ISSN: 1543-9518|Vol. 24

Effects of American Football on Height in High School Players

Brian Campbell, Torie Guidry, Matt Lopez, Kristina Estis and David Bellar

### Abstract

The aim of the present study was to investigate height change of high school football players during a single game. Ten high school football players served as participants. The participants were selected according to position and expected playing time. The chosen positions experience the repetitive longitudinal loading of the spine that may lead to a creep response in the vertebral disk. Height was measured using a standard physician beam scale with height rod. A practicing certified athletic trainer served as the tester for all measures (pre – post). A paired samples T-test was performed to determine significance between height before and after the game. A significant difference was shown in height magnitude (Mpre = 176.56±6.9cm, Mpost = 175.81±6.94cm, p = .032). The results indicate that high school football players’ height decreases during the course of a game. This process is likely due to the creep response caused by intermittent high impact compressive loading of the spinal column, as well as low impact continuous compressive forces from equipment weight.

**Key words:** American football, compression, spinal shrinkage, creep response

### Introduction

American football (football) places many physical demands on its participants due to the aggressive nature of the sport. External forces from running, blocking and tackling can cause much stress on the human body. Even with protective equipment such as helmets and pads, these forces are inevitable. During the course of a game, football players may experience substantial longitudinal loading of vertebral column from the compressive forces of running and tackling as well as the continuous load due to equipment mass. This loading of the spine may accelerate the creep response which could result in a decrease in height after a game.

Spinal creep is a process by which continual loading or compressive forces placed upon the spinal column cause a reduction in the vertical size of the intervertebral discs. This creep response is due to the viscoelastic properties of the intervertebral discs of the spinal column, and is also referred to as spinal shrinkage. When compressive loading of the spine exceeds the interstitial osmotic pressure of the discal tissue, water is expelled from the intervertebral discs. This results in a loss of disc height which is reflected as a loss in stature (11). Since the spinal column composes about 40% of total body length, and the intervertebral discs account for roughly one-third of the length of the spinal column (Reilly, 2002), fluid loss from the discs can potentially cause substantial change in stature.

Studies of the intervertebral discs have shown that by narrowing in response to compressive forces, the discs also stiffen, which alters the dynamic response characteristics of the intervertebral disc complex (7). Once the disc has been narrowed and stiffened, its ability to absorb sudden direct and indirect changes in force is reduced, and thus the disc is therefore more susceptible to injury (9), and is often suggested to be a major causal factor of back pain (8). Some of the sports that have the highest risk of these injuries are football, ice hockey, and rugby (1). Within the sport of football it is believed that there is an increase in risk factors associated with spinal creep that may cause many athletes to develop low back pain (5). Because specific spine injuries like fracture, disc herniation, and spondylolysis are more frequent in football players (5), the occurrence of spinal shrinkage during a football game may be greater than other activities.

Studies have investigated spinal shrinkage in various activities ranging from running (4), weight lifting (3) and circuit training (6), but currently there exists a gap in the literature surrounding spinal creep and American football. The compressive loads that can affect the vertebral column include gravity, changes in motion, truncal muscle activity, external forces and external work (13) all factors that can be involved in football. These factors may lead to an accelerated creep response which could result in a decrease in height after a game. In a sport such as football, any minute decrease in stature may mean the difference between blocking a last second field goal, or making a game winning catch. Chronic exposure to these factors may also lead to back pain or injuries to the spine or discs. Therefore, the purpose of this study was to investigate the amount of shrinkage due to spinal loading during a high school football game.

### Methods

#### Participants

Ten high school football players took part in the study. Mean values for height and weight were 176.6±6.9cm and 86.4± 9.5kg, respectively. All players were high school seniors aged 18 years and were selected according to position and expected playing time. The positions chosen were ones that experience the repetitive longitudinal loading of the spine that may lead to a creep response in the vertebral discs. This information was determined after interviewing the coach for the team and from observations made at other similar games. Based on these criteria, eligible (18yr old) players were recruited who started at the following positions: linebackers, running backs, and linemen. Players were also selected who would be likely to play the entire game with very few rest breaks.

#### Apparatus

A standard physician beam scale with height rod was used in this study for measuring changes in stature before and after participation in the game. All measurements were collected by a practicing certified athletic trainer. The apparatus was accurate to within 0.01 inches and all measurements were converted to millimeters.

#### Procedures

The football game used for this experiment was an evening high school football game, which took place after a regular day of school. An evening game was selected to ensure that any shrinkage occurring from normal daily activities would not affect the results of the study. Participants were measured barefoot while standing and wore t-shirt and shorts for both pre-game and post-game measurements. Pre-game measurements were taken prior to warm ups to ensure that starting heights reflected absolutely no football activity. Post-game measurements were taken immediately after completion of the game. Three consecutive measurements were taken each time by the certified athletic trainer to ensure that the apparatus was reliable.

#### Data Analysis

The effects of playing football on changes in stature were analyzed using a paired sample T-test. Post hoc power calculations were performed following any statistically significant finding. Comparisons were made between the pre- and post-game height measurements. All statistical analyses were performed with the use of a modern computer software package (SPSS 17.0 for Macintosh, G*Power 3). Statistical significance was set a priori at an alpha level > 0.05.

### Results

The mean and standard deviation for the pre-game height measurements was 176.6 ± 6.9 cm. Post-game measurements yielded a mean and standard deviation of 175.8 ± 6.9 cm. The results show that there was a significant increase in spinal shrinkage due to participation in a high school football game (p =0.032, power = 0.674). The average height loss for the ten participants was 7.62 (±SD = 9.25) mm.

### Discussion

The present study showed that participation in a high school football game causes measurable height differences before and after the game, the demonstrated mean loss of stature was 7.62mm. It can be assumed that the decrease in height is due to the increased external forces and equipment weight that are involved in the sport. These potentially lead to a rise in the intradiscal pressure and fluid to be expelled, resulting in a reduction in disc height. Though it is logical that loss of intervertebral disc height is responsible for all variations in height, it is also possible that the cartilage in joints and the soft tissue covering the scalp and soles of the feet may have been compressed. However, the total height of the intrajoint cartilage is small and the degree of compression is thought to be negligible (6). The soft tissue covering the scalp is also thin and the height rod of the scale used for measurement would compress the tissue to an insignificant level. The tissue covering the soles of the feet might also be compressed upon standing but it is likely that equilibrium was quickly reached (6). As a result, the measured changes in stature can be considered to reflect only the changes in disc height.

The spinal shrinkage recorded during a football game was greater than what was observed in previous research of other activities. The 7.62 mm decrease in stature in this study was greater than the 3.25 mm decrease during a 6 km run (6), 5.4 mm decrease during circuit-weight training (6), 3.6 mm decrease during weight training (3), and 1.81 mm during a drop jump regimen (2). Although shrinkage during participation in football was greater than other activities, it is not the greatest recorded occurrence of spinal shrinkage. The results of this study are comparable to the 7.8 mm loss in height during a 19 km run (6), and much less than the recorded loss of 11.2 mm during static loading with a 40 kg barbell (14).

A study that examined spinal recovery in pregnant women showed that women with lower back pain were unable to recover from spinal shrinkage to the same extent as women with no lower back pain (12). These findings suggest that lower back pain may be related to the diminished ability to recover, rather than the magnitude of the spinal shrinkage imposed during the task. Since there is believed to be a relationship between football and the development of lower back pain (5), this could suggest that football players may have a diminished ability to recover from spinal compression. This may be provoked by the magnitude and frequency of spinal loading that a football player is subjected to.

The inability of the spine to recover may also lead to serious acute and chronic injuries to the spine and discs. Football is considered to be one of the sports with the highest risks for the occurrence of spinal injuries (1). Many of the spinal injuries that are common in football include fractures, disc herniation, and spondylolysis (5). There may also be a positive correlation between the years of involvement in football and the chances of developing degenerative disc disease (5).

### Conclusions

Based on prior research, it can be assumed that more spinal shrinkage occurs during participation in a football game as compared to other less impactful activities because of a greater spinal load. Football players experience this load on the spine not only from running, but also from the static load from the weight of equipment and from direct impact forces caused by collisions with other players. Both these components, running (6) and static loading of the spine (14), have been found to cause accelerated loss in stature. This combination, along with the collisions during a football game, may be the reason for greater spinal shrinkage.

Although the present study was conducted on high school players, the results should be also consistent with higher levels of play. A previous study was conducted to compare the response to spinal loading between different age groups of males (10). When comparing younger males (18-25 years of age) and older males (47-60 years of age), it was found that regardless of age the pattern of spinal shrinkage between the two groups was similar. Based on this research, high school, college, and professional football players should experience a similar response to spinal loading during a game.

### Applications In Sport

In a game such as football, winning and losing can be a matter of inches. If a player decreases in height at the end of a game, the extra length could be the difference in catching a football, blocking a kick, or batting down a pass. Thus this height difference might be the difference between winning and losing. The degree of hydration may play a role in the extent of the creep effect and should not be overlooked. It may be beneficial to conduct future research on the effects of height decrease on athletic performance. Future research may also investigate if frequent practice of spinal unloading throughout a player’s career can prevent or reduce spinal injuries and back pain.

