Conflict of interest policies at Belgian medical faculties: Cross-sectional study indicates little oversight
Notice bibliographique
Résumé
BACKGROUND: Medical students encounter pharmaceutical promotion from the very start of their training. Medical schools have an important role to play in educating medical students regarding the interactions between healthcare professionals (HCPs) and industry and in protecting them from commercial influence and conflict of interest (COI). In 2019, medical student associations in Belgium and abroad called for more preparation in dealing with COI and for a more independent medical training. As little information is available on the situation in our country, we undertook an assessment of conflict of interest policies at Belgium's medical schools. We relied on a methodology already used in studies from USA, Canada, Australia, France and Germany and adapted it to the Belgian context. METHODS: We identified 10 medical schools in Belgium. We searched the website of each medical school in November 2019 with standardized keywords for COI policies and learning activities on COI in the curriculum. The deans of medicine were invited to participate by sending us information that we could have overlooked during our web-based searches. We also consulted personal contacts within faculties among students and teachers. Based on a list of 15 criteria adapted from North American and French studies, we calculated a total for each faculty of medicine with a maximum score of 30 points. RESULTS: By December 2019, we had gathered a set of written documents for four faculties of medicine (40%) containing policies with varying degrees of precision and relevance to our survey. We found elements of the curriculum addressing the COI issue for one faculty (10%). In all cases, these policies consisted of "moderate" initiatives with little or no "restrictive" elements. Only one faculty showed interest in our study by providing us with relevant information (10%). Half of the faculty notified us of their refusal to participate in the study (50%) and the other faculties either did not respond or did not provide us with any information (40%). The maximum score obtained was 3 out of 30 points with six faculties scoring 0 (60%). CONCLUSION: There is little transparency regarding interactions between medical students and pharmaceutical companies at Belgian medical faculties, which may create COI issues. Initiatives to protect students from pharmaceutical promotion and to train them to manage their future interaction with pharmaceutical companies have a limited scope and are isolated. This is inconsistent with international recommendations from Health Action International, World Health Organization or the American Medical Students' Association. The Belgian government has legislated in favor of more transparency in the relation between HCPs and pharmaceutical industry. Indeed, it made the disclosure of benefits granted by the industry compulsory and limited their value. Our results show that there is still some way to go to ensure an independent medical training for future Belgian physicians.
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 | 0,007 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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 ».