An Environmental Scan of Preparation for Occupational Therapy Intraprofessional Collaboration in Ontario
Bibliographic record
Abstract
Intraprofessional collaboration between occupational therapists (OTs) and occupational therapist assistants (OTAs) is important for safe, effective, and efficient occupational therapy services. However, challenges such as role misunderstandings in Canada exist, which impact OT-OTA intraprofessional collaboration and the quality of care provided. This study aimed to reveal the OT-OTA intraprofessional collaboration preparation taking place in Ontario, Canada, during entry-to-practice education. An explanatory sequential environmental scan was conducted, which involved a survey distributed to OT and OTA educators, followed by six focus groups: two with OT educators, two with OTA educators, and two with OT and OTA recent graduates. Key findings revealed an opportunity and a need to develop ready-made, easy-to-use foundational online resources to support OT-OTA intraprofessional collaboration preparation in the Canadian context. The environmental scan revealed distinct competencies, skills, and attitudes that must be addressed and explicitly taught for effective OT-OTA intraprofessional collaboration. Participants emphasized that while ready-made online resources are needed to address existing knowledge gaps, scaffolded real-world OT-OTA interactions are also required to develop OT-OTA competence in intraprofessional collaboration. Contact theory provides insight into these findings. This study presents the initial phase in a broader initiative that created, disseminated, and evaluated resources designed to support OT-OTA intraprofessional collaboration across Canada.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".