores displayed a quadratic polynomial effect across the three weeks of overtraining (p <.01), with the highest TMD scores occurring in the second week. Average TMD scores were lower during the taper than at baseline (p <.02) and lower at taper than overtraining (p <.0005). Cycling performance (pursuit time and average power output) improved during the three weeks of overtraining; additional improvements were observed during the taper. There were no significant correlations between TMD and performance. However, pursuit time, average power output, and mood disturbance scores were at optimal levels throughout the taper period. These findings suggest that high-intensity, short-duration overtraining may not result in an overtraining syndrome in 4-km pursuit cyclists. Bonnie G. Berger is now with the School of Human Movement, Sport, and Leisure Studies, Bowling Green State University, Bowling Green, OH Robert W. Motl is now at the Department of Exercise Science, University of Georgia. David R. Owen is with the Department of Psychology, Brooklyn College, CUNY. Brian D. Butki is now at the Department of Kinesiology and Health Education, Southern Illinois University, Edwardsville, IL. David T. Martin is now at the Department of Physiology and Applied Nutrition, Australian Institute of Sport. John G. Wilkinson is with the School of Physical and Health Education, University of Wyoming. 444

2 Mood and Overtraining 445 Athletes often undertake systematic periods of intensified, sport-specific training to achieve necessary adaptations for maximal performance. This process is known as overtraining and can result in enhanced performance (O Connor, 1997). It also may be accompanied by undesirable changes such as short-term exhaustion, fatigue, and negative effect, which are characteristic of overreaching (e.g., Hooper & Mackinnon, 1995). Without adequate rest and recovery, the continued stress of overtraining may lead to physical exhaustion, psychological fatigue, and severe performance decrements that are symptomatic of overtraining syndrome (e.g., O Connor, 1997; Urhausen, Gabriel, & Kindermann, 1995). Overtraining syndrome is a state wherein an athlete s ability to train and perform at customary levels is compromised, even after a period of rest (e.g., Fry, Morton, & Keast, 1991; O Connor, 1997). Researchers have examined a variety of physiological and psychological accompaniments to overtraining to identify possible markers of overtraining syndrome. Identifying early warning signs could help coaches and athletes maximize the performance benefits of overtraining while minimizing potential negative consequences. However, there has been relatively little success in determining which markers are most predictive of the overtraining syndrome. Physiological factors such as morning heart rate (e.g., Dressendorfer, Wade, & Schaf, 1985), muscle glycogen (e.g., Costill et al., 1988), cortisol (e.g., Barron, Noakes, Levy, Smith, & Millar, 1985; O Connor, Morgan, Raglin, Barksdale, & Kalin, 1989), and neuromuscular functioning (e.g., Raglin, Koceja, Stager, & Harms, 1996) have been monitored during periods of overtraining. Nevertheless, these markers exhibit considerable individual variability in response to overtraining (O Connor, 1997; Raglin, 1993). The practicality of employing some of these physiological measures in a field setting also is limited due to the required technology. In addition, repeated use of the sometimes invasive measures to monitor overtraining may be unethical (Raglin, 1993). To identify practical markers, researchers have examined psychological factors related to overtraining that require less technology. Mood, as measured by the Profile of Mood States (POMS) (McNair, Lorr, & Droppleman, 1971, 1981, 1992), has been a common psychological marker for monitoring athletes during periods of overtraining (e.g. Dishman, 1992; Hooper & Mackinnon, 1995; O Connor, 1997; Raglin, 1993). During periods of overtraining, athletes generally have reported undesirable changes on Total Mood Disturbance and a flattened or even inverted iceberg profile on the POMS subscales. When the training load is reduced during taper periods, athletes have reported improvements in mood as reflected by a return of POMS scores to baseline values. Results such as these suggest that assessing effective states throughout a training season may be helpful for adjusting workout parameters to avoid overtraining. Changes in mood also have been observed in controlled overtraining regimens. Testing the relationship between mood and swimming duration, Morgan, Costill, Flynn, Raglin, and O Connor (1988) investigated psychological and physiological variables in response to a sudden increase in distance from 4,000 day 1 at baseline to 9,000 day 1 which was performed for 10 consecutive days. Training intensity remained at approximately 94% V O 2max. Results indicated that mood disturbance scores were significantly elevated even though the nearly twofold increase in training distance did not adversely affect swimming performance. This suggests that a sudden increase in training duration is associated with undesirable mood changes. Mood decrements may serve as an indicator of future

