Reproducibility of dynamometers in handrail format in evaluating handgrip strength and traction in young and older adults
Bibliographic record
Abstract
BACKGROUND: The aim of the present study was twofold: (1) to assess the reproducibility of two dynamometers in handrail format to measure handgrip strength and traction force in the young and older adults; (2) to compare the handgrip strength and traction of these two populations. APPROACH: Twenty-four volunteers (12 older adults and 12 young adults) performed a functional effort related to handgrip strength and traction force during stair climbing. The participants were evaluated two times (separated by one week) using a coupled dynamometer that quantifies the muscular effort in grip and traction simultaneously to simulate stair climbing in bus service. RESULTS: The young adults performed significantly better (p < 0.04) than the older adults in both handgrip and traction efforts (medium to large effect size), with excellent reliability (Intraclass Coefficient Correlation > 0.9) and low error of measure. The dynamometers were able to discriminate the two population groups (sensitive validity) and showed excellent reproducibility estimates for handgrip and traction strength in both young and older adults. CONCLUSION: These instruments could be useful in assessing handgrip and traction strength needed to climb stairs, especially for the older adults, who normally have more difficulty performing this task.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".