Collaborative Occupational Therapy: Teachers' Impressions of the Partnering for Change (P4C) Model
Bibliographic record
Abstract
AIMS: Occupational therapists (OTs) often face barriers when trying to collaborate with teachers in school-based settings. Partnering for change (P4C), a collaborative practice model designed to support children with developmental coordination disorder, could potentially support all students with special needs. Therefore, the aim of this study was to explore how teachers experience OT services delivered using the P4C model to support children with a variety of special needs. METHODS: P4C was implemented at one elementary school in Courtenay, British Columbia. Eleven teachers participated in two focus groups and a one-on-one interview to gather descriptive, qualitative data. Grounded theory techniques were used for data analysis. RESULTS: Four themes (collaborating in the thick of it all, learning and taking risks, managing limited time and resources, and appreciating responsive OT support) represented teachers' experiences of P4C. CONCLUSIONS: Teachers strongly preferred collaborative OT services based on the P4C model. Students with a variety of special needs were supported within their classrooms as teachers learned new strategies from the OT and found ways to embed these strategies into their daily routines.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".