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Table 1 AI profiles of simulation instructors

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

Sim instructor AI profile

ChatGPT

(n = 850)

Gemini

(n = 644)

Claude

(n = 520)

p-value

Age in years, mean (SD)

41.4 (8.9)

47.9 (8.3)

40.5 (9.7)

< 0.001

Gender (as per LLM output)

   

< 0.001

 Female

425 (50.0)

329 (51.1)

264 (50.8)

 Male

424 (49.9)

243 (37.7)

256 (49.2)

 Non-binary

1 (0.1)

44 (6.8)

0 (0.0)

 Other

0 (0.0)

28 (4.3)

0 (0.0)

Race/ethnicity

   

< 0.001

 White

246 (28.9)

196 (30.4)

179 (34.4)

 Asian

211 (24.8)

197 (30.6)

145 (27.9)

 Black

207 (24.4)

108 (16.8)

103 (19.8)

 Hispanic/Latin

175 (20.6)

99 (15.4)

82 (15.8)

 Undetermined

11 (1.3)

44 (6.8)

11 (2.1)

Specialty

   

< 0.001

 Anesthesiology (n = 180)

62 (7.3)

59 (9.2)

59 (11.3)

 Emergency medicine (n = 265)

73 (8.6)

127 (19.7)

65 (12.5)

 Surgery (all types) (n = 203)

86 (10.1)

54 (8.4)

63 (12.1)

 Internal medicine (n = 188)

73 (8.6)

53 (8.2)

62 (11.9)

 Pediatrics (n = 201)

83 (9.8)

59 (9.2)

59 (11.3)

 All others (n = 979)*

473 (55.6)

292 (45.3)

214 (40.9)

  1. *Specialties mentioned, with less than 7% 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, nursing, otolaryngology (ENT), and urology