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Record W3094346900 · doi:10.1136/medethics-2020-106458

US direct-to-consumer medical service advertisements fail to provide adequate information on quality and cost of care

2020· article· en· W3094346900 on OpenAlexaboutno aff
Sung‐Yeon Park, Gi Woong Yun, Sarah Friedman, Kylie N. Hill, So Young Ryu, Thomas L. Schwenk, Max J. Coppes

Bibliographic record

VenueJournal of Medical Ethics · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsAdvertisingBusinessQuality (philosophy)Service (business)CommissionQuarter (Canadian coin)Service qualityScarcityMarketingInternet privacyComputer scienceEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: In the 1970s, the Federal Trade Commission declared that allowing medical providers to advertise directly to consumers would be "providing the public with truthful information about the price, quality or other aspects of their service." However, our understanding of the advertising content is highly limited. OBJECTIVE: To assess whether direct-to-consumer medical service advertisements provide relevant information on access, quality and cost of care, a content analysis was conducted. METHOD: Television and online advertisements for medical services directly targeting consumers were collected in two major urban centres in Nevada, USA, identifying 313 television advertisements and 200 non-duplicate online advertisements. RESULTS: Both television and online advertisements reliably conveyed information about the services provided and how to make an appointment. At the same time, less than half of the advertisements featured insurance information and hours of operation and less than a quarter of them contained information regarding the quality and price of care. The claims of quality were substantiated in even fewer advertisements. The scarcity of quality and cost information was more severe in television advertisements. CONCLUSION: There is little evidence that medical service advertising, in its current form, would contribute to lower prices or improved quality of care by providing valuable information to consumers.

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

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)0.006
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.009
Insufficient payload (model declined to judge)0.0020.000

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 head0.560
GPT teacher head0.612
Teacher spread0.051 · 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

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations4
Published2020
Admission routes1
Has abstractyes

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