Survey of equity, diversity, and inclusion in Canadian anesthesiology residency programs
Notice bibliographique
Résumé
BACKGROUND: Increased diversity in the healthcare workforce is associated with a higher quality of patient care, reduction in health disparities, and enhanced team performance. Women and individuals from minoritized groups continue to face underrepresentation in the medical workforce. Specifically, existing data has shown women and minoritized groups are underrepresented in the speciality of anesthesiology in the United States. To address this, increased diversity is needed within residency training programs to better address the widening healthcare inequities affecting marginalized populations. Currently, there are no studies describing either the demographics of Canadian anesthesiology residents or equity, diversity, and inclusion (EDI) initiatives within their training programs. This study aims to describe these in order to guide future EDI initiatives in Canada. METHODS: Ethics approval was obtained from the University of Alberta Research Ethics Board. An anonymous online survey focusing on demographics, perceptions of EDI, and existing EDI initiatives was distributed to resident trainees across the seventeen Canadian anesthesiology residency programs. RESULTS: We analyzed 123 responses from 15 of 17 residency programs. For gender, 49% of respondents identified as male, 48% as female, and 1% as non-binary. For sexual identity, 84% of respondents identified as heterosexual, 8% as bisexual, and 7% as lesbian or gay. For ethnicity, 67% identified as White, 13% as East Asian, 6% as Arab, 4% as Black, 1% as Southeast Asian, 1% as Indigenous, and 0% as West Asian or Hispanic. Furthermore, 87% of respondents felt EDI was important, however 52% were unaware of any initiatives in their programs, and 43% reported receiving no EDI training. The overall gender representation seen in our data closely mirrors that of the Canadian 2021 census data. We saw a four times higher representation of LGBTQ individuals compared to Canadian demographic data. Indigenous, Hispanic, Southeast Asian, and West Asian individuals were underrepresented, while other ethnicities were well represented. CONCLUSIONS: Our study used self-identification data of ethnicity, gender, and sexuality to reduce bias and provide a more accurate representation of the EDI landscape in Canadian anesthesiology residency programs. Our results showed that there is still underrepresentation of multiple ethnicities compared to Canadian demographics. Most residents believe EDI is important, however, the majority were unaware of any initiatives within their programs. Areas of future growth include better defining which EDI initiatives exist within training programs, studying how EDI programs are implemented in training programs, and examining perceived barriers to both having and implementing said initiatives. Through doing so, anesthesiology residency programs across Canada can best ensure their trainees reflect the diverse communities they serve and are educated to care for minoritized groups.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,004 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».