Weightlifting during the COVID-19 Pandemic—A Transnational Study Regarding Motivation, Barriers, and Coping of Master Athletes
Bibliographic record
Abstract
Sport has been heavily impacted by the pandemic for over a year with restrictions and closures of facilities. The main aims of this study are to identify motivation and barriers for an international group of Master weightlifters (ages 35 and up) and analyze age and gender differences in pandemic-related changes to physical activities. A sample of 1051 older athletes, 523 women and 528 men, aged from 35 to 88 years, from Australia, Canada, Europe, and the USA provided responses to an online survey conducted in June 2021. A confirmatory factor analysis was performed to examine age, gender, and regional differences about motivation, barriers, and pandemic impact on sport and physical activities. Participants showed enthusiasm for the opportunity to compete despite health challenges with increasing age but faced barriers due to access to training facilities and qualified coaches even before the pandemic. The oldest athletes had the greatest reduction in physical activities during the pandemic. Weightlifters had the opportunity to compete in virtual competitions and 44% would like to see some of these continued in the future, especially women. These findings highlight the benefits of competitive sports and may provide future directions in strength sports for organizations, sports clubs, and coaches.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".