Effects of a Family-Centered Teaching Model on Occupational Therapy Interns’ Perceptions and Children’s Occupational Performance
Bibliographic record
Abstract
AIMS: To compare perceptions of family-centered behaviors and children's occupational performance between occupational therapy interns in Taiwan who received a family-centered teaching (FACT) model and those who received a conventional family approach. METHODS: A two-group quasi-experimental design was employed. Participants included 49 interns, 44 caregivers, and 45 children with disabilities under 6 years old. The FACT model consisting of didactic lessons and hands-on practice was developed to strengthen interns' competencies in identifying parental concerns related to children's goals, writing goals using GAS format, and collaborating with caregivers in implementation of interventions. The interns' perceptions of their family-centered behaviors were measured using the Chinese version of the "Measure of Processes of Care-Service Provider" (C-MPOC-SP). Children's occupational performance was rated using the "Canadian Occupational Performance Measure" (COPM). RESULTS: Interns who received the FACT model demonstrated a significant increase in the Showing Interpersonal Sensitivity and Treating People Respectfully scales of C-MPOC-SP compared to the comparison group. The ratings of caregivers who received the FACT model increased significantly for children's performance, but not for satisfaction with performance. CONCLUSIONS: The family-centered teaching model implemented in the internship increased interns' perception toward more family-centeredness and children's occupational performance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".