Cross-sectional analysis of women in neurosurgery: a Canadian perspective
Notice bibliographique
Résumé
OBJECTIVE: Although the past decades have seen a steady increase of women in medicine in general, women continue to represent a minority of the physician-training staff and workforce in neurosurgery in Canada and worldwide. As such, the aim of this study was to analyze the experiences of women faculty practicing neurosurgery across Canada to better understand and address the factors contributing to this disparity. METHODS: A historical, cross-sectional, and mixed-method analysis of survey responses was performed using survey results obtained from women attending neurosurgeons across Canada. A web-based survey platform was utilized to collect responses. Quantitative analyses were performed on the responses from the study questionnaire, including summary and comparative statistics. Qualitative analyses of free-text responses were performed using axial and open coding. RESULTS: A total of 19 of 31 respondents (61.3%) completed the survey. Positive enabling factors for career success included supportive colleagues and work environment (52.6%); academic accomplishments, including publications and advanced degrees (36.8%); and advanced fellowship training (47.4%). Perceived barriers reported included inequalities with regard to career advancement opportunities (57.8%), conflicting professional and personal interests (57.8%), and lack of mentorship (36.8%). Quantitative analyses demonstrated emerging themes of an increased need for women mentors as well as support and recognition of the contributions to career advancement of personal and family-related factors. CONCLUSIONS: This study represents, to the authors' knowledge, the first analysis of factors influencing career success and satisfaction in women neurosurgeons across Canada. This study highlights several key factors contributing to the low representation of women in neurosurgery and identifies specific actionable items that can be addressed by training programs and institutions. In particular, female mentorship, opportunities for career advancement, and increased recognition and integration of personal and professional roles were highlighted as areas for future intervention. These findings will provide a framework for addressing these factors and improving the recruitment and retention of females in this specialty.
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 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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».