A Survey of Canadian Pharmacists’ Knowledge and Comfort in the Management of Epilepsy and Antiepileptic Drugs
Bibliographic record
Abstract
Background: As antiepileptic drugs (AED) remain the mainstay of epilepsy management, pharmacists have the potential to play an integral role in the management. Objective: The goal of our study was to characterize Canadian pharmacists’ knowledge and comfort in managing epilepsy and AED and identify areas of need for the development of support tools. Methods: An electronic survey was designed and distributed to Canadian pharmacists through professional organizations. The survey consisted of 4 sections, including demographics, knowledge, comfort, and needs assessment around epilepsy management. Results: A total of 605 complete responses were included. Nearly two-thirds of the participants were females (61.6%) and most reported more than 10 years of practice experience (61.6%). For comfort, a majority of the participants responded agree or strongly agree to the statement inquiring about the comfort in checking prescriptions, answering questions about drug interactions, and counseling on AED. Conversely, more than 50% of the participants selected disagree or strongly disagree when asked about their comfort regarding interpreting therapeutic drug monitoring and assisting patients withdraw from AED. For the knowledge section, the overall average score was 57.6% ± 19.1%. Hospital practice, recent graduation, and neurology experience were independent predictors of high scores. Many participants indicated a need for tools addressing newer AED and monitoring of therapy. Conclusion: Although Canadian pharmacists displayed knowledge and comfort in certain aspects of epilepsy management, some clear knowledge and comfort gaps are prevalent. These findings indicate a need for the development of epilepsy educational support tools.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".