### References

1. Boden, B., Jarvis, C. (2009). Spinal injuries in sports. Physical Medicine and Rehabilitation Clinics of North America, 20(1), 55-68
2. Boocock, M. G., Garbutt, G., Linge, K., Reilly, T., Troup J. D. (1989). Changes in stature following drop jumping and post-exercise gravity inversion. Medicine and Science in Sports and Exercise, 22(3), 385-390
3. Bourne, N., Reilly, T. (1991). Effects of a weightlifting belt on spinal shrinkage. British Journal of Sports Medicine, 25(4), 209-212
4. Dowzer, C., Reilly, T., Cable, N. (1998). Effects of deep and shallow water running on spinal shrinkage. British Journal of Sports Medicine, 32, 44-48
5. Gerbino, P., d’Hemecourt, P. (2002). Does football cause an increase in degenerative disease of the lumbar spine? Current Sports Medicine Reports, 1(1), 47-51
6. Leatt, P., Reilly, T., Troup J. D. G. (1986). Spinal loading during circuit weight-training and running. British Journal of Sports Medicine, 20(3), 119-124
7. Markolf, K. (1972). Deformation of the thoracolumbar intervertebral joints in response to external loads. The Journal of Bone and Joint Surgery, A, 511-533
8. Nachemson, A. L. (1976). The lumbar spine: an orthopedic challenge. Spine, 1(1), 59-69
9. Perey, O. (1957). Fracture of the vertebral end plate in the lumbar spine: an experimental biomechanical investigation. Acta Orthop Surg Suppl, 25, 1-100
10. Reilly, T., Freeman, K. A. (2006). Effects of loading on spinal shrinkage in males Of different age groups. Applied Ergonomics, 37(3), 305-310
11. Reilly, T., Tyrrell, A., Troup, J. D. G. (1984). Circadian variation in human stature. Chronobiology International, 1, 121-126
12. Rodacki, C. L., Fowler, N. E., Rodacki, A. L., Birch, K. (2003). Stature loss and recovery in pregnant women with and without low back pain. Archives of Physical Medicine and Rehabilitation, 84(4), 507-512
13. Troup, J. D. G. (1979). Biomechanics of the vertebral column. Physiotherapy, 65(8), 238-244
14. Tyrrell, A., Reilly, T., Troup, J. D. G. (1984). Circadian variation in human stature and the effects of spinal loading. Spine, 10, 161-164

### Figures

#### Figure 1
Percent change in height pre- to post-game among high school athletes participating in American football.

![Figure 1](/files/volume-14/447/figure-1.jpg)

### Corresponding Author

Brian J. Campbell, PhD, ATC
Department of Kinesiology
University of Louisiana at Lafayette
225 Cajundome Blvd.
Lafayette, LA 70506
<campbell@louisiana.edu>
(337) 501-0634

Brian J. Campbell is the Curriculum Coordinator of Exercise Science at the University of Louisiana at Lafayette. Dave Bellar, PhD is the Exercise Physiology Lab Director at the University of Louisiana at Lafayette. Kristina Estis is a Certified Athletic Trainer for Champion Sports Medicine at St. Vincent’s Birmingham. Tori Guidry is an undergraduate student of Exercise Science at the University of Louisiana at Lafayette. Matt Lopez is a DPT student at the University of South Alabama.

2013-11-22T22:56:36-06:00January 3rd, 2012|Contemporary Sports Issues, Sports Coaching, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on Effects of American Football on Height in High School Players
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The Effects of Conference Realignment on National Success and Competitive Balance: The Case of Conference USA Men’s Basketball

Martin M. Perline, G. Clayton Stoldt, Mark C. Vermillion

### Abstract

Collegiate athletic conferences serve multiple functions, including providing regular opportunities for members to compete in a relatively equitable environment and contributing to the financial well being of member institutions. Many conferences have undergone realignment in recent years, and the effects of those changes may impact the degree to which conferences realize those desired outcomes. The purpose of this paper is to assess how the churning of various institutions (i.e., changes in conference membership as institutions leave or are added) within Conference USA over a 10-year period affected the conference’s men’s basketball programs in regard to success at the national level and competitive balance within the conference. Both national success and competitive balance within the conference can significantly impact the financial well-being of the conference. Results of the study indicate decreases in both the competitive success of the men’s basketball programs at the national level and the in-conference competitive balance between the 2000-2001 through 2004-2005 and the 2005-2006 through 2009-1010 time periods.

**Key Words:** college athletics, competitive balance, conference realignment, basketball, conference USA

### Introduction

While amateur athletic conferences serve many functions for the individual member institutions, one important purpose is to attempt to enhance the financial status of their members. Although there are numerous ways this can be achieved, two important ways include (1) an attempt to accumulate a group of conference teams that are successful nationally against teams from rival conferences, and (2) an effort to insure teams are somewhat evenly matched within the conference—what is referred to as competitive balance.

Both winning against non-conference opponents and competitive balance are important as they tend to enhance the financial status of conference members. Indeed, “everyone loves a winner,” and is willing to attend games featuring successful teams more often and pay more to attend. Likewise, while people want their teams to win, fans like the games to be exciting and not a foregone conclusion as to the winner (5, 9, 12, 17, and 18).

Almost all major college athletic conferences have experienced changes in their membership within the last six years. These changes—commonly referred to as churning as members come and go—impact conferences in many ways. Competitive success at the national level and in-conference competitive balance are among the desired outcomes commonly impacted.

The purpose of this study was to assess how churning within Conference USA over a 10-year period has affected the conference’s men’s basketball programs in regard to success at the national level and competitive balance within the conference. The study is important because it assesses the impact of churning on two key but unrelated dimensions. A conference may be well balanced competitively but have negligible success at the national level. Conversely, a conference may be highly unbalanced, but the few teams who win consistently in-conference, may also enjoy considerable success at the national level. This can provide considerable financial rewards for the conference.

Competitive success at the national level and the financial well-being of conference members are inextricably linked because the number of teams a conference places in the NCAA national championship tournament and the number of victories those teams accrue determine the NCAA’s payout to participating conferences. Other studies have examined the effects of churning on competitive balance (see, for example, 13-15, 18) or the relationship between realignment and program revenue (8). This project is the first to combine both considerations, allowing for a more comprehensive assessment of churning outcomes.

### Related Literature

College conferences are comprised of college and universities that have established an association, one of the purposes of which is regular athletic competition (1). In 2011, Staurowsky and Abney (20) stated conferences “establish rules and regulations that support and sustain a level playing field for member institutions, while creating in-season and postseason competitive opportunities” (p. 149). And Rhoads (18) has observed that “(i)t is reasonable that conferences should be quite active in ensuring optimal levels of competitive balance” (p. 5).

Sustained competition among equitable teams is not the sole purpose of athletic conferences, however. Depken (4) observed:

> Sport leagues exist, in part, to insure profitability of their member franchises. Although the NCAA specializes in amateur sports, in which players do not receive direct salaries for their athletic performance, it is readily apparent that the schools that comprise the NCAA are often anxious to earn as much profit as possible from the sports programs (p. 4).

College athletic conferences contribute to their member institutions’ revenue by distributing rights fees from media agreements, corporate sponsorships, licensing and other forms of revenue received by the league (7). One source of revenue for NCAA Division I conferences are distributions from the annual Division I Men’s Basketball Championships. Payouts to conferences are based on financial values linked to units, which are accrued each time a conference member plays a game in the tournament (22). For example, a conference member advancing to the third round (i.e., “Sweet Sixteen”) is valued at three units. Payments to conferences are based on six-year averages of the financial values associated with units accrued (22).

#### Conference Churning

As illustrated in Table 1, 10 of the 11 conferences in the NCAA Division I’s Football Bowl Subdivision (FBS) experienced membership changes between 2005 and 2011. Additional changes at the FBS level are planned for 2012, and Quirk (16) has observed similar instability among non-FBS Division I conferences. Fort and Quirk (6) argued that football is the predominant consideration when institutions change conference affiliations. Competitive imbalance in existing conferences often results in churning because enhanced competitive balance is linked to desirable financial outcomes. Other scholars (5, 9, and 17) support that argument, observing that consumer uncertainty of a game’s outcome is linked to increased demand. Rhoads (18) specifically linked competitive balance with increased ticket sales and enhanced television rights fees.

Little scholarly attention has been devoted to effects of conference churning on competitive success against non-conference opponents. Minimal research has been devoted to evaluating conference realignment in terms of financial outcomes. One exception is Groza (8), who found FBS teams that changed conferences enjoyed an increase in attendance, even controlling for increased quality in competition. Of course, ticket sales (i.e., attendance) is only one of many financial factors that may be impacted by churning. Others include, but are not limited to, BCS and other bowl related revenue, NCAA tournament payouts; media rights fees, athletic donations, and corporate sponsorship fees.

Several studies have been conducted assessing the effects of conference churning on competitive balance within select sport programs. Rhoads (18) examined the Western Athletic and Mountain West conferences and found that membership changes in those conferences had resulted in enhanced competitive balance in football. The changes had no impact on competitive balance in men’s basketball however. Perline and Stoldt (13-14) conducted two studies focusing on competitive balance before and after the Big 8 Conference expanded to become the Big 12. Their first study focused on men’s basketball, for which they concluded that competitive balance within the sport decreased after the conference’s expansion (13).Their second study centered on football, for which they concluded that competitive balance improved after the merger (14). The same scholars also examined competitive balance in women’s basketball before and after the merger between the Gateway Collegiate Athletic Conference and Missouri Valley Conference (15). Multiple methods of assessing of competitive balance produced mixed results, with more measurements indicating more competitive balance after the merger.

#### Conference USA: History and evolution

Conference USA (C-USA) was formed in 1995 during a time of great upheaval in college athletics, which included the dissolution of the Southwest Conference and the formation of the Big XII in 1996 (21). C-USA is a Division I-A league that is divided into two competitive divisions: East and West. In the eastern division members include East Carolina University, Marshall University, the University of Memphis, Southern Mississippi University, University of Alabama- Birmingham, and the University of Central Florida. The western division includes the University of Houston, Rice University, Southern Methodist University, Tulane University, the University of Tulsa, and the University of Texas- El-Paso (2).

Since its inception in 1995, C-USA has endured much change. In the beginning the conference consisted of the University of North Carolina-Charlotte, the University of Cincinnati, DePaul University, the University of Houston (starting competition in 1996), Marquette University, the University of Memphis, Tulane University, St. Louis University, University of Alabama- Birmingham, and the University of Southern Florida. Mike Slive was appointed as the first commissioner, but left to become the commissioner of the Southeastern Conference in 2002 (19), leaving C-USA to appoint Britton Banowsky as its new commissioner. Additionally, in 2002, the C-USA headquarters moved from Chicago to Irving, Texas (2).

The major realignment of C-USA in 2005 was set in motion by larger conference realignment issues. The Atlantic Coast Conference’s (ACC) desire for football prestige triggered a mass reordering of conferences (23). Specifically, the ACC invited the University of Miami (FL), Virginia Polytechnic and State University, and Boston College to join their conference, thereby depleting the Big East Conference. In order to reestablish its conference, the Big East invited C-USA members the University of Cincinnati, DePaul University, Marquette University, the University of Louisville, and the University of South Florida (11). Additionally, four other institutions relinquished their C-USA memberships in 2005. Texas Christian University left to join the Mountain West Conference, the University of North Carolina-Charlotte and St. Louis University left to join the Atlantic 10 Conference, and the U.S. Military Academy (aka Army) became independent [11). Figure 1 lists the various institutions that have been members of C-USA, the dates of their memberships, and their current conference affiliations.

