Comparing the Predictive Value of Task Performance and Task-Specific Sensitivity During Physical Function Testing Among People With Knee Osteoarthritis
Bibliographic record
Abstract
Study Design Cross-sectional cohort. Background Knee osteoarthritis (OA) is a leading cause of pain and mobility restriction. Past research has advocated the use of brief, functional tasks to evaluate these restrictions, such as the six-minute-walk test and the timed up-and-go test. Typically, only task performance (ie, walking distance, completion time) is used to inform clinical practice. Recent research, however, suggests that individual variance in how people feel while completing these tasks (ie, task sensitivity) might also have important clinical value. Objective To compare the predictive value of task performance and task-specific sensitivity in determining OA-related physical function (measured by the Western Ontario and McMaster Universities Osteoarthritis Index) and pain-related interference (measured by the Multidimensional Pain Inventory). Methods One hundred eight participants with chronic knee OA completed the six-minute-walk test and the timed up-and-go test, and reported levels of discomfort and affective response (mood) associated with each test. Results In separate regression models, both task performance and task-specific sensitivity predicted OA-related physical function and pain-related interference. A final regression model including all significant predictors showed that task-specific sensitivity (specifically, post-six-minute-walk discomfort) emerged as a unique predictor of both outcomes. Conclusion These findings highlight the value of a novel clinical assessment strategy for patients with knee OA. While clinicians commonly focus on how patients perform on standardized functional tasks, these results highlight the value of also considering levels of posttask sensitivity. Measures of task-specific sensitivity relate to Maitland's concept of pain irritability, which may be a useful framework for future research on sensitizing factors and pain-related disability. J Orthop Sports Phys Ther 2016;46(5):346-356. Epub 21 Mar 2016. doi:10.2519/jospt.2016.6311.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".