“Asset exchange”—interactions between patient groups and pharmaceutical industry: Australian qualitative study
Notice bibliographique
Résumé
OBJECTIVE: To understand and report on the nature of patient group interactions with the pharmaceutical industry from the perspective of patient group representatives by exploring the range of attitudes towards pharmaceutical industry sponsorship and how, why, and when interactions occur. DESIGN: Empirical qualitative interview study informed by ethics theory. SETTING: Australian patient groups. PARTICIPANTS: 27 participants from 23 Australian patient groups that represented diverse levels of financial engagement with the pharmaceutical industry. Groups were focused on general health consumer issues or disease specific topics, and had regional or national jurisdictions. ANALYSIS: Analytic techniques were informed by grounded theory. Interview transcripts were coded into data driven categories. Findings were organised into new conceptual categories to describe and explain the data, and were supported by quotes. RESULTS: A range of attitudes towards pharmaceutical industry sponsorship were identified that are presented as four different types of relationship between patient groups and the pharmaceutical industry. The dominant relationship type was of a successful business partnership, and participants described close working relationships with industry personnel. These participants acknowledged a potential for adverse industry influence, but expressed confidence in existing strategies for avoiding industry influence. Other participants described unsatisfactory or undeveloped relationships, and some participants (all from general health consumer groups) presented their groups' missions as incompatible with the pharmaceutical industry because of fundamentally opposing interests. Participants reported that interactions between their patient group and pharmaceutical companies were more common when companies had new drugs of potential interest to group members. Patient groups that accepted industry funding engaged in exchanges of "assets" with companies. Groups received money, information, and advice in exchange for providing companies with marketing, relationship building opportunities with key opinion leaders, coordinated lobbying with companies about drug access and subsidy, assisting companies with clinical trial recruitment, and enhancing company credibility. CONCLUSIONS: An understanding of the range of views patient groups have about pharmaceutical company sponsorship will be useful for groups that seek to identify and manage any ethical concerns about these relationships. Patient groups that receive pharmaceutical industry money should anticipate they might be asked for specific assets in return. Selective industry funding of groups where active product marketing opportunities exist might skew the patient group sector's activity towards pharmaceutical industry interests and allow industry to exert proxy influence over advocacy and subsequent health policy.
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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 | 0,017 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,009 | 0,008 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,004 |
| 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 ».