Five-repetition sit-to-stand test performance by community-dwelling adults: A preliminary investigation of times, determinants, and relationship with self-reported physical performance
Bibliographic record
Abstract
The 5-repetition sit-to-stand (STS) test is a widely used, but insufficiently evaluated, test for lower limb strength. We therefore described STS test times for a sample of community-dwelling adults, examined the association of age, gender, height, weight, and body mass index (BMI) with STS time, and determined the relationship of STS time with self-reported physical functioning. Ninety-four community dwelling adults participated. Repeated measures of STS time were reliable (intraclass correlation coefficient =0.957). The mean STS time for all 94 subjects was 7.6 seconds. Age, weight, and BMI were (r=0.281–0.528), but gender and height were not(r=−0.074–0.007), correlated significantly with STS time. Regression analysis showed that age and BMI explained 43.7 percent of the variance in STS time. The correlation between STS time and physical functioning r=−0.474) was significant (p<0.001). Regression analysis showed that age and BMI added slightly to the explanation of variance in physical functioning provided by STS time. In conclusion, this study provides STS times that might be useful for interpreting performance of adults screened with the test. Such performance should be considered in light of age and BMI. The relationship of STS time with physical functioning provides evidence of the validity of the measure.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".