Crytzer (3) noted the unusual current geographical size of C-USA (over 1,500 miles separate the eastern most and western most schools) is a barrier for many of the member schools, which range in student population from 5,000 to 50,000. Additionally, conference defections over the past 15 years helped fuel speculation that future NCAA conference realignments could render C-USA obsolete.

### Methods

The purpose of this paper was to assess how churning within Conference USA over a 10-year period has affected the conference’s men’s basketball programs in regard to success at the national level and competitive balance within the conference. We employed two tactics each in evaluating winning success nationally and competitive balance.

#### Winning Success

In order to measure winning success, we measured the success of Conference USA teams against outside competition before the departure of teams in the 2004-05 season and after the addition of teams in the 2005-06 season. While the conference mean will always be .500, the non-conference mean could vary. We also measured the number of Conference USA teams that participated in the NCAA post-season tournament in both periods. The latter was a major source of revenue to the conference and ultimately to each team. The value of each appearance in the tournament varied from $94,086 in 2001 to $222,206 in 2010 and has continued to grow in magnitude over time. These values were paid annually for six years. Thus one appearance in 2001 would be worth $564,516 to the conference and one appearance in 2010 would be worth $1,333,236 to the conference over the six-year period. It is, therefore, readily apparent that the more appearances a conference makes in the tournament, the more revenue it receives.

#### Measuring Competitive Balance

There were several methods used in measuring competitive balance. The most appropriate of these methods depended on what the researcher was attempting to specifically measure (9). Methods most appropriate for measuring competitive balance within a given season may be different from those used to measure competitive balance between seasons (10). To measure competitive balance within a given year, we rely on the standard deviation of winning percentages and to measure competitive balance between seasons, we use the Hirfindahl-Hirschman Index (HHI).

##### Standard Deviation of Winning Percentages

Possibly the method most often used to measure competitive balance within a conference in a given season is the standard deviation of winning percentages. Since there will, outside of a tie, always be one winner and one loser for each game, the average winning percentage for the conference will always be .500.

In order to gain insight into competitive balance, we would need to measure the dispersion of winning percentages around this average. To do this we can measure the standard deviation. This statistic measures the average distance that observations lie from the mean of the observations in the data set. The formula for the standard deviation is:

![Formula 1](/files/volume-14/441/formula-1.jpg)

The larger the standard deviation, the greater is the dispersion of winning percentages around the mean, and thus the less competitive balance.

#### Championship Imbalance

While using the standard deviation as a measure of competitive balance provides a good picture of the variation within a given season, it does not indicate whether it is the same teams winning every season, or if there is considerable turnover among the winners, i.e., whether there is between season variation. Therefore, another method economists have used to measure imbalance is the Hirfindahl-Hirschman Index (HHI), which was originally used to measure concentration among firms within an industry ([10). We determine the HHI by counting the number of times a team won a championship during a given period, summing those values and then dividing by the number of years in the period considered.

![Formula 2](/files/volume-14/441/formula-2.jpg)

Using this method, the greater the number of teams that achieve championship status over a specific time period, the greater would be the competitive balance.

### Results

#### Winning Success

Table 3 gives the winning percentages for Conference USA teams against non-conference opponents in the two periods under consideration. For the earlier period the mean winning percentage was .606 and for the latter period it was .577—an approximate 5% differential favoring the earlier period. It should be noted that the highest winning percentage over this total period was .638 (2003-04) and the lowest was .539 (2005-06). The data suggest that Conference USA was more successful against outside competition in the earlier period.

Table 4 reflects the number of Conference USA members participating in the NCAA post-season tourney, the unit value of each appearance and the dollars received in each year from conference participation. The data in Table 4 indicates that in the 2001-05 period the conference received $30,722,250, and in the 2006-10 period the conference receipts were only $21,269,388. These numbers reflect a participation of 39 appearances in the earlier period and 19 in the latter period. Consequently, even though the dollars per unit were considerably higher in the latter period, the conference earned almost $10 million more in the earlier period.

#### Competitive Balance

##### Standard Deviation of Winning Percentages

Tables 5 and 6 display the winning percentage for men’s basketball for the years 2000-01 through 2004-05 and for 2005-06 through 2009-10. Table 7 displays the standard deviations for both time periods.

As shown in Table 7, the mean standard deviation was .208 for 2000-01 through 2004-05, and it was .250 for 2005-06 through 2009-10. As indicated above, the lower the standard deviation the greater the competitive balance. This is a 20.3% difference favoring competitive balance in the earlier period. It should also be pointed out that not only was the mean standard deviation lower for the earlier period, but the lowest standard deviation for the period, .173 (2000-01), was lower than the lowest standard deviation for the later period, .238 (2006-07). Likewise the highest standard deviation for the later period, .261 (2009-10) was higher than the highest standard deviation, .236 (2003-04) in the earlier period. As a matter of fact the standard deviation was lower every year of the earlier period than for the later period.

Why the standard deviation was lower for the earlier period can also be seen by the range of the means in the two periods. As indicated in Table 5 (the earlier period) the range was a high of .725 (Cincinnati) and a low of .266 (East Carolina). This was a range of .459 from top to bottom of the standings. On the other hand, and as indicated Table 6 (the latter period), the means ranged from a high of .948 (Memphis) to a low of .216 (East Carolina). This was a range of .732 from top to bottom. Indeed in this period Memphis had a perfect record of 16-0 in three of the five years investigated, while two teams, East Carolina and SMU, had losing records all five years.

##### Championship Imbalance

Using the data from Table 8 to construct the HHI to measure competitive balance between the two periods we find the results are consistent with the results found when using the standard deviation. Using the regular season standings we find that during the 2000-01 through 2004-05 period (see Table 8), three teams–Cincinnati, Marquette and Louisville–won the championship once each. Multiple teams shared the title for two seasons–2001-02 when Cincinnati and Southern Mississippi tied and 2003-04 when there was a five-team (DePaul, Memphis, Cincinnati, UAB and Charlotte) tie for first. If we give one point for each outright championship, .5 for a two-team tie, and .2 for a five-team tie, we find:

HHI = 1.72 + 12 + 12 + .52 + .22 + .22 + .22 + .22= 2.89 + 1 + 1 + .25 + .04 + .04 + .04 + .04 = 5.3/5 = 1.06

When measuring the HHI over the 2005-06 through 2009-10 period (see Table 8), we find considerably less competitive balance. During this period one team, Memphis, won the regular season championship four times and another team, UTEP, won the championship the other year. Measuring these results we find:

HHI= 42 + 12 = 16 + 1 = 17/5 = 3.4

These calculations indicate less competitive balance during the 2005-06 through 2009-10 period.

### Conclusions

The results of this study offer strong evidence that the churning that occurred in C-USA over the 10-year period 2000-2001 through 2009-2010 had negative effects for men’s basketball in terms of both competitive success at the national level and competitive balance within the conference. Both of the indicators of national success—winning percentage against non-conference opponents and revenue derived from member appearances in the national championship tournament—were better during the earlier period than the latter. In addition both measures of competitive balance within the conference—standard deviation of winning percentages and the HHI—indicate more competitive balance in the earlier period.

It is also important to note that while this study examined the financial ramifications of C-USA’s success, or lack thereof, in the men’s basketball national championship tournament, that revenue stream was but one of several that determine the overall financial well-being of the conference and its members. However, Crytzer (3) has observed that as the financial benefits of the C-USA’s success in men’s basketball from 2003-2005 in particular run out, the conference’s long-term viability may be at risk. Clearly, multiple factors relating to a variety of sport programs will affect whether C-USA is susceptible to additional churning and/or will even survive. However, the findings of this study pertaining to one flagship sport, men’s basketball, indicate the conference faces significant challenges in the near future.

### Applications In Sport

While the results of this study are not to be generalized to other sports programs or other conferences, they do align with the findings of other studies that have examined the effects of conference churning on competitive balance in men’s basketball. While Rhoads (9) found realignment in the Western Athletic and Mountain West conferences had enhanced competitive balance in football, it did not have the same positive effect in men’s basketball. And two studies on the effects of churning in the Big 12 found improved competitive balance in football (14) but diminished competitive balance in men’s basketball (13). Since football is recognized as the primary factor in conference realignment (6), it may be that conference churning commonly results in desirable outcomes for that one sport program while others (i.e., men’s basketball) do not enjoy the same benefits. Given the potential for revenue generation in men’s basketball, and perhaps a few other sport programs aside from football (depending on the institution), the appeal of competitive success on a national level, and the importance of in-conference competitive balance, university and college leaders are well advised to consider likely ramifications for multiple sport programs when considering conference affiliation options.

### Tables

Conference Last Change Description
Atlantic Coast Conference 2005 Boston College joins
Big East Conference 2011 Texas Christian joins
Big Ten Conference 2011 Nebraska joins
Big 12 Conference 2011 Two institutions withdraw
Conference USA 2005 Five institutions join, four withdraw
Mid-American Conference 2007 Temple joins as football-only member
Mountain West Conference 2011 Two institutions withdraw, Boise State joins
Pac-10 Conference 2011 Two institutions join
Southeastern Conference 1990 Two institutions join
Sun Belt Conference 2010 New Orleans withdraws
Western Athletic Conference 2011 Boise State withdraws

#### Table 2
Evolution of C-USA, 1995-2011

Conference Last Change Description
UNC Charlotte 1995-2005 Atlantic 10
Cincinnati 1995-2005 Big East
DePaul 1995-2005 Big East
Houston 1995-Present C-USA
Louisville 1996-Present C-USA
St. Louis 1995-2005 Atlantic 10
Southern Miss 1995-Present C-USA
Tulane 1995-Present C-USA
Alabama, Birmingham 1999-Present C-USA
Southern Florida 1995-2005 Big East
Central Florida 2005-Present C-USA
Texas Christian 1999-2005 Mountain West1
East Carolina 1996-Present C-USA
Army 1997-2005 Independant
Marshall 2005-Present C-USA
Rice 2005-Present C-USA
Southern Methodist 2005-Present C-USA
Tulsa 2005-Present C-USA
Texas, El-Paso 2005-Present C-USA

