Interrater Reliability of the Observable Movement Quality Scale for Children
Bibliographic record
Abstract
Purpose: The authors investigated the interrater reliability, the standard deviation of the random measurement error, and the limits of agreement (LoA) of the Observable Movement Quality (OMQ) scale in children. Movement quality is important in the recognition of motor problems, and the OMQ scale, a questionnaire used by paediatric physical therapists, has been developed for use with an age-specific motor test to observe movement quality and score relative to what is expected for a child's age. Method: Paediatric physical therapists (n=28; 2 men, 26 women) observed video-recorded assessments of age-related motor tests in children (n=9) aged 6 months to 6 years and filled in the OMQ scale (possible score range 15–75 points). For our analyses, we used linear mixed models without fixed effects. Results: The interrater reliability was moderate (intra-class correlation coefficient [ICC2,1]: 0.67, 95% CI: 0.47, 0.88); neither work setting nor work experience exerted any influence on it. The standard deviation of the random measurement error was 5.7, and the LoA was 31.5. Item agreement was good (proportion of observed agreement [Po] total 0.82–0.99). Conclusion: The OMQ scale showed moderate interrater reliability when being used by therapists who were unfamiliar with the questionnaire and who had received only 2 hours of training. Feedback from the participants suggested a need for more comprehensive training in using the OMQ scale in clinical practice.
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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 | 0.045 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".