Boston Marathon Athlete Self-Reported Nutrition And Hydration Information Source Utilization
Bibliographic record
Abstract
PURPOSE: To describe current trends in endurance athletes’ information resource utilization for education around nutrition and hydration in preparation for participation in a community-based marathon event. METHODS: Institutional Review Board approval was obtained. Athletes ≥18 yrs registered for the 2022 Boston Marathon were recruited to complete an online Informed Consent and pre-race survey. Survey link was included in a weekly email newsletter sent by the event host organization to all registrants 4 wks pre-race. Survey included 2 separate questions on: “what resources, professionals, and/or media types they referenced for information in preparation for the marathon” for nutrition and for hydration. Question stems directed athletes to “check all that apply,” with option to indicate “I did not consult any resources.” RESULTS: 1,030 athletes (F: 546, M: 484) completed the survey (response rate: 3.6%). Mean age 47.2 ± 13.1 years, range (19-88 yrs). Self-reported information sources are summarized for nutrition (Table 1) and hydration (Table 2). CONCLUSION: Approximately half of study participants reported utilizing no resources for education on nutrition (49.5%) or hydration (58.8%) during marathon preparation, followed by online resources. These findings highlight opportunities to further optimize outreach and education on both nutrition and hydration among marathon athletes. Table 1. - Nutrition information sources utilized by study participants in preparation for marathon Information Source Category Utilization forNutrition Informationn (%) “I did not consult any resources” 523 (49.5%) Online resources (e.g. news, editorials, blogs) 223 (21.1%) Scientific publications (e.g. journals, books) 187 (17.7%) Audio programs (e.g. podcasts, radio) 129 (12.2%) Coach 122 (11.6%) Social media 121 (11.5%) Sports Dietitian 106 (10.0%) Information provided by event host organization 95 (9.0%) Medical Doctor 42 (4.0%) Television, film, documentaries 41 (3.9%) Educational conferences 21 (2.0%) Chiropractor 19 (1.8%) Disordered eating specialist 11 (1.0%) Naturopath/Herbalist 5 (0.5%) Sports scientist 4 (0.4%) Other 58 (5.5%) Table 2. - Hydration information sources utilized by study participants in preparation for marathon Information Source Category Utilization forNutrition Informationn (%) “I did not consult any resources” 621 (58.8%) Online resources (e.g. news, editorials, blogs) 178 (16.9%) Coach 134 (12.7%) Scientific publications (e.g. journals, books) 113 (10.7%) Social media 93 (8.8%) Information provided by event host organization 83 (7.9%) Audio programs (e.g. podcasts, radio) 75 (7.1%) Sports Dietitian 70 (6.6%) Medical Doctor 19 (1.8%) Television, film, documentaries 21 (2.0%) Educational conferences 13 (1.2%) Chiropractor 6 (0.6%) Disordered eating specialist 2 (0.2%) Naturopath/Herbalist 1 (0.1%) Sports scientist 10 (0.9%) Other 36 (3.4%) Joe and Clara Tsai Foundation as part of the Wu Tsai Human Performance Alliance; Eleanor and Miles Shore Faculty Development Awards Program, Harvard Medical School: Boston Children's Hospital Department of Orthopaedic Surgery and Sports Medicine Award
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".