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Enregistrement W2157228972

Media portrayal of conflicts of interest in herbal remedy clinical trials.

2006· article· en· W2157228972 sur OpenAlexaffabout
Megan Koper, Tania Bubela, Timothy Caulfield, Heather Boon

Notice bibliographique

RevuePubMed · 2006
Typearticle
Langueen
DomaineMedicine
ThématiqueComplementary and Alternative Medicine Studies
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésConflict of interestMainstreamPublic interestQuality (philosophy)MedicinePublic relationsJudgementAlternative medicineClinical trialPolitical scienceLaw
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Complementary and Alternative Medicine (CAM) encompasses wide variety of treatments, such as herbal remedies, not currently thought to be part of mainstream medicine. Our study focuses on herbal remedies, as their use is significant and increasing. (1) We ask whether media coverage of conflicts of interest in clinical trials of herbal remedies is of sufficient quality to provide the public with information to make decisions that are rational, well-informed, and low-risk. We know that the vast quantity of information available on CAM through popular media is of varying quality. (2) In recent years, the scientific community is increasingly interested in studying herbal remedies. (3) As conflict of interest has been an issue in synthetic drug trials, especially those receiving funding industry, we have reason to believe that this will also be true of clinical trials of herbal remedies, many of which are industry funded. What is conflict of interest and why are we interested? In his thoughtful and widely accepted analysis, Thompson defined conflict of interest as a set of conditions in which professional judgement concerning primary interest (such as patient's welfare or validity of research) tends to be unduly influenced by secondary interest (such as financial gain). (4) He also noted that, while secondary interest is usually not illegitimate in itself, its relative weight in professional decision-making is problematic. The goal, therefore, is to prevent secondary interests from dominating or appearing to dominate the relevant primary interest in the making of professional decisions, rather than to reduce or eliminate them completely. (5) Conflict of interest rules, those regulating the disclosure and avoidance of these conflicts, generally focus on financial gain because it is relatively objective and easier to regulate by impartial rules. This does not mean, however, that financial gain has greater potential for harm than other secondary interests. (6) The subtle distinction between conflict of interest and bias must also be emphasized. A declared conflict should merely be seen as an association creating the potential for bias, rather than an indication of bias itself. (7) It has also been noted that if an association does compromise one's judgment, it is generally result of unconscious bias rather than outright dishonesty. (8) Because the influence of secondary interests can be extremely subtle, the presence of bias is often difficult to determine with any degree of certainty. Why are these issues important in media context? As the popular press is often cited as prominent source of medical information for the general public, it has the ability to shape public views and interpretations of new medical research. (9) It follows that media reporting has the capacity to shape public perceptions of safety and efficacy of particular herbal remedy, thereby influencing patterns of use. The goal of our analysis is to infer how reporting of herbal remedy clinical trials by the popular media may be influenced by the disclosure of funding information and competing interests (i.e., the perception of conflict) in the scientific and medical literature. Approach We used coding frame analysis to examine the media coverage of conflicts of interest in clinical trials of herbal remedies. (10) This technique allowed us to systematically compare newspaper articles to the reporting of the same trials in the medical literature. We compared 389 newspaper articles (from the U.S., U.K. and Canada) reporting on herbal remedy clinical trials with the reporting of the 58 clinical trials in the medical literature. Primarily, we assessed tone, claims of efficacy, reporting of risk, and the disclosure of funding information and competing interests. Our coding frame allowed us to compile information regarding the date and location of publication, authorship, the portrayed likelihood of benefits and risks, disclosure of conflicts of interest, disclosure of funding information and funding agency involvement, whether the article was framed as controversy, and overall tone in both newspaper articles and medical journal reports of clinical trials. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,045
score de la tête « metaresearch » (Gemma)0,236
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: Incitatifs · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,992
Score d'incertitude au seuil0,240

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0450,236
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0060,005
Études des sciences et des technologies0,0050,008
Communication savante0,0130,010
Science ouverte0,0010,007
Intégrité de la recherche0,0080,009
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,500
Tête enseignante GPT0,440
Écart entre enseignants0,060 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineIncitatifs
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2006
Routes d'admission2
Résumé présentoui

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