1. Moving to the Big East in 2011-2012 season

#### Table 3
Conference Winning Percentage in Games Against Non-Conference Opponents

Year Winning Percentage
2000-01 .550
2001-02 .622
2002-03 .607
2003-04 .638
2004-05 .615
5-Year Mean .606
2005-06 .539
2006-07 .590
2007-08 .585
2008-09 .589
2009-10 .583
5-Year Mean .577

#### Table 4
NCAA Tournament Appearances and Related Revenue

Year NCAA Appearances Unit Volume ($) Yearly Value ($) 6 Year Value ($)
2001 5 94,086 470,430 2,822,580
2002 4 100,672 402,688 2,416,128
2003 9 130,697 1,176,273 7,057,638
2004 11 140,964 1,550,604 9,303,624
2005 10 152,038 1,520,380 9,122,280
5-Year Totals 39 618,457 5,120,375 30,722,250
2006 5 163,981 819,905 4,919,430
2007 4 176,864 707,456 4,244,736
2008 5 191,013 955,065 5,730,390
2009 3 206,020 618,060 3,708,360
2010 2 222,206 444,412 2,666,472
5-Year Totals 19 960,084 3,544,898 21,269,388

#### Table 5
Winning Percentage for Men’s Basketball Teams, 2000-01 through 2004-05

Year Cin Char Marq StL Lou DeP SouM Mem USF UAB Hou Tul ECar TCU
2000-01 0.688 0.625 0.563 0.5 0.5 0.25 0.688 0.625 0.563 0.5 0.375 0.125
2001-02 0.875 0.688 0.813 0.563 0.5 0.125 0.25 0.75 0.5 0.375 0.563 0.313 0.313 0.375
2002-03 0.562 0.5 0.875 0.562 0.688 0.5 0.313 0.813 0.438 0.5 0.375 0.5 0.188 0.188
2002-04 0.75 0.75 0.5 0.563 0.563 0.75 0.375 0.75 0.063 0.75 0.188 0.25 0.313 0.438
2004-05 0.75 0.75 0.438 0.375 0.875 0.625 0.25 0.563 0.313 0.625 0.563 0.25 0.25 0.5
Mean 0.725 0.663 0.638 0.513 0.625 0.45 0.375 0.700 0.375 0.55 0.413 0.288 0.266 0.375

#### Table 6
Winning Percentage for Men’s Basketball Teams for 2005-06 through 2009-10

Year Memphis UAB UTEP Hou UCF Tulsa Rice Tulane Marshall SMU So.Miss E.Car.
2005-06 0.929 0.857 0.786 0.643 0.5 0.429 0.429 0.429 0.357 0.286 0.214 0.143
2006-07 1 0.438 0.375 0.625 0.688 0.563 0.5 0.563 0.438 0.188 0.563 0.063
2007-08 1 0.75 0.5 0.688 0.563 0.5 0 0.375 0.5 0.25 0.563 0.313
2008-09 1 0.688 0.625 0.625 0.438 0.75 0.25 0.438 0.438 0.188 0.25 0.313
2009-10 0.813 0.688 0.938 0.438 0.375 0.625 0.063 0.188 0.688 0.438 0.5 0.25
Mean 0.948 0.684 0.645 0.604 0.512 0.573 0.248 0.399 0.484 0.27 0.418 0.216

#### Table 7
Standard Deviation for Winning Percentages

Year SD
2000-01 0.173
2001-02 0.223
2002-03 0.202
2003-04 0.236
2004-05 0.205
5-Year Mean SD 0.208
2005-06 0.253
2006-07 0.238
2007-08 0.256
2008-09 0.243
2009-10 0.261
5-Year Mean SD 0.250

#### Table 8
Regular Season Conference Champions, 2000-01 through 2004-05

Year Champion(s)
2000-01 Cincinnati, Southern Mississippi
2001-02 Cincinnati
2002-03 Marquette
2003-04 DePaul, Memphis, Cincinnati, UAB, Charlotte
2004-05 Louisville
2004-05 Louisville
2005-06 Memphis
2006-07 Memphis
2007-08 Memphis
2008-09 Memphis
2009-10 UTEP

### References

1. Abbott, C. (1990). College athletic conferences and American regions. Journal of American Studies, 24, 220-221.
2. C-USA: Official site of Conference USA. (2011). About Conference USA. Retrieved March 21, 2011 from <http://conferenceusa.cstv.com/ot/about-c-usa.html>
3. Crytzer, J. (2009, August 30). The future of college football and the death of Conference USA 1995-2011 [Web log post]. Retrieved from <http://bleacherreport.com/articles/245204-the-future-of-college-football-and-the-death-of-conference-usa-1995-2011>
4. Depken II, C.A. (2011). Realignment and profitability in Division IA college football. Unpublished paper. Retrieved April 2, 2011 from <http://www.belkcollege.uncc.edu/cdepken/P/confsize.pdf>
5. Depken, C.A., & Wilson, D. (2005). The uncertainty outcome hypothesis in college football. Department of Economics, University of Texas-Arlington.Paper under review.
6. Fort, R., & Quirk, J. (1999). The college football industry. In J. Fizel, E. Gustafson and L. Hadley (Eds.) Sports economics: Current research (pp. 11-26). Westport, CT: Praeger.
7. Grant, R.R., Leadley, J., & Zygmont, Z. (2008). The economics of intercollegiate sports. Mountain View, CA: World Scientific.
8. Groza, M.D. (2010). NCAA conference realignment and college football attendance.Managerial and Decision Economics, 31, 517-529.
9. Humpreys, B. (2002). Alternative measures of competitive balance. Journal of Sports Economics, 3, (2), 133-148.
10. Leeds, M., & von Allmen, P. (2005).The Economics of Sports.Boston: Pearson-Addison Wesley.
11. Nunez, T. (2010, June 6). Conference realignment will have ripple effect on Conference USA. The Times-Picayune. Retrieved from <http://www.nola.com/tulane/index.ssf/2010/06/conference_realignment.html>
12. Paul, R.J., Wachsman, Y., & Weinbach, A. (2011). The role of uncertainty of outcome and scoring in the determination of satisfaction in the NFL. Journal of Sports Economics, 12, 213-221.
13. Perline, M.M., & Stoldt, G.C. (2007a). Competitive Balance and the Big 12. The SMART Journal, 4 (1), 47-58.
14. Perline, M.M., & Stoldt, G.C. (2007b). Competitive balance and conference realignment: The case of Big 12 football. The Sport Journal, 10 (2). <http://www.thesportjournal.org/2007Journal/Vol10-No2/Perline08.asp>.
15. Perline, M.M., & Stoldt, G.C. (2008). Competitive balance in women’s basketball: The Gateway Collegiate Athletic Conference and Missouri Valley Conference merger.Women in Sport and Physical Activity Journal, 17 (2), 42-49.
16. Quirk, J. (2004).College football conferences and competitive balance. Journal of Managerial and Decision Economics, 25, 63-75.
17. Rein, I., Kotler, P., & Shields, B. (2006). The elusive fan.New York: McGraw-Hill.
18. Rhoads, T.A. (2004). Competitive balance and conference realignment in the NCAA. Paper presented at the 74th Annual Meeting of Southern Economic Association, New Orleans, LA.
19. SECSports.com (2011). About the SEC. Retrieved March 21, 2011 from http://www.secdigitalnetwork.com/SECSports/Home.aspx
20. Staurowsky, E.J., & Abney, R. (2011). Intercollegiate athletics. In P.M. Pedersen, J.B. Parks, J. Quarterman, & L. Thibault (Eds.) Contemporary sport management (4th ed., pp. 142-163). Champaign, IL: Human Kinetics.
21. The State of Conference Realignment. (ND). The national championship issue: Perspectives on college football. [Web log post]. Retrieved March 22, 2011 from <http://thenationalchampionshipissue.blogspot.com/2008/01/state-of-conference-realignment.html
22. Where the money goes. (2010). Champion. Retrieved April 2, 2011 from http://www.ncaachampionmagazine.org/Exclusives/WhereTheMoneyGoes.pdf>
23. Wieberg, S. (2005, June 29). Conference shakeup continues as schools seek right fit. USA Today. Retrieved March 22, 2011 from <http://www.usatoday.com/sports/college/2005-06-28-conference-hopscotch_x.htm>

### Corresponding Author

G. Clayton Stoldt
Wichita State University
Department of Sport Management
1845 Fairmount
Wichita, KS 67260-0127
clay.stoldt@wichita.edu
P: (316) 978-5441

Martin Perline is a professor and Bloomfield Foundation fellow in the Department of Economics at Wichita State University. G. Clayton Stoldt is chair and professor in the Department of Sport Management at Wichita State University. Mark Vermillion is an assistant professor in the Department of Sport Management at Wichita State University.

2015-11-08T07:40:19-06:00January 3rd, 2012|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on The Effects of Conference Realignment on National Success and Competitive Balance: The Case of Conference USA Men’s Basketball
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Psychological and Physiological Effects of Aquatic Exercise Program Among the Elderly

Matsouka Ourania, Yfantidou Georgia, Trigonis Ioannis, Michailidou Marina

### Abstract

The purpose of this study was to investigate the effectiveness of a 3-week daily physical activity program in outdoor spring hot water on joint mobility and mood state in 31 healthy elderly people aged between 60 and 82. The variables comprising mood state were positive engagement revitalization, tranquillity and physical exhaustion whereas joint mobility focused on shoulder flexibility. Subjects were allocated to one exercise group (n= 20) and one control group (n=11). The exercise group participated in a 45-minute-per-day aquatic exercise program in hot water for 20 consecutive days whereas the control group didn’t participate in any kind of organized exercise. Subjects were pre- and post-tested for the variables of mood state and shoulder flexibility. The results indicate that the elderly people who participated in the outdoor aquatic exercise program had significant improvements in positive engagement (z=2.4, p<.05), revitalization (z=2.8, p<.05), tranquillity (z=2.8, p<.05), physical exhaustion (z=2.7, p<.05), and shoulder flexibility (t=9.25, p<.05). No significant changes in these variables were observed in the control group. The results indicate that an aquatic exercise program is an alternative training method for improving psychological state and functional fitness performance in healthy elderly people.