3 446 Berger, Motl, Owen, et al. compromised training status and performance, decrements, or both. In a related study, O Connor, Morgan, and Raglin (1991) examined mood and performance responses to a three-day protocol that again focused on increased swimming duration. Results indicated that an abrupt increase in swimming duration was associated with mood decrements and decreased biomechanical performance, which included increased stroke frequency and decreased stroke length. These controlled studies suggest that mood and performance responses may be related to the specific parameters of overtraining. Ideally, overtraining will promote optimal performance adaptations rather than severe performance and mood decrements. The specific changes in performance and mood may depend on the parameters of overtraining (Lehmann et al., 1997; Raglin, 1993). For example, Lehmann et al. (1992) examined changes in performance and hormone responses during periods of high-intensity, long-duration overtraining and high-intensity, short-duration overtraining in middle- and longdistance runners. The high-intensity, long-duration protocol resulted in the overtraining syndrome as indicated by a plateau in submaximal performance, decreased maximal performance, and increased exercise-related plasma catecholamine levels. In contrast, the high-intensity, short-duration protocol did not result in overtraining syndrome as illustrated by improved submaximal and maximal performance and decreased exercise-related plasma catcholamine levels. Because high-intensity, short-duration overtraining promoted performance benefits and hormonal adaptations, it may not result in negative mood changes. High-intensity, short-duration overtraining seems to be less physically draining, monotonous, and psychologically taxing than a high-intensity, long-duration overtraining (Lehmann et al., 1997). To maximize performance adaptations and to minimize concomitant mood decrements, overtraining protocols may need to be designed for a specific activity. Specificity of training allows for intensity and duration to be matched to the cardiorespiratory and metabolic demands of a sporting event (e.g., Wilmore & Costill, 1994). For example, parameters of overtraining may need to be congruent with whether the sporting activity requires primarily aerobic or anaerobic efforts such as in swimming, running, or cycling (Boulay, 1995). Pursuit cyclists who race only 4-km may need to follow an overtraining program that focuses on high intensity, but shorter duration interval workouts at or above the anaerobic threshold as well as weekly pursuit tasks (Boulay, 1995). In contrast, endurance cyclists may need to employ an overtraining protocol that focuses on long duration combined with lower intensity to gain necessary performance adaptations (Boulay, 1995). The present study extended past research on overtraining, mood, and performance by focusing on high-intensity, short-duration overtraining designed to meet the specific challenges of 4-km pursuit cycling performance. We objectively monitored training success by recording performance changes in cycling pursuit time and average power output throughout baseline, overtraining, and taper periods. By measuring mood throughout the overtraining and subsequent taper periods, we were able to examine effective responses to a sport specific and realistic training regimen that was high in intensity and short in duration. Cyclists were hypothesized to report relatively positive moods prior to the overtraining regimen because athletes generally have high levels of mental health (Morgan, 1980). We also anticipated that cyclists would not report drastic mood disturbances during the period of high-intensity, short-duration overtraining, and that the cyclists mood

4 Mood and Overtraining 447 states would be similar to baseline values in the recovery period. In addition, cyclists were hypothesized to exhibit performance benefits in the taper period that followed overtraining. Method Participants Male pursuit cyclists (N = 10) between 17 and 25 years of age (M = 20.8; SD = 2.7) at the United States Olympic Training Center (USOTC) participated in this project. Eight cyclists completed the entire project. Two participants dropped out of the USOTC program because of scholastic or family problems. As might be expected, the cyclists were highly skilled. Three cyclists were United States Cycling Federation (USCF) licensed Category I racers, the highest rank among amateur cyclists in road or track racing. The other five cyclists held USCF Category II ratings. The cyclists averaged between three and seven years of competitive cycling experience (M = 4.5; SD = 1.4) and had earned eight national championships in various events. Even though this study was conducted in the off-season, the cyclists were fit as evidenced by a mean V O 2peak of 63.0 kg min 1 (SD = 5.7) and average body fat of 7.6% (SD = 2.3). All participants signed informed consent forms and were treated in accordance with ethical guidelines of the American Psychological Association (1992). Measures Psychological measures. Cyclists completed several paper-and-pencil questionnaires: Lie Scale of the Eysenck Personality Inventory (Eysenck & Eysenck, 1975), POMS (McNair et