2021 Scientific Abstracts: Canadian Society of Pharmacology and Therapeutics annual conference
Bibliographic record
Abstract
Background: School-based immunization clinics are associated with student fear and pain.School principals can play a role in planning clinics that result in more positive student experiences.At present, public health nurses do not systematically involve principals in planning immunization clinics.Objectives: To assess principal willingness to collaborate with public health nurses planning school-based immunization clinics.Methods: This descriptive analysis was part of a cluster trial evaluating the impact of a complex intervention, which included collaborating with principals to plan upcoming immunization clinics, on the immunization experience of grade 6 and 9 students undergoing routine immunizations at school in Calgary.Each intervention school principal met with a nurse to plan upcoming clinics.A checklist was used to guide the discussion.Control schools received standard care (without guided discussion).The proportion of nurse recommendations accepted by intervention school principals was calculated.Results: Out of 50 participating intervention schools, 14 (28%) had grade 6 and 9 students, 30 (60%) had grade 6 students and the remainder had grade 9 students.All principals (100%) agreed to a separate clinic waiting area and private space for students who prefer to be immunized out of view of peers.Forty-seven (94%) agreed to a support person; 46 (92%) agreed to topical anesthetics; and 39 (71%) agreed to use of personal devices (e.g., phones) as coping strategies.Thirty-six (72%) agreed to school snacks.Conclusions: Principals are agreeable to evidence-base interventions to mitigate pain and fear during school-based vaccinations and should be involved in vaccination planning activities.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.412 | 0.151 |
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".