**Key Words:** elderly, aquatic training program, mood state, joint mobility.

### Introduction

Evidence shows that increase of age is associated with the decline of many motor functions, (1,18,8,17) and the subsequent disenabling of performance of basic daily requirements. In addition, as individuals progress beyond 60 years of age, there are also tendencies for increased prevalence of mood disturbance; i.e., increased negative effect and decreased positive effect; (6). Past research on activity, aging and psychological well-being has concluded that exercise has a positive effect on psychological well-being (12). Exercise prescribed for the elderly differs from that of younger individuals in the method in which it is applied. Since an elderly person is more fragile and has to overcome more physical and medical limitations in comparison to younger individuals, training methods should not include high impact activities, and possibly a more gradual training progression (2).

Exercising in water has become widely prominent, and it has been reported that water exercise, especially in hot water, is therapeutically beneficial for elderly individuals (3).Water exercise is also a viable form of conditioning for those who are suffering orthopaedic problems (20). Training in water provides buoyancy and a required resistance for training, resulting in a training regimen that provides high levels of energy expenditure with relatively low impact on the joint extremities (21). Furthermore, this method of training is more motivating for overweight individuals because their bodies are not exposed to other participants (9). The authors of the present study hypothesized that participation of the elderly in a daily physical activity program in hot water, would improve their physiological and psychological status. Specifically, the purpose of this study was to investigate the effect of a daily physical activity program in an outdoor hot water spring, on joint mobility and mood state in older men and women.

### Methods

#### Subjects

Subjects in this study were 31 independently living elderly volunteers (6 males, 25 females) ranging in age from 60 to 82 years old (M = 71, SD = 5), with body weights between 63kg and 86kg (M=75.7, SD=5.5), and heights between 154cm and 163cm (M=156, SD=3). Subjects were recruited from a resort community in Edipsos, Greece during the summer of 2009. None of the elderly had been involved in any physical activity for at least 6 months before the exercise program began. They were assigned randomly into one experimental group (n=20) and one control group (n=11). Participants were graduates of elementary education (55.1%) and the majority of them were retired (71.5%). Their previous profession was 31.3% civil servants, and 42.3% free professionals. The majority of them (79.4%) were married and living with their spouses (65.4%). The greater part of the participants (65.5%) had a moderate daily mobility level according to the AAHPERD exercise consent form for adults (16). The subjects also had similar health status. Specifically, the participants of this study did not suffer from serious cardiovascular problems (coronary illness, infarction) respiratory or neurological diseases or serious orthopaedic problems. The more prominent health problems that they faced were of orthopaedic nature (34.4%) as well as high blood pressure (31.5%), which did not constitute obstacles to their participation in the research. Therefore, no subject was excluded for medical reasons. Subjects who missed more than four exercise sessions were excluded from the analysis.

#### Procedures

The experimental procedure was 20 days in duration, with 1 day of pretesting and 1 day of post-testing. The pre- and post-exercise assessments were performed by the same person for both groups. In an effort to ensure maximum compliance with the program, the same instructor conducted the intervention program in all groups. The intervention program took place in an outdoor swimming pool consisting of 100 % spring water at 34 ºC located in the Revitalization Club. The 12-item Exercise-Induced Feeling Inventory (7) was employed to assess the responses of positive engagement (enthusiastic, happy and upbeat), revitalization (refreshed, energetic and revived), tranquility (calm, relaxed and peaceful), and physical exhaustion (fatigued, tired and worn-out) that arise as a result of exercise participation. On a 5-point scale, subjects were asked to indicate how strongly they had experienced each feeling state immediately after one hour of exercise. The scale ranged from 0 (do not feel) to 4 (feel very strongly). Internal consistency exceeded .70 for each subscale (11). Flexibility measurement focusing on the shoulder was based on the Senior Fitness Test. This test was done in the standing position. The subject placed one hand behind the head and back over the shoulder, and reached as far as possible down the middle of the back, with palm were touching the body and the fingers directed downwards. They placed the other arm behind their back, palm facing outward and fingers upward and reached up as far as possible attempting to touch or overlap the middle fingers of both hands. An assistant directed the subjects so that their fingers were aligned, and measured the distance between the tips of the middle fingers. If the fingertips touched then the score was zero. If they did not touch, the distance between the fingers tips was measured (a negative score). A positive score was measured by how far the fingers overlapped. Subjects practiced two times, and tested two times. The best score to the nearest centimeter was recorded. (18).

##### Preprogram procedures

Prior to enrollment in the training program, all subjects who wanted to participate in the study were required to provide a signed letter of clearance from their personal general physician regarding their participation in the program. At the onset of the program, individuals were informed that they would be participating in a 45-minute-per-day aquatic exercise program for 20 consecutive days, and were given a brief demonstration of the program content. Information forms were then distributed to all individuals volunteering to participate in the investigation.

Once informed consent forms were read and signed by all subjects, a preprogram questionnaire packet was distributed. During the first day, both experimental and control groups completed the Revised Physical Activity Readiness Questionnaire (22) and a short demographic questionnaire assessing age, height, weight, and mobility level (16). Finally, before the training program began, each participant completed the Exercise-Induced Feeling Inventory (EFI), and participated in shoulder flexibility measurements.

##### Intervention Program

The experimental group participated in a 45-minute aquatic exercise program for 20 consecutive days. The control group was not involved in the exercise program but participated in spring water bath therapy. The exercise program was based on the Long Term Physical Activity Workshop (4), and consisted of 15 minutes of warm-up and callisthenic exercises for the improvement of flexibility, 10 minutes of resistance exercise, 10 minutes of endurance-type exercise (walking and dancing), and 10 minutes of cool-down exercise and leisure activities for the reinforcement of self-esteem and self confidence. The exercise intensity recommended by the American Heart Association varied from 50% to 75% of the subject’s maximum heart rate, as determined by a pilot study. However, no heart rates were recorded during the study. Instead subjects were taught to monitor their pulse rate according to perceived exertion (4). During exercise, the Borg Scale (6 – 20) was used to monitor perceived exertion relative to exercise intensity. Self-monitoring how hard their body was working helped them adjust the intensity of the activity by speeding up or slowing down their movements. The elderly exercisers were working in the Moderate (12-14) exertion range. Also, subjects were able to speak in their normal voices and tones during the exercise, in order to maintain a consistent heart rate and exercise intensity.

##### Post-program Procedures

At the conclusion of the aquatic exercise program, on the 21st day, each participant once again completed the EFI and shoulder flexibility measurement.

##### Stastistical Analysis

All data analyses were performed using SPSS, version 14.0. The normality of the distribution and the equality of variances for all variables were checked with the Kolmogorov-Smirnov test for each group. Bartlett-Box and Cochran’s C tests were used to identify differences among groups of the selected items. From the pretest, there were no differences beyond the .05 level of significance between any of the two groups. Wilcoxon test for two related samples was used to compare differences of means scores between the initial and final measurements of both the experimental and control groups in the mood state variables. Comparisons of means scores between the initial and final measurements of two groups in the shoulder flexibility parameter were performed using a paired t-test analysis.

### Results

The results revealed significant differences between pre- and post- measures for the experimental group regarding the four subscales of mood state (Table 1). In contrast, there were no changes in mood state for the control group at pre- and post- measures on any of the 4 subscales. As shown in table 1, after a 45-minute-per-day aquatic exercise program for 20 consecutive days, there was a marked increase in reported variables of mood state for the experimental group while the control group showed no changes during the same period of time.

The aquatic exercise program induced significant improvement in shoulder flexibility. In particular, the t-test for paired groups analysis revealed that shoulder flexibility had significantly improved in the experimental group (t=9.25, p<.05), while no significant difference was observed in the control group (t=0.89, p>.05). Scores for the pre- and post-tests for both groups on the selected variable are shown in figure 2.

### Discussion

The results reveal that a 45-minute-per-day aquatic exercise program for 20 consecutive days produced significant improvements in mood state as well as in shoulder flexibility of sedentary elderly people. The lack of improvement for the subjects of the control group gives additional support to the idea that the program applied was responsible for the improvement of the experimental group. It seems that even a 20-day aquatic exercise program is capable of producing significant changes in basic physiological and psychological variables similar to the ones in the present study. Significant improvements in the elderly in a number of physical abilities after following a training program have been reported by researchers. Takeshima et al., (21), reported significant improvements in 45 elderly women (60-75 yrs. of age) who had participated in a 12-wk supervised water exercise program, 70 minutes per day, 3 days per week, in cardiovascular fitness, muscle strength and power, flexibility, agility, and subcutaneous fat. Additionally, the exercising group demonstrated an improvement in pulmonary function and blood lipids. In 2006, Tsourlou et al. (23), reported significant improvements in a number of physical abilities (maximal isometric torque of knee extensors and knee flexors, grip strength and dynamic strength during chest press, knee extension, lat pull down, and leg press, jumping performance functional mobility, and trunk flexion) in 22 healthy women over 60 years of age, after their participation in a 24-week aquatic training program.

Furthermore, these results are consistent with the conclusions of previous studies reporting changes in elements of psychological well-being in terms of physical activity. These changes are referred to as enhanced perceptions of mastery (11), improved life satisfaction (14), and mood (15,5,10) as well as reduced negative affect of psychological state. Moreover, similar results were found in a 12-week investigation by Whitlatch et al. (24). In addition, Moore and Blumental’s narrative review (13) with older adults, focusing on specific elements of mood, supported the positive role of aerobic exercise in reducing negative affect.

### Conclusions

The results of the present study indicate that water-based exercise elicits significant improvement in psychological well-being and joint mobility in the elderly. Specifically, a 45-minute–per-day aquatic exercise program in hot water for 20 consecutive days can result in considerably better positive engagement, revitalization, and tranquillity, as well as joint mobility focused on shoulder flexibility, in older men and women. Moreover, it may provide additional benefits by reducing negative mood in terms of physical exhaustion. Therefore, water-based exercise is one of the most potent alternative training methods for improving basic elements of their psychological and physiological health.

### Applications In Sport

Overall, the findings of the present investigation should be adopted by public and private institutes that offer water-based exercise programs for older men and women. Elderly people’s participation in a 45-minute aquatic exercise regimen for 20 consecutive days with various enjoyable activities results in significant improvements to general shoulder range of motion, facilitating their performance at common activities of daily living and allowing them to maintain independent lifestyles. Besides, their participation in this kind of program makes them familiar and sociable persons. This suggests that water-based exercise may be a valuable short- term strategy for the self regulation of mood in older people. Finally, practical exercise prescriptions from instructors must take into account the special interests and needs of the elderly, inducing happiness, tranquillity, pleasant tiredness and, at the same time, initiating progressive improvement in general physical and psychological health.

