78 Direct-to-consumer advertising: a modifiable driver of overdiagnosis and overtreatment
Notice bibliographique
Résumé
The New Zealand government is this year developing a new Therapeutic Products Bill to replace the antiquated Medicines Act 1981. Among the many issues at stake is whether direct-to-consumer advertising (DTCA) of prescription medicines will continue to be permitted. Besides the United States, New Zealand is the only other high-income country that allows unrestricted DTCA. Despite the centre-left Labour Party historically opposing DTCA, the current Labour cabinet has proposed that DTCA should continue, based on 4 key arguments,1 summarised here in relation to the research evidence: the existing combination of government and self-regulation (by industry) of DTCA is adequate. This claim is manifestly false, based on the fact that the present arrangement is unable to ensure that ads contain accurate information on either benefits or harms of medicines, or on how advertised products compare to other available treatment options, including lifestyle modification.2 the increased prescribing (and drug expenditure) triggered by DTCA may be appropriate and useful. While this assertion is doubtless true in some cases, the best overall evidence comes from a randomised controlled trial which showed, as expected, that brand-specific requests stimulate unnecessary prescriptions. Crucially, this trial found that requests from patients with adjustment disorder (pharmacotherapy inappropriate) stimulated prescribing to a greater extent than requests from patients with treatable depression.3 Complementary evidence showing that DTCA-stimulated prescribing can be both inappropriate and harmful comes from a study of patients requesting advertised COX-2 inhibitors.4 people with lower educational status, poorer health, or from an ethnic minority are more likely to seek care as a result of DTCA. While this is presented as a positive attribute, it is taken out of context from a New Zealand study which concludes that DTCA may lead to ‘…the misuse or overuse of medications for diseases that may otherwise be improved by a healthier lifestyle’5 having a more informed society enables better conversations and relationships between patients and prescribers. While a well-informed public is to be encouraged, this argument is undermined by evidence of the poor quality and misleading information typical of DTCA, irrespective of whether it comes from broadcast, print, or online advertising.2 In conclusion, the government’s main arguments for allowing DTCA to continue in New Zealand are both unsustainable and bear remarkable similarity to those advanced by Medicines New Zealand, a body representing the pharmaceutical industry. This coincidence may reflect the virtually unregulated access that lobbyists have to senior government officials in this country.6 In any case, available evidence indicates that banning DTCA would help to promote population health by reducing overdiagnosis, overtreatment, and iatrogenic harm. References Available from: https://www.health.govt.nz/our-work/regulation-health-and-disability-system/therapeutic-products-regulatory-regime New Zealand Medical Journal 2019;132:59-65. JAMA 2005;293:1995-2002. Medical Care Research and Review 2005;62:544-59. Australian and New Zealand Journal of Public Health 2019;43:190-6. Available from: https://www.rnz.co.nz/news/lobbying/486670/lobbyists-in-new-zealand-enjoy-freedoms-unlike-most-other-nations-in-the-developed-world
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».