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

2012· review· en· W2103936380 on OpenAlexaff
Barbara Mintzes

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.

How this classification was reachedexpand

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0040.004
Science and technology studies0.0000.003
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0120.001

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.

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

Classification

machine, unvalidated

Labeled directly by 3 models reading the full record.

Meta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations76
Published2012
Admission routes1
Has abstractyes

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