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Background: Patient sex is known to affect patient outcomes in sports medicine. Historically, many studies on athletes have focused on male athletes and been generalized to female athletes. Hypothesis: Studies with female first or senior authors will isolate female athletes as study participants more frequently than studies with male first or senior authors. Study Design: Systematic review; Level of evidence, 4. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocols, original research studies published between 2017 and 2021 that analyzed athletes were systematically screened from the 6 top sports medicine journals (British Journal of Sports Medicine ; Arthroscopy: The Journal of Arthroscopic and Related Surgery ; Knee Surgery, Sports Traumatology, Arthroscopy ; American Journal of Sports Medicine ; Orthopaedic Journal of Sports Medicine ; Sports Health: A Multidisciplinary Approach). Articles were included for analysis if they met the following criteria: (1) original sports medicine research study, (2) analysis involving athletes, and (3) inclusion of ≥10 participants. Exclusion criteria included (1) review articles of any type and (2) cadaveric studies. The determination of author sex was completed using the name-to-gender assignment algorithm Genderize.io (https://genderize.io/). Results: A total of 1146 studies were included in quantitative analysis. There were 246 studies with a female first author (21.5%) and 191 studies with a female senior author (16.7%). When looking at all authors (first, senior, and intermediate), 19.9% were female. Female first authors were over 4 times more likely to isolate female athletes in clinical research than male first authors (17.5% vs 3.8%, respectively; P <.001). Female senior authors were approximately twice as likely to isolate female athletes compared with male senior authors (11.5% vs 5.8%, respectively; P <.001). Conclusion: Female first authors were significantly more likely to perform research isolating female athletes. While improving the frequency of female athlete research is multifactorial, increasing the number of female researchers may have a direct effect on improving gender equality in sports medicine research. [ABSTRACT FROM AUTHOR]

Background: ChatGPT is an artificial intelligence chatbot capable of providing human-like responses for virtually every possible inquiry. This advancement has provoked public interest regarding the use of ChatGPT, including in health care. The purpose of the present study was to investigate the quantity and accuracy of ChatGPT outputs for general patient-focused inquiries regarding 40 orthopaedic conditions., Methods: For each of the 40 conditions, ChatGPT (GPT-3.5) was prompted with the text "I have been diagnosed with [condition]. Can you tell me more about it?" The numbers of treatment options, risk factors, and symptoms given for each condition were compared with the number in the corresponding American Academy of Orthopaedic Surgeons (AAOS) OrthoInfo website article for information quantity assessment. For accuracy assessment, an attending orthopaedic surgeon ranked the outputs in the categories of <50%, 50% to 74%, 75% to 99%, and 100% accurate. An orthopaedics sports medicine fellow also independently ranked output accuracy., Results: Compared with the AAOS OrthoInfo website, ChatGPT provided significantly fewer treatment options (mean difference, -2.5; p < 0.001) and risk factors (mean difference, -1.1; p = 0.02) but did not differ in the number of symptoms given (mean difference, -0.5; p = 0.31). The surgical treatment options given by ChatGPT were often nondescript (n = 20 outputs), such as "surgery" as the only operative treatment option. Regarding accuracy, most conditions (26 of 40; 65%) were ranked as mostly (75% to 99%) accurate, with the others (14 of 40; 35%) ranked as moderately (50% to 74%) accurate, by an attending surgeon. Neither surgeon ranked any condition as mostly inaccurate (<50% accurate). Interobserver agreement between accuracy ratings was poor (κ = 0.03; p = 0.30)., Conclusions: ChatGPT provides at least moderately accurate outputs for general inquiries of orthopaedic conditions but is lacking in the quantity of information it provides for risk factors and treatment options. Professional organizations, such as the AAOS, are the preferred source of musculoskeletal information when compared with ChatGPT., Clinical Relevance: ChatGPT is an emerging technology with potential roles and limitations in patient education that are still being explored., Competing Interests: Disclosure: No external funding was received for this work. The Article Processing Charge for open access publication was funded by St. Joseph's University Medical Center. The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article (http://links.lww.com/JBJSOA/A636)., (Copyright © 2024 The Authors. Published by The Journal of Bone and Joint Surgery, Incorporated. All rights reserved.)