A-01 Trait Mindfulness Gains Associated with Executive Functioning Improvements Following Physical Exercise in Older Adults
Bibliographic record
Abstract
Abstract Purpose Although there are certain injury risks associated with sports participation (e.g., concussion), there are also neuropsychological benefits relating to physical activity. Evidence suggests that trait mindfulness (TM) may contribute to the neuropsychological benefits of physical activity and exercise, including those pertaining to executive functioning (EF) and mood. The present study aimed to investigate the degree to which changes in TM accounted for changes in neuropsychological functioning following a remote physical exercise training program for older adults. It was hypothesized that increases in TM would predict improvements in self-reported EF and symptoms of depression and anxiety. Methods As part of a larger RCT, 43 older adults (70% females, 65-81 years-old) from across Canada completed an online assessment measuring TM, EF, and mood before and after engaging in an 8-week remote physical exercise training program. Results Linear regression analyses showed that pre-post changes in TM explained a significant proportion of variance in self-reported changes in EF, r2=.18, F(1,24)=5.11, p<.05, but did not for symptoms of depression, r2=.06, F(1,24)= 1.53, p= 23 or anxiety, r2=.04, F(1,24)=1.08, p=.31. More specifically, bivariate correlations demonstrated that gains in TM were significantly associated with increases in reported impulse control, r=.48, p=.01, and empathy, r=.42, p<.05. Conclusions These results suggest that for older adults engaging in exercise, gains in trait mindfulness may be associated with benefits to certain aspects of executive functioning. These findings also invite sports neuropsychologists to consider level of mindfulness when evaluating individuals (e.g., athletes) engaged in exercise.
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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 | 0.002 |
| 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 | 0.000 |
| 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".