Table 2.

Aims and outcome variables

Aim	Items used	Predictor variables
Aim 1: examine the sociodemographic variables associated with support for AI in Australia	1. Level of support for the development of AI (B01)	Gender (A03) Age (A01/A02) Self-identifies as having a chronic health condition or disability (F18) Education (F07) Household income (F06) Speaks languages other than English at home (F16) Resides in a capital city (A04)* SEIFA (A04)* Self-reported health (F17) Computer science or programming experience (F05)
Aim 2: examine the sociodemographic variables associated with support for HCAI	2. Level of support for HCAI that is unexplainable (C03) 3. Level of support for HCAI that requires sharing personal data (C04) 4. Level of support for HCAI that leads to clinician deskilling (C05)
Aim 3: determine whether sociodemographic characteristics were associated with different preferences in AI-integrated healthcare	5. Importance of explainability (C01a) 6. Importance of getting an answer quickly (C01b) 7. Importance of getting an accurate answer (C01c) 8. Importance of being able to talk to a person about one’s health (C01d) 9. Importance of knowing who is responsible for one’s care (C01e) 10. Importance of reducing health system costs (C01f) 11. Importance of knowing the system treats everyone fairly (C01g)

*Residing in a capital city and SEIFA are derived from self-reported postcode.

AI, artificial intelligence; HCAI, healthcare artificial intelligence; SEIFA, Socio-Economic Indexes for Areas.