Regulating Direct-to-Consumer Drug Information: A Case Study of Eli Lilly’s Canadian 40over40 Erectile Dysfunction Campaign
Bibliographic record
Abstract
Like most jurisdictions, Canada prohibits direct-to-consumer advertising (DTCA) of prescribed drugs.However, direct-to-consumer information (DTCI) is permitted, allowing companies to inform the public about medical conditions.An analysis of Eli Lilly' s 40over40 promotion campaign for erectile dysfunction (ED), which included a quiz on ED, shows that DTCI, like DTCA, can be an effective means of drug familiarization.The pharmaceutical industry is "playing by the rules" currently in effect in Canada.Regulators should thus seriously consider whether existing rules permitting DTCI actually meet stated objectives of protecting the public from marketing campaigns (i.e., DTCA) that may deliver misleading information. RésuméComme dans la plupart des pays, le Canada interdit la publicité directe auprès des consommateurs (PDAC) pour les médicaments sur ordonnance.Toutefois, on y autorise l'information destinée directement aux consommateurs (IDDC), permettant ainsi aux compagnies d'informer la population sur certains états de santé.Une analyse de la campagne de promotion 40desplusde40 d'Eli Lilly sur le dysfonctionnement érectile (DE) -laquelle comprenait un questionnaire sur le DE -démontre que l'IDDC, comme la PDAC, peut constituer un moyen efficace de familiarisation a un médicament.L'industrie pharmaceutique « se plie aux règles du jeu » actuellement en vigueur au Canada.Mais les organismes de réglementation devraient sérieusement s' assurer que les règles qui permettent l'IDDC atteignent réellement les objectifs en place visant à protéger la population des campagnes de marketing (à savoir la PDAC), lesquelles peuvent donner une information trompeuse.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.049 | 0.012 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.016 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".