Members of the Swedish national swimming team (N = 16) traveled by air from Stockholm to Tokyo via Copenhagen enroute to the FINA (La Federation Internationale de Natation Amateur) world cup competitions in Hobart, Tasmania, and Sydney, Australia. The team was scheduled to train for 9 days at Cronulla Beach, 1 hr south of Sydney, following the competitions. This investigation assessed the effect of a regimen of diaphragmatic breathing and sleep training that some team members practiced, on sleep, jet lag, and swimming performance. Prior to the start of the investigation, swimmers were matched in terms of ability (by gender), using the FINA point-scoring system. Each swimmer in each of the 8 matched pairs was assigned to the experimental or control group via a flip of a coin. This procedure produced 2 matched groups that were statistically equal [falling within 2.75 FINA points of each other, t(14) = .071, ns]. The experimental group listened to a sleep-training tape and did diaphragmatic breathing each night during the 21-day experiment. To assess mood, the POMS questionnaire was administered daily, except when competitions were held in Hobart and Sydney. Following arrival first in Tokyo and then in Hobart, each swimmer assessed his or her experience of jet lag using an 11-point Likert-like scale. Each swimmer’s sleep was assessed daily using an Actiwatch, a wristwatch-like device that was programmed and positioned on the swimmer’s non-dominant wrist to record sleep length, sleep efficiency, movement and fragmentation index, and other sleep variables. The FINA point system was used to measure swimming performance. Univariate and multivariate analyses of the sleep, jet lag, mood, and performance data did not find any significant between-group differences. It was concluded that sleep training and diaphragmatic breathing as carried out by this study’s participants did not affect sleep, mood, jet lag, or swimming performance.

Effects of Diaphragmatic Breathing and Sleep Training On Sleep, Jet Lag, and
Swimming Performance

In a recent review, Youngstedt and O’Connor (1999) concluded that more rigorous research is needed to establish whether athletic performance is influenced by air travel. Youngstedt and O’Connor accepted that rapid transmeridian flight is a common reality for modern athletes and noted that “the scientific evidence supporting the view that performance is impaired [by such travel] is neither consistent nor compelling” (p. 197), because major methodological flaws characterize studies of athletic performance following transmeridian flight.

Despite Youngstedt and O’Connor’s (1999) assessment, there is growing evidence that high-speed transmeridian flight may have debilitating effects on athletes, especially on their sleep–wake cycles. Loat and Rhodes (1989), for example, reported that jet lag caused de-synchronization of an athlete’s physiological and psychological cycles and had adverse effects on performance. The severity of these adverse effects depends on number of time zones crossed, direction of flight, and type of individual (introvert or extrovert), along with age, social interaction, physical activity, and diet (Loat & Rhodes, 1989). Manfredini et al. (1998) also reported that athletes who cross multiple time zones experience a shift in their internal biological clocks.

In addition to assessing the effect of jet lag on athletic performance, this investigation determined the effect of diaphragmatic breathing and sleep training on sleep and jet lag. Diaphragmatic breathing is as old as the ancient exercises of yoga and tai chi and is a fundamental component of these practices. The rationale for the use of diaphragmatic breathing is well supported by stress management authorities such as Seaward (2002), who offered a physiological explanation of diaphragmatic breathing’s effects on the nervous system. According to Seaward, when pressure due to the expansion of the chest wall and muscular contraction is taken off the thoracic cavity, sympathetic drive decreases. Parasympathetic drive overrides the sympathetic system, and homeostasis results. Bentov (1988) provides a second explanation for the pacifying effect of diaphragmatic breathing, which is that vibrations emitted from the heart send a wave of stimulation through the aorta.

The study of sleep is gaining in popularity since the publication of texts by Dement (1999) and Maas (1998). Sleep research has been further helped along by the development of the Actiwatch, a wristwatch-like device that contains an accelerometer and measures such important information as sleep length, sleep efficiency, and movement and fragmentation. However, no previous studies of sleep training conducted among athletes were found.

The present study’s hypothesis was that athletes who engaged in diaphragmatic breathing and sleep training would sleep more effectively, have relatively enhanced mood, suffer less from jet lag, and perform more effectively than athletes in a control group.