al., 1971, 1981, 1992), and a brief demographic survey including questions about cycling history, skill level, and expectancy. The Lie Scale has been a valid and reliable measure of social desirability (Eysenck & Eysenck, 1975), and was employed in this study to determine whether subjects faked good when responding to psychological questionnaires. It contained 9 items that were answered Yes or No. Lie-scale scores above five may indicate faking good, and no cyclist scored above this criterion. The POMS consistently has been employed to measure the mood states associated with overtraining (e.g., Dishman, 1992; Hooper & Mackinnon, 1995; O Connor, 1997; Raglin, 1993). The inventory contains 65 items which are rated on a 5-point Likert scale and includes six subscales: Tension-anxiety, Depressiondejection, Anger-hostility, Vigor-activity, Fatigue-inertia, and Confusionbewilderment. Test-retest reliability coefficients for the subscales have ranged between 0.65 (Vigor) and 0.74 (Depression). Estimates of internal consistency have ranged between 0.84 and 0.95 (McNair et al., 1971, 1981, 1992). The six subscales on the POMS can be combined into a Total Mood Disturbance (TMD) score by summing the T scores for the five negative mood subscales (Tension, Depression, Anger, Fatigue, and Confusion), and subtracting the T score for Vigor (McNair et al., 1971, 1981, 1992). Employing T scores in this calculation weighted each POMS subscale score equally. The TMD scores computed from POMS subscale T scores were employed in all statistical analyses. For comparability to previous research in the area of overtraining and mood, we also calculated TMD using raw scores and adding a constant of 100 (cited in

5 448 Berger, Motl, Owen, et al. Morgan et al., 1987). Although only the use of standardized T scores really weights each mood scale equally in the TMD composite, these two methods of computing TMD produced nearly identical ANOVA results in our study. The correlation between the results of the two analyses (each with nine p-values from the day s effect plus the eight contrasts partitioned from it) was , indicating that the results are essentially indistinguishable. This is not surprising, of course, as the 13 correlations between the pairs of TMD scores themselves across the eight cyclists ranged from to Physiological measures. Body fat was estimated using a sum of seven skin folds and the equations provided by Jackson and Pollock (1985). Peak oxygen consumption (V O 2peak ) was measured employing an automated open-circuit expired air analysis system (SensorMedics 2,900, SensorMedics Corp., Yorba Linda, CA) during a discontinuous graded exercise test (GXT) performed to volitional fatigue. The GXT consisted of 4-min stages, which were partitioned into 3 min of work and 1 min of active recovery. The initial workload was 110 watts. Subsequent stages increased by 40-watt increments until the cyclist reached volitional fatigue; active recovery was performed at 100 watts. Expired gases were analyzed every 20 seconds and the highest average of three successive readings was recorded as a cyclist s V O 2peak. The cyclist s heart rate measured upon termination of the GXT via a Polar Vantage-XL monitor was recorded as peak heart rate (HR peak ). Performance measures. Cyclists completed a simulated 4-km pursuit to assess changes in pursuit time and average power output. The protocol involved a modified test developed for elite Australian pursuit cyclists (Pyke, Craig, & Norton, 1988). Pyke and colleagues found that the Australian cyclists accumulated 120 kj of work during a 4-km pursuit that lasted 4.75 minutes. The cyclists also produced an average power output of between 420 to 430 watts during the pursuit. To more closely approximate the laboratory pursuit to an actual 4-km pursuit effort for the cyclists in this study, the resistance setting for the simulated test was modified from the criterion work of 120 to 110 kj. Thus, each kilometer of the pursuit was equal to 27.5 kj of work. The pursuit test was conducted on an electronically braked bicycle ergometer that was connected to a computer to record total work. To simulate a pursuit bicycle, the ergometer was modified with aerobars, clipless pedals, and a racing saddle. Similar to an actual pursuit, cyclists started the test from a standing position. Cyclists were informed that they had completed one kilometer of the test for every 27.5 kj of work. For the final 27.5 kj of work, the cyclists were informed when they reached the equivalent of both 500 meters and 200 meters left in the test. Pursuit time was measured by two investigators, and the average value was recorded. Average power output during the pursuit was calculated from the finish time and total work accumulated. Procedure Pursuit cyclists completing a six-week training camp at the USOTC in Colorado Springs participated in this study. To encourage cyclists to volunteer, we provided them with a carefully planned protocol designed to improve their pursuit performance. The United States national team coaches also recommended that cyclists participate in the project to increase their performance levels. Cyclists resided at the USOTC for the duration of the study, and this helped to ensure that they followed the exact training protocol. All training sessions were performed indoors with each

