Psychometric Properties of the Young Children's Participation and Environment Measure
Bibliographic record
Abstract
OBJECTIVE: To evaluate the psychometric properties of the newly developed Young Children's Participation and Environment Measure (YC-PEM). DESIGN: Cross-sectional study. SETTING: Data were collected online and by telephone. PARTICIPANTS: Convenience and snowball sampling methods were used to survey caregivers of children (N=395, comprising children with [n=93] and without [n=302] developmental disabilities and delays) between the ages of 0 and 5 years (mean age±SD, 35.33±20.29 mo) and residing in North America. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The YC-PEM includes 3 participation scales and 1 environment scale. Each scale is assessed across 3 settings: home, daycare/preschool, and community. Data were analyzed to derive estimates of internal consistency, test-retest reliability, and construct validity. RESULTS: Internal consistency ranged from .68 to .96 and .92 to .96 for the participation and environment scales, respectively. Test-retest reliability (2-4 wk) ranged from .31 to .93 for participation scales and from .91 to .94 for the environment scale. One of 3 participation scales and the environment scale demonstrated significant group differences by disability status across all 3 settings, and all 4 scales discriminated between disability groups for the daycare/preschool setting. The participation scales exhibited small to moderate positive associations with functional performance scores. CONCLUSIONS: Results lend initial support for the use of the YC-PEM in research to assess the participation of young children with disabilities and delays in terms of (1) home, daycare/preschool, and community participation patterns; (2) perceived environmental supports and barriers to participation; and (3) activity-specific parent strategies to promote participation.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".