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Trends in Female Authorship at American Academy of Otolaryngology-HNS Annual Meetings From 2007 to 2022.

作者信息

Ferraro Tatiana, Ganesan Sandhya, Arrighi-Allisan Annie, Zaheer Myra A, Fangmeyer Sarah, Sotudeh Sajad, Lee Esther, Tummala Neelima, Thakkar Punam, Lee Sean M, Hwa Tiffany Peng

机构信息

Drexel University College of Medicine, Philadelphia, Pennsylvania, USA.

George Washington University Department of Otolaryngology, Washington, DC, USA.

出版信息

Otolaryngol Head Neck Surg. 2025 Sep;173(3):626-635. doi: 10.1002/ohn.1316. Epub 2025 Jun 25.

Abstract

OBJECTIVE

This study aims to trends in female authorship in poster and oral presentations at American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) annual meetings.

STUDY DESIGN

Retrospective analysis of AAO-HNS annual meeting presentations.

SETTING

Abstract data from scientific contributions at AAO-HNS annual meetings.

METHODS

ChatGPT 3.5 API was used to predict gender identities of author names extracted from publicly available scientific oral and poster presentation abstracts between 2007 and 2022. Secondary variables included presentation type (oral or poster presentation), presentation topic, and authorship order (first author, presenter, and senior author). Logistic regression models were explored to determine the probability of female author participation as first, presenting, and senior author.

RESULTS

Our analysis included 48,877 authors extracted from 11,850 abstracts. For all oral and poster presentations, 29% of authors were female, increasing from 21.2% in 2007 to 37.9% in 2022 (P < .001). Although female authors accounted for 32% of presenters and 31% of first authors, they represented 22% of senior authors. Logistic regression models determined that the probability of female author participation increased by 5% each year; however, there remained a significant gap of 24.2% between male and female author participation in 2022.

CONCLUSION

Representation of female authors at annual AAO-HNS meetings has increased from 2007 to 2022 as demonstrated by artificial intelligence (AI)-generated gender identification of authors in this study. These trends reflect the changing demographics of otolaryngology trainees and their mentors. Future studies exploring methods to promote gender diversity are crucial for increasing female representation at all levels within otolaryngology research.

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