Table 5.
Binary logistic regression between baseline characteristics of the study population and the knowledge of artificial intelligence*.
| Categories | P-value | Odds ratio | Lower | Upper | |
|---|---|---|---|---|---|
| Age | 21–30 | 0.997 | Reference | ||
| 31–40 | 0.830 | 1.125 | 0.830 | 1.125 | |
| 41–50 | 0.999 | 0.000 | 0.999 | 0.000 | |
| 51–60 | 0.722 | 1.373 | 0.722 | 1.373 | |
| 60< | 0.891 | 1.174 | 0.891 | 1.174 | |
| Level of education | undergraduate | Reference | |||
| graduate | 0.276 | 2.366 | 0.503 | 11.129 | |
| Gender | Male | Reference | |||
| Female | 0.256 | 1.182 | 0.886 | 1.576 | |
| If undergraduate, then which professional? | 1st professional | 0.001 | Reference | ||
| 2nd professional | 0.299 | 1.508 | 0.299 | 1.508 | |
| 3rd professional | 0.978 | 0.989 | 0.978 | 0.989 | |
| 4th professional | 0.002 | 3.327 | 0.002 | 3.327 | |
| 5th professional | 0.025 | 2.092 | 0.025 | 2.092 | |
| 6th professional | 0.673 | 1.150 | 0.673 | 1.150 | |
| Graduate | 0.692 | 0.724 | 0.692 | 0.724 | |
| If postgraduate, specify the rank | Student | 0.569 | Reference | ||
| Resident | 0.231 | 1.639 | 0.231 | 1.639 | |
| Senior registrar | 0.528 | 1.652 | 0.528 | 1.652 | |
| Assistant professor | 0.053 | 3.784 | 0.053 | 3.784 | |
| Associate Professor | 1.000 | - | - | - | |
| Professor | 0.221 | 5.251 | 0.370 | 74.602 | |
| Constant | 0.000 | 0.107 |
*
The logistic regression model was statistically significant, X2 (7) = 58.33, p-value = 0.000, Hosmer and lemeshow test: 15.73(P-value = 0.028), The model explained 0.065 Nagelkerke R Square of the variance in knowledge of artificial intelligence among doctors and medical students in Syria.