Acute effect of <scp>S</scp>nus on physical performance and perceived cognitive load on amateur footballers
Bibliographic record
Abstract
Smokeless tobacco (Snus) is a substance that contains nicotine, which has been placed on World Anti-Doping Agency's 2014 Monitoring Program. A proliferation of nicotine use in sport has been observed in recent years, but little is known regarding its effects, especially on football players' performance. Therefore, the aim of this study was to assess the effect of Snus on physical performance, heart rate variability, subjective activation, mental fatigue, and perceived readiness before a physical test in non-smoker, non-Snus user, amateur football players. Participants were administered either Snus or placebo 40 min prior to a fitness test battery (handgrip test, countermovement jump, agility test, and Yo-Yo intermittent recovery test). Results showed that Snus intake (compared with placebo) increased perceived mental fatigue level and mental load, and reduced perceived readiness level and heart rate variability. No significant differences between the two experimental conditions were found in either performance in the physical tests or perceived physical fatigue levels. In light of these results, Snus could not be considered an ergogenic substance. On the contrary, based on the extant evidence linking mental load and fatigue with physical performance, we argue that the observed negative effects on mental fatigue, perceived readiness, and heart rate variability should be considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".