Changes to physical activity behavior during the COVID-19 pandemic and their associated factors: a cross sectional survey of Mexican women
Bibliographic record
Abstract
BACKGROUND: On March 24, 2020, the Mexican Government established social distancing measures to address the outbreak of the COVID-19 pandemic. The resulting home confinement affected daily lifestyle habits such as eating, sleeping, and physical activity (PA). The objectives of this study were to determine changes in PA behaviors among Mexican women due to the COVID-19 pandemic and to assess potential factors associated with these changes. METHODS: This was a cross-sectional study based on an anonymous online questionnaire developed by the Task Force on Physical Activity for Persons with Disabilities (PAPD) within the International Society of Physical and Rehabilitation Medicine (ISPRM). Descriptive, quantitative statistics were used for data analysis. A Chi-squared (χ²) test was used to explore associations between dependent and independent variables. RESULTS: A total of 1882 surveys were completed. Among the respondents, 53.3% declared that their PA was reduced during the pandemic, 26.6% reported similar PA behavior, and 20.1% declared that their PA had increased during the pandemic. Lower PA behavior during the pandemic was associated with lower education levels, stricter pandemic constraints, obesity, and lower self-perceived functioning levels. A statistically significant association between poorer self-perceived mental health and decreased PA behaviors was also found. Respondents who were younger, self-perceived as unimpaired, not overweight, and whose income was not impacted by COVID-19 were associated with higher levels of reported physical and mental health. CONCLUSIONS: The study results identify disparities experienced in PA behavior during the COVID-19 pandemic among Mexican women and highlights the need for social support for PA participation.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".