Table 6.
Concurrent GEE model predicting PGSI categories during lockdown
| Wald Chi-Square | df | Sig | |
|---|---|---|---|
| (Intercept) | 117.393 | 1 | .00 |
| Gambling online | 1212.354 | 2 | .00 |
| Gambling fallacies | 67.940 | 1 | .00 |
| Total gambling losses | 46.681 | 1 | .00 |
| Impulsivity | 38.105 | 1 | .00 |
| Gambling frequency | 26.336 | 1 | .00 |
| Tobacco use | 20.235 | 7 | .01 |
| Age | 16.143 | 1 | .00 |
| Time spent gambling | 14.967 | 1 | .00 |
| Data collection period | 11.643 | 1 | .00 |
| # Of types of gambling games | 9.485 | 1 | .00 |
| Stress | 7.943 | 1 | .01 |
| Marijuana use | 4.782 | 7 | .69 |
| Social interaction | 3.903 | 1 | .05 |
| Illicit drug use | 3.755 | 1 | .05 |
| COVID—self health | 3.076 | 1 | .08 |
| COVID——employment impacts | 1.508 | 1 | .22 |
| Mood disorder | .224 | 1 | .64 |
| COVID—other’s health | .006 | 1 | .94 |
Concurrent GEE output (n = 1666) ordered by resultant Wald score after Intercept. Df = degrees of freedom. Sig = obtained significance level