ISSN: 1543-9518|Vol. 24

Energy Drinks’ Effects on Student-Athletes and Implications for Athletic Departments

Submitted by: Russ Paddock – United States Sports Academy

Abstract

Worldwide, the market for so-called energy drinks has grown exponentially in the last decade. The primary targets of the industry’s marketing campaigns are young adults, and college athletes are frequent consumers of the products. Campaigns promote consumption of energy drinks to enhance performance and suggest their addition to cocktails. Studies have shown college athletes to engage regularly in binge drinking; they are also, clearly, individuals eager to maximize performance. In this article, the ingredients of energy drinks are discussed and the dangers of combining those ingredients with alcohol are explored. In addition, recent research about energy drinks and athletic performance is reviewed. Specific implications for college athletic departments are discussed.

Energy Drinks’ Effects on Student-Athletes and Implications for Athletic Departments

The worldwide market for so-called energy drink has grown exponentially in the last decade. The primary targets of the industry’s marketing campaigns are young adults. As a result, university and college athletes are frequent consumers of the products. The effects of these beverages can be quite significant. Therefore, their use by student-athletes requires analysis, results of which administrators and coaches need to be aware of so that they can share this knowledge with student-athletes in need of direction. They should also track the current trends among student-athletes concerning energy drinks.

Caffeine is the main “energy” ingredient in energy drinks. Its ability to enhance performance, under certain conditions, has been well documented. Yet consuming too much caffeine often has negative effects on overall wellness. Elite athletes continually strive for enhanced performance, trying a variety of strategies to reach that goal. Incorporating energy drinks within a training regime may be one such strategy. Many of the marketing campaigns explicitly state that an energy drink improves functioning, implying that it can boost athletic performance.

Binge drinking, too, has a negative effect on wellness, and research findings indicate that student-athletes—to a greater extent than other students—display a propensity to engage in it. On college campuses today, students commonly use energy drinks as an ingredient in alcoholic cocktails. When they consume alcohol and large amounts of caffeine in combination, many students find themselves drinking more and becoming more intoxicated, which can lead to serious health and other consequences.

History of the Energy Drink

Energy drinks entered the North American beverage market with exotic names, catchy slogans, and expensive marketing campaigns and now occupy a significant portion of the industry. They have become available everywhere, offered alongside soft drinks in vending machines, convenience stores, and grocery stores. Their manufacturers say that, in addition to providing a boost in energy, the drinks promote wellness through medicinal properties (they usually contain vitamins and/or ingredients like ginseng, guarana, and taurine). In 2005 such claims prompted Health Canada (the department of Canada’s federal government responsible for helping Canadians maintain and improve their health) to state, “Energy drinks are meant to supply mental and physical stimulation for a short period of time” (Safe Use of Energy Drinks, n.d., Background section, ¶ 2). Whatever their intended use and purported benefits, consumers today consume energy drinks for a variety of reasons: to boost energy, quench thirst, mix cocktails. Moreover, consumers are constantly pioneering new uses, such as flavoring smoothies with popular energy drinks.

The term energy drink suggests activity, and the uninformed consumer may assume that such a drink would support physical exercise. Locating energy drinks on store shelves adjacent to traditional sports drinks like Gatorade and Powerade reinforces such an assumption of a positive relationship between their use and exercise. Caffeine, the main stimulant ingredient in most energy drinks, has been shown by research to offer questionable potential (at best) as a performance enhancer, in light of the broad variation in individuals’ tolerance of it and also in light of an accompanying range of possible adverse effects (Caffeine—Performance, n.d.).

Drinks providing high doses of caffeine are not a new concept. Jolt cola, a precursor to today’s energy drink phenomenon, was first distributed in the 1980s (Retelny, 2007). Jolt was not marketed as a medicinal health product as, to an extent, energy drinks are. But like energy drinks, it was and is laden with caffeine. The Red Bull energy drink, introduced in the United States in 1997, was the forerunner of the modern energy drink and remains the most recognizable brand in the industry (Retelny, 2007). However, it has considerable competition in today’s marketplace: 500 new varieties of energy drink were introduced to the worldwide market in 2006 (Fornicola, 2007). According to Cohen (2008), the marketing research firm A. C. Nielsen indicated that worldwide sales of the drinks rose from $3.5 billion in 2006 to $4.7 billion in 2007. This speaks volumes for the drinks’ profitability and potential new markets, chiefly within the young teen to young adult demographic. Many companies continue to introduce new drinks, hoping to capture a share of a growing consumer base. Responding to the influx of new products with which they must compete, manufacturers push the boundaries, producing drinks with increasingly complex combinations of medicinal ingredients, with ever higher levels of caffeine, served in larger sizes (Fornicola, 2007).

Ingredients of the Energy Drink

Content labeling has always been inconsistent across North America, and the steady stream of new products developed for the energy drink market further complicates the picture. Energy drinks’ proliferation and popularity clearly caught regulatory agencies such as Health Canada off guard; by all accounts, agencies were ill equipped to respond to initial claims made by the drinks’ various manufacturers. In Canada, most energy drinks have been approved since 2004 as “natural health products.” Approval was a controversial decision, resulting in the establishment of Health Canada’s Natural Health Products Directorate (Raging Bull, 2005). Dr. Eric Marsden of the Ontario Association of Naturopathic Doctors considers Red Bull to be like “sin in a tin” (Raging Bull, 2005, p. 2, All In a Label section, ¶ 8), making a mockery of proper natural health products. On the other hand, energy drinks’ designation as natural health products means that, in Canada, they must be labeled with detailed information about amounts of medicinal and nonmedicinal ingredients and about recommended uses and doses, including cautionary statements.

In the United States, in contrast, the Food and Drug Administration (FDA), while it regulates caffeine content in soft drinks, does not regulate caffeine contained in energy drinks (Cohen, 2008, Anxiety Attacks section, ¶ 9). The FDA is authorized to move to regulate caffeine in energy drinks but tends not to do so unless a given product provides more caffeine than is found in the average cup of coffee (Cohen, 2008, Anxiety Attacks section, ¶ 10). In the United States, it is not required that manufacturers list the ingredients of energy drinks; therefore, it is difficult for consumers to appreciate how much caffeine they ingest with an energy drink. While the information often is available on the manufacturer’s website, it is unlikely typical consumers are concerned about product ingredients to the point of visiting a website. Most take it for granted that a product is safe simply because it is found on the shelves of food stores. And yet, studies have suggested that people with high blood pressure or heart disease should avoid energy drinks. The American Heart Association issued an alert in November 2007 concerning dangers energy drinks pose to those with known cardiovascular issues (Lofshult, 2008).

The variety of energy drinks available makes a complete review of their contents a daunting task. Sugar (whether in the form of glucose, sucrose, fructose, or other compound) is found in most, and sugar’s effects are well known. Sugar-free varieties of energy drinks are now being consumed in significant numbers, as well. In their study, Malinauskas, Aeby, Overton, Carpenter-Aeby, and Barber-Heidal (2007) found that 26% of college students who use energy drinks chose sugar-free versions; significantly more females than males opted for the low-calorie version. Sugar and sweeteners are household ingredients, but the various brands of energy drinks also contain many exotic components, as well. Four in particular seem central in the majority of the marketed products: caffeine, taurine, glucuronolactone, and vitamins.

Caffeine

The primary exotic ingredient of energy drinks is the stimulant drug caffeine. According to the website of the Sports Medicine Council of Manitoba (Caffeine—Performance, n.d.), there is scientific evidence that caffeine raises both heart rate and blood pressure, which can increase alertness and enhance performance of some tasks if small doses only are consumed. Caffeine’s effects are such that it is included in the World Anti-Doping Agency’s monitoring program, although the agency removed caffeine from its list of restricted substances in 2004 (Desbrow & Leveritt, 2007). The decision by the World Anti-Doping Agency implies that the performance-enhancing capacity of caffeine is limited; most research confirms that. Although caffeine in limited quantities improves mood and cognitive performance (Scholey & Kennedy, 2004), consuming more than limited quantities can generate many negative effects. As a result, any beneficial effect on athletic performance proposed for caffeine is not universally accepted.

The Sports Medicine Council of Manitoba (Caffeine—Performance, n.d., p. 2) indicated that a 250-ml can of Red Bull contains 80 mg of caffeine, while in caffeinated soft drinks the concentration ranges from 29 mg to 55 mg per 355-ml serving. Coffee’s caffeine content varies, but it typically contains 100 mg per 250-ml serving (Fornicola, 2007). Popular energy drinks including Monster, Full Throttle, and Rockstar contain about the same amount of caffeine as Red Bull. Some manufacturers, however, in attempting to create a unique product, have added significantly more caffeine to certain niche energy drinks. An article in the McLatchy–Tribune Business News (Energy Drinks’ Buzz, 2008) identified three drinks with extremely high caffeine levels: Boo-Koo Energy, with 360 mg of caffeine in 24 oz; Wired X344, with 344 mg in 16 oz; and Fixx, with 500 mg in 20 oz (Energy Drinks section).