6 Mood and Overtraining 449 participant s bicycle mounted on a stationary, electromagnetic trainer (RacerMate CompuTrainer, Model CAT 8000, RacerMate, Seattle WA) to monitor power output. We also employed Polar Vantage-XL monitors to record heart rate and downloaded this data into a computer to assess training intensity. Training protocol. The training protocol consisted of a six-week regimen that was designed in consultation with the national coaches, specifically to improve 4-km pursuit cycling performance. The six-week protocol as outlined in Figure 1 was partitioned into three time periods: a week of baseline training, three weeks of overtraining, and a two-week taper. The baseline week began with a twohour continuous ride at less than 70% HR peak to familiarize participants with the CompuTrainers. Subsequently, cyclists completed two days of recovery training which consisted of 1 set, min intervals (1:1.5 work:relief ratio) in the morning and a 60-min continuous ride at less than 70% HR peak in the afternoon. Additional baseline activities included two 4-km pursuit tests and a maximal GXT. The three weeks of overtraining consisted primarily of high-intensity interval training performed at greater than 85% HR peak as illustrated in Figure 1. Throughout each of the three weeks, cyclists completed seven or eight interval sessions in three or four consecutive days. The initial day of interval training always consisted of 1 set, min (1:1) and 1 set, min (1:1) in the morning that was followed by 2 sets, min (1:1.5) in the evening. The subsequent days of interval training involved 1 set, min (1:1) and 2 sets, min (1:1) in the morning and 2 sets, min (1:1.5) in the evening. Other weekly activities, which followed the consecutive days of interval training, included a recovery training day, a pursuit performance test, and a maximal GXT. Figure 1 Training protocol and mean total mood disturbance score.

7 450 Berger, Motl, Owen, et al. The two-week taper period involved high-intensity but short-duration training as suggested by Shepley et al. (1992). Training intensity remained at 100% of the value employed in the overtraining phase of the study, but total training time and training frequency were reduced during the two weeks of taper as illustrated in Figure 1. The initial taper week included three recovery training days, three pursuit performance tests, and a maximal GXT. The second week included a recovery training day, two pursuit performance tests, and a maximal GXT. POMS testing schedule. Cyclists completed the POMS in the morning before training on 13 occasions throughout the study. Three POMS were completed prior to exercise during the baseline week. As noted in Table 1, the first two administrations employed the how have you been feeling during the past week including today instructions to establish baseline trait values; the third administration of the POMS included the right now response set. We administered the POMS on six occasions using the right now response set throughout the three weeks of overtraining. During each of the overtraining weeks, cyclists completed the POMS in the morning before both the last day of interval training and the 4-km pursuit test. Thus, cyclists completed the POMS following two or three days of interval training and after one day of recovery training. During the two-week taper period, cyclists completed the POMS four times, every third day. The first three utilized the right now response set; the final POMS was based on the past week instructional set. Results Exercise Intensity Heart rate was recorded every five seconds via Polar Vantage-XL monitors to determine average intensity of the interval training sessions. Training intensity was quantified as a percentage of HR peak. Cyclists performed the intervals at a high intensity, which was at or above anaerobic threshold. Results indicated that cyclists performed the 5-min intervals at an average intensity of 94.7% HR peak. The 3-min intervals were performed at 94.2% HR peak, and the 2-min interval training sessions at an average intensity of 93.8% HR peak. Mood Scores Average TMD scores were computed by adding T scores for the five negative POMS subscales and subtracting Vigor T scores for the training periods: baseline (assessments 1, 2, and 3), high-intensity days of the overtraining period (assessments 4, 6, and 8), recovery days of the overtraining period (assessments 5, 7, and 9), and taper (assessments 10, 11, 12, and 13). Mood seemed to be responsive to consecutive days of high-intensity interval training, rest periods that followed the repeated days of interval training, and taper days (see Table 1). The average TMD score for the three POMS administered during the baseline week was (SD = 34.27). During the high-intensity days of the overtraining period, TMD scores increased to an average of (SD = 49.63). Following the recovery days of the overtraining period, scores declined to a mean of (SD = 31.82). Finally, TMD scores for the taper period averaged (SD = 17.11). A search using Mahalanobis distance did not indicate any outliers in the data set (Frane, 1983).

