The development of the Pediatric Motivation Scale for rehabilitation
Bibliographic record
Abstract
BACKGROUND: Clinicians recognize that client motivation is key to optimizing rehabilitation; however, they are limited in its assessment by a paucity of motivation measures. PURPOSE: This paper presents the preliminary psychometrics of the Pediatric Motivation Scale (PMOT) designed to measure motivation from a child's perspective. METHOD: Content validity of the PMOT was measured through expert feedback (n = 12), and field testing ocurred with 41 children, 21 in rehabilitation and 20 healthy. Pearson product-moment correlations were used to analyze subscale correlations, test-retest reliability, and convergent validity with the Pediatric Volitional Questionnaire (PVQ). Internal consistency was measured using Cronbach's alpha. FINDINGS: Preliminary psychometric evaluation indicates strong internal consistency for PMOT total (α = .96) and subscales (α = .79-.91). The PMOT and PVQ moderately correlated in the rehabilitation subsample (r = .71, p < .01); no correlation was found in the healthy subsample (p > .05). Test-retest reliability was excellent (r = .97). IMPLICATIONS: This study provides preliminary psychometric evidence of the PMOT for children undergoing rehabilitation. These pilot findings warrant ongoing scale development.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".