When used in moderation, caffeine rarely produces visible effects, despite the fact that many negative effects have been identified in research. The acceptance and use of caffeine in contemporary society is commonplace, most caffeine being consumed without ill effect in morning coffee, to improve alertness and mood. Since coffee is generally served hot, it is generally drunk slowly. But energy drinks’ good taste and chilled state mean they can be consumed quickly (Fornicola, 2007), allowing a high dose of caffeine to enter the body fairly quickly. Even moderate amounts of caffeine can lead to severe negative effects in people who are caffeine sensitive, as well as in children, with their relatively low body weight. High doses of caffeine can negatively affect concentration, attention, and behavior and can produce irregular heartbeat, nausea, restlessness, headache, and dehydration (Griffith, 2008). Even when dehydration is not a problem, choosing an energy drink over drinks like juice, milk, and water can deprive children of nutrients (and can deplete a parent’s budget). Their students’ increasing access to energy drinks is for good reason causing concern among school officials.

Taurine

The most widely used medicinal ingredient in energy drinks after caffeine is also, perhaps, the least understood: the amino acid taurine. The human body on its own replenishes its supply of taurine (Lidz, 2003, With Taurine section, ¶ 3), which is involved in several metabolic processes and may also have antioxidant properties (Raging Bull, 2005, p. 4, Medicinal Ingredients chart, ¶ 1). A typical person’s intake of taurine is about 60 mg per day (Laquale, 2007), but a single serving of Red Bull (and of most other energy drinks) contains 1,000 mg of taurine. That amount is doubled in the 473-ml serving of Monster and nearly doubled (1,894 mg) in the same size container of Rock Star. Manufacturers imply that a special synergy exists among energy drink ingredients, and certainly taurine would be key to it. Laquale (2007) challenges the synergy notion, suggesting that taurine’s benefits were declared on the basis of testing on house cats in the 1970s.

The taurine in Red Bull has been promoted as the drink’s secret and controversial ingredient. Research on the effects of taurine is limited and inconclusive. But taurine is the reason Red Bull’s acceptance has been delayed in many countries; until recently it was actually illegal to sell Red Bull in Canada (Raging Bull, 2005). According to Lidz, Red Bull’s manufacturer “admits that taurine’s main function [in its product] is simply that of flavor enhancer” (2003, With Taurine section, ¶ 3). The German Institute for the Protection of Consumer Health suggests that claims of taurine’s value are “misleading” (Lidz, 2003, With Taurine section, ¶ 3). Alford et al.’s study (as cited in Laquale, 2007) indicated that Red Bull improved aerobic endurance and anaerobic performance, but whether that resulted from caffeine or taurine (or the combination of the two) was not determined. Griffiths’ research (also cited in Laquale, 2007) furthermore showed that consumers were being misled and that energy drinks’ effects depended on how much caffeine they contained. At this point, not enough research has been done to substantiate any positive effect of taurine, much less to investigate long-term effects of consuming taurine in the amounts present in energy drinks.

Glucuronolactone

Glucuronolactone is a carbohydrate that occurs naturally in the body and, like taurine, is suspected of helping “detoxify the body” (Raging Bull, 2005, p. 4, Medicinal Ingredients chart, ¶ 2). Red Bull includes glucuronolactone to increase energy and feelings of well-being (Laquale, 2007). Not surprisingly, the hundreds of energy drink brands joining the market following Red Bull’s introduction also contain glucuronolactone. Laquale notes that glucuronolactone has been made known by undocumented reports that it was given to American soldiers during the Vietnam War to increase energy but was eventually linked to deadly brain tumors and banned. Glucuronolactone research to date has focused on animals, making its effects in humans difficult to assess (Raging Bull, 2005, p. 4, Medicinal Ingredients chart, ¶ 2).

Vitamins

An assortment of B vitamins (B2, riboflavin; B3, niacin; B6; and B12) are the final ingredient common to the majority of energy drinks. While these vitamins’ importance to healthy living is undeniable, it may be more appropriate to ingest them in the form of a balanced diet than in the form of an energy drink supplement.

Although U.S. products may not be labeled as to their ingredients, they may include some type of warning label with recommendations for use of the product.

Effects

The long-term effects of energy drink consumption are unknown. Many studies have analyzed extended use of caffeine, generating mixed findings—although moderate use of caffeine is commonly accepted to pose little health risk. Fornicola (2007) found that on average, adults consumed 200 mg of caffeine per day, the amount in about two cups of coffee. While caffeine is undoubtedly the greatest contributor to the effect produced by energy drinks, the fact remains there is no research into possible problems associated with long-term ingestion of high concentrations of taurine and glucuronolactone.

Red Bull states that short-term positive effects of the drink—of its particular combination of ingredients—are proven by publicly available academic studies (FAQ, n.d., What proof is there that Red Bull energy drink does what it says it does? section). But the Red Bull website does not provide links or directions for accessing those studies. The majority of the extant research clearly disputes the claims, essentially attributing to caffeine the quantifiable short-term effect of increased energy (Malinauskas et al., 2007). Caffeine is also a diuretic, however, and the manufacturer of Red Bull recommends that users of its product drink ample amounts of water when they exercise (FAQ, n.d., Is Red Bull Energy Drink Suitable As Fluid Replacement? section).

There remains considerable concern regarding the negative effects of energy drinks. Emergency room visits arising from energy drink consumption are becoming commonplace. For example, Child Health Alert reported a 23-year-old was hospitalized with a dangerously high heart rate after consuming the energy drink GNC Speed Shot followed by a Mountain Dew soft drink, also containing caffeine (Caffeine: Watch Out, 2008). The report noted that the GNC Speed Shot website does warn against using the product together with others that contain caffeine. There are countries, France, Denmark, and Norway among them, that continue to ban the sale of Red Bull. Several highly publicized deaths linked to energy drinks have fueled ongoing suspicion. In one such tragedy, a healthy 18-year-old Irish basketball player experienced cardiac arrest after consuming four cans of Red Bull prior to a game (Laquale, 2007).

Consumption Patterns

Malinauskas et al. (2007) stated that energy drinks are intended for young adults but that little formal research is available accurately describing the multibillion-dollar energy drink industry’s actual clientele. Studying energy drink consumption by college students, Malinauskas et al. found that 51% used energy drinks, defined as consuming more than one energy drink monthly during the academic semester in which they were surveyed. In Canada, energy drinks labeled as natural health products must provide cautions complying with requirements of Health Canada’s Natural Health Products Directorate. For example, the beverages are not recommended for nursing or pregnant women, caffeine-sensitive persons, or children. Product labeling also establishes a maximum daily dose and advises against mixing the beverages with alcohol. An analysis of the labels on three popular energy drinks found that all delivered the same messages except when offering a maximum daily dose. Red Bull and Rock Star advise consumers not to exceed 500 ml of the product per day, while Monster recommends no more than 1,000 ml per day.

It is not clear how many adults consume energy drinks, but it is certain that, despite manufacturers’ warnings, many children are regular consumers. The Florida Poison Control Center started to track cases of caffeine overexposure after 39 people ages 2 to 20 years developed symptoms between January 2007 and March 2008 (Cohen, 2008, Anxiety Attacks section, ¶ 3). A school nurse in California sent three students to hospital by ambulance in the past year because they had irregular heart rates brought on by consumption of energy drinks (Dorsey, 2008). Energy drinks are not recommended for children or adolescents nor are they marketed directly to them. But surprisingly, there is currently no restriction on children’s purchase of energy drinks, even though caffeine’s effects are more pronounced in children than adults, due to body size and tolerance. It is furthermore clear that children and adolescents contribute significantly to the total market. Some schools have banned energy drinks from school property, and many jurisdictions are considering attempting to restrict energy drink sales to children.

Marketing

Energy drinks are marketed with colorful descriptions and provocative names that make them sound fun and exciting. Rockstar, Monster, Full Throttle, Throw Down, and Sobe No Fear are just a sampling of the inviting products that fill store shelves. Marketing slogans are developed to stimulate interest in a product and distinguish it from its competition: “Get spiked,” “Party like a rockstar,” and “Feel the freak” are slogans representing the marketing strategies of energy drink companies. The language and images of such advertising are not directed at mature adults. If anything, the marketing of energy drinks removes all ambiguity about whom these products are meant to appeal to: teens and young adults.