8 Mood and Overtraining 451 Table 1 Total Mood Disturbance (TMD) Scores During the Baseline, Overtraining, and Taper Periods Day Period M SD Baseline Period Week 1 1 a Baseline a Baseline b Baseline Average Overtraining Period Week 2 4 b High-intensity b Recovery Week 3 6 b High-intensity b Recovery Week 4 8 b High-intensity b Recovery High-intensity average Recovery average Taper Period Week 5 10 b Taper b Taper Week 6 12 b Taper a Taper Taper average a Instructional set: How have you been feeling during the last week including today? b Instructional set: How do you feel right now? Note. TMD mean scores were computed by summing T scores for Tension, Depression, Anger, Fatigue, and Confusion, and then subtracting the T score for Vigor. Possible changes in TMD scores across the 13 days were examined through a repeated measures ANOVA. The day s hypothesis also was subdivided into a series of pre-planned, one-degree-of-freedom contrasts based on the four training periods. To protect against violations in compound symmetry, we used the Hunyh- Feldt adjustment when evaluating the reported significance levels. The repeated measures ANOVA suggested a trend for differences in mood disturbance across the 13 days, F (12, 84 reduced to 3, 24) = 2.27; p = The one-degree-of-freedom contrasts compared TMD changes between pairs of the four training periods: baseline, high-intensity days of overtraining, recovery

9 452 Berger, Motl, Owen, et al. days of overtraining, and taper. The major findings were that the mood disturbance scores during the taper were significantly lower than TMD scores during each of the other periods: the high-intensity training days of the overtraining period versus taper, F(1, 84 reduced to 1, 24) = 15.98, p <.0005; the recovery days of the overtraining period versus taper, F(1, 84 reduced to 1, 24) = 5.66; p <.03; and the baseline period versus taper, F(1, 84 reduced to 1, 24) = 6.45; p <.02. Although TMD scores associated with the high-intensity training days of the overtraining period appeared to be higher than those during the baseline period and recovery days of the overtraining period, the differences were not significant (p >.18, and.14, respectively). There also was no evidence that TMD scores during the baseline period and recovery days of the overtraining period differed from one another (p >.88). Polynomial trend analysis on the total mood disturbance scores over the three high-intensity days of overtraining revealed a nonsignificant linear trend (p >.88) and a significant quadratic effect, F(1,84 reduced to 1, 24) = 7.82; p <.01. The first high-intensity TMD scores were no higher than baseline. During the second week of overtraining, TMD increased significantly from baseline scores. In the final week of overtraining, TMD scores decreased and returned to near-baseline values as shown in Table 1. An examination of the individual POMS subscales and the corresponding T scores provided additional insight into the changes in TMD. See Figure 2 for the mean scores on the POMS subscales throughout the six-week training protocol. The testing days in Figure 2 included a baseline period (b), a period of alternating high intensity (h) and recovery (r) days, and a taper (t) period. Changes in Vigor scores correlated highly with changes in average TMD scores (r = 0.90); Vigor scores were above the college norms (McNair et al., 1971, 1981, 1992) at all testing times except on assessments 6 and 7 (assessed in the second week of the overtraining period). The five other subscales of Tension, Depression, Anger, Fatigue, and Confusion were slightly above the mean in the first baseline week and decreased until the first week of overtraining. Each subscale peaked during the second week of overtraining, after which they all decreased again. Each of these five subscales reached their most favorable scores during the recovery. Of particular interest was Anger because scores on this subscale often increases during highintensity, long-duration overtraining (Morgan et al., 1987, 1988; O Connor et al., 1991). Results of the ANOVA indicated that the cyclists showed significant increases in Anger subscale scores from baseline to the high-intensity day of the second week of overtraining (p <.0008). During recovery, T scores on Anger returned to a level lower than baseline levels. Performance Variables Quality of performance was indicated by pursuit time and average power output during simulated 4-km pursuit cycling tests. Pursuit time improved throughout the study, from an initial mean of sec (SD = 34.2) at baseline to sec (SD = 26.6) after three weeks of overtraining. Pursuit time further improved eight days into the taper period to a mean of sec (SD = 28.2). In summary, pursuit time decreased by 6.5% during the three-week overtraining period and by an additional 2% during the taper. Average power output also increased throughout the study from a baseline mean of watts (SD = 35.9) to a mean of watts (SD = 36.3) during the

