Table 2.

Comparison of demographics between respondents who had and had not used artificial intelligence (AI) chatbots.

		Had used AI chatbots (n=59), n (%)	Had not used AI chatbots (n=135), n (%)	P value
Age (years), mean (SD)		38.7 (9.1)	38.7 (9.5)	>.99
Gender					.40
	Woman	39 (66.1)	103 (76.3)
	Man	19 (32.2)	29 (21.5)
	Nonbinary or third gender	0 (0.0)	1 (0.7)
	Preferred not to self-describe	1 (1.7)	2 (1.5)
Years of practice					.41
	0-5	15 (25.4)	40 (29.6)
	6-10	16 (27.1)	62 (45.9)
	11-15	11 (18.6)	21 (15.6)
	>15	17 (28.8)	39 (28.9)
Area of practice					.002
	Hospital	38 (64.4)	74 (54.8)
	Community	4 (6.8)	25 (18.5)
	Ambulatory	12 (20.3)	24 (17.8)
	Academia	11 (18.6)	5 (3.7)
	Specialty	0 (0.0)	6 (4.4)
Coworker use of AI chatbots					<.001
	Yes	25 (42.4)	9 (6.7)
	No	9 (15.3)	69 (51.1)
	Unsure	25 (42.4)	57 (42.2)
AI policy at practice site					.02
	Yes	11 (18.6)	8 (5.9)
	No	30 (50.8)	82 (60.7)
	Unsure	18 (30.5)	45 (33.3)
“How likely would you be to make a health care (ie, patient care or treatment) related recommendation based on the information an AI Chatbot (eg, ChatGPT) provides you?”					.33
	Extremely unlikely	32 (54.2)	57 (42.2)
	Somewhat unlikely	16 (27.1)	41 (30.4)
	Neither likely nor unlikely	9 (15.3)	25 (18.5)
	Somewhat likely	2 (3.4)	12 (8.9)
	Extremely likely	0 (0.0)	0 (0.0)
“How likely would you be to make a policy related decision based on the information an AI Chatbot (eg, ChatGPT) provides you?”					.25
	Extremely unlikely	17 (28.8)	49 (36.3)
	Somewhat unlikely	15 (25.4)	37 (27.4)
	Neither likely nor unlikely	16 (27.1)	34 (25.2)
	Somewhat likely	11 (18.6)	12 (8.9)
	Extremely likely	0 (0.0)	3 (2.2)