A Prospective Before-and-After Trial of an Educational Intervention about Pharmaceutical Marketing
Bibliographic record
Abstract
PURPOSE: There is increasing evidence that physicians may be compromised by their interactions with the pharmaceutical industry. The authors aimed to develop and determine the effect of an educational intervention to inform family medicine residents about pharmaceutical marketing. METHOD: Confidential, self-administered questionnaires were administered to family medicine residents at McMaster University, Hamilton, Canada, immediately before and after a two-part, 2.5-hour educational intervention. The curriculum consisted of (1) a faculty-led debate and discussion of a systematic review of physician-pharmaceutical industry interactions, and (2) an interactive workshop that included a presentation highlighting key empirical findings, a video illustrating techniques to optimize pharmaceutical sales representatives' visits, and small- and large-group problem-based discussions. Residents were asked about their attitudes toward five marketing strategies: drug samples, industry-sponsored continuing medical education, one-on-one interactions with sales representatives, free meals, and gifts worth less than CAN $10. RESULTS: A total of 37 residents responded to both questionnaires. After the intervention residents had more cautious attitudes, rating marketing strategies on a five-point Likert scale as less ethically appropriate (-0.41, p < .05) and less valuable to patients or useful to the resident (-0.39, p < .05), and reporting less intention to use them in the future (-0.44, p < .01). CONCLUSION: This intervention appears to have promoted more cautious attitudes toward pharmaceuticals marketing. Its long-term sustainability and effect on behavior remain unknown.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".