With 40% of the market share, Red Bull remains the leader in energy drink sales (Agriculture and Agri-Food Canada, 2008, Background section, ¶ 2). Not surprisingly, the “Red Bull gives you wiiings” slogan is widely recognized. Red Bull has developed its image over the past decade by sponsoring extreme sports and targeting college students (Lidz, 2003, Red Bull’s Effects Have Been Recognized by World-Class Athletes section, ¶ 3-4). More than other brand’s marketing, Red Bull’s marketing has created a connection between the product and sports and fitness, with the implication that greater performance in athletics is achieved by those who consume Red Bull. Currently, Red Bull containers feature the phrase “Vitalizes body and mind.” Lidz (2003) identified other slogans from Red Bull that have made a connection to sports: “increases concentration,” “improves reaction speed,” “stimulates metabolism,” and “Red Bull’s effects have been recognized by world-class athletes.” Miller (2008) suggested that other manufacturers have copied Red Bull’s strategy, since “energy drink advertising consistently emphasizes a physically active lifestyle featuring a range of extreme sports” (p. 481). Miller further suggested that, in their appeal to the young, energy drink marketing strategies are similar to those of the tobacco and alcohol industry (p. 488). Such an affinity between a “healthy natural product” and smoking and drinking is incongruous.

Consumption Among Student-Athletes

Malinauskas et al. (2007) found that 51% of college students consume energy drinks, so logic would dictate that student-athletes in colleges and universities consume the product at a similar or perhaps higher rate, given the marketing-constructed connection between energy drinks and sports. Promotional statements for Red Bull suggest consuming the product prior to a demanding athletic contest like a race or game (FAQ, n.d., When Should Red Bull Energy Drink Be Consumed? section). Also suggesting student-athletes’ susceptibility to energy drink marketing is Miller’s confirmation (2008) of the phenomenon called toxic jock identity. Miller defined toxic jock identity as the state of having “a sport-related identity predicated on risk taking and hyper masculinity” (p. 481). Toxic jock identity may increase risky behaviors, and consuming energy drinks may be a predictor of the phenomenon (Miller, 2008). The drive to improve athletic performance and exhibit one’s athletic identity could influence student-athletes to consume energy drinks at a relatively high level compared to that of the general student body.

Consumption to Boost Athletic Performance

Does ingestion of an energy drink really boost athletic performance? Caffeine is the only ingredient in energy drinks that has been studied in depth and that shows proven effects; short- and long-term effects of high doses of taurine and glucuronolactone require additional study. Athletes have long used caffeine prior to training sessions and competitions, but most nevertheless do not well understand how the drug works, for example that, as a diuretic, caffeine is capable of aggravating the dehydration athletes may experience during competition. The scientific literature itself provides mixed messages about caffeine’s performance-enhancing capability and its value prior to exercise. Fornicola (2007) stated that no real need exists to use energy drinks for performance advantage and that that quick caffeine fix is not a very intelligent strategy. In contrast, the website of the Sports Medicine Council of Manitoba reports that endurance athletes might gain some advantage by exploiting caffeine to derive energy from fat early in a competition, thereby leaving more muscle glycogen available to provide energy later on (Caffeine—Performance, n.d., p. 1). However, the website also advises athletes that “4% dehydration equals 20% of performance lost” (p. 1). Caffeine promotes dehydration, so the amount of it to be ingested for athletic advantage would have to be determined very precisely. Desbrow and Leveritt (2007) demonstrated that the majority of elite triathletes use caffeine to improve physical performance and concentration. However, these athletes’ knowledge of which products contain caffeine (and how much they contain) was limited (Desbrow & Leveritt, 2007). Umaña-Alvarado and Moncada-Jiménez (2005) studied the effects of energy drinks on male athletes’ aerobic activity, finding no performance improvement from energy drink consumption prior to testing. However, their results did demonstrate that those participants who consumed energy drinks reported lower levels of perceived exertion.

Consumption With Alcohol

Studies show student-athletes are more prone to binge drinking than other students. Grossman, Wechsler, Davenport, and Dowdall (1997) found college athletes engaged in binge drinking and used chewing tobacco at higher rates than nonathletes, although they were less likely to smoke cigarettes or marijuana. Other research indicates that team sports participants are especially likely to consume alcohol in a high-risk manner (Brenner & Swanik, 2007). Such findings, particularly when considered in light of something like toxic jock identity, suggest that the newly popular practice of mixing energy drinks into alcoholic cocktails may place student-athletes at an elevated risk. Consuming energy drinks along with alcohol lessens the subjective sense of intoxication (O’Brien, McCoy, Rhodes, Wagoner, & Wolfson, 2008). This means one can consume more alcohol than usual because one doesn’t feel intoxicated. In addition, the alcohol-induced fatigue that normally tends to limit further alcohol consumption may be masked by the caffeine in the energy drink (Dunlap, 2008).

Although energy drink companies may caution consumers against mixing the products with alcohol, young people, especially, do so. According to Miller (2008), the website Drinknation.com contained 201 Red Bull–based alcoholic beverage recipes. And despite the Red Bull label’s warning about mixing the product with alcohol, the manufacturer’s website tells visitors that Red Bull can be used for more than nonstop partying (Benefits, n.d., Red Bull—More Than Just a Myth section, ¶ 3).

Combining a depressant (alcohol) with a stimulant (energy drink containing caffeine) clearly could exacerbate the typical risks of alcohol consumption. The practice, combined with the tendency of student-athletes to binge on alcohol, should raise concern. O’Brien et al. (2008) indicated that “students who reported consuming alcohol mixed with energy drinks had significantly higher prevalence of alcohol–related consequences, including being taken advantage of sexually, taking advantage of another sexually, riding with an intoxicated driver, being physically hurt or injured, and requiring medical treatment” (p. 453). Further, the U.S. Surgeon General has reported that in the United States, close to 5,000 people under age 21 die each year of alcohol-related injuries (Dunlap, 2008).

Consumption in Conjunction With Studying

Long before the introduction of energy drinks, students used caffeine to stay up late at night studying. Today student-athletes who do not like the taste of coffee can choose an energy drink instead. In moderation, use of energy drinks to sustain a study session would appear to be harmless. Nevertheless, coaches and athletic department staff should make sure student-athletes are familiar with caffeine’s potential negative effects (when it is consumed to excess), in order to help them make informed and responsible choices, whatever the circumstance.

Consumption Representing Casual Use

Casual consumption of energy drinks accounts most significantly for the rapid rise in their popularity. Now available everywhere, energy drinks strike many consumers as a choice akin to a soft drink or coffee. The market seems poised for continued expansion, supported by aggressive marketing. The consumption of energy drinks is likely to become even more common and socially acceptable. Student-athletes are likely to be part of the trend, increasing their consumption, especially if they lack complete information about energy drinks, their ingredients, and their actual effects on athletic performance and health.

Summary and Conclusions

Given the proliferation of energy drinks and their growing popularity despite possible negative effects, coaches and athletic department administrators should take the initiative in educating student-athletes about the products. Energy drinks are aggressively marketed to college students with messages touting the performance and other benefits of consuming the beverages. Students are urged be energy drink consumers, and for the uninformed student-athlete, the trend’s influence may produce negative consequences.

While the purported benefits of the taurine and glucuronolactone in energy drinks are unproven, potential positive and negative effects of another common ingredient, caffeine, are well documented. The choice to use caffeine prior to training or competition should belong to the individual, based on adequate knowledge of pros and cons and on past experiences with caffeine. Student-athletes who choose to use caffeine should be encouraged to do so in moderation. They should also be provided information about levels of caffeine contained in various foods and beverages, in order to monitor their intake. Most energy drinks in fact have not contained more caffeine than a cup of coffee, but there is a noticeable trend toward selling the beverages in larger containers—meaning larger servings and more caffeine. If consuming an energy drink before a competition improves mood and concentration, it would be difficult to suggest that it poses significant danger. Assuming a consumer is not caffeine-sensitive, caffeine’s negative effects are unlikely to become evident unless intake becomes excessive. Although deaths associated with energy drink consumption and sport have been reported, they seem to be isolated cases involving multiple servings with high levels of caffeine.

While it is important to provide student-athletes with accurate information on energy drinks and caffeine as these affect athletic performance, of greater concern to athletic departments should be the growing trend of combining energy drinks and alcohol. Take the not uncommon pattern of student-athletes, dehydrated by the effort of playing a game, gathering after that game to consume alcohol. If the alcohol is mixed with caffeinated energy drinks, the student-athletes are subjected to a double diuretic effect, since alcohol, like caffeine, has diuretic properties. Thus they further compromise hydration.

Moreover, energy drinks’ capacity to mask intoxicated feelings allows increased alcohol consumption, which in turn increases the likelihood that a young drinker will make the kind of choices that have negative, if not disastrous, results. Evidence suggests that energy drink consumption with and without alcohol remains on the increase, so educating student-athletes on all aspects of energy drink consumption needs to become an athletic department priority, to ensure both wellness and safety.

