Table 4.
Regression Models Predicting Alcohol Consumption from IATs and Explicit Predictors.
| Consumption B | SE B | t | Cohen’s d | |
|---|---|---|---|---|
| Drinking Identity IAT | ||||
| Gender | −0.24 | 0.13 | −1.85 | 0.22 |
| Drinking Identity IAT | 0.67** | 0.20 | 3.32 | 0.39 |
| ASCS | 0.10*** | 0.02 | 6.02 | 0.71 |
| IAT × ASCS | −0.07 | 0.03 | −2.10 | 0.25 |
| Alcohol Excitement IAT | ||||
| Gender | −0.46*** | 0.13 | −3.62 | 0.43 |
| Alcohol Excitement IAT | 0.50** | 0.16 | 3.10 | 0.37 |
| DMQ-Enhance | 0.56*** | 0.06 | 9.14 | 1.09 |
| IAT × DMQ-Enhance | −0.37* | 0.15 | −2.39 | 0.29 |
| Alcohol Approach IAT | ||||
| Gender | −0.49** | 0.14 | −3.40 | 0.41 |
| Alcohol Approach IAT | 0.63** | 0.21 | 2.97 | 0.35 |
| BAS-Fun | 0.17*** | 0.03 | 5.25 | 0.63 |
| IAT × BAS-Fun | −0.17 | 0.09 | −1.88 | 0.22 |
| Alcohol Cope BIAT | ||||
| Gender | −0.53*** | 0.14 | −3.75 | 0.44 |
| Alcohol Cope BIAT | 0.19 | 0.16 | 1.20 | 0.14 |
| DMQ-Cope | 0.63*** | 0.11 | 5.66 | 0.67 |
| BIAT × DMQ Cope | −0.08 | 0.23 | −0.35 | 0.04 |
| Combined IAT Model | ||||
| Gender | −0.26 | 0.15 | −1.72 | 0.21 |
| Drinking Identity IAT | 0.78*** | 0.20 | 3.95 | 0.48 |
| Alcohol Excitement IAT | 0.44† | 0.20 | 2.17 | 0.26 |
| Alcohol Approach IAT | 0.39 | 0.23 | 1.71 | 0.21 |
| Alcohol Cope BIAT | 0.12 | 0.17 | 0.68 | 0.08 |
Note. IAT scores and explicit predictors were grand-mean centered. Gender was dummy-coded (0 = men, 1 = women). Cohen’s d = 2t/√df. The regression models used generalized linear models with a negative binomial log link. Consumption = number of drinks consumed on a typical week in the last three months. ASCS = Alcohol Self-Concept Scale. DMQ-Enhance = the enhance subscale of the Drinking Motives Questionnaire; DMQ-Cope = the coping subscale of the Drinking Motives Questionnaire; BAS-Fun = the fun-seeking subscale of the Behavioral Activation Scale. Corrected alpha = .029.
*
p < .029.
**
p < .01.
***
p < .001.