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Enregistrement W4417004621 · doi:10.1182/blood-2025-2867

A Canadian national needs assessment for an immunology curriculum for hematology residents

2025· article· en· W4417004621 sur OpenAlexaffabout
Jennifer Teichman, Eric Tseng, Christopher Lemieux, Hayley Merkeley, Vicky Chan, Christine Cserti‐Gazdewich, Catharine M. Walsh

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueInnovations in Medical Education
Établissements canadiensHospital for Sick ChildrenSt. Paul's HospitalUniversité LavalSt. Michael's HospitalUniversity Health NetworkUniversity of TorontoUniversity of British Columbia HospitalSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésCurriculumHematologyClinical immunologyMEDLINEClinical PracticeScholarshipNeeds assessment

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Hematology training in Canada is competency-based and consists of two years of integrated clinical and laboratory training following completion of internal medicine residency. Understanding the fundamental principles of immunology is critical to both clinical practice and scholarship in hematology. However, there is currently no national consensus on which immunology topics should be taught in Canadian hematology training programs. We conducted a national needs assessment of immunology teaching topics, as perceived by hematologists and trainees, as an initial step in Kern's model for curriculum development. Methods: An online REDCap survey was distributed across Canada to current hematology residents (postgraduate years 4 and 5), recent (within two years) graduates, current and former (within five years) hematology program directors (PDs), academic hematologists with clinical teaching roles, and community hematologists with leadership roles and/or experience delivering immunotherapies in community settings (purposive sampling). Results: There were 88 survey respondents. Fifty-five identified as female, 32 as male, and one preferred not to say. 27% were current trainees, 25% recent graduates, 25% academic (non-PD) hematologists, 15% current or former PDs, and 8% were community hematologists. Forty-seven (53%) resided in Ontario, 14 (16%) in Quebec, 12 (14%) in British Columbia, 10 (11%) in Alberta, 2 (2%) each in Manitoba and Nova Scotia, and 1 (1%) in Newfoundland. Of the non-trainees, 27 (42%) had been in independent practice for ≤2 years; 11 (17%) for >2 to ≤5 years; 4 (6%) for >5 to ≤10 years; 8 (13%) for >10 to ≤15 years; 7 (11%) for >15 to ≤20 years, and 4 (6%) for >20 years. The percentage of non-trainees who spend ≥50% of clinical time in malignant hematology, classical hematology, transfusion medicine, stem cell transplantation or other was 56%, 27%, 11%, 8% and 3%, respectively. Sixty-four percent of respondents self-rated their knowledge of immunology concepts as “basic” (“I know the fundamentals and could explain these concepts to patients”), 25% as “limited” (“I’ve been introduced to some of these concepts”), 8% as “expert” and 2% as “no knowledge.” Nine of the 13 (69%) current and former PDs reported that their programs included dedicated teaching on immunology topics; only 33% of non-PDs (trainees and hematologists) indicated this and 15% could not recall. According to PDs, the topics most commonly taught included mechanisms of immunosuppressive therapies and immune therapeutics, B cell development and activation, immune checkpoints, the function of cells/tissues of the immune system, and HLA biology. Respondents were asked whether the current amount of immunology taught in their programs was adequate to prepare residents for clinical hematology practice. On a sliding scale from 0 (far too little content) to 5 (just right) to 10 (far too much content), the median score was 3, and 70% of respondents selected either 2 or 3. This was similar across PDs and non-PDs. Seventy-eight percent of non-trainees indicated that immunology concepts were either “extremely” or “very” relevant to everyday clinical hematology practice; 17%, 2% and 2% indicated they were occasionally, rarely and not relevant, respectively. Eighty percent of respondents felt it was either “very” or “extremely” important to incorporate immunology topics into hematology training; 17%, 2% and 0% felt it was either “somewhat important”, “neutral”, or “not important”, respectively. Greater immunology knowledge was felt to have the greatest potential impact on respondents' comfort with the following clinical activities: prescribing treatments that harness the immune system, counselling patients starting immunotherapies, managing patients with acquired immunodeficiency, and interpreting/critically appraising scientific literature involving immunotherapies or disease biology. Respondents' preferred formats of curricular delivery were an immunology bootcamp (77%), online learning modules (60%) and case-based teaching (61%). Conclusion: There is broad agreement among trainees, PDs, and practicing hematologists across Canada that current immunology teaching in hematology training programs is insufficient and a dedicated immunology curriculum would enhance competencies in clinical hematology practice. The next step involves a Delphi process to achieve consensus on key curricular topics to be incorporated into a future national curriculum.

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)0,006
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,964
Score d'incertitude au seuil0,370

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,015
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0040,001
Communication savante0,0010,001
Science ouverte0,0020,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,369
Écart entre enseignants0,356 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
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

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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