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Record W1609600546

Energy drinks' effects on student-athletes and implications for athletic departments.

2008· article· en· W1609600546 on OpenAlexaboutno aff
Russ Paddock

Bibliographic record

VenueThe Sport Journal · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsAthletesPsychologyElite athletesBinge drinkingMedical educationMarketingAdvertisingMedicineApplied psychologyEnvironmental healthBusinessSuicide preventionPoison controlPhysical therapy
DOInot available

Abstract

fetched live from OpenAlex

Drinks' Effects on Student-Athletes and Implications for Athletic Departments The worldwide market for so-called 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 drinks. Caffeine is the main energy ingredient in 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 drinks within a training regime may be one such strategy. Many of the marketing campaigns explicitly state that an 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 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 Drink 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 Drinks, n.d., Background section, [paragraph] 2). Whatever their intended use and purported benefits, consumers today consume 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 drinks. The term drink suggests activity, and the uninformed consumer may assume that such a drink would support physical exercise. Locating 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 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 drink phenomenon, was first distributed in the 1980s (Retelny, 2007). Jolt was not marketed as a medicinal health product as, to an extent, drinks are. But like drinks, it was and is laden with caffeine. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.312
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2008
Admission routes1
Has abstractyes

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