References

Agriculture and Agri-Food Canada. (2008). Agri-Food Trade Service: The Energy Drink Segment in North America, January 2008. Retrieved July 10, 2008, from http://www.ats.agr.gc.ca/us/4387_e.htm

Benefits (n.d.). Retrieved July 10, 2008, from the Red Bull website: http://www.redbullusa.com/#page=ProductPage.Benefits

Brenner, J., & Swanik, K. (2007). High-risk drinking characteristics in collegiate athletes. Journal of American College Health, 56(3), 267-272.

Caffeine—Performance enhancement or hindrance? (n.d.). Retrieved June 30, 2008, from the Sports Medicine Council of Manitoba website: http://www.sportmed.mb.ca/uploads/pdfs/Caffeine%20good%20and%20bad.pdf

Caffeine: Watch out for “energy drinks.” (2008, May). Child Health Alert, 26, 2-3.

Cohen, H. (2008, April 2). Kids + energy drinks = dangerous mix. The Miami Herald. Retrieved June 5, 2008, from http://seattletimes.nwsource.com/html/health/2004322357_zhea02energy.html

Desbrow, B., & Leveritt, M. (2007). Well-trained endurance athletes’ knowledge, insight, and experience of caffine use. International Journal of Sport Nutrition and Exercise Metabolism, 17(4), 328-339.

Dunlap, L. (2008). Wake up to the facts: Energy drinks and alcohol don’t mix. The Journal of the Air Mobility Command’s Magazine, 17(2), 20-21.

Energy drinks’ buzz may pose some risk. (2008, January 30). McClatchy–Tribune Business News. Retrieved June 5, 2008, from the ProQuest database.

FAQ (n.d.). Retrieved July 10, 2008, from the Red Bull website: http://www.redbullusa.com/#page=ProductPage.FAQS

Fornicola, F. (2007). Energy drinks: What’s all the “buzz” about? Coach and Athletic Director, 76(10), 38-43.

Griffith, D. (2008, May 11). Energy drinks make caffeine the drug of choice among California youth. Sacramento Bee. Retrieved June 5, 2008, from http://search.ebscohost.com/login.aspx?direct=true&db=nfh&AN=2W62W6639513775&site=ehost-live

Grossman, S. J., Wechsler, H., Davenport, A. E., & Dowdall, G. W. (1997). Binge drinking, tobacco, and illicit drug use and involvement in college athletics: A survey of students at 140 American colleges. Journal of American College Health, 45(5), 195-200.

Laquale, K. (2007). Red Bull: The other energy drink and its effect on performance. Athletic Therapy Today, 12(2), 43-45. Retrieved October 5, 2008, from the SportDiscus database.

Lidz, F. (2003). The fuel of extremists (or, taurine in your tank). Sports Illustrated, 99(4), 8-16.

Lofshult, D. (2008). Energy drinks may present danger. Idea Fitness Journal, 5(4), 58.

Malinauskas, B. M., Aeby, V. G., Overton, R. F., Carpenter-Aeby, T., & Barber-Heidal, K. (2007). A survey of energy drink consumption patterns among college students. Nutrition Journal, 6(1), 35.

Miller, K. E. (2008). Wired: Energy drinks, jock identity, masculine norms, and risk taking. Journal of American College Health, 56(5), 481-490.

O’Brien, M. C., McCoy, T. P., Rhodes, S. C., Wagoner, A., & Wolfson, M. (2008). Caffeinated cocktails: Energy drink consumption, high-risk drinking, and alcohol-related consequences among college students. Academic Emergency Medicine, 15(5), 453-460.

Raging bull: Health warnings over popular energy drink being brushed off? (2005, February 6). Retrieved July, 10, 2008, from the Canadian Broadcasting Corporation (CBC) website: http://www.cbc.ca/consumers/market/files/health/redbull/

Retelny, V. S. (2007). Energy drinks. Obesity Management, 3(3), 139-142.

Safe use of energy drinks. (n.d.). Retrieved June 20, 2008, from the Health Canada website: http://www.hc-sc.gc.ca/hl-vs/iyh-vsv/prod/energy-energie-eng.php

Scholey, A. B., & Kennedy, D. O. (2004). Cognitive and physiological effects of an “energy drink”: An evaluation of the whole drink and of glucose, caffeine and herbal flavouring fractions. Psychopharmacology, 176(3-4), 320-330.

Umaña-Alvarado, M., & Moncada-Jiménez, J. (2005). Consumption of an “energy drink” does not improve aerobic performance in male athletes. International Journal of Applied Sport Sciences, 17(2), 26-34.

2015-02-12T11:36:51-06:00October 7th, 2008|Contemporary Sports Issues, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off on Energy Drinks’ Effects on Student-Athletes and Implications for Athletic Departments
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Motives for Sport Participation as Predictors of Motivation Outcomes in Track and Field: A Self-Determination Theory Perspective

Submitted by: Taruna Bhatnagar and Costas I. Karageorghis – Brunel University

Abstract

The extent to which motives for sport participation predict motivation outcomes was investigated in a study embracing self-determination theory and couched in Vallerand’s hierarchical model of motivation at the contextual level. Data were collected from 159 collegiate athletes. Motives for sport participation were assessed using the Sport Motivation Scale. Cognitive, affective, and behavioral measures were used to assess contextual motivation outcomes. Linear regression analyses examined the extent to which sport motives predicted motivation outcomes (satisfaction, concentration, and persistence). Amotivation emerged as a strong negative predictor of the outcome measures. External and introjected regulations and three intrinsic motives did not predict any of the motivation outcomes. The results do not support previous findings and offer only limited support of Vallerand’s model.

Motives for Sport Participation as Predictors of Motivation Outcomes in Track and Field: A Self-Determination Theory Perspective

Two types of motivation, intrinsic and extrinsic, have been of particular interest to researchers in the field of sport psychology (Deci & Ryan, 1985, 2000, 2008; Vallerand, 1997, 2001). Intrinsic motivation entails participation in an activity for the feelings of fun, pleasure, excitement, and satisfaction associated with it, while extrinsic motivation involves participation for the attainment of such rewards as money, trophies, and social approval or to avoid punishment. One of the most widely applied theoretical approaches to these types of motivation is self-determination theory, or SDT (Deci & Ryan, 1985, 2000; Ryan, 1995; Ryan & Deci, 2000). SDT also involves the concept of amotivation, or having no sense of purpose and lacking intent to engage in a particular behavior. SDT posits that the different types of motivation range on a continuum from high to low self-determination: intrinsic motivation–extrinsic motivation–amotivation (Deci & Ryan, 1985, 2000).

Vallerand (1997, 2001) embraced elements of SDT and integrated them within a hierarchical theory of motivation. His model asserts that social factors, mediators (autonomy, competence, and relatedness), motivations, and consequences (affect, cognition, and behavior) exist at three levels, the global level, contextual level, and situational level. A number of studies have indicated that behavioral regulations spanning the SDT continuum would lead to a corresponding pattern of consequences (Ratelle, Vallerand, Chantal, & Provencher, 2004; Sarrazin, Vallerand, Guillet, Pelletier, & Cury, 2002; Standage, Duda, & Ntoumanis, 2003; Standage & Vallerand, 2008; Taylor, Ntoumanis, & Standage, 2008; Vlachopoulos, Karageorghis, & Terry, 2000; Wilson, Rodgers, Fraser, & Murray, 2004). That is, autonomous regulations and intrinsic motivation are expected to correspond with more positive outcomes, whereas less self-determined forms of regulation (external and introjected regulations) correspond with more negative outcomes, such as poor focus, burnout, and dropout. Vallerand’s proposals have found broad support in a range of sport and physical activity contexts (Standage et al., 2003; Wilson et al., 2004; Ntoumanis, 2001, 2005; Spray, Wang, Biddle, & Chatzisarantis, 2006); however, to date no study has examined these proposals in the context of a single sport.

The purpose of the present study was to examine the extent to which motives for sport participation predicted motivation outcomes at the contextual level of motivation, thus affording a direct test of Vallerand’s (1997, 2001) model. On the basis of previous work (Ntoumanis, 2001; Vallerand & Bissonnette, 1992; Pelletier, Fortier, Vallerand, Tuson, Briere, & Blais, 1995; Ntoumani & Ntoumanis, 2006), it was hypothesized that identified regulation and the dimensions of intrinsic motivation would be significant positive predictors of motivation outcomes, while amotivation would be a significant negative predictor.

