The Relative Merits of an Individualized Versus a Generic Approach to Rating Functional Performance in Childhood Dystonia
Bibliographic record
Abstract
AIMS: The Performance Quality Rating Scale (PQRS) is an observational measure that captures performance at the level of activity and participation. Developed for use with the Cognitive Orientation to daily Occupational Performance (CO-OP), it is a highly individualized approach to measurement. CO-OP is currently being studied in childhood-onset hyperkinetic movement disorders (HMD) and deep brain stimulation. The purpose of this study was to compare two different approaches to rating performance, generic (PQRS-G) and individualized (PQRS-I), for children with childhood-onset hyperkinetic movement disorders (HMD) including dystonia. METHOD: Videotaped activity performances, pre and post intervention were independently scored by two blind raters using PQRS-G PQRS-I. Results were examined to determine if the measures identified differences in e performance on goals chosen by the participants and on change scores after intervention. Dependent t-tests were used to compare performance and change scores. RESULTS: The two approaches to rating both have moderate correlations (all data: 0.764; baseline: 0.677; post-intervention: 0.725) and yielded some different results in capturing performance. There was a significant difference in scores at pre-intervention between the two approaches to rating, even though post-intervention score mean difference was not significantly different. The PQRS-I had a wider score range, capturing wider performance differences, and greater change between baseline and post-intervention performances for children and young people with dystonic movement. CONCLUSIONS: Best practice in rehabilitation requires the use of outcome measures that optimally captures performance and performance change for children and young people with dystonic movement. When working with clients with severe motor-performance deficits, PQRS-I appears to be the better approach to capturing performance and performance changes.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".