Medications for Children: A Survey of Community Pharmacists
Bibliographic record
Abstract
BACKGROUND: Seamless and safe discharge of children from hospital requires successful collaboration with community pharmacists, for whom pediatrics is often a small part of their practice. OBJECTIVES: The purpose of this study was to understand community pharmacists' comfort level and confidence in providing care for children. METHODS: We conducted a self-administered online survey of community pharmacists in Ontario, Canada. Respondents rated their comfort and confidence on a scale of 1 to 7 in each of 3 scenarios: oral morphine, prednisone, and amoxicillin. We also evaluated the relationship between participants' comfort level and demographics. RESULTS: We included 622 responses (377 completed and 245 partially completed surveys). A total of 182 participants (48%) were female, 271 participants (72%) had children of their own, and they had practiced pharmacy for a median (interquartile range) of 19 (5-28) years. The percentage of respondents who were comfortable (5-7 on a 7-point scale) with filling the prescriptions as written was 64% for morphine, 58% for prednisone, and 61% for amoxicillin and was not different among the scenarios. Having children was associated with increased comfort (p = 0.02), whereas other demographic variables were not. Compared to the amoxicillin scenario, pharmacists reported being significantly more likely to choose another course of action for prednisone (p = 0.01) but not for morphine (p = 0.25). Although 428 pharmacists (70%) agreed that they maintained adequate knowledge of pediatric topics, 558 (91%) were interested in more education. CONCLUSIONS: Variability exists in the confidence and comfort levels of community pharmacists when dealing with children, and many are not comfortable with the common prescriptions in this survey.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".