Performance Measures Provide Assessments of Pain and Function in People With Advanced Osteoarthritis of the Hip or Knee
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Pain and physical function are core outcome measures for people with osteoarthritis, and self-report questionnaires have been the preferred assessment method. There is evidence suggesting that self-reports of physical function represent what people experience when performing activities rather than their ability to perform activities. The purpose of this study was to examine the factorial validity of performance-specific assessments of pain and function. SUBJECTS: The sample consisted of 177 participants who had osteoarthritis of the hip (n=81) or knee (n=96) and who were awaiting total joint arthroplasty. METHODS: Through a cross-sectional design, participants performed 4 performance activities (self-paced walk test, stair test, Timed "Up & Go" Test, and Six-Minute Walk Test). OUTCOMES: were time or distance (function) and pain ratings obtained immediately after each activity. The authors conceptualized 2 correlated factors, with pain items loading uniquely on 1 factor and functional items loading on the second factor, and uncorrelated error terms. Confirmatory factor analysis was applied. RESULTS: Initial analysis yielded results consistent with the conceptualized model in this study with the exception of a nonzero correlation between the stair pain and function error terms. Dropping the stair test provided results consistent with the conceptualized model. DISCUSSION AND CONCLUSION: Given the limitations of self-report alone as a method of obtaining reasonably distinct assessments of pain and function, the extent to which performance-specific assessments could accomplish this goal was examined in this study. It was found that collectively the walk test, Timed "Up & Go" Test, and Six-Minute Walk Test yielded 2 factors consistent with the health concepts of pain and function. The authors believe that the application of these tests may provide clinicians and clinical researchers with more distinct impressions of pain and function that complement information from self-report measures.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".