The availability of references and the sponsorship of original research cited in pharmaceutical advertisements
Bibliographic record
Abstract
BACKGROUND: The primary goal of pharmaceutical advertisements is to convince physicians to prescribe the manufacturer's product. We sought to determine what materials are cited in support of claims in pharmaceutical ads and medical research articles, and whether health care professionals seeking to verify the claims could obtain these references. METHODS: We reviewed 438 unique ads from the 1999 issues of 10 American medical journals, and a random sample of 400 references in medical research articles selected from the same journals. We classified references as journal article, data on file, meeting abstract or presentation, book or monograph, marketing report, prescribing information, government document or Internet site. We attempted to confirm or obtain each reference through library and Internet searches or by direct request from the manufacturer. The main outcome we sought to determine was the availability of the reference to a clinician. We also ascertained the source of funding for original research cited in the ads and the research articles. RESULTS: In the 438 ads with medical claims, 126 contained no references and 312 contained 721 unique references. Of these ad references, 55% (396/721) cited journal articles and 19% (135/721) cited data on file. In contrast, in the sample of research article references, 88% (351/400) cited journal articles and 8% (33/400) cited books. Overall, 84% of the citations from the ads were available: 98% of journal articles, 86% of books, 71% of meeting abstracts or presentations and 20% of data-on-file references. In all, 99% of the sample of research article references were available. We determined that 58% of the original research cited in the pharmaceutical ads was sponsored by or had an author affiliated with the product's manufacturer, as compared with 8% of the articles cited in the research articles. INTERPRETATION: Many pharmaceutical ads contain no references for medical claims. Although references to journal articles were usually obtainable, other published sources were not as easily acquired. The majority of unpublished data-on-file references were not available, and the majority of original research cited to substantiate claims in the pharmaceutical ads was funded by or had authors affiliated with the product's manufacturer.
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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 | 0.043 | 0.349 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.027 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".