Method

Participants

A sample of 159 volunteer track and field athletes was tested at eight athletics clubs in the London, United Kingdom, area (66 women and 93 men). Their mean age was 19.7 years (SD = 2.8). English was the first language of all participants. Full details of the ethnicity and level of participation of participants can be requested from the second author. Eighty-five athletes participated in sprint events (53.5%), 30 in middle distance events (18.9%), 33 in throwing events (20.7%), 4 in long-distance events (2.5%), and 7 in multievents (4.4%). Their years of experience in track and field ranged from 1 to 18 (M = 5.8 years, SD = 3.5).

Measures

Sport Motivation Scale. The 28-item Sport Motivation Scale (Pelletier et al., 1995) was based on SDT and designed to assess contextual intrinsic motivation, extrinsic motivation, and amotivation. Athletes respond to the item “Why do you practice your sport?” with responses from a Likert-type scale that ranges from 1 (does not correspond at all) to 7 (corresponds exactly). The Sport Motivation Scale (SMS) consists of seven subscales with four items attached to each. The participation motives operationalized by the SMS, ranging from the most to the least self-determined, are as follows: intrinsic motivation to know (“for the pleasure of discovering new training techniques”); intrinsic motivation toward accomplishment (“for the satisfaction I experience while I am perfecting my abilities”); intrinsic motivation to experience stimulation (“for the excitement I feel when I am really involved in the activity”); identified regulation (“because in my opinion, it is one of the best ways to meet people”); introjected regulation (“because I must do sports regularly”); external regulation (“to show others how good I am at my sport”); and amotivation (“it is not clear to me anymore; I really don’t think my place is in sport”). The SMS has strong psychometric properties (Pelletier et al.; Vallerand & Losier, 1999). Confirmatory factor analysis was used to support the factor structure, while correlations between subscales and criterion measures were consistent with theoretical predictions. Further, internal consistency estimates were acceptable for all subscales (α = .74– .80) with the exception of identified regulation (.63).

Affective outcome measure. Satisfaction was used as an affective outcome and was assessed using a single item: “I am satisfied with my participation in the sport I currently practice” (Vlachopoulos et al., 2000). Participants responded on a Likert-type scale ranging from 1 (I do not at all feel satisfied) to 7 (I feel extremely satisfied).

Cognitive outcome measure. Concentration was used as a cognitive outcome and was assessed using the dimension of concentration on task at hand from the Dispositional Flow Scale-2 (Jackson & Eklund, 2002). This dimension consists of four items (e.g., “I have total concentration”) and participants provided responses on a Likert-type scale ranging from 1 (never) to 5 (always).

Behavioral outcome measure. The behavioral outcome of persistence was assessed using the mean of three items: “I intend/I will try/I am determined to continue participation in the sport I currently practice during this year” (Vlachopoulos et al., 2000). Responses were provided on a semantic differential scale ranging from 1 (extremely unlikely) to 7 (extremely likely).

Procedure

The study was approved in accordance with the published procedures of the Brunel University Ethics Committee. Coaches and team managers were approached by both authors, in order to obtain permission to administer questionnaires to athletes. The general purpose of the study was explained, and, subsequently, written informed consent was sought from participants. Only two athletes did not provide informed consent and thus did not participate in the study.

Prior to a training session, participants provided demographic details, then completed the SMS (Pelletier et al., 1995). Following a gap of 1 week, the contextual motivational outcomes were assessed prior to the corresponding training session. The time gap was used to reduce the possibility of any extraneous environmental factors impacting upon the relationship between motives for sport participation and motivation outcomes (Kelly, 1988).

Data Analysis

Data screening was undertaken to check for missing data and to ensure that values were within expected ranges. Univariate outliers were identified using z scores > ±3.29 and multivariate outliers using the Mahalanobis distance method (p < .001; Tabachnick & Fidell, 2007). Cases that had multiple univariate outliers or were multivariate outliers were deleted from the data file, while additional univariate outliers were reduced by modifying their raw score toward the mean, to a unit below the next least extreme raw score (Tabachnick & Fidell, p. 77). Checks were conducted for the parametric assumptions underlying standard linear regression, specifically normality, linearity, homoscedasticity, and independence of residuals. Standard linear regression analyses were used to predict the three outcome
measures from the seven SMS subscales.

Results

Following data screening, three cases that had multiple univariate outliers and one case that was a multivariate outlier were identified and deleted. Also, 11 univariate outliers were identified and transformed to ensure that the corresponding z score fell within the accepted range (Tabachnick & Fidell, 2007). The mean Sport Motivation Scale scores were highest for the self-determined motives (see table 1), indicating that the present sample participated in sport predominantly for intrinsic and identified reasons rather than external and introjected reasons.

Table 1

Descriptive Statistics for the Sport Motivation Scale and Outcome Measures

VariableMSDRangeSkewnessKurtosis

Sport Motivation Scale
Amotivation 7.46 4.24 4.00-2.00 1.24 0.97
External regulation 15.35 4.68 4.00-27.00 0.14 -0.45
Introjected regulation 15.90 5.53 4.00-28.00 0.25 -0.67
Identified regulation 15.98 4.74 4.00-28.00 0.10 -0.42
Intrinsic motivation to know 19.88 4.34 9.00-28.00 -0.19 -0.57
Intrinsic motivation toward accomplishments 21.50 3.92 10.00-28.00 -0.56 -0.38
Intrinsic motivation to experience stimulation 20.68 3.72 11.00-28.00 -0.26 -0.35
Outcome measures
Satisfaction 5.40 1.25 1.00-7.00 -1.25 1.42
Concentration 15.26 2.18 9.00-20.00 0.19 -0.15
Persistence 6.89 0.27 6.00-7.00 -2.46 4.92

Normality checks of skewness and kurtosis values indicated that the only problematic variable among the 10 examined was persistence (see table 1). This is indicative of the fact that participants generally indicated strong intentions to persist in track and field. Given that this was the only problematic variable, a decision was taken not to apply logarithmic transformation.

Thereafter, three separate linear regression analyses were conducted to predict each outcome measure from the SMS subscales (see table 2). Collectively, independent variables revealed a significant (p < .01) overall prediction within each regression equation. Amotivation emerged as a strong negative predictor of each of the three motivation outcomes. Contrary to expectations, the intrinsic motives did not predict the outcome measures in any of the equations. The predictor variables accounted for the highest degree of percentage variance in the outcome of satisfaction (16%), followed by concentration (9%), and persistence (6%).

Table 2

Standard Linear Regression to Predict Motivation Outcomes from Motives for Sport Participation

Dependent variablePredictor variableStandardized beta (β)

Satisfaction Amotivation -0.40*
External regulation 0.18
Introjected regulation -0.06
Identified regulation -0.02
Intrinsic motivation to know 0.05
Intrinsic motivation toward accomplishment 0.02
Intrinsic motivation to experience stimulation 0.09
R = 0.45
R2 = 0.16
Concentration Amotivation -0.24*
External regulation 0.19
Introjected regulation -0.02
Identified regulation -0.06
Intrinsic motivation to know -0.16

Note. The analysis of variance corresponding with each linear regression analysis was significant (p < .01).

* p < .01.

Discussion

The purpose of the present study was to examine the extent to which motives for sport participation predicted motivation outcomes at the contextual level of motivation in a single sport. More specifically, this study examined the proposition that more self-determined forms of motivation are positively associated with motivation outcomes than either their controlling counterparts or amotivation (Deci & Ryan, 1985; Ryan & Deci, 2000).

Results indicated that amotivation negatively predicted the contextual motivation outcomes, which corroborates recent findings pertaining to this dimension (Deci & Ryan, 2000; Wilson et al., 2004). However, neither intrinsic motives nor external or introjected regulations predicted any of the outcome measures. Collectively, the present results appear to offer only very limited support for the research hypothesis; autonomous regulations and intrinsic motivation were not positive predictors of the motivation outcomes.

Contrary to expectations, the present findings do not support those of previous studies which showed that identified regulation and intrinsic motivation were positively associated with motivation outcomes at the contextual level of motivation (Wilson et al., 2004; Ntoumanis, 2001; Ntoumani & Ntoumanis, 2006). It is plausible that the predictive efficacy of intrinsic motivation to know may be lower in track and field than in some other sports, because track and field is primarily a motoric sport involving relatively few tactics; athletes follow their coaches’ instructions closely and do not exhibit a particularly deep desire to explore new performance strategies. However, it is acknowledged that anecdotal evidence suggests this may not generalize to elite performers (Johnson, 1996; Lewis & Jeffrey, 1990). A further plausible cause for the anomalous findings is that coaches emphasize and strongly encourage peer or social comparison (competition) among athletes, which may well weaken the link between intrinsic motivation and outcomes (Spray et al., 2006; Whitehead, 1993).

