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Record W2924856144 · doi:10.5539/gjhs.v11n5p1

Knowledge Towards Energy Drinks Consumption and Related Factors Among Young Male Athletes in the United Arab Emirates

2019· article· en· W2924856144 on OpenAlexvenueno aff
Aisha A. Almulla, Hadia Radwan, Nada Al Adeeb

Bibliographic record

VenueGlobal Journal of Health Science · 2019
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAthletesMedicineClubConsumption (sociology)Young adultCross-sectional studyDemographyEnvironmental healthGerontologyPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVES: We aim to investigate the knowledge towards Energy Drinks (EDs) consumption and related factors among young male athletes in the United Arab Emirates (UAE). SUBJECTS & METHODS: A cross-sectional study included 688 young male athletes from Al Ain sports club aged between 7 to 18 years. Data were collected using a modified version of a validated questionnaire from the European Food Safety Authority. RESULTS: Overall EDs consumption was 24%. About 44% of the athletes consumed EDs one to two times per month. Athletes who were training between 5-7 days per week consumed significantly more EDs compared to those who were training 3-4 days per week (81% vs. 15 %, P<0.001). Athletes aged 7-12 years were 2.4 times more likely to consume EDs than athletes aged 13-18 years (P<0.001). Moreover, athletes living with both parents were significantly less likely to consume EDs compared to those living with a single parent (P=0.01). Knowledge score about EDs consumption was significantly higher for non EDs consumers compared to EDs consumers (P<0.001). CONCLUSIONS: EDs consumption among young male athletes was moderate. Educational programs are needed to increase the awareness regarding EDs consumption and its potential adverse effects among the young athletes. A regulation policy for EDs consumption should be addressed and consideration of labels with EDs contents and age identification is highly recommended.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.044
GPT teacher head0.365
Teacher spread0.321 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2019
Admission routes1
Has abstractyes

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