Physician and Educator Co-design of a Canadian School-Based Health Centre Referral Form: a Quality Improvement Study
Bibliographic record
Abstract
Background: A school-based health centre (SBHC) in Toronto, Canada, supports students with academic, developmental, and behaviour-related challenges. The educators in this centre complete a referral form to provide information to the SBHC. The present study aimed to a) collaborate with the educators to co-design the existing SBHC referral form and b) provide the educators with a resource on a common pediatric disorder.Methods: The current quality improvement study was performed using a Plan-Do-Study-Act (PDSA) cycle. Data was collected from November 2020 to January 2021. Twenty-three educators rated their understanding of the original SBHC referral form using a 6-point Likert scale. The symptom descriptors flagged by >10% of the educators as unclear were updated and re-evaluated through a second survey. The educators voted on a common medical issue for which a pamphlet was created and evaluated for its effectiveness. Statistical analysis was performed using GraphPad Prism. Paired data were assessed by Wilcoxon rank-order test, unpaired data with Fischer’s exact, and proportions via Chi-squared test.Results: The original referral form had 13/48 (27%) presenting symptoms identified for revision. After this revision, significantly fewer presenting symptoms met the criteria for revision (3/50, 6%; P<0.01). Most educators (10/23, 43%) requested an educational pamphlet on childhood anxiety. The majority of them (13/16, 81%) strongly agreed that they knew more about childhood anxiety after reviewing the resource and all of them (16/16, 100%) thought the resource would be helpful and could be shared with parents.Conclusion: Collaboration with the educators to co-design a SBHC referral form clarified its descriptors, enhancing the communication between the two parties in the referral process. Physician-created educational resource enhanced the educators’ knowledge about anxiety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.155 | 0.213 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".