The regression analyses predicted a relatively small percentage of the variance in the cognitive and behavioral outcomes but a considerable percentage of the affective outcome (16%). This indicates that behavioral regulations are strong predictors of how people feel about their participation in sport. Most notably, amotivation was found to be a strong antithetical marker of satisfaction, a finding that is entirely consistent with theoretical predictions (Ntoumanis, 2001; Wilson et al., 2004). This implies that if coaches are to address the potentially deleterious effects of amotivation, an effective strategy would be to apply mood- and emotion-regulation strategies and to demonstrate some sensitivity toward athletes’ affective states.

Another interesting aspect of track and field which may, to a degree, account for the somewhat anomalous findings, is its multidisciplinary nature. This means not only are psychological needs underlying intrinsic motivation being frustrated by the sport’s coactive nature and emphasis on social comparison, there is in addition a further level of competition between event groups, for example sprints versus throws or jumps versus distance running. Proponents of each event group vie for use of facilities, limited financial resources, and media attention. This fusion of conflicting forces makes track and field a very distinct sport, which may account for the present results’ lack of support for the propositions of SDT. This is indeed the first study in the sport literature to offer a voice of dissent by suggesting that SDT has very limited predictive efficacy in terms of motivation outcomes.

Limitations of the Present Study

Data for the present study were collected at the height of the summer track and field season, and participants were, consequently, immersed in their preparations for competition. A strong orientation toward performance outcomes may have served to undermine their intrinsic motivation to a degree. More specifically, the overt emphasis on competition at that time of year may have promoted an external locus of causality, given that competition is
inherently controlling in nature (Fortier, Vallerand, Briere, & Provencher, 1995; Vansteenkiste & Deci, 2003).

The varying participation levels of athletes in the present sample could also have accounted for unexpected findings pertaining to the predictive efficacy of self-determined forms of motivation. Essentially, it is conceivable that different combinations of motives may be relevant to athletes competing at different levels. For example, the external regulation score of international athletes (M = 16.37) indicated that their sport participation was less self-determined than was the participation of their recreational counterparts (M = 14.71), albeit this difference did not reach statistical significance (p < .05).

Conclusions and Recommendations

The present findings provide very limited support for Vallerand’s (1997, 2001) hierarchical model of intrinsic and extrinsic motivation and, indeed, for posits of SDT (Deci & Ryan, 1985, 2000; Ryan & Deci, 2000). Contrary to expectations, results indicated that amotivation was the only predictor of the contextual motivational outcomes.

The practical implications of the present findings lie in promoting factors that underpin intrinsic motivation in track and field. Perceptions of autonomy and individual mastery will nurture intrinsic motivation and ultimately improve sport performance (Edmunds, Ntoumanis, & Duda, 2006; Whitehead, 1993; Wilson & Rodgers, 2004). Coaches should emphasize positive sensations such as fun and excitement that result from participation, while tempering their emphasis on peer comparison (Taylor et al., 2008; Whitehead, 1993). Further, coaches should be trained in the principles underlying emotional intelligence, given that the present findings suggest that sensitivity to athletes’ affective states is likely to buffer the potentially negative consequences of amotivation.

A promising direction for further research would be to investigate the psychological need for relatedness, given that much past sport motivation research has focused on the need for autonomy and the need for competence (e.g., Deci & Ryan, 2008; Vallerand & Losier, 1999). It appears likely that the need for relatedness may be frustrated in track and field, owing to the track and field sports’ potential for conflict and coaches’ overt emphasis on peer comparison.

Future research should explore additional motivation outcomes, for example cognitive outcomes such as attention span and level of learning (Ntoumanis, 2001). Moreover, additional research is warranted into the antecedents of amotivation, in order to minimize negative consequences such as burnout and dropout. Finally, replication of the present study during the off-season would yield insightful comparative data, since participation in track and field is orientated more toward self-development than it is toward peer or social comparison. The predictive efficacy of sport motives may well vary from competitive periods to noncompetitive periods, and this would hold important implications for theory development.

References

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum.

Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-68.

Deci, E. L., & Ryan, R. M. (2008). Facilitating optimal motivation and psychological well-being across life’s domains. Canadian Psychology, 49, 14-23.

Edmunds, J., Ntoumanis, N., & Duda, J. L. (2006). A test of self-determination theory in the exercise domain. Journal of Applied Social Psychology, 9, 2240-2265.

Fortier, M. S., Vallerand, R. J., Briere, N. M., & Provencher, P. (1995). Competitive and recreational sport structures and gender: A test of their relationship with sport motivation. International Journal of Sport Psychology, 26, 24-39.

Jackson, S. A., & Eklund, R. C. (2002). Assessing flow in physical activity: The Flow State Scale-2 and Dispositional Flow Scale-2. Journal of Sport & Exercise Psychology, 24, 133-50.

Johnson, M. (1996). Slaying the dragon. New York: HarperCollins.

Kelly, J. R., & McGrath, J. E. (1988). On time and method. London: Sage.

Lewis, C., & Jeffrey, M. (1991). Inside track: My professional life in amateur track and field. London: Sphere Books.

Ntoumani, C. T., & Ntoumanis, N. (2006). The role of self-determined motivation in the understanding of exercise-related behaviours, cognitions and physical self-evaluation. Journal of Sports Sciences, 24, 393-404.

Ntoumanis, N. (2001). A self-determination approach to the understanding of motivation in physical education. British Journal of Educational Psychology, 71, 225-42.

Ntoumanis, N. (2005). A prospective study of participation in optional school physical education using a self-determination theory framework. Journal of Educational Psychology, 97, 444-453.

Pelletier, L. G., Fortier, M. S., Vallerand, R. J., Tuson, K. M., Briere, N. M., & Blais, M. R. (1995). Toward a new measure of intrinsic motivation, extrinsic motivation, and amotivation in sports: The Sport Motivation Scale. Journal of Sport & Exercise Psychology, 17, 35-53.

Ratelle, C. F., Vallerand, R. J., Chantal, Y., & Provencher, P. (2004). Cognitive adaptation and mental health: A motivational analysis. European Journal of Social Psychology, 34, 459-76.

Ryan, R. M. (1995). Psychological needs and the facilitation of integrative processes. Journal of Personality, 63, 397-428.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development and well-being. American Psychologist, 55, 68-78.

Sarrazin, P., Vallerand, R. J., Guillet, E., Pelletier, L., & Cury, F. (2002). Motivation and dropout in female handballers: A 21-month prospective study. European Journal of Social Psychology, 32, 395-418.

Spray, C. M., Wang, C. K. J., Biddle, S. J. H., & Chatzisarantis, N. L. D. (2006). Understanding motivation in sport: An experiment test of achievement goal and self determination theories. European Journal of Sport Science, 6, 43-51.

Standage, M., Duda, J. L., & Ntoumanis, N. (2003). A model of contextual motivation in physical education: Using constructs from self-determination and achievement goal theories to predict physical activity intentions. Journal of Educational Psychology, 95, 97-110.

Standage, M., & Vallerand, R. J. (2008). Self-determined motivation in sport and exercise groups. In M. R. Beauchamp & M. A. Eys (Eds.), Group dynamics advances in sport and exercise psychology: Contemporary themes (pp.179-199). New York: Routledge.

Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Allyn and Bacon.

Taylor, I. M., Ntoumanis, N., & Standage, M. (2008). A self-determination theory approach to understanding the antecedents of teachers’ motivational strategies in physical education. Journal of Sport & Exercise Psychology, 30, 75-94.

Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. In M. P. Zanna (Ed.), Advances in experimental social psychology: Vol. 29 (pp. 271-360). New York: Academic Press.

Vallerand, R. J. (2001). A hierarchical model of intrinsic and extrinsic motivation in sport and exercise. In G. C. Roberts (Ed.), Advances in motivation in sport and exercise (pp. 263-320). Champaign, IL: Human Kinetics.

Vallerand, R. J., & Bissonnette, R. (1992). Intrinsic, extrinsic, and amotivational styles as predictors of behavior: A prospective study. Journal of Personality, 60, 599-620.

Vallerand, R. J., & Losier, G. F. (1999). An integrative analysis of intrinsic and extrinsic motivation in sport. Journal of Applied Sport Psychology, 11, 142-69.

Vansteenkiste, M., & Deci, E. L. (2003). Competitively contingent rewards and intrinsic motivation: Can losers remain motivated? Motivation and Emotion, 27, 273-99.

Vlachopoulos, S. P., Karageorghis, C. I., & Terry, P. C. (2000). Motivation profiles in sport: A Self-determination Theory perspective. Research Quarterly for Exercise and Sport, 71, 387-97.

Whitehead, J. R. (1993). Physical activity and intrinsic motivation. Physical Activity and Fitness Research Digest, 1, 1-8.

Wilson, P. M., & Rodgers, W. M. (2004). The relationship between perceived autonomy support, exercise regulations and behavioral intentions in women. Psychology of Sport and Exercise, 5, 229-242.

