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Advertising of Prescription-Only Medicines to the Public: Does Evidence of Benefit Counterbalance Harm?

2012· review· en· W2103936380 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Public Health · 2012
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHarmScrutinyMedical prescriptionDirect-to-consumer advertisingCausality (physics)MedicinePublic healthPublic economicsHealth careBusinessFamily medicinePsychologyNursingEconomicsPolitical science

Abstract

fetched live from OpenAlex

Since the global withdrawal of rofecoxib (Vioxx) in 2004, concerns about public health effects of direct-to-consumer advertising (DTCA) have grown. A systematic review of the research evidence on behavioral, health, and cost effects, published in 2005, found four studies meeting inclusion criteria, which showed that DTCA increases prescribing volume and patient demand, and shifts prescribing. From 2005 to 2010, nine studies met similar criteria. These largely confirm previous results. Additional effects include a shift to less appropriate prescribing, differential effects by patient price sensitivity and drug type, switches to less cost-effective treatment, and sustained sales despite a price increase. Claimed effects on adherence do not stand up to scrutiny and are based mainly on negative trials. There is no evidence of improved treatment quality or early provision of needed care. If policy is to be informed by evidence, the strength of research methods and ability to assess causality need to be considered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
grokno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
opusMeta-epidemiology (broad)
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.556
GPT teacher head0.608
Teacher spread0.052 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it