Perceived Exertion during Moderate and Vigorous Physical Activity While Mask Wearing: A Quantitative and Qualitative Pilot Study
Bibliographic record
Abstract
There is limited research examining the perception of exertion during exercise while wearing a facemask. The current study examined if mask usage during moderate or vigorous physical activity (MVPA) changed the self-reported perception of exertion. Seventy-two adults (18 years and older) who were physically active before the COVID-19 pandemic completed a questionnaire that assessed exercise habits and perceptions of mask wearing during MVPA. Participants reported their ratings of perceived exertion (RPE, on a scale of 1−10) while exercising. Wearing a mask resulted in higher RPE vs. no mask during both vigorous (8.4 ± 0.2 vs. 7.4 ± 0.1; p < 0.001) and moderate PA (6.6 ± 0.2 vs. 5.6 ± 0.2; p < 0.001). Qualitative analysis revealed mostly negative perceptions of exercising while wearing a mask, including respiratory issues, detriments to cardiovascular endurance, and general discomfort. A total of 40% of participants reported that they stopped exercising in an indoor/public setting because of a mask mandate in their region. Participants reported participating in less vigorous PA (4.7 ± 0.4 vs. 4.0 ± 0.4 h/week; p = 0.046), but not less moderate PA (3.3 ± 0.3 vs. 3.0 ± 0.3 h/week; p = 0.443) pre vs. during the pandemic. Our study suggests that facemask usage during MVPA causes an increase in RPE and may be one reason for a decrease in vigorous PA 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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".