Reliability and Minimal Detectable Change Values for Performance-Based Measures of Physical Functioning in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine the relative and absolute reliabilities of 5 key performance-based measures of physical function in the Canadian Longitudinal Study on Aging (CLSA). METHODS: An age-stratified subsample of 147 participants from the CLSA who were undergoing their 3-year data collection visit participated in 2 repeat visits (within 1 week). Participants underwent tests of grip strength, 4-m gait speed, Timed Up and Go (TUG), chair rise, and single-leg stance (left, right, mean, maximum). Intraclass correlation coefficients (ICCs), standard error of measurement, and minimal detectable change (MDC) values were calculated. RESULTS: The relative reliability for grip strength was excellent (ICC = 0.95); the TUG and single-leg stance tests had good reliability (ICC = 0.80 or 0.78-0.82, respectively); gait speed and the chair-rise test had moderate reliability (ICC = 0.64 for both) for participants overall. For participants between 50 and 64 years, TUG and gait speed had poor reliabilities (ICC = 0.38 or 0.33, respectively). For participants aged 75 years and older, the single-leg stance had poor reliability (ICC = 0.30-0.39). The MDC90 was about 6 kg for grip strength, 2.3 seconds for TUG, 0.2 m/second for gait speed, 5.2 seconds for chair rise, and ranged from 22.8 to 26.2 seconds for the single-leg stance. CONCLUSIONS: Among community-dwelling Canadians older than 50 years, the reliabilities of the CLSA measures were moderate to excellent. The TUG and gait speed in the youngest age group, and the single-leg stance in the oldest age group, showed poor reliability. MDC values can be used to interpret changes over time.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".