Protein Supplement Users Among High School Athletes Have Misconceptions About Effectiveness
Bibliographic record
Abstract
Protein supplements commonly are ingested by athletes to improve strength, agility, and speed. While athletes require a higher amount of protein (g.kg body weight) than nonathletes do to support protein synthesis, they do not necessarily need to consume protein from supplemental sources. To date, no studies have shown an advantage of ingesting protein supplements over natural, protein-containing foods; therefore, dietary sources of protein may be just as effective as protein supplemental sources in the regulation of muscle protein synthesis. Misconceptions regarding protein supplement effectiveness may originate from athletes' nutrition information sources. A survey questionnaire queried high school football players about sources of information and measured protein supplement misconceptions by using scores on a Protein Supplement Misconceptions Index. Sixty-one high school football players participated in the study; 39 were protein supplementers, and 22 were non-protein supplementers. There was a significant difference between index scores of protein supplementers and non-protein supplementers (t = -3.4, p = 0.001), indicating that protein supplementers had a greater level of misconceptions than non-protein supplementers did. Bonferroni post hoc procedures used with individual index items revealed that protein supplementers were more likely than non-protein supplementers to agree that "athletes should take protein supplements" (p = 0.001) and needed them "to gain as much muscle as possible" (p = 0.001). Greater misconceptions for protein supplementers may have resulted from the sources chosen for information and advice. Since coaches, parents, and friends were the primary sources of advice about protein supplements for protein supplementers, it would be valuable to provide nutrition education to these groups concurrently with educating young athletes to dispel ongoing misconceptions regarding the need for and effectiveness of protein supplements.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".