10 Mood and Overtraining 453 Figure 2 Profile of mood states subscale scores throughout the training protocol. three weeks of overtraining, to an average of watts (SD = 36.6) on the eighth day of taper. Power output increased by approximately 6.7% during the three weeks of overtraining and an additional 2.3% during taper. Relationship between Psychological and Performance Variables There were no significant correlations between the changes in TMD scores and the cycling performance variables. Although the overtraining protocol led to temporary decrements in mood, performance improved steadily throughout the study. Throughout the two weeks of taper, TMD, pursuit time, and average power output reached optimum levels. Discussion The high-intensity and short-duration overtraining protocol employed in this study was not associated with significant chronic mood disturbances, and it did promote improvements in measures of cycling pursuit performance. Although the cyclists reported a significant increase in TMD during the second week of overtraining in comparison to baseline, the increase in TMD was short-lived. During the third and final week of overtraining, TMD scores were not significantly different than baseline. There were significant improvements in mood during the taper period in comparison to scores during both the baseline and the three weeks of overtraining. Thus, the overtraining protocol employed in this study, which consisted of highintensity and short-duration interval training, was not associated with chronic mood

11 454 Berger, Motl, Owen, et al. decrements. Instead, the overtraining protocol seemed to promote psychological adaptations as illustrated by more positive TMD scores in the taper than at baseline. This suggests that overtraining may be associated with both psychological and physiological adaptations. The high-intensity, short-duration overtraining protocol was effective for enhancing performance as indicated by improvements in pursuit time and average power output. When compared with baseline measures, pursuit time and average power output improved throughout the three weeks of overtraining. Further improvements occurred during the taper period in comparison to both the baseline and overtraining periods. Illustrating the success of the high-intensity, short-duration overtraining protocol, improvements in pursuit time, average power output, and TMD were observed during the two-week taper period. Because performance improved throughout the study without long-lasting mood decrements, the highintensity and short-duration overtraining protocol could not be characterized as producing overtraining syndrome. In contrast to the present study, which included high-intensity and shortduration overtraining, other studies have focused on the performance and mood changes associated with high-intensity and long-duration overtraining protocols, e.g., 9,000 day 94% V O 2max (Morgan et al., 1988). Results of studies employing high-intensity and long-duration overtraining protocols have indicated that athletes generally exhibit performance decrements and chronic mood disturbances (Morgan et al., 1987; O Connor et al., 1991). The high-intensity and short-duration overtraining protocol in this study yielded performance improvements, and it avoided the chronic mood decrements often associated with high-intensity and long-duration overtraining protocols in endurance athletes. Our results are supported by Lehmann et al. (1992) who reported that middle- and long-distance runners exhibited improved performance and hormonal adaptations to high-intensity and short-duration overtraining; there were negative performance and hormonal responses to high-intensity and long-duration overtraining. It seems that highintensity and short-duration overtraining may promote improvements in performance without the chronic mood decrements and hormonal dysregulation associated with high-intensity and long-duration overtraining protocols. Our results also support the idea that the specificity of an overtraining protocol may differentially influence changes in mood and performance (Boulay, 1995; Hooper, Mackinnon, & Hanrahan, 1997; Raglin, 1993). Specificity refers to matching the intensity and duration of overtraining to the cardiorespiratory and metabolic demands of a sporting event (e.g., Wilmore & Costill, 1994). To accumulate sport specific