Approval of the study was obtained from the university human subjects committee. All participating swimmers signed consent forms. The participants (N = 16) ranged in age from 15 to 26 years. Mean age, height, and weight were 21.1 years, 179.5 cm, and 72.6 kg, respectively. For males in the group (n = 6), mean age, height, and weight were 22.7 years, 188.5 cm, and 86.0 kg, respectively. For females in the group (n = 10), mean age, height, and weight were 20.1 years, 174.1 cm, and 64.6 kg, respectively. In general, the athletes were quite accomplished. One swimmer had recently set a world record at the European Short Course Championship, and four had competed in the 1996 Atlanta Olympic Games. Three of the swimmers were attending college, while one had graduated from an American university where he had been named an All-American.

Formation of the Experimental and Control Groups

Prior to traveling, the investigators had ranked the male and female team members (separately) from best performer to poorest performer, using the point-based FINA performance rating system (Thierry, 1998). The top 2 male swimmers and top 2 female swimmers were assigned by coin toss to either the experimental group or the control group. In similar fashion, the 3rd- and 4th-ranked male swimmers and 3rd- and 4th-ranked female swimmers were assigned to a group, as were the 5th- and 6th-ranked swimmers, and so forth until all swimmers were assigned to either the experimental or the control group. This matching process produced 2 groups that were within 2.75 FINA points of each other: for the experimental group M = 953.88 (SD = 79.98), while for the control group M = 951.13 (SD = 74.71). A t test conducted with the matched pairs indicated that no statistically significant difference between the groups existed, t(14) = .071, ns. Each group comprised 8 swimmers (5 females and 3 males).


On January 8, 2000, 13 members of the Swedish national swimming team, the primary investigator, and 2 coaches traveled by air from Stockholm to Tokyo, via Copenhagen, enroute to FINA world cup meets taking place in Hobart, Tasmania, Australia, and Sydney, New South Wales, Australia. Because jet lag varies with the direction of flight and the number of time zones crossed, these were carefully recorded for each leg of the journey. The team stayed overnight in Tokyo and worked out at a pool near their hotel before flying to Hobart, via Melbourne, on January 10, 2000. In Hobart, the team was joined by 2 additional swimmers whose attendance at college required alternative travel arrangements. A third team member met up with the team in Sydney to take part in the training camp, although she was not competing in the world cup meets. In Hobart, competition took place January 12–13. On January 14, the team traveled by air from Hobart to Sydney, via Melbourne. Competition was conducted in Sydney on January 17–18, at the Homebush Bay Swimming Venue, site of the 2000 Sydney Olympic Games. On January 19, the team traveled by bus to their Cornulla Beach training facility and participated in 9 days of intensive preparation before returning to Stockholm.

Measurements and Apparatus

Direction of Flights, Time Zones Crossed

Flying east from Stockholm to Tokyo, the swimmers crossed 9 time zones; flying east from Tokyo to Hobart required crossing 1 time zone only. On the return trip from Sydney to Stockholm (via Bangkok and London), the team flew west through 9 time zones. Typically, flying east is more problematic than flying west. It is well documented that crossing greater numbers of time zones is associated with more intense jet lag (Oren et al., 1993).

Assessment of Jet Lag

For 4 consecutive days following each flight, each swimmer was asked to rate the degree of jet lag he or she experienced, using an 11-point Likert-like scale with 0 indicating no jet lag and 10 indicating severe disturbance. Swimmers rated jet lag upon arrival in Tokyo and in Hobart. Sleep disturbance is one of the most common problems associated with jet lag.

Assessment of Sleep

During the 21 days of the experiment, each swimmer used an Actiwatch, a wristwatch-like device that had been programmed and was worn continually on the swimmer’s non-dominant wrist (when not swimming or showering). The Actiwatch collected sleep data nightly throughout the 21 consecutive days. It contains an accelerometer that records the wearer’s movements at an epoch interval programmed into the device, in this case an epoch interval of 1 min. Chang et al. (1999) verified the validity of data collected with the Actiwatch, finding that the device correctly identified sleep 91.8% of the time, based on epoch-by-epoch comparisons with polysomnography. The swimmers’ Actiwatches recorded sleep length, sleep efficiency, movement and fragmentation index, and other sleep variables. Before the investigation began, each Actiwatch had been programmed with a swimmer’s name, age, gender, and epoch interval (1 min), which were uploaded into it. The primary investigator employed a watch position protocol to ensure that each Actiwatch was worn correctly, positioned on the non-dominant wrist just above the distal end of the head of the radius. Each watch was allowed to record data for 5 days; then, those data were downloaded using Mini-Mitter software (Mini-Mitter Company, 1999), and the Actiwatch was again programmed for the swimmer so that data could be recorded over the next 5 days.

