School participation among young people with craniofacial microsomia and other childhood‐onset disabilities
Bibliographic record
Abstract
AIM: To examine how school environment, physical functioning problems, and behavioral problems explain levels of school participation (i.e. attendance and involvement) among young people with craniofacial microsomia (CFM) and other childhood-onset disabilities, and whether participation-focused caregiver strategies play a role in these relationships. METHOD: We conducted secondary analyses of a subset of data (n = 260 families: 120 with CFM and 140 with other childhood-onset disabilities) from the second follow-up phase of a longitudinal cohort study. We applied structural equation modeling with data collected from the Participation and Environment Measure - Children and Youth version, the Child Behavior Checklist, and the Pediatric Quality of Life Inventory physical functioning scale. RESULTS: Model fit was acceptable to close (comparative fit index = 0.973; root mean square error of approximation = 0.055; standardized root mean squared residual = 0.043; Tucker-Lewis index = 0.958). School environmental support had a positive effect on young people's participation attendance and involvement, and physical functioning problems had a negative effect on participation involvement. The number of disclosed caregiver strategies had a significant positive effect on the relationship between school environmental support and school participation attendance. INTERPRETATION: Findings confirm the effect of school environmental support and physical functioning problems on school participation and highlight the role of participation-focused caregiver strategies to intensify the positive effect of school environmental support on school participation attendance. WHAT THIS PAPER ADDS: Environmental support had a positive effect on participation attendance and involvement. Physical functioning problems had a negative effect on school participation involvement. Disclosed caregiver strategies intensified the impact of environmental support on participation attendance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".