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. 2023 Mar 2;57(5):653–665. doi: 10.1007/s43465-023-00845-2

Table 4.

Multivariable model controlling for age, gender, and education

Multivariable model1 Beta coeff. (95% CI) p value
Base model
 Age (continuous) 0.016 (0.00020, 0.031) 0.0471
 Gender  < .0001
 Female Reference
 Male 1.06 (0.58, 1.53)  < .0001
 Other/unknown 0.30 (− 1.48, 2.09) 0.7389
Education 0.0018
 Less than HS/unknown − 0.73 (− 1.79, 0.34) 0.1812
 High school/equivalent Reference
 Associate degree 0.0052 (− 0.78, 0.79) 0.9896
 Bachelor’s degree 0.81 (0.17, 1.46) 0.0136
 Graduate degree 0.85 (0.24, 1.46) 0.0065
Base model +  experience with AI/ML
 Experience with AI/ML 0.0018
 Work(ed) in a field relevant/directly related to AI/ML 0.56 (− 0.46, 1.58) 0.2784
 Understand how AI/ML function 1.06 (0.40, 1.72) 0.0016
  Have researched terms 0.64 (− 0.11, 1.39) 0.0935
 Have heard of terms Reference
 Unknown/do not know what AI/ML mean − 0.43 (− 1.02, 0.16) 0.1515
Base model + perceived impact of AI in orthopaedic care
 Perceived impact of AI in orthopaedic care  < .0001
  Positive Reference
  Negative − 4.70 (− 5.42, − 3.98)  < .0001
 Not sure/unknown − 2.39 (− 2.77, − 2.01)  < .0001
Base model + perceived impact of AI on healthcare costs
 Perceived impact of AI on healthcare costs 0.0013
  Increase Reference
  Decrease 1.20 (0.55, 1.84) 0.0003
 Not sure/unknown 0.43 (− 0.080, 0.93) 0.0987
Base model + Would refuse AI if increased healthcare costs
 Would refuse AI if increased healthcare costs  < .0001
  Yes Reference
  No 2.16 (1.57, 2.76)  < .0001
 Not sure/unknown 1.00 (0.49, 1.52) 0.0001
Base model + acceptable for doctor to sell health data to a third party for building intelligent computers for healthcare
 Acceptable for doctor to sell health data to a third party for building intelligent computers for healthcare  < .0001
  Yes 1.28 (0.71, 1.85)  < .0001
  No Reference
 Not sure/unknown 0.67 (0.15, 1.20) 0.0116
Base model + survey format
 Survey format  < .0001
  REDCap Reference
  Tablet − 2.36 (− 3.26, − 1.47)  < .0001
  Paper − 0.24 (− 1.30, 0.82) 0.6526

Base model includes the three significantly associated variables, age, gender, and education. Subsequent regressions were performed with the base model and one additional predictor for statistical testing

1Except for Base model only results for demographic control variables not shown