Public Perceptions of Physician–Pharmaceutical Industry Interactions: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Interactions between physicians and the pharmaceutical industry have led to concerns about conflict of interest (COI), resulting in COI guidelines that suggest a threshold beyond which interactions may be considered unacceptable. Guidelines have also outlined the importance of public opinion on the topic. Consequently, we conducted a systematic review to determine the Canadian public's opinions of physician-pharmaceutical industry interactions. METHODS: A systematic review of the standard health sciences literature as well as grey literature was conducted and a number of experts were contacted. Pre-determined eligibility criteria were used to identify appropriate studies. Meta-analysis of the study findings was not possible owing to the variety of methods of reporting outcomes, the types of interactions studied and the diversity of populations studied. RESULTS: No studies on Canadian opinions were identified. Ten international studies (n=13,637), seven with patient groups and three with public citizens, were identified that examined opinions on aspects of awareness, acceptability, disclosure and perceived effects of physician-pharmaceutical industry interactions. Heterogeneity was observed in the awareness, acceptability and perceived effects of physician-pharmaceutical industry interactions; however, there appeared to be greater acceptability and fewer perceived effects with smaller, less costly interactions that directly benefit patients or a medical practice. Desire for disclosure of these interactions was consistent across studies. INTERPRETATION: Research on the public's perception of physician-pharmaceutical industry interactions has been inadequate internationally and non-existent in Canada, and is urgently needed to help shape policies regarding potential conflict of interest.
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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 | 0.023 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".