Wilson, P. M., Rodgers, W. M., Fraser, S. N., & Murray, T. C. (2004). Relationships between exercise regulations and motivational consequences in university students. Research Quarterly for Exercise and Sport, 75, 81-92.

2016-04-01T09:43:41-05:00October 7th, 2008|Contemporary Sports Issues, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on Motives for Sport Participation as Predictors of Motivation Outcomes in Track and Field: A Self-Determination Theory Perspective
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An Examination of Preservice Routines of Elite Tennis Players

Submitted by: Noah B. Gentner – Ithaca College, Theodore J. McGraw – University of Tennessee, Stephen Gonzalez and Daniel R. Czech – Georgia Southern University

Abstract

A preperformance routine may support consistent optimal performance. Preperformance routines’ benefits for closed skills are largely accepted, but effects of time and situational factors are little understood, nor have results of altering movements of preperformance routines been much studied. This observational study investigated preservice routines of 4 elite tennis players. Inconsistent with much prior research, the presence of a routine did not enhance performance in this study: Mean serving percentage measured 66% for players with routines, 69% for others. The findings do support Jackson (2003) and Jackson and Baker (2001), studies of rugby players forced to alter routines during competition. Observation of preservice routines and performance over several months at various tournaments may advance the research on this topic.

An Examination of Preservice Routines of Elite Tennis Players

The development and administration of a preperformance routine has been linked to optimal and consistent performances in many activities. Past research has shown the positive effects of preperformance routines in various sports, including tennis (Moore, 1986), golf (Cohn, Rotella, & Lloyd, 1990), bowling (Kirschenbaum, Ordman, Tomarken, & Holtzbauer, 1982), basketball (Czech & Burke, 2003; Lobmeyer & Wasserman, 1986; Wrisberg & Pein, 1992), and skiing (Orlick, 1986). Preperformance routines seem most beneficial within closed skill and self-paced tasks found in these sports, for example free-throw shooting in basketball, serving in tennis, kicking in football, and putting in golf.

Previous research has shown that preperformance routines can help athletes focus attention, enhance confidence, eliminate distractions, and reduce anxiety (Weinberg & Gould, 1995). Eliminating distractions and focusing attention creates an ideal state of concentration prior to performance; consistently replicating this state of concentration can create consistent performances (Schmidt & Peper, 1998). Focus and concentration allow for other psychological skills (i.e., visualization and relaxation) to be implemented during the preperformance routine, which helps block any external stressors and unwanted environmental stimuli (Schmidt & Peper, 1998). The ability to eliminate distractions before a performance may be the difference between a good athlete and a great one (Orlick, 1997).

Another benefit of preperformance routines is that they structure and organize the time leading up to a desired task, mentally preparing the athlete for the performance (Weinberg & Gould, 1995). For example, Crews and Boutcher (1987) observed the preperformance routines of golfers in the Ladies Professional Golf Association (LPGA), measuring the time taken for routines. Results indicated that all the golfers were automatic in their routines, starting and finishing with consistent and purposeful actions and completing their routines in a consistent amount of time. Purposeful behavior is key to consistent and effective performance during a preperformance routine. Foster, Weigand, and Baines (2006) studied free-throw shooters found to have superstitious behaviors and attempted to implement a preperformance routine among the athletes. Surprisingly, the effect of preperformance routines and of superstitious behavior differed little (performance worsened when neither was conducted before shooting). Purposeful behavior, whether based on superstition or on a structured preperformance routine, resulted in consistent and effective performances.

A preperformance routine can also help athletes reactivate appropriate physiological and mental processes before each shot, hit, service, or putt, increasing the chance of a successful performance (Schmidt, 1982). Boutcher and Zinsser (1990) studied the cardiac, respiratory behavior patterns of elite and nonelite golfers during a putting task. Elite golfers’ consistent preperformance routines resulted in slower breathing and heartbeats, indicating relaxation and focus on the task. Nonelite golfers lacked consistent preperformance routines and had higher heart rates. Physiologically, preperformance routines prepare the body for competition and sync mind and body for better control.

Some research argues that consistency of performance as a result of using a preperformance routine involves more than simply keeping the routine to a consistent time period. For example, Southard and Miracle (1993) conducted a study of female basketball players that manipulated how fast their free-throw routines occurred (time for the routine was doubled, was cut in half, etc.). Despite the manipulations of time, the results showed that the relative time to complete the routine did not vary, and that the rhythm of the routine was most important to successful performance.

While there is little argument about the positive effects of preperformance routines on closed skills, external variables make each skill unique, making necessary the investigation of various skills. Lobermeyer and Wasserman (1986), Gayton, Cielinski, Francis-Keniston, and Hearns (1989), and Wrisberg and Pein (1992) have investigated the effects of preshooting routines in basketball extensively, but the literature reflects little research on preservice routines in tennis (Moore, 1986). Additionally, little research is found on the effects of time and situation (i.e., winning or losing) on preperformance routines. Research shows that altering the movements of a preperformance routine can lead to poor or inconsistent performances (Gayton et al., 1989).

The purpose of this study was to investigate the preservice routines of 4 elite tennis players. Observation of the players was expected, ultimately, to yield visual identification of the presence of a preservice routine. Then, correlation would be sought between use of a preservice routine and successful service attempts.

Method

Participants

The participants in this study were 4 professional tennis players (2 men and 2 women) who were competitors belonging to the United States Tennis Association or the Women’s Tennis Association.

Procedure

Videotapes were viewed of 2 male participants playing in the Australian Open and 2 female participants playing in the Olympic Games. Data were collected during several matches in each tournament. To control for external variables, only first services were examined. The Preservice Routine Index (appendix) was developed to record data. Each researcher recorded data independently; then the data were compared and combined to produce a single set of final data to be used in analysis. Data discrepancies were discussed by the researchers until all felt comfortable with the data.

Collection of the data was initiated when a server placed his or her feet in their final ready position. For each service the following information was collected: server’s gender, server’s score in the game or match (i.e., leading or trailing the opponent), success of the service, and preservice routine. After several practice trials, racket position (low/high, horizontal/vertical) as well as number of times the player bounced the ball prior to serving were identified as the predominant variables in a preservice routine. These two elements were the most consistent and measurable preservice actions the players displayed. A minimum of 30 services were needed to determine the presence or absence of a preservice routine. A service was counted only if the server was fully visible from the time he or she set his or her feet until the final service motion was initiated.

Data Analysis

The first step of data analysis was identification of a preservice routine. Each player’s preservice data was examined to determine whether or not a consistent routine was present. Looking at the data, the researchers established for each player his or her most common racket position and the typical number of bounces used prior to a service. These comprised the player’s preservice routine, which in this study had to precede at least 80% of a player’s services in ordered to be considered a consistent preservice routine. Players who did not follow the identified routine at least 80% of the time were assigned to one of two groups in the study, the nonroutine group.

For each player, the researchers calculated the percentage of services (over all 30 trials) featuring the identified preservice routine. Restricting the calculation to first services only, they also computed the serving percentages for the entire tournament, in an effort to balance effects of emotion across “good” and “bad” matches. The serving percentages were compared by gender and by group (routine, RG, or nonroutine, NRG). Use or omission of a routine by players in the routine group was evaluated in the context of the player’s score (game and match) at the time of each service.

Results

Only one study participant, Player 1, could be assigned to the routine group; the remaining players showed limited consistency of preservice actions. Player 1 used a preservice routine 83% of the time and had an overall serving percentage of 66% over the entire tournament. Player 2’s use of a preservice routine had the second-highest rate of consistency, 67%. Players in the nonroutine group had an overall successful serving percentage of 69%: Player 2 was successful 65% of the time; Player 3, 78% of the time; and Player 4, 63% of the time. Overall for the tournament, the routine group had a mean serving percentage of 66%, while the nonroutine group had a mean serving percentage of 69%.

One of the two men in the sample had a detectable preservice routine, while neither of the women had a detectable routine. Mean serving percentage for the men was 65%; for the women, mean serving percentage was 70%.

Finally, the participant who used a detectable preservice routine seemed to do so more frequently when he trailed, rather than led, his opponent in either the game or match. Player 1 followed his routine 100% of the time when he was losing a game and 82% of the time when he was losing a match. He followed his routine 72% of the time when he was winning a game and 68% of the time when he was winning a match.

Discussion

In light of the performance benefits research shows to derive from a preperformance routine, the studied elite tennis players’ lack of consistency in using such routines was unexpected. The findings could be explained in three ways. First of all, research suggests that preperformance routines can be cognitive in nature. Imagery and self-talk are two examples of mental skills that could play a very important role in the preperformance routine (Wrisberg & Anshel, 1989). Cognitive preperformance strategies may or may not have constituted significant elements of our participants’ preservice rituals. With videotape observation the sole means of data collection, cognitive routines were undetectable. It is quite possible that the presence or absence of a cognitive strategy influenced effects of the psychomotor aspects of positioning the racket and bouncing the ball. For example, Player 3’s high percentage of successful services could have been supported by focused, consistent use of imagery before each service. Future research on preservice routines definitely should include interviews aimed at understanding players’ preservice cognitive strategies.

