On the shoulders of giants: correlation of rates of female first authorship with senior authorship gender
Notice bibliographique
Résumé
Dear Editor Surgical subspecialties have historically had among the greatest gender imbalances in medicine1, manifesting in lower and slower rates of promotion among female physicians2. Publications contribute significantly to academic promotion2, but women are under-represented among authors of RCTs in surgery3. Given the importance of mentorship and sponsorship in surgical career development and promotion2, the predictors of female first authorship among RCTs of novel minimally invasive surgical (MIS) techniques were investigated, with a particular focus on the correlation between female senior (last) and female first authorship. A systematic review of RCTs examining novel MIS techniques was performed using Embase (OvidSP), MEDLINE (OvidSP), and Cochrane (Wiley) databases. The search strategy has been published previously3. Study selection was performed independently by three reviewers. Data were independently abstracted by two researchers and verified by two separate researchers. This review was conducted in concordance with PRISMA guidelines and was registered prospectively in the PROSPERO database (CRD4202021158). For each study, first and last author names were extracted. Author gender was determined via an online search using full name, institutional affiliation, and year of publication, and subsequently validated using Genderize.io (https://genderize.io/). Study variables included: last author gender, study design, sample size, median follow-up, participant age and gender, risk of bias, number of participating centres/nations, and funding source. χ2 and Fisher’s exact tests were used for univariable comparisons. Univariable and multivariable logistic regression analyses were used to calculate predictors of female first authorship. Only variables significant in univariable analyses were included in the multivariable model. Variable multicollinearity was evaluated using the variance inflation factor test; a cut-off value of 5 excluded variables on the basis of high degree of multicollinearity. The likelihood ratio test was used to determine the overall significance of categorical variables. P < 0.050 was considered statistically significant. All statistical analyses were undertaken using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria). Among 9321 initial citations, 496 were deemed eligible, although it was not possible to determine first or last author gender in nine studies. Women were first author in 66 (13.9%) and last author in 60 (12.1%) studies. Of studies with female last authors, 13 (21%) also had a female first author, whereas 53 studies (12.8%) with a male last author had a female first author (Table 1). In both univariable (OR 1.93, 95 per cent c.i. 0.94 to 3.73) and multivariable (adjusted OR 1.71, 0.80 to 3.46) logistic regression models, female senior authorship was not associated with increased odds of female first authorship. RCTs with female-only patient populations were more likely to have a female first author (OR 2.46, 1.08 to 5.30; P = 0.025). First and last author gender in RCTs of minimally invasive surgical techniques Values in parentheses are percentages. Among RCTs in surgery, there was no significant correlation between female senior authors and female first authors; however, there was a non-significant trend towards trials with female senior authors being more likely to have female first authors. This non-significant trend suggests that female senior surgeon mentorship may be influential in academic success for early-career female surgeons. Although it included RCTs published over more than 30 years, the present analysis was underpowered to demonstrate a statistically significant relationship between last author gender and the likelihood of female first authorship. Inclusion of as few as 50 more studies would have provided more than 50 per cent probability of conventional statistical significance (P < 0.050)4. Gender diversity has been shown to improve team and work quality across a variety of industries. As women are penalized for diversity-valuing behaviours5, it is paramount that men embrace the role of mentoring women in surgery. Female authors also demonstrate increased focus on female-only populations, illustrating a heightened awareness of issues affecting women. A.N.L. and C.J.D.W. are joint senior authors of this article. Disclosure. The authors declare no conflict of interest.
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 | 0,006 | 0,001 |
| 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 | 0,000 | 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) | 0,001 | 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 ».