### Acknowledgments

We acknowledge the participants for their voluntary involvement in this study.

### Tables

#### Table 1
Means, Standard deviations and Wilcoxon test for mood state variables in the pretest and post-test measurements for elderly people in experimental and control groups.

Variables Experimental Group Control Group
pre-test post-test pre-test post-test
M SD M SD z sig M SD M SD z sig
Positive Engagement 1.5 0.5 3.6 0.2 2.4 .01 1.2 0.3 1.5 0.4 0.0 1.0
Tranquility 2 0.6 2.9 0.8 2.8 .00 1.5 0.4 1.5 0.2 0.9 .30
Physical Exhaustion 1 0.3 0.5 0.2 2.7 .00 0.5 0.3 0.6 0.3 0.0 1.0

### Figures

#### Figure 2
Pre-test and Post-test shoulder flexibility in older men and women in both experimental and control groups.

![Figure 2](/files/volume-14/439/figure-2.jpg)

### References

1. Agre, J.C., Pierce, L.E., Raad, D.M., McAdam, M., & Smith, E.L. (1988). “Light Resistance and Stretching Exercise in Elderly Women: Effect upon strength” Archives of Physical Medicine and Rehabiliation, 69, 273-276.
2. American College of Sports Medicine. (1998). The recommended quantity and quality of exercise for developing and maintaining cardio respiratory and muscular fitness,and flexibility in healthy adults. Medicine and Science in Sports and Exercise, 30, 975-991.
3. Douglas, J. C. (1999). Exercise in the Heat. I. Fundamentals of Thermal Physiology, Performance Implications, and Dehydration. Journal of Athletic Training, 34, 246-252.
4. Ecclestone, N.C., Tubor-Locke, D.A., Meyers Lazowski, A. (1995). Programming and evaluation insights into physical activity for special older populations. International Conference on Aging and Physical Activity, “Promoting Vitality and Wellness in Later Years”, Colorado Springs, Colorado, October 1995. Journal of Aging and Physical Activity 4, (3),424-25.
5. Emergy, C.F., & Blumental, J.A. (1990) Perceived change among participants in an exercise program for older adults. The Gerodolist, 30, 517-521.
6. Fillingim, R.B., & Blumental, J.A. (1993) Psychological effects of exercise among the elderly. In P. Seraganian (Ed.), Exercise physiology: the influence of physical exercise on psychological processes, New York: Wiley, pp. 237-254.
7. Gauvin, L., & Rejeski, J.W. (1993). The exercise-induce Feeling Inventory: development and initial validation: Journal of Sport and Exercise Psychology, 15, 403-423.
8. Judge, J.O., Underwood, M., & Gennosa, T. (1993). “Exercise to improve Gait Velocity in Older Persons” Archives of Physical Medicine and Rehabilitation, 74, 400-406
9. Lepore, M., Gayle, G.W., & Stevens, S.F. Adapted Aquatics Programming: Professional Guide. Champaign, IL: Human Kinetics, 1998, pp. 12-16.
10. Matsouka, O., Kabitsis, C., Harahousou, Y., & Trigonis, I. (2005). Mood alterations following an indoor and outdoor exercise program in healthy elderly women. Perceptual and Motor Skills, 100, 707-715.
11. McAuley, E., & Courneya, S.K. (1994). The Subjective Exercise Experiences Scale: development and initial validation. Journal of Sport & Exercise Psychology, 16, 163-177.
12. McAuley, E., & Rudolph D. (1995). Physical Activity, Aging, and Psychological Well-Being. Journal of Aging and Physical Activity, 3, 67–96.
13. Moore, K.A., & Blumental, J.A. (1998). Exercise training as an alternative treatment for depression among older adults. Alternative Therapies in Health and Medicine, 4, 48-56.
14. Morgan, K., Dollosso, H., Bassey, E.J., Ebrahim , S., & Arie, T.H.F. (1991) Customary Physical activity, psychological well-being and successful ageing. Ageing and Society, 11, 399-415.
15. Moses, J., Steptoe, A. Mathews, A., & Edwards, S. (1989) The effects of exercise training on mental well-being in the normal population: a controlled trial. Journal of Psychosomatic Research, 33, 47-61.
16. Osness, W.H., Adrian, M., Clark, B., Hoeger, W., Raab, D., & Wisnell, R. (1990). Functional fitness assessment for adults over 60 years (a field based assessment). Reston, VA: American Alliance for Health Physical Education Recreation and Dance
17. Parkatti, T., Rantanen, T., & Hartkka, K. (1994). The Effect of an Intensive Physical Activity Training Program on Functional Ability Among Frail Elderly People. Physical Activity And Health In The Elderly, Scotland.
18. Jones C.J., & Rikli R.E. (2002). Measuring functional fitness of older adults, The Journal on Active Aging, pp. 24–30.
19. Rikli, R.E., & Edwards, D.J. (1991). “Effects of a Tree-Year Exercise Program on Motor Function and Cognitive Processing in Older Women” Research Quarterly for Exercise and Sport, 62, 61-67.
20. Robert, J. J., Jones, L., & Bobo, M. (1996). The physiologic response of exercising in the water and on land with and without the X1000 Walk’N Tone Exercise Belt. Research Quarterly for Exercise & Sport, 67, 310-315.
21. Takeshima, N., Rogers, M.E., Watanabe, E., Brechue, W.F., Okada, A., Yamada, T., Islam, M.M., & Hayano., J. (2002). Water-based exercise improves health-related aspects of fitness in older women. Medicine and Science in Sports and Exercise, 33, 544-551.
22. Thomas, S., Reading, J., & Shephard, R.J. (1992). Revision of the Physical Activity Readiness Questionnaire (PAR-Q). Canadian Journal of Sport Science, 17, 338-345.
23. Tsourlou, T., Benik, A., Dipla, K., Zafeiridis, A., & Kellis, S. (2006). The effects of a twenty-four-week aquatic training program on muscular strength performance in healthy elderly women. The Journal of Strength & Conditioning Research, 20,811-8.
24. Whitlactch, S., & Adema, R. (1996). Activities, Adaptation and Aging, 75-85.

### Corresponding Author

Matsouka Ourania
Lecturer
Department of Physical Education & Sport Sciences
University of Thrace
Komotini, 69100
Greece
<oumatsou@phyed.duth.gr>

2013-11-25T14:48:57-06:00January 2nd, 2012|Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on Psychological and Physiological Effects of Aquatic Exercise Program Among the Elderly
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Body Image Disturbances in NCAA Division I and III Female Athletes

Kato, K., Jevas, S., and Culpepper, D.

### Abstract

The purpose of this study was to examine and compare eating characteristics and body image disturbances in female NCAA Division I and III athletes in the mainstream sports of basketball, softball, track/cross country, volleyball, soccer, tennis, swimming/diving, and ice hockey. Female collegiate athletes (N = 118) from Division I and III universities completed the EAT-26 and MBSRQ. Personal demographics and anthropometric data including height, weight, BMI and Body Fat estimates were also assessed. The study found that 49.2% (Division I) and 40.4% (Division III) of female athletes were in the subclinical eating disorder range. Results assessing body satisfaction, reported that 24.2% of Division I female athletes and 30.7 % of Division III female athletes were either very dissatisfied or mostly dissatisfied with their overall appearance. Results also showed that Division I female athletes were less satisfied with their appearance evaluation (body areas satisfaction, and lower torso). Division III female athletes reported higher levels of bulimic behaviors and weight preoccupation. The results indicate that athletes in refereed female sports are at risk for eating disorders, and that body image risk factors vary between NCAA competition divisions. This research provides sport professionals with a better understanding of risk factors influencing the prevalence of eating disorders between female athletes’ divisional competition levels.

**Key words:** body dissatisfaction, eating disorders, NCAA division, collegiate female athletes, eating disorder risk factors

### Introduction

Eating disorders are among the four leading causes of disease that may lead to disability or death (2). Eating disorders have the highest mortality rate of any mental health illness (41). Approximately nine million Americans suffer from an eating disorder with a lifetime prevalence rate of 0.9% – 4.5% and approximately 10% of college women suffer from a clinical or near clinical eating disorder (19,22).

Body image refers to the self-perception and attitudes an individual holds with respect to his or her body and physical appearance. Body image is a complex synthesis of psychophysical elements that are perpetual, emotional, cognitive, and kinesthetic. Cash and Fleming (10) defined body image as “one’s perceptions and attitudes in relation to one’s own physical characteristics” (p. 455). Body dissatisfaction focuses on body build and is often operationalized as the difference between ideal and current self selected figures (7).

Body dissatisfaction is a significant source of distress for many females. Gender is reported to be a convincing risk factor for disordered eating since females are 10 times more likely to develop an eating disorder compared to males (14). Research shows that the size of the “ideal” woman is far smaller than the size of the average woman (25). “The overwhelming evidence of female gender as a risk factor for the development of an eating disorder highlights the importance of determining the factors that put women at risk, particularly the sociocultural context in which these disorders develop” (31, p. 766).

Risk factors that accompany eating disorders are multi-factorial in nature. Research has revealed that sociocultural, developmental, personality, athletic, trauma, familial, and biological factors are critical identifiable areas that house potential eating disorder risk factors (31). Within these specific areas, body image dissatisfaction and low self-esteem are two situational aspects typically associated with individuals who are at risk for developing an eating disorder. In an early study on body dissatisfaction (5), 23% of the women expressed dissatisfaction with various parts of their body. The particular areas problematic for women were the abdomen, hips, thighs, and overall weight. When the study was replicated in the mid-1980s (11), the percentage of females dissatisfied with their body increased to 38%, with the same general body areas being defined by the participants. These same general body areas were also identified in a more recent study (16) in 56% of women.

