Isokinetic Muscle Strength and Postural Sway of Recreationally Active Older Adults vs. Master Road Runners
Bibliographic record
Abstract
Trunk muscle strength and control is an important prerequisite for everyday activities among elderly people decreasing the predisposition to falls. High levels of physical exercise performed by older athletes could offer benefits to core/trunk muscle strength and postural control compared with recreational physical activities and among elderly people with lower levels of physical activity. The present study aimed to compare trunk muscle strength and postural control of older running athletes vs. older physically active adults. Participants were master road runners (RUN, n = 15, six women, 64.3 ± 3.6 years) and physically active elderly (control group, CON, n = 15, six women, 65.4 ± 5.0 years) people that were submitted to the evaluations: esthesiometer, posturography (force plate), and isokinetic test (Biodex dynamometer) of trunk muscle extension and flexion. RUN presented higher values for relative peak torque of trunk extensor muscles at 60°/s (p = 0.046) and 180°/s (p = 0.007) and relative average power during trunk extension at 60°/s (p = 0.008) and 180°/s (p = 0.004) compared to CON. CON had a higher medial-lateral oscillation speed of the center of pressure in the stable condition with eyes closed (p = 0.004) compared to RUN. RUN presented higher isokinetic torque of extensor trunk muscles and better postural control than CON. This supposedly could help with postural control and balance and contribute to the prevention of falls among the elderly. The practice of running systematically by master athletes may partially explained our findings.
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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 | 0.000 | 0.000 |
| 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".