Investigating the role of mindfulness in the relationship between physical activity and mental health
Bibliographic record
Abstract
Regular physical activity minimizes the deleterious effects of stress on the body and mind to protect against stress-related mental health issues. Regular physical activity also promotes mindfulness—a mental state of non-judgmental, present-oriented attention, and this may further augment the mental health benefits of being physically active. The present study examined the role of mindfulness as a moderator of the association between physical activity and stress reactivity. Sedentary and recreationally active university students (N = 28) completed questionnaires of physical activity, mindfulness, and mental health. We experimentally induced a stress response using the Trier Social Stress Test (TSST) and measured its impact on physiological (heart rate) and psychological (state anxiety) reactivity. Participants were stratified by physical activity level and by mindfulness for subsequent analyses. Preliminary results reveal that highly active participants were more mindful than their less active counterparts (p = 0.02). They also had lower physiological stress reactivity to the TSST, as indicated by lower maximum and average heart rates (p < 0.01). Moreover, participants who were both highly active and highly mindful exhibited less depression (p = 0.004), anxiety (p = 0.03), and stress (p = 0.01), and experienced less psychological stress reactivity to the TSST, as indicated by trends toward lower state anxiety before, during, and after the stressor. The results suggest that mindfulness may moderate the association between physical activity and stress reactivity, and point to the promise of interventions that combine physical activity and mindfulness training to reduce stress and improve mental health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".