Each athlete’s sleep data were analyzed with sleep-analysis software (Mini-Mitter Company, 1999). The analysis relied on the calculation of the sleep–wake cycle, so the swimmers were asked to press an event marker on the Actiwatch, both upon going to bed and again upon awaking in the morning. With the event marker feature establishing the beginning and end of the sleep–wake cycle for each swimmer, the software could generate a sleep profile for each participant, describing sleep length, sleep efficiency, movement and fragmentation index, number of awake and asleep bouts, and number of minutes spent moving. After the Actiwatch data were recorded in tabular form, univariate and multivariate analyses were used to look for differences between the experimental and control groups.

Assessment of Mood

Except on days when swim competitions occurred, each studied swimmer’s mood was monitored via daily administration of the written Profile of Mood States (POMS) Questionnaire (McNair, Lorr, & Droppleman, 1992). (During the 4 days of competition in Hobart and Sydney, the swimmers did not complete the paper-and-pencil assessments of mood.) The POMS questionnaire measures 6 important components of mood: tension, anger, fatigue, depression, vigor, and confusion. It is a valid, reliable assessment, with factor-analytic and concurrent validity studies consistently showing that POMS measures what it is supposed to measure (McNair et al., 1981). For example, correlation between the POMS and the MMPI–2 ranges from .52 to .69 (McNair et al., 1981). The POMS questionnaire was used to produce, for each swimmer, a score for total mood disturbance, calculated by adding scores for tension, anger, fatigue, depression, and confusion and then subtracting that sum from a negative score for vigor.

Diaphragmatic Breathing and Sleep Training

The experimental group (n = 8) received 2 treatments, diaphragmatic breathing and sleep training. Diaphragmatic breathing consisted of completing, once daily, a 49-breath exercise developed by Williams (1996). To complete the exercise, the swimmers were asked to assume a seated position with feet flat on the floor, hands resting on the thighs, trunk slightly flexed and chin resting on the manubrium of the sternum. In this position they were to take a series of breaths, inhaling through the nose, breathing deep into the abdomen, and forcing air deep into the lungs. The neck was to be hyperextended during each inhalation; the diaphragm muscle was to be fully contracted allowing the lungs to inflate to capacity. The experimental group members were asked to complete 3 sets of 14 breaths each, and a final set of 7 breaths, again, once each day.

Sleep training (intended to make sleep more effective) comprised listening to a sleep-training CD (Uneståhl, Leissner, & Leissner, 1995) each night. The CD, which is widely available in Swedish pharmacies, has been used by hundreds of thousands of Swedes since the early 1990s. It has three components, (a) 19 min of sleep training, (b) 10 min of sleep napping, or “siesta sleep,” and (c) a sleep onset portion lasting 29 min. Only the third component was used in this study; its goal is to foster quicker sleep onset and improve sleep quality. The approach involved is to let sleep happen, as opposed to making an effort to get to sleep. Swimmers in the experimental group were allowed to examine the entire contents of the CD, thereafter listening nightly (throughout the 21-day experiment) to the third component, after getting into bed. In addition, for the 25-hr flight between Sydney and Stockholm (via Bangkok and London), swimmers in the experimental group were asked to listen to the third part of the CD before attempting to sleep on the plane.

Assessment of Swimming Performance

Each swimmer earned points under the FINA scoring system based on his or her competitive performance. Official FINA points accumulated in 5 specified venues comprised the assessment of swimming performance used in the study.


Swimming Performance

Because 5 participating swimmers became sick during training at Cronulla Beach in Australia following the FINA world cup competitions, the study was affected by missing data.

FINA swimming points employed in this study’s analyses had been accumulated by the swimmers at 5 venues: Hobart (Tasmania, Australia), Sydney (New South Wales, Australia), Malmö and Stockholm (Sweden), and Athens (Greece). Table 1 presents the average number of FINA points earned by members of the experimental group and the control group and illustrates that there was no significant difference between the swimming performance of the experimental group and that of the control group, at any of the venues.

The analytical strategy that had been planned was a mixed ANOVA comparing the experimental and control groups’ FINA points from the 5 venues; in light of the missing data, this plan was replaced with 2 other strategies able to maximize the data that were available. First, the FINA points accumulated by the experimental group and control group were subjected to separate independent-samples t testing, by venue, to compare the groups’ swimming performances, by venue. No significant difference was found between FINA points accumulated by the experimental-group swimmers and by the control-group swimmers. Second, the average FINA points earned by each swimmer were calculated. An independent-samples t test compared the grand mean for the experimental group (M = 931.85, SD = 27.63) to that of the control group (M = 942.31, SD = 20.98). This analysis indicated that FINA points (i.e., swimming performance) did not differ significantly between the experimental and control groups, t(14) = -.854, ns.