Considerable scientific attention has been directed toward the potential role that sport involvement play in an athletes’ development of attitudes and behaviors about disordered eating. Female athletes experience a higher rate of eating disorders than non-athletes (4,24,43). Female athletes have an eating disorder prevalence of 15% to 62% compared to 0.5% to 3% in late adolescent and young adult female non-athletes (21). Researchers (33) assessed disordered eating in female collegiate athletes (N = 204) from three NCAA universities. The responses to the Questionnaire for Eating Disorder Diagnoses (Q-EDD) found 72.5% (n = 148) of the female athletes were asymptomatic, 25.5% (n = 52) symptomatic, and 2.0% (n = 4) eating disorder (29). Compared to recent research (8,39), this research study found a higher percentage of female athletes who were symptomatic. Athlete’s prevalence rate is an important factor, but understanding variables associated with increasing or decreasing risk factors for disordered eating is significant etiological information that should be evaluated (32).

Athletic factors promoting eating disorder development were first identified through research that began in the 1980s, which found particular sports induced higher rates of disordered eating behaviors (1,17). Even though physical activity may develop self-esteem and encourage physical and emotional well-being, there is verification that female athletes are at greater risk for developing disordered eating than their peers who are non-athletes (6). Female athletes encounter the same sociocultural pressures that of non – athletes, however the increased demand of sport – related pressures may independently or dependently increase their risk of eating disordered attitudes and behaviors (40). Coaches, sponsors, and families may all play a role in influencing an athlete’s weight and shape. Negative comments from those that surround and evaluate the athlete may trigger the onset of abnormal eating behaviors leading to an eating disorder (12,28).

The type of sport may also play a role in predisposing an individual to eating disorders based on struggles with body performance satisfaction. Specific sports where performance is judged on body leanness, shape and movement such as ballet, gymnastics, figure skating, diving, and cheerleading have a higher incidence of eating disorders (1,42,47). Shape judged sports such as gymnastics, diving, cheerleading, and dance place more importance on the individual’s body appearance, which may lead to body shape discontent among competitors (47). Researchers also report that 15% to 65% of women in “thin build” sports such as gymnastics or ballet have pathogenic eating patterns known to influence or manipulate the history and development of the eating disorder (27,44). Participation in competitive “thin build” sports in conjunction with personality traits associated with disordered eating could put these individuals at an even greater risk for developing an eating disorder (15, 44). The personality trait of many perfectionist increase disordered eating behaviors for female athletes (20). Researchers (26) compared athletes and non-athletes and reported perfectionism was the only factor that significantly distinguished the groups. In addition, Wilmore (46) reported that athletes high in perfectionism had an increased drive for thinness than athletes low in perfectionism. Refereed sports such as basketball place a stronger emphasis on training and do not rely as much on body appearance; therefore athletes participating in these sports may be less likely to be associated with disordered eating patterns (47).

Most research to date focuses on Division I female athlete’s prevalence rates, while female athletes regardless of NCAA division, experience similar sport specific pressures associated with body image disturbances. Limited research has compared prevalence between NCAA divisions, eating attitudes, and body image disturbances in female athletes. Research has reported that the prevalence of disordered eating, unhealthy dieting, and distorted body image in the athletic population ranges from 12% to 57% (30). Elite female athletes who suffer from eating disorders put themselves at greater risk for serious illnesses and/or death (38). Research has shown that more than one-third of female Division I NCAA athletes report attitudes and symptoms placing them at risk for an eating disorder (2). The National Collegiate Athletic Association study that surveyed student athletes from 11 Division I schools (N = 1,445) reported 1.1% of the female athletes met DSM-IV criteria for bulimia nervosa while 9.2% of female athletes had clinically significant symptoms of bulimia nervosa. This study also reported 0% female athletes met the DSM-IV criteria for anorexia nervosa while 2.85% of the female athletes had clinically significant symptoms of anorexia nervosa (24). Researchers believed the results suggest that Division I female athletes are at significant risk for the progression of eating disorder thoughts and behaviors. The study also stressed the need for future research to examine non-elite Division I, II and III schools since eating disorder risk factors may be higher among lower tier schools. Comparing divisional levels of competition in NCAA athletics could be an important aspect to understanding risk factors involved in the developmental process of an eating disorder.

The purpose of this study was to examine and compare eating characteristics and body image disturbances in female NCAA Division I and III athletes in mainstream sports of basketball, softball, track/cross country, volleyball, soccer, tennis, swimming/diving, and ice hockey. This study also examined female body part dissatisfaction and eating attitudes utilizing the Multidimensional Body Self-Relations Questionnaire (MBSRQ) and Eating Attitudes Test (EAT-26). These findings may assist coaches, strength and conditioning coaches, and athletic trainers in understanding disordered eating and body image disturbances across various female sports in different competition divisions.

### Methods

#### Participants

Participants (N = 118) included Division I (n = 41) and Division III (n = 87) female athletes from National Collegiate Athletic Association (NCAA) member institutes of the following sports: basketball, softball, track/cross country, volleyball, soccer, tennis, swimming/diving, and ice hockey. The convenient sample participants were voluntary, anonymous, and in accordance with university and federal guidelines for human subjects.

#### Instruments

Each athlete completed questionnaires assessing participant demographics and athletic involvement (sport, division). Eating behavior patterns were assessed utilizing the Eating Attitudes Test (EAT-26) and attitudes concerning body image were assessed with the Multidimensional Body-Self Relations Questionnaire (MBSRQ). Anthropometric measurements (height and weight) and body fat measurements were taken on each athlete. (Omron Fat Loss Monitor, Model HBF-306C). The Fat Loss Monitor (Omron Fat Loss Monitor, Model HBF-306C) displays the estimated value of body fat percentage by bioelectrical impedance method and indicates the Body Mass Index (BMI). The bioelectrical impedance, skinfold, and hydrostatic weighing methods have all been shown to be reliable measures of body composition (r = .957 – .987) (23).

##### Eating Attitudes Test (EAT-26)

Eating Attitudes Test (EAT-26) was used to differentiate participants with anorexia nervosa, bulimia nervosa, binge-eating, and those without disordered eating characteristics. It is a 26-item measurement consisting of three subscales: 1) dieting, 2) bulimia and food perception, and 3) oral control. Scoring for this instrument was a Likert scale of six possible answers (always, usually, often, sometimes, rarely, never). Scores ranged from zero to three for each question and a total score greater than 20 indicates excessive body image concern that may identify an eating disorder (Garner et al., 1982; Williamson et al., 1987). EAT-26 has been proven to be a reliable measurement (r = .88) (17). The total score of the EAT-26 and the Drive for Thinness scale of the Eating Disorder Inventory (EDI) have reports of a 90% agreement (37).

##### Multidimensional Body-Self Relations Questionnaire

The Multidimensional Body-Self Relations Questionnaire: The Multidimensional Body-Self Relations Questionnaire (MBSRQ) is a 69 item self-report inventory for the assessment of self-attitudinal aspects of the body image construct. The MBSRQ measures satisfaction and orientation with body appearance, fitness, and health. In addition to seven subscales (Appearance Evaluation and Orientation, Fitness Evaluation and Orientation, Health Evaluation and Orientation, and Illness Orientation), the MBSRQ has three special multi-item subscales: (1) The Body Areas Satisfaction Scale (BASS) approaches body image evaluation as dissatisfaction-satisfaction with body areas and attributes; 2) The Overweight Preoccupation Scale assesses fat anxiety, weight vigilance, dieting, and eating restraint; and 3) The Self-Classified Weight Scale assesses self-appraisals of weight from “very underweight” to “very overweight.” Internal consistency for MBSRQ subscales range from .74 – .91. This questionnaire has been studied and used extensively in the college population. Internal consistency for the subscales of the MBSRQ ranged from .67 to .85 for males and .71 to .86 for females (9).

### Results

#### Descriptive statistics

Participants in the study included 118 female athletes from NCAA Division I (34.7%) and Division III (73.7%) universities. Participants reported their ethnicity as 80.5% White (n =95), 16.1% Black (n =19), .02% Hispanic (n =2), .01% Asian (n =1), and .01% as other (n = 1). The female athletes had a mean age of 19.81 years + 1.29 and a mean body fat percentage of 21.17% + 5.07 (Table 1). There was no significant difference between the divisions in regards to body fat percentage F (1,117) = .727, p = .395.

#### Test for Significance

A multiple analysis of variance (MANOVA) was conducted to determine the effect of NCAA Divisional Status (I or III) on eating characteristics and body image (Table 2). Significant differences were found between Division I and III, Wilks’s Lambda = .664, F(17, 114), p<.0001.

##### Disordered Eating Behaviors

Base frequency scores indicated that 49.2% of Division I female athletes and 40.4% of Division III female athletes scored a 20 or higher on the EAT-26. A follow – up ANOVA reported no significant differences between 20 or higher EAT-26 scores and NCAA Division, F (1, 117) = 1.732, p = .190. A significant difference was found between divisions on the bulimia subscale of the EAT-26, F (1, 117) = 9.107, p = 003. No significant differences were found between division for the EAT-26 dieting subscale, F (1, 117) = .125, p = .724 and oral control subscale F (1, 117) = 2.123, p = .148.

##### Body Disturbance

The results of the MANOVA indicated a significant difference between divisions on the MBSRQ, F(17,114 ) = 3.391, p = .000. The results of the MBSRQ, which assessed body satisfaction, found that 24.2 % of Division I female athletes and 30.7 % of Division III female athletes were either very dissatisfied or mostly dissatisfied with their overall appearance. In addition, a difference was found between Division I and III athletes for appearance evaluation, F (1, 3) = 10.525, p = .001, body areas satisfaction F (1, 3) = 8.36, p = .004, lower torso F (1, 3) = 5.975, p = .016, and overweight preoccupation F (1, 3) = 17.895, p = .000. Division I female athletes were less satisfied with their appearance evaluation, body areas satisfaction, and lower torso than Division III female athletes. Division III female athletes were more weight preoccupied than Division I female athletes.

### Discussion

The main purpose of this study was to examine and compare the eating attitudes and body image satisfaction in female NCAA Division I and III athletes in mainstream sports of basketball, softball, track/cross country, volleyball, soccer, tennis, swimming/diving, and ice hockey. Limited research is available comparing eating disturbances between NCAA divisions so the information acquired may help explain the prevalence of body image disturbances and eating disorder among college female athletes at different levels of competition.

