Attitudes of physicians and public to pharmaceutical industry ‘gifts’
Bibliographic record
Abstract
BACKGROUND: Few studies have reported the attitudes of both individual doctors and members of the public toward the appropriateness of 'gifts' from pharmaceutical companies. AIMS: To investigate the attitudes of both doctors and members of the public toward the appropriateness of receiving particular 'gifts' from pharmaceutical companies, and to consider whether public acceptability is a suitable criterion for determining the ethical appropriateness of 'gifts'. METHODS: A survey questionnaire of medical specialists in Australia and a survey questionnaire of members of the public itemized 23 'gifts' (valued between AU$10 and AU$2500) and asked whether or not each was appropriate. RESULTS: Both medical specialists and members of the public believe certain 'gifts' from pharmaceutical companies are appropriate but not others. There was a tendency for members of the public to be more permissive than medical specialists. CONCLUSION: Although some professional guidelines place importance on the attitudes of the general public to 'gift' giving, and other guidelines give importance to a need for transparency and public accountability, we question whether public acceptability is a suitable criterion for determining the ethical appropriateness of 'gifts'. We suggest that more weight be given to the need for independence of clinical decision making, with empirical evidence indicating that even small 'gifts' can bias clinicians' judgments, and to important values such as the primacy of patient welfare, autonomy and social justice. We conclude that it is time to eliminate giving and receiving of promotional items between the pharmaceutical industry and members of health professions.
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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 | 0.017 | 0.061 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".