Pharmaceutical Marketing to Medical Students: The Student Perspective
Bibliographic record
Abstract
It has been estimated that pharmaceutical companies spend $1.7 billion every year promoting their products to physicians in Canada. At least $21 billion are spent every year on drug promotion in the United States. Although pharmaceutical marketing campaigns are primarily directed toward practicing physicians and residents, medical students are targeted as well. The goal of this study was to assess medical student attitudes toward pharmaceutical promotion in a Canadian academic centre. A questionnaire was designed to assess the attitudes of medical students about pharmaceutical promotion, including the acceptability of receiving various gifts and incentives. The survey was administered to first, second, and fourth-year medical students at the University of Western Ontario (London, Ontario, Canada). Statistical methods were employed to compare subpopulations of students based on demographic and socioeconomic data. Some 81% of students were not opposed to interacting with drug companies in medical school. Medical students felt comfortable accepting gifts of low monetary value, such as lunches (75%) and penlights (74%), but were willing to accept gifts of higher monetary value if the gifts served an educational purpose, such as textbooks (65%) and drug company-sponsored educational seminars (66%). 17% of students said that if presented with a choice of drugs identical in terms of price, efficacy, and effectiveness, they would prescribe the drug from the company that provided them with financial incentives. Statistical analysis showed no differences in responses among the different years of medical students. There were some differences in responses between medical students who had a doctor parent compared to those who did not have a doctor parent. Medical students are generally not opposed to interacting with or receiving gifts from pharmaceutical companies. Insights gained from this study raises issues that may be of interest to medical educators concerning the attitudes of the future physicians in Canada.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".