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Table 2 AI profiles of head of simulation labs

From: AI and inclusion in simulation education and leadership: a global cross-sectional evaluation of diversity

Head of sim lab AI profile

ChatGPT

(n = 848)

Gemini

(n = 624)

Claude

(n = 406)

p-value

Age in years, mean (SD)

47.5 (7.45)

42.0 (8.69)

57.0 (5.28)

< 0.001

Gender (as per LLM outputs)

   

< 0.001

 Female

420 (49.5)

333 (53.4)

148 (36.5)

 Male

442 (49.8)

252 (40.4)

258 (63.5)

 Non-binary

6 (0.7)

39 (6.3)

0 (0.0)

 Other

Race/ethnicity

   

< 0.001

 White

238 (28.1)

204 (32.7)

194 (47.8)

 Asian

220 (25.9)

166 (26.6)

110 (27.1)

 Black

186 (21.9)

105 (16.8)

48 (11.8)

 Hispanic/Latin

171 (20.2)

100 (16.0)

40 (9.9)

 Undetermined

33 (3.9)

49 (7.9)

14 (3.4)

Specialty

   

< 0.001

 Anesthesiology (n = 187)

47 (5.6)

48 (7.7)

92 (22.7)

 Emergency medicine (n = 265)

60 (7.2)

121 (19.4)

84 (20.7)

 Surgery (all types) (n = 221)

87 (10.4)

43 (6.9)

91 (22.4)

 Internal medicine (n = 175)

73 (8.7)

58 (9.3)

44 (10.8)

 Pediatrics (n = 156)

74 (8.9)

56 (9.0)

26 (6.4)

 All others (n = 861)*

494 (59.2)

298 (47.8)

69 (17.0)

  1. *Specialties mentioned, with less than 5% of representation: radiology, cardiology, obstetrics and gynecology, neurology, psychiatry, family medicine, dermatology, orthopedics, ophthalmology, pathology, critical care, gastroenterology, pulmonology, oncology, infectious diseases, endocrinology, rheumatology, trauma surgery, urology, allergy and immunology, geriatrics, pain management, palliative care, public health, plastic surgery, otolaryngology (ENT), nursing, medical education, simulation technology, and hematology