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Record W1936554457 · doi:10.1111/sms.12377

Nutritional supplement and doping use in sport: Possible underlying social cognitive processes

2014· article· en· W1936554457 on OpenAlexfundno aff
Vassilis Barkoukis, Lambros Lazuras, Fabio Lucidi, Haralambos Tsorbatzoudis

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsCognitionPsychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

There is growing evidence suggesting that nutritional supplement (NS) use is strongly associated to doping use in elite and amateur sports. However, there is a paucity of research on the psychological processes that underlie this association. The present study investigated the cognitive and behavioral components of the association between NS use and doping among adolescent sub-elite athletes. Six hundred and fifty adolescent athletes completed a questionnaire including measures of doping intentions, attitudes, norms, and beliefs about NS use. The results showed that NS users who did not report doping use had significantly stronger doping intentions and more positive attitudes and favorable beliefs toward doping use, as compared with athletes who did not use NS. In support of the "shared mental representations" hypothesis, the present findings show that NS use is associated with biased reasoning patterns in favor of doping use. This mechanism may explain why some NS users decide to engage in doping.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.368
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), 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

Citations61
Published2014
Admission routes1
Has abstractyes

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Same venueScandinavian Journal of Medicine and Science in SportsSame topicDoping in SportsFrench-language works237,207