Jet Lag, Sleep, and Mood

Data collected in Tokyo and Hobart to measure the swimmers’ jet lag were analyzed. A 4 x 2 between-subjects ANOVA showed a significant main effect of the data-collection point, F(3,27) = 19.324, p<.0001. As seen in Table 2, the swimmers experienced jet lag most strongly in Tokyo (January 9, 2000) and least strongly in Hobart (January 12, 2000). However, the interaction between data-collection point and group was not significant, F(3.27) = .891, ns. The results show that degree of jet lag experienced by the swimmers differed based on the data-collection point, but the effect was the same for the experimental group and the control group.

The swimmers’ sleep data, downloaded from the Actiwatches they wore continually except when swimming or showering, produced the measures presented in Table 4, namely means, standard deviations, sample sizes, and t test values. The sample size was small, and the number of testing days was too large; thus repeated measures ANOVA for each sleep variable could not be calculated. As an alternative, the averages for all measured sleep variables across all testing days were calculated, for both the experimental and control group (Table 5). None of the sleep variables differed significantly between the two groups, leading the researchers to conclude that the sleep training tape did not enhance sleep among members of the experimental group.

As for measures of mood, Table 3 shows the means, standard deviations, and t test values for experimental-group and control-group swimmers. None of the POMS factors was found to be statistically significant. It is clear that both groups incurred extremely low scores on the vigor subscale. Because of the small sample size, only the score for total mood disturbance (TMD) was used for ANOVA comparisons. A mixed design ANOVA (days x condition), with days as the repeated measures factor and condition as the between-subjects factor, was calculated. This analysis revealed no significant main effect of day, F(13,117) = 1.62, ns. This value indicates that the TMD did not differ significantly from day to day. Nor was the interaction of day and condition found to be significant, F(13,117) = .475, ns. Thus no significant difference in mood between the experimental and control groups was indicated.


Swimming Performance

Excepting Youngstedt and O’Connor (1999), most authorities believe that jet lag adversely affects athletic performance (Manfredini et al., 1998; Reilly, 1998; Sasaki, 1980). In a review paper, Youngstedt and O’Connor indicated that support for the jet lag–performance hypothesis is neither consistent nor compelling. They cogently pointed out the methodological flaws in numerous studies in which jet lag showed a debilitating effect on athletes. In the present study, after traveling halfway around the world, the swimmers in our experimental and control groups did not differ in terms of swimming performance.

Many factors may be involved in the results of this investigation. First, perhaps the experimental treatments (sleep training, diaphragmatic breathing) were ineffective strategies for combating jet lag. Second, perhaps loss of sleep does not significantly affect athletic performance; some athletes apparently claim to perform better upon getting relatively less sleep the night before a competition. As Uneståhl points out, a little fatigue may increase relaxation and prevent over-arousal that could otherwise have an impact during important competitions (personal communication, July 19, 2000).

The present findings support Youngstedt and O’Connor’s contention that jet lag does not affect athletic performance (1999), in that no significant differences in swimming performance were found between experimental-group and control-group participants. Thus, the null hypothesis of no difference in swimming performance was accepted. Our study’s findings, however, run counter to Reilly and Piercy’s findings (1994) suggesting that 4 days of sleep deprivation adversely affected weightlifters. The weightlifters studied by Reilly and Piercy showed significant increases in perceived exertion, along with progressive drops in maximal lifts. Takeuchi and Davis (1985) furthermore found athletes’ jumping ability to decrease with sleep deprivation, which they attributed to the athletes’ diminished level of alertness.

Jet Lag, Sleep, and Mood

Jet lag measures were highest in Tokyo, reached by flying east for 9 hr and crossing the greatest number of time zones crossed during this investigation. At a practice session in Tokyo, it became evident that the swimmers were very tired. Many authorities on jet lag (Ehret & Scanlon-Waller, 1987, for example) recommend 1 day of rest for each time zone crossed. The swimmers’ flight from Tokyo to Hobart lasted about the same 9 hr, but in Hobart the athletes did not assign the same high scores for jet lag as in Tokyo. Perhaps this discrepancy resulted from the need to cross only 1 time zone during the eastbound flight. Moreover, the flight from Stockholm to Tokyo was a daytime flight, whereas the flight from Tokyo to Hobart was at night; perhaps while traveling the athletes got more sleep at night than during the day. An important anti–jet lag principle is to schedule a flight at the right time (Dement, 1999; Maas, 1998; Oren et al., 1993). The principle has been used, for instance, by Dement (1999), who was able to help the Stanford University football team minimize jet lag on a trip to Tokyo to play in the Coca-Cola Bowl.