cardiorespiratory and metabolic adaptations, 4-km pursuit cyclists need to follow an overtraining program that focuses on high-intensity, but shortduration exercise bouts. High-intensity interval training performed at or above the anaerobic threshold would be ideal for 4-km pursuit cyclists. In contrast, endurance cyclists need to employ an overtraining protocol that focuses on long-duration combined with lower-intensity exercise bouts to stimulate biological adaptations necessary for maximal performance (Boulay, 1995). Matching the overtraining stimulus to the demands of the sport event is not a new idea, and it seems to be beneficial in optimizing sport performance and avoiding the symptoms of the overtraining syndrome. Other explanations could account for the small increases in TMD with the three weeks of overtraining. Although the baseline period in this study included a

12 Mood and Overtraining 455 low volume of intense training, it still may not have been a true baseline period for establishing comparison scores on the POMS. Cyclists could have been nervous or concerned about the approaching overtraining period, and their moods may have been more negative than usual. Simply being housed at the Olympic Training Center could have produced extra pressure to perform and thus influenced the initial POMS scores. To obtain true baseline scores in future studies, athletes should be tested well in advance of the training (i.e., one month) before nervousness and worry become possible influences. This study has three primary implications for applied practice. First, this study supports the validity and reliability of utilizing the POMS to monitor endurance athletes during periods of overtraining (e.g., Dishman, 1992; O Connor, 1997; Raglin, 1993). The overtraining protocol employed in this study did not result in significant chronic mood disturbances as measured by the POMS, and it did promote improvements in measures of cycling pursuit performance. Previous research has reported concomitant mood and performance decrements with overtraining and subsequent taper periods. Accordingly, chronic mood decrements on the POMS should only be observed with performance disturbances in agreement with the mental health model (Morgan, 1980); lack of mood decrements should correspond with no changes or improvements in performance. Second, it appears that the parameters of an overtraining protocol differentially influence changes in performance variables and mood. Overtraining protocols that involve high volume seem to increase the occurrence of overtraining syndrome in endurance athletes (Lehmann et al., 1997). Third, the results emphasize the need to utilize sport specific overtraining protocols that promote cardiorespiratory and metabolic adaptations for maximal performance and minimize negative consequences such as mood disturbances. The generalizability of the present results to samples other than 4-km pursuit cyclists may be limited based on the lack of a comparison group. With the inclusion of a comparison group that performed high-intensity and long-duration overtraining, our conclusions would be stronger. It is possible, however, that the performance improvements and lack of mood disturbances associated with highintensity and short-duration overtraining would be observed in other studies of pursuit cyclists and perhaps other endurance athletes. Possibly supporting the generalizability of the results, Lehmann et al. (1992) reported positive performance and hormonal responses to high-intensity and short-duration overtraining but not in response to high-intensity and long duration overtraining in middle- and longdistance runners. In conclusion, this study demonstrated that a high-intensity and short-duration overtraining program was associated with improved performance but not with the often cited, chronic mood disturbances. Because other studies have found mood and performance decrements to be associated with overtraining, additional research is needed to help determine the point at which overtraining becomes excessive. Research also is needed to further delineate how the intensity and/or duration of overtraining may differentially influence the occurrence of overtraining syndrome. It seems clear, however, that high-intensity and long-duration training aimed at maximal performance may be detrimental to both performance (Lehmann et al., 1992, 1997) and mood variables (Morgan et al., 1987, 1988; O Connor et al., 1991). Perhaps the best that athletes can hope for in regard to mood is a relative absence of decrements with corresponding performance improvements during overtraining periods.

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