Impact of social isolation on the level of physical activity in young Brazilian athletes caused by COVID-19
Bibliographic record
Abstract
BACKGROUND: Social detachment to prevent the spread of the COVID-19 pandemics in the year 2020 can significantly contribute to the physical inactivity of citizens worldwide. The study aimed to analyze the level of physical activity by identifying the training methods used during the social isolation resulting from the COVID-19 pandemic. METHODS: Sixty-eight Brazilian athletes (both sexes, 14.7±1.68 years) answered and adapted the International Physical Activity Questionnaire (I-PAQ) through an online platform. Participants were asked to report their level of physical activity before and during the period of social distance. RESULTS: According to our results, 67.7% of the interviewed athletes said they were able to adapt their sports training to the isolation environment under the guidance of a distance physical education professional. Only 4.38% of the sample was not training under such supervision and, therefore, inactive. Among the activities performed in the isolation environment, calisthenics was the primary practice (effect size: ƒ2=0.50, P<0.0001) and the sport practiced at home was the secondary practice (effect size: ƒ2=0.27, P=0.004). During the pandemic, the training hours of athletes reduced significantly from ~3h to ~1h per day (effect size: 1.74, P<0.0001), as well as the perceived intensity decreased from "high" to "moderate" (effect size: 1.38, P<0.0001). The weekly training frequency decreased from ~6 to 7 days to ~3 to 5 days (effect size: 0.40, P=0.03). CONCLUSIONS: Despite the social distance and the reduced pace of training, the young Brazilian athletes analyzed managed to remain physically active during the COVID-19 pandemic.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".