A second explanation of our study’s findings is the limited time span of the play we observed. Relatively unchanged situational factors from match to match may have positively or negatively affected the data. For instance, perhaps one of the study participants had an injury affecting performance. In addition, it was unknown whether any players used a specific number of preservice bounces, a number that might have changed during the rest of the tournament. Our findings are interesting, given that traditional research focuses on consistency of the preperformance routine, and they support previous findings reported in Jackson (2003) and Jackson and Baker (2001). Jackson and Baker (2001) studied professional rugby players in a highly competitive environment and found that preperformance routines were often altered during competition due to factors beyond players’ control (i.e., time running out, players out of position, speeding or delaying in response to others, and the like). Future research should include several months of observation of the participants’ services, involving a variety of different tournaments. An expanded time frame would help control such external variables as injuries, skill constraints, and development of the preservice routine.

A final explanation for the discrepancy between participants’ behavior reflected in this study and in earlier research findings on preperformance routines is that in tennis, serving may not be positively affected by a preperformance routine. While earlier researchers have found a positive correlation between free-throw success and preshooting routines, it is entirely possible that environmental, physiological, and psychological aspects of closed skills from basketball and closed skills from tennis differ enough to drastically affect the results of a preperformance routine. But this is unlikely. In our study Player 1, whom we observed to employ a consistent preservice routine, is consistently ranked (by the United States Tennis Association) among the best tennis players and servers in the world. Individual differences must also be taken into account. Preservice routines are as unique as the players who use them, meaning each routine’s benefits are likely to be unique as well.

One strength of our study is that the services were observed in the most elite competitive venues. Player 1 and Player 2 were videotaped competing in a grand slam competition; Player 3 and Player 4 were videotaped contending for Olympic gold. Environmental distractions during each of these tournaments were significant. In addition, it can be assumed that each player tried his or her best to serve successfully in each observed trial. Many consider first-service success an important component of elite competitive tennis. Such anecdotal evidence can certainly be challenged, but it is useful to consider. Future research might also explore the benefits of a preservice routine to second services.

References

Boutcher, S. H., & Zinsser, N. (1990). Cardiac deceleration of elite and beginning golfers during putting. Journal of Sport and Exercise Psychology, 12, 37-47.

Cohn, P. J., Rotella, R. J., & Lloyd, J. W. (1990). Effects of a cognitive-behavioral intervention on the preshot routine and performance in golf. The Sport Psychologist, 4, 33-47.

Crews, D. J., & Boutcher, S. H. (1987). An exploratory observational behavior analysis of professional golfers during competition. Journal of Sport Behavior, 9, 51-58.

Czech, D. R. & Burke, K. L. (2003). An examination of the maintenance of pre-shot routines in basketball free throw shooting. Journal of Sport Behavior, 3, 23-32.

Foster, D. J., Weigand, D. A., & Baines, D. (2006). The effect of removing superstitious behavior and introducing a preperformance routine on basketball free-throw performance. Journal of Applied Sport Psychology, 18, 167-171.

Gayton, W. F., Cielinski, K. L., Francis-Keniston, W. J., & Hearns, J. E. (1989). Effects of pre-shot routine on free-throw accuracy of intercollegiate female basketball players. Journal of Sport Psychology, 5, 343-346.

Jackson, R. C. (2003). Preperformance routine consistency: Temporal analysis of goal kicking in the Rugby Union World Cup. Journal of Sport Sciences, 21, 803-814.

Jackson, R. C., & Baker, J. S. (2001). Routines, rituals, and rugby: Case study of a world class goal kicker. Sport Psychologist, 15, 48-65.

Kirschenbaum, D. S., Tomarken, A. J., & Ordman, A. M. (1982). Specificity of planning and choice in adult self-control. Journal of Personality and Social Psychology, 41, 576-585.

Lobmeyer, D. L., & Wasserman, E. A. (1986). Preliminaries to free-throw shooting: Superstitious behavior? Journal of Sport Behavior, 9, 70-78.

Moore, W. E. (1986). Covert-overt service routines: The effects of a service routine training program on elite tennis players. Unpublished doctoral dissertation, University of Virginia.

Orlick, T. (1986). Psyching for sport: Mental training for athletes. Champaign, IL: Leisure Press.

Orlick, T. (1997). In pursuit of excellence (3rd ed.). Champaign, IL: Leisure Press.

Schmidt, A., & Peper, E. (1998). Strategies for training. In J. Williams (Ed.), Applied sport psychology: Personal growth to peak performance (pp. 316-328). Mountain View, CA: Mayfield.

Schmidt, R. A. (1982). Motor control and learning. Champaign, IL: Human Kinetics.

Southard, D., & Miracle, A. (1993). Rythmicity, ritual, and motor performance: A study of free throw shooting in basketball. Research Quarterly for Exercise and Sport, 3, 284-290.

Weinberg, R. S., & Gould, D. (1995). Foundations of Sport and Exercise Psychology, Champaign, IL: Human Kinetics.

Wrisberg, C. A., & Anshel, M. H. (1989). The effect of cognitive strategies on free throw shooting performance of young athletes. The Sport Psychologist, 3, 95-104.

Wrisberg, C. A., & Pein, R. L. (1992). The pre-shot interval and free throw shooting accuracy: An exploratory investigation. The Sport Psychologist, 6, 14-23.

2013-11-25T21:17:08-06:00October 7th, 2008|Sports Exercise Science, Sports Management|Comments Off on An Examination of Preservice Routines of Elite Tennis Players
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Music in Sport and Exercise : An Update on Research and Application

Submitted by: Costas Karageorghis and David-Lee Priest – Brunel University

Abstract

In spring 1999, almost a decade ago, the first author published in The Sport Journal an article titled “Music in Sport and Exercise: Theory and Practice.” The present article’s origins are in that earlier work and the first author’s research while a master’s student at the United States Sports Academy in 1991–92. To a greater degree than in the original 1999 article, this article focuses on the applied aspects of music in sport and exercise. Moreover, it highlights some new research trends emanating not only from our own publications, but also from the work of other prominent researchers in the field. The content is oriented primarily towards the needs of athletes and coaches.

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2016-10-20T13:47:06-05:00July 7th, 2008|Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on Music in Sport and Exercise : An Update on Research and Application
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Active Versus Passive Recovery in the 72 Hours After a 5-km Race

Submitted by: Andy Bosak – West Virginia Wesleyan College; Phil Bishop and Matt Green – University of Alabama; Mike Iosia – Lee University

Abstract

We do not clearly understand what type and duration of recovery works best after a hard run to restore the body to peak racing condition. This study compared 72 hr of active recovery after a 5-km running performance with 72 hr of passive recovery. A sample of 9 male and 3 female runners of above-average ability completed 3 trials within 6 days. Each 5-km trial was followed by 72 hr of passive recovery (PAS) or 72 hr of active recovery (ACT), a counterbalanced protocol. The 2 initial 5-km trials constituted separate PAS and ACT baselines. Mean finishing times did not differ significantly (p = 0.17) between ACT (19:35 + 1.5 min) and baseline (19:41 + 1.7 min); nor was there significant difference (p = 0.21) between PAS (19:30 + 1.5 min) and baseline (19:34 + 1.6 min). Average heart rate for PAS (177.9 + 6.3 b/min) was significantly higher (p = 0.04) than baseline (175.4 + 6.5 b/min), but ACT average heart rate (175.9 + 6.6 b/min) was significantly lower (p = 0.02) than baseline (178.9 + 6.4 b/min). For PAS, perceived rate of exertion at ending (19.8 + 0.6) was significantly greater (p = 0.01) than baseline (19.3 + 0.9), yet for ACT, perceived rate of exertion at ending (19.6 + 0.8) did not differ significantly (p = 0.17) from baseline (19.7 + 0.7). During PAS trials, 2 individuals ran a mean 12.0 + 2.8 s slower, 2 individuals ran a mean 33.0 + 21.0 s faster, and 8 individuals ran within 5.1 + 2.5 s of their first run. During the ACT trials, 1 participant ran 13.0 s slower, 3 participants ran a mean of 34.7 + 13.5 s faster, and 8 nonresponders ran within 5.5 + 2.7 s of baseline. Results indicate that 72 hr of passive and active recovery result in similar mean 5-km performance.

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2016-10-19T11:20:16-05:00July 7th, 2008|Sports Coaching, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off on Active Versus Passive Recovery in the 72 Hours After a 5-km Race
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