Consumer Medication Information: Similarities and Differences Between Three Canadian Pharmacies
Bibliographic record
Abstract
Prescription medication use is prevalent. When a new prescription medication is dispensed, Consumer Medication Information (CMI) is provided to communicate various important aspects of the medication (e.g., benefits, administration instructions, potential side effects). However, CMI is not regulated and differs from pharmacy to pharmacy. This study explores the similarities and differences between the CMI from three pharmacies (two paper print outs and one online source) for a single medication. The three CMI were assessed in terms of readability and utility. This evaluation revealed drastic differences in the length of the CMI (Range = 453 to 2 337 words). The online CMI was longer, described more topics and provided more detail than the print versions. Although online CMI has the advantage of interactivity to expedite navigation to specific topics of interest (e.g., heading links) and searching for key words, this CMI was not layered but rather presented as one long continuous page. Consumers with lower eHealth literacy skills may be deterred by the length of the document. As CMI makes the shift to online presentation an improved understanding of optimal information organization and media presentation will be needed.
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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 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".