A Mental Health Paradox: Mental health was both a motivator and barrier to physical activity during the COVID-19 pandemic
Bibliographic record
Abstract
Abstract The COVID-19 pandemic has impacted the mental health, physical activity, and sedentary behavior of citizens worldwide. Using an online survey with 1669 respondents, we sought to understand why and how by querying about perceived barriers and motivators to physical activity that changed because of the pandemic, and how those changes impacted mental health. Consistent with prior reports, our respondents were less physically active (aerobic activity, −11%, p <0.05; strength-based activity, −30%, p <0.01) and more sedentary (+11%, p <0.01) during the pandemic as compared to 6-months before. The pandemic also increased psychological stress (+22%, p <0.01) and brought on moderate symptoms of anxiety and depression. Respondents’ whose mental health deteriorated the most were also the ones who were least active (depression r = −.21, p <0.01; anxiety r = −.12, p <0.01). The majority of respondents were unmotivated to exercise because they were too anxious (+8%, p <0.01), lacked social support (+6%, p =<0.01), or had limited access to equipment (+23%, p <0.01) or space (+41%, p <0.01). The respondents who were able to stay active reported feeling less motivated by physical health outcomes such as weight loss (−7%, p <0.01) or strength (−14%, p <0.01) and instead more motivated by mental health outcomes such as anxiety relief (+14%, p <0.01). Coupled with previous work demonstrating a direct relationship between mental health and physical activity, these results highlight the potential protective effect of physical activity on mental health and point to the need for psychological support to overcome perceived barriers so that people can continue to be physically active during stressful times like the 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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".