No significant differences in sleep variables were observed between swimmers in the experimental group and those in the control group. In brief, the sleep training CD did not increase sleep efficiency, and it did not reduce the number of awake bouts, the percentage of time spent awake, or the movement and fragmentation index. Compliance with the CD-auditing regimen may have been a problem, although most swimmers said they had used the tape on approximately 80% of the nights they were asked to.

Morgan (1985) has repeatedly demonstrated that elite athletes possess what he refers to as the iceberg profile, indicated by mood inventories producing low scores for tension, fatigue, depression, confusion, and anger, along with high scores for vigor. Swimmer profiles obtained for the present study (see Table 3) resemble Morgan’s iceberg profile, except in terms of vigor. The low scores recorded for vigor by both groups of swimmers were perhaps due to the duration and intensity of their training during the training camp at Cornulla Beach. Working out twice daily at high intensity and high volume perhaps drained their energy. Many swimmers appeared very tired; 5 became sick and missed several days of training. According to the study data, swimmers constituting both groups score low for tension, anger, fatigue, confusion, and depression and also for vigor. The absence of significant differences between groups may have been due to the restricted range of abilities: All participants were elite athletes, with relatively low component scores.

A careful review of the POMS profiles for athletes who became sick indicates that they experienced considerable mood disturbance. In brief, swimmers who became sick had inverse iceberg profiles, meaning high scores for tension, anger, fatigue, depression, and confusion as well as a low score for vigor. Coaches began to cut back on training when the swimmers’ POMS profiles suggested considerable mood disturbance.


Statistical analyses of sleep, POMS questionnaire data, and performance variables indicated no significant overall differences between the experimental and control groups. It was concluded that diaphragmatic breathing and sleep training were not effective in altering mood, sleep, or swimming performance among swimmers traveling long distances to compete or train.

Table 1: FINA Swimming Performance Point Values for Experimental and Control Groups

Location Experimental Control t-test
Hobart Mean 910.17
t(12) = -1.6, n.s
Sydney Mean 915.14
t(12) = -1.04, n.s.
Malmo Mean
t(11) = -.922, n.s.
Stockholm Mean
t(12) = -.031, n.s.
Athens Mean
t(10) = -.185, n.s.

Table 2


2 Groups’ Likert-like (0–10) Ratings of Jet Lag Effects, by Location

Table 2: Average Jet Lag Ratings for Experimental and Control Groups

Location Experimental Control Total
Tokyo (1/9) Mean 7.10
Tokyo (1/10) 5.58
Hobart (1/11) Mean
Hobart (1/12) Mean

Note. 0 = no jet lag and 10 = severe jet lag. The date (in 2000) is given in parentheses next to the city.

Table 3

Descriptive Statistics and t Test Values Assessing Swim Team Members’ Mood

Variable Experimental
.402, n.s.
.039, n.s.
.397, n.s.
2.43 14.73
.650, n.s.
.590, n.s.
.338, n.s.
.420, n.s.

Note. For the t test, df = 14.

Table 4


Descriptive Statistics and t Test Values Assessing Swim Team Members’ Sleep

Table 4: Descriptive Statistics and t-test values for Sleep for Experimental and Control Group Swimmers

Variable Experimental
Sleep Efficiency (%) t(14) = .183, n.s
Number of Awake Bouts
t(14) = .267, n.s.
Percent Awake (min.)
t(14) = -.157, n.s.
Number Sleep Bouts
t(14) = .271, n.s.
Number Minutes Moving
t(14) = .170, n.s.
Percent Moving
t(14) = .079, n.s.
Move & Frag.
t(14) = .421, n.s


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Author Note

William F. Straub, Life University; Michael P. Spino, Life University; Lars-Eric Uneståhl, University of Örebro; Anna-Karin Englund, Norrbotten County Council, Luleå, Sweden.

Appreciation is extended to members of the Swedish national swim team and their coaches for their willingness to participate in this investigation. Appreciation is extended to Dr. Richard Darlington, Department of Psychology, Cornell University, and Dr. Ann Lynn, Department of Psychology, Ithaca College, for assistance with research design and statistical treatment of data. Appreciation is extended to Dr. Bruce Pfleger, director of research for Life University, for reviewing this manuscript.

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