3. The Inter-rater Variability and Reliability of the use of the Modified Ashworth Scale for the Upper Motor Neuron Syndrome
Bibliographic record
Abstract
This poster reports on the results of a quality improvement project. The objective was to determine the inter-rater variability and reliability of the Modified Ashworth Scale for assessing spasticity in people with traumatic brain injury.Hamilton Health Sciences operates the comprehensive spasticity management program. In this regional program, the MAS is used by physical therapists, occupational therapists and physicians as a quantitative measure of spasticity. The MAS is used to make determinations related to treatment options as well as follow the efficacy of treatment.The participants were 28 practitioners from the disciplines of medicine, physical therapy and occupational therapy. Each practitioner was provided an explicit set of written instructions and then asked to examine two patients with traumatic spinal cord injury. The MAS scores were reported anonymously. As well, the two patients were assigned MAS scores by two expert spasticity management clinicians.There was substantial inter-rater variability with MAS scores. Fleiss' Generalized Kappa, which is chance-corrected measure of agreement among three or more raters, was 0.18. This is interpreted as poor agreement. Furthermore, only 46 percent of the participants agreed with the MAS scores assigned by the physician expert in the first subject and 50 percent of the participants agreed with the MAS scores assigned by the physician expert in the second subject.Clinicians should be cognizant of the variability of the MAS when making determinations related to patient management.
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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 | 0.099 | 0.127 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".