Table 2.
Multivariable binary logistic regression model.a
| Characteristics | Unstandardized coefficient | SE | Wald | P value | Odds ratio (95% CI) |
| Age | –0.075 | 0.038 | 3.910 | .048 | 0.928 (0.861-0.999) |
| Education level | –0.967 | 1.289 | 0.563 | .45 | 0.380 (0.030-4.755) |
| Early premorbid adjustment scale [38] | –0.285 | 0.110 | 6.695 | .01 | 0.752 (0.606-0.933) |
| Trail Making Test A [39] | –0.030 | 0.025 | 1.488 | .22 | 0.970 (0.924-1.018) |
| Trail Making Test B | –0.005 | 0.010 | 0.278 | .60 | 0.995 (0.976-1.014) |
| Cognitive insight | 0.062 | 0.061 | 1.043 | .31 | 1.064 (0.944-1.200) |
aModel χ26= 25.3, P<.001. The model explained 44.7% (Nagelkerke R2) of the variance and correctly classified 77% (59/77) of the cases. Specifically, 55% (13/24) of users and 88% (47/53) of nonusers were correctly predicted by the model.