“I Really Wish We Had a Talk on Advocacy That Wasn't Boring”: Toward a Health Advocacy Curriculum That Meets the Needs of Canadian Hematology Residents
Notice bibliographique
Résumé
Background: There is an ongoing need to incorporate health advocacy training into postgraduate medical education. In Canadian hematology training, there are no existing dedicated health advocacy curricula. As a first step toward the development of such curricula, we sought to determine what the health advocate role entails for hematologists, identify necessary health advocacy competencies in hematology, and understand how these competencies could be learned in hematology residency training. Methods: Semi-structured interviews were conducted with practicing hematologists in Ontario, Canada to elicit key health advocacy competencies for hematologists and learn how these are acquired. Participants were selected using a purposeful, maximal variation sampling strategy. Interviews were recorded in their entirety and transcribed by hand. Data were deidentified after collection and a computer software (NVivo) was used to create codes through an iterative approach. The codes were analyzed using the thematic analysis technique outline by Braun and Clarke (Braun & Clarke, 2006). A deductive approach was employed, incorporating the CanMEDs framework and previously described conceptual frameworks pertaining to health advocacy. Results: 8 hematologists (5 academic-based, 3 community-based; 4 malignant hematologists and 4 non-malignant hematologists) were included. Hematologists engage in advocacy activities at the clinical, paraclinical, and supraclinical levels and conduct advocacy work most commonly through a directed agency strategy. Drug access was the most prominent advocacy challenge encountered by hematologists. Health disparities that were identified included the rural/remote divide and socioeconomic status. Health advocacy competencies employed by hematologists closely resembled those used by other physicians, with some difference on emphasis. Skills that hematologists found were important to advocacy training were leveraging interprofessional connections, using research as advocacy, and acquiring health systems knowledge. Early exposure to advocacy in training, effective mentorship, and learning from practical examples and experience were viewed as the most effective ways to learn health advocacy skills. Conclusion: This study identified the breadth of advocacy activities conducted by hematologists and identified numerous competencies that are important to being an effective health advocate. Health advocacy education in hematology training programs should start early, be practical and engaging, be integrated longitudinally into existing teaching and learning activities, and harness the power of mentorship relationships. This work is the first step in addressing the informational gap required to design a novel health advocacy curriculum for hematology residents.
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 | 0,011 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,027 | 0,010 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,003 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
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 ».