The results of this study indicated that 49.2% (Division I) and 40.4% (Division III) of the female athletes scored 20 or higher on the EAT-26, putting them in a subclinical eating disorder range (18). Comparative research studies using the EAT-26 reported percent subclinical populations of females athletes to be 15.2%, N = 425 (3); 5.8%, N = 190 (13); and 10.2%, N = 59 (36). The current research study did not find a significant difference between subclinical population scores and division, however both Division I and Division III female athletes had a considerably higher subclinical eating disorder female athletic population compared to these previous studies. This finding may be an important implication because the desire to be thin does not always result in clinically diagnosed signs and symptoms of anorexia or bulimia. If left undetected, subclinical eating disorders may result in dysfunctional social interaction, decreased physical performance reduced physical health, and an increase in the propensity for athletic injury.

Between divisions, a significant difference was found on the bulimia subscale of the EAT-26. Division III female athletes struggled more with bulimic behaviors compared to the Division I female athletes. This finding agrees with previous research suggesting that disturbed eating behavior may be higher among lower tiered athletes (35). Bulimic behaviors may be viewed as more destructive to athletic performance so the elite competitive athletes (Division I) may be deterred from participating in such behaviors. Bulimic behaviors may also require a greater level of secrecy, so elite competitive female athletes competing may avoid such behaviors due to increased time commitment, travel requirements, and contact they experience with their coaches and athletic trainers.

It has been reported that female athletes participating in judged sports such as gymnastics, cheerleading, and dance are more prone to eating disorders compared to those who participate in referred sports such as basketball, swimming, and softball (26,34,47). The assessment of body satisfaction through the MBSRQ found that 24.2 % of Division I female athletes and 30.7 % of Division III female athletes were either very dissatisfied or mostly dissatisfied with their overall appearance. We believe that our findings warrant further investigation into the relationship of female athlete’s body dissatisfaction and those participating in referred sports.

A significant difference was also reported on the MBSRQ subscales between Division I and III athletes for appearance evaluation, F (1, 3) = 10.525, p = .001, body areas satisfaction F (1, 3) = 8.36, p = .004, lower torso F (1, 3) = 5.975, p = .016, and overweight preoccupation F (1, 3) = 17.895, p = .000. Division I female athletes were less satisfied with their appearance evaluation, body areas satisfaction, and lower torso than Division III female athletes. Division III female athletes were more weight preoccupied than Division I female athletes. A performance-related drive for thinness through appearance evaluation, body areas satisfaction and lower torso may have a greater impact on female athletes that compete in higher level divisions such as Division I. Being weight preoccupied may not be as closely associated with physical performance measures as compared to general body dissatisfaction.

Even though this was a well-designed study and used a diverse sample of female athletes, it is not without limitations. The participant sample was limited in racial/ethnic minorities, therefore future research should examine female athletic samples with greater racial/ethnic diversity. This research also compared Division I female athletes to Division III female athletes. Increasing the number of institutes and divisions would greatly benefit the findings of this study. Lastly, although a diverse group of female athletic teams was represented in this study, equal number of female athletes from each team was not available due to the sports each institution offered, scholarships, and general participation. For example, ice hockey could only be evaluated at the Division III level. It is possible that the results would have varied if there were equal participant representation. Future research should examine a greater number of institutions at varied divisions to increase participant representations among each sport.

### Conclusion

Our results indicate that refereed female sports are at risk for eating disorders and body image risk factors vary between NCAA competition divisions of female sports. Body dissatisfaction factors that may lead to serious eating disorders will continue to impact the female athletic audience due to added pressures innate to sport performance. Female athletes, regardless of sport, show evidence of risk for developing an eating disorder. Understanding what motivates the developmental process to accelerate in sport may vary depending on level of competition. The educational and scholarly implications of this research project include contributing to the body of literature in the area of body image and eating attitudes of female athletes and providing professionals with a better understanding of the risk factors that influence the prevalence of eating disorders at varied levels of competition.

### Applications in Sport

These findings may assist coaches, strength and conditioning coaches, and athletic trainers in understanding disordered eating and body image disturbances across various female sports in different competition divisions. Professionals that work with female athletes understand the sensitive nature of optimizing performance without compromising overall health. Recognizing and identifying prevention indicators for body image disturbances that lead to disordered eating will assist professionals when dealing with at risk female athletes in varied levels of competition of referred sports. This information will also greatly benefit programs aimed at ceasing the progression of disordered eating

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### Corresponding Author

Kim Kato, Ed.D.
PO Box 13015, SFA Station
Nacogdoches, TX 75962-3015
<kkato@sfasu.edu>
936-468-1610

Dr. Kim Kato is an Assistant Professor in Health Science in the Department of Kinesiology and Health Science at Stephen F. Austin State University in Nacogdoches, Texas.

### Authors

**Kim Kato**, EdD, NSCA-CPT
Stephen F. Austin State University

**Stephanie Jevas**, PhD, ATC, LAT
Stephen F. Austin State University

**Dean Culpepper**, PhD, CC-AASP
Lubbock Christian University

2016-04-01T09:52:41-05:00September 30th, 2011|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology, Women and Sports|Comments Off on Body Image Disturbances in NCAA Division I and III Female Athletes
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Two United States Olympic Committee Olympism Programs: Team USA Ambassador Program and Olympic Day

The United States Olympic Committee administers a number of programs with the objective of spreading Olympism and the Olympic Ideals. Outlined below are its two most robust Olympism programs: the Team USA Ambassador Program and Olympic Day.

### Team USA Ambassador Program

The USOC considers its athletes the greatest representatives of the Olympic Movement and Olympic values. By developing the Olympic values in elite athletes, and, through sharing their stories, we aim to inspire others to seek the highest levels of excellence and to have respect for all, regardless of nationality, religion, race or background.

Started prior to Beijing 2008, the goal of the Team USA Ambassador Program is to expose U.S. Olympians, Paralympians and hopefuls to the expectations, roles, and responsibilities of representing the United States at the Olympic and Paralympic Games. This extensive athlete education program guides athletes through what it means to be an ambassador for their sport and country, how to embrace and maximize their role as a role model, and to consider the legacy and impact they hope to create.

The multi-phase program includes presentations, inspirational speakers and small group activities to cover such topics as:

* What it means to be an Olympian/Paralympian
* The athlete’s role as an ambassador
* The Olympic Ideals and why they matter
* Interview and media preparedness
* Leadership
* Leaving a lasting legacy through sport and Olympism
* Challenges all Olympians and Paralympians face

The 2012 program includes mandatory half-day sessions that take place at seminars conducted around the country, based on National Federation availability. The program allows for comprehensive discussions on the program objectives, including small group activities and interactive elements. A brief wrap-up session will be conducted in conjunction with the 2012 Olympic and Paralympic Games, providing a quick overview of ambassador program learnings, while focusing on inspirational activities and final tips.

The program is primarily delivered by iconic U.S. Olympians and Paralympians who have demonstrated sportsmanship and perseverance on and off the field of play in their own careers. The Olympic facilitators have included speedskaters Bonnie Blair, Eric Heiden and Dan Jansen; football player Brandi Chastain; softball player Jessica Mendoza; skier Picabo Street; decathlete Dan O’Brien; and others.

### Positive Outcomes

* The program was first administered in 2008, followed by 2010. Both Olympic and Paralympic Games resulted in better behavior and self-awareness by members of Team USA. The overall feedback from the American public was pride in the athletes’ performances on the field of play, but also their conduct off the field as good representatives of the USA and members of the Olympic Movement.
* Athlete feedback on the program has been overwhelmingly positive. All athletes who complete the program are surveyed and rank program elements on a scale of 1-5, with 5 being the highest ranking. For the 2010 program, the average score on each question ranged from 4.0 to 4.4.
* The program has been a successful case study in bringing together cross-functional teams consisting of staff members throughout the National Olympic Committee, National Federations, alumni, coaches and athletes.

Not only have Team USA athletes represented themselves well on and off the field of play, but a nation and beyond have been inspired by their demonstration of the Olympic values. With 4 billion individuals around the world witnessing the Olympic Games, this program has the opportunity to disseminate elements of Olympism globally.

### Olympic Day

Olympic Day in the United Sates represents the pinnacle USOC-led event to educate youth on the values of Olympism by coordinating all the leaders within the U.S. Olympic Family. All constituencies within the U.S. Olympic Family work in tandem to spread the message of Olympism and plant seeds among youth about entering the athlete pipeline and pursuing their Olympic and Paralympic dreams.

U.S. Olympic Day celebrations of a national magnitude occurred for the first time in 2009 thanks to the support of Chicago 2016 and the U.S. Conference of Mayors, in conjunction with the U.S. Olympic Committee. In 2010, the U.S. Olympic Family rose to the challenge of surpassing the success of 2009 through increased participation among the National Federations, Athletes’ Advisory Council (AAC), Multi-Sport Organizations (MSO), current athletes, athlete alumni and more.

2011 proved to be the most successful U.S. Olympic Day in history From June 19-27, the U.S. saw:

* 385 events
* 311 participating cities in all 50 United States
* 230 Olympians, Paralympians, hopefuls and coaches
* 90,000 participants

At these events, athletes led discussions with youth about the Olympic Values of excellence, friendship and respect. Sports demonstrations, fun runs and festivals helped introduce young people to Olympic and Paralympic sport.

The U.S. Olympic Committee has designed a turnkey program that assists communities across the nation in celebrating Olympic Day. The organization creates a team of account managers who work directly with a portfolio of communities to provide assistance in preparing for the events. In addition, an online toolkit is available for each event, consisting of:

* Olympic Education Materials (scripts and DVD) for one of the following topics: fair play, respect, perseverance, sportsmanship
* Recommended Olympic Day agenda
* U.S. Olympic Flag
* Certificate of Participation
* Olympic Day Mayoral Proclamation Template
* News Release Templates
* Team USA Logo and Guidelines
* User-Generated website for posting photographs

The account manager also works with the more than 5,000 Olympians and Paralympians currently living in the United States, endeavoring to have an athlete present at most Olympic Day celebration to share their experiences and the role the Olympic Ideals have played in their lives.

Thanks to the support of all participating organizations, Olympic Day is on the verge of appearing in every community across America within the next several years while continuing to expand partnerships among the U.S. Olympic Family. Olympic Day is becoming a great springboard in the United States for disseminating Olympic values across and grassroots organizations and participants.

2013-11-25T16:22:09-06:00August 30th, 2011|Sports Coaching, Sports Facilities, Sports Management, Sports Studies and Sports Psychology|Comments Off on Two United States Olympic Committee Olympism Programs: Team USA Ambassador Program and Olympic Day
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