The Unsupported Upper Limb Exercise Test in People Without Disabilities: Assessing the Within-Day Test–Retest Reliability and the Effects of Age and Gender
Bibliographic record
Abstract
Purpose: To estimate the within-day test–retest reliability and standard error of measurement (SEM) of the unsupported upper limb exercise test (UULEX) in adults without disabilities and to determine the effects of age and gender on performance of the UULEX. Method: A cross-sectional study was conducted with 100 adults without disabilities (44 men, mean age 44.2 [SD 26] y; 56 women, mean age 38.1 [SD 24.1] y). Participants performed three UULEX tests to establish within-day reliability, measured using an intra-class correlation coefficient (ICC) model 2 (two-way random effects) with a single rater (ICC[2,1]) and SEM. The effects of age and gender were examined using two-factor mixed-design analysis of variance (ANOVA) and one-way repeated-measures ANOVA. For analysis purposes, four sub-groups were created: younger adults, older adults, men, and women. Results: Excellent within-day reliability and a small SEM were found in the four sub-groups (younger adults: ICC[2,1]=0.88; 95% CI: 0.82, 0.92; SEM∼40 s; older adults: ICC[2,1]=0.82; 95% CI: 0.72, 0.90; SEM∼50 s; men: ICC[2,1]=0.93; 95% CI: 0.88, 0.96; SEM∼30 s; women: ICC[2,1]=0.85; 95% CI: 0.78, 0.91; SEM∼45 s). Younger adults took, on average, 308.24 seconds longer than older adults to perform the test; older adults performed significantly better on the third test (p<0.0001; η 2 =0.096). Gender effects were not found (p>0.05). Conclusion: The within-day test–retest reliability and SEM values of the UULEX may be used to define the magnitude of the error obtained with repeated measures. One UULEX test seems to be adequate for younger adults to achieve reliable results, whereas three tests seem to be needed for older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".