Pharmacists’ knowledge, experiences and perceptions of treatments for attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that begins in childhood and often persists into adulthood. ADHD increases the risk of various negative impacts, and pharmacists are well positioned to address these issues in the community. OBJECTIVES: This survey study aims to first identify pharmacists' ADHD knowledge gaps and experience with ADHD management and to second assess their preferences for continuing education and their experience with sleep-related issues in ADHD. METHODS: = 6022). Descriptive statistics were used to analyze survey data, while free-form answers were pooled and evaluated for common themes and trends. RESULTS: A total of 238 complete responses were received. The average self-reported ADHD knowledge was 5.8 ± 1.96 on a 10-point scale. There was no correlation between the number of years of practice as a pharmacist, the number of working hours per week or the location of practice on pharmacists' self-reported knowledge scores. There was a significant difference in self-reported knowledge of ADHD between pharmacists who were not aware of the Canadian ADHD Resource Alliance (CADDRA) guidelines (5.1 ± 2.1) and those who refer to it for standard of care (7.1 ± 1.5). Almost all pharmacists (95%) indicated they could benefit from additional ADHD education, with a strong preference for "online continuing education modules" (81%). The majority of responders considered psychostimulant ADHD medication as the major possible contributor to sleep disturbances (47%) in ADHD, highlighting a need for further education on the inconclusive link between ADHD medication effects on sleep. CONCLUSION: 2021;154:xx-xx.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".