Construct validity and reliability of the 2-minute step test in patients with knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To validate and evaluate the intra- and inter-rater reliability of the 2-min step test (2MST) in measuring the functional performance of patients with knee pain associated with osteoarthritis (OA). METHODS: Forty-one patients with knee OA was included. Two examiners assessed the patients at two times with interval between the test and retest from 7 to 14 days. All executions of 2MST were recorded in real time by the examiners and were also recorded by video. The intraclass correlation coefficient (ICC) and 95% confidence interval (CI), standard error of measurement (SEM) and minimum detectable difference (MDD) were used to determine reliability. In the construct validity, we correlate the score of the 2MST with the other instruments used in the study: The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Numerical Pain Scale (NPS), Pain-Related Catastrophizing Thoughts Scale (PCTS) and Chronic Pain Self-Efficacy Scale (PSEQ). The agreement between the face-to-face assessment and the evaluation based on the video record was assessed using the Bland-Altman methodology in the 4 moments of the 2MST. RESULTS: 2MST presented excellent intra- (ICC = 0.94, SEM = 4.47, MDD = 12.40) and inter-rater reliability (ICC = 0.97, SEM = 3.07, MDD = 8.52). The agreement was acceptable between face-to-face assessments and the analyzes performed on video. All instruments showed a statistically significant correlation with 2MST, except the PCTS. A correlation magnitude above 0.50 was found between the 2MST and pain and function domains of the WOMAC, and a correlation magnitude between 0.30 and 0.50 with the joint stiffness domain of the WOMAC, NRPS and PSEQ. CONCLUSION: 2MST proved to be valid for assessing functional capacity in patients with knee OA, with excellent reliability.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".