Abstract: Sexual Inequality for Women in Plastic Surgery: A Systematic Scoping Review
Notice bibliographique
Résumé
INTRODUCTION: Previous research has highlighted the gender-based disparities that are present throughout the field of surgery.1 The aim of this study is to evaluate the breadth and variability of the issues facing women in plastic surgery, worldwide. METHODS: A systematic scoping review was undertaken from October 2016 to January 2017, with no restrictions on date or language. We followed the five scoping review steps as proposed by Arskey and O’Malley: (1) Identification of the research question; (2) Identification of relevant studies; (3) Study selection; (4) Data charting and (5) Collation and reporting of results.2 A narrative synthesis of the literature according to themed issues was developed, together with a summary of relevant numeric data. RESULTS: From the 2,247 articles found in the search, a total of 53 articles were included in the final analysis. The majority of articles were published from the US. Eight themes were identified, as follows: 1. Workforce figures; 2. Gender bias and discrimination; 3. Leadership and academia; 4. Mentorship and role models; 5. Pregnancy, parenting and childcare; 6. Relationships, work-life balance and professional satisfaction; 7. Patient/public preference; and 10. Retirement and financial planning. DISCUSSION AND CONCLUSION: There were several key findings. First, despite improvement in numbers over time, women plastic surgeons continue to be underrepresented in the United States, Canada and Europe, with prevalence ranging from 14%-25.7%.3,4 Academic plastic surgeons are less frequently female than male, and women academic plastic surgeons score less favorably when outcomes of academic success, such as h index and number of peer-reviewed publications are evaluated.5 Finally, there has been a shift away from overt discrimination towards a more ingrained, implicit bias affecting individuals and institutions; most published cases of bias and discrimination are in association with pregnancy. The first step toward addressing the issues facing women plastic surgeons is recognition and articulation of the issues. Further research may focus on analyzing geographic variation in the issues and developing appropriate interventions. Reference Citations: 1. Kawase K, Carpelan-holmstrom M, Kwong A, Sanfey H. Factors that Can Promote or Impede the Advancement of Women as Leaders in Surgery: Results from an International Survey. World J Surg. 2016;40:258–66. 2. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8:19–32. 3. Aspalter M, Linni K, Metzger P, Hölzenbein T. Female choice for surgical specialties: development in Germany, Austria, and Switzerland over the past decade. Eur Surg. 2014;46:234–8. 4. Macadam SA, Kennedy S, Lalonde D, Anzarut A, Clarke HM, Brown EE. The Canadian plastic surgery workforce survey: interpretation and implications. Plast Reconstr Surg. 2007;119:2299–306. 5. Therattil PJ, Hoppe IC, Granick MS, Lee ES. Application of the h-Index in Academic Plastic Surgery. Ann Plast Surg. 2014;0:1.
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 | 0,013 | 0,076 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| 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 ».