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|
Predictor
|
Coefficient [95% CI]
|
SE
|
\(t\)
|
\(p\)
|
|---|
|
Log standard drinks/daya
|
|
Intercept
|
− 1.38 [− 1.82, − 0.95]
|
0.22
|
− 6.19
|
< 0.001*
|
|
Age
|
− 0.01 [− 0.02, 0.00]
|
0.01
|
− 2.32
|
0.021*
|
|
Male
|
1.14 [0.84, 1.44]
|
0.15
|
7.53
|
< 0.001*
|
|
Remote
|
0.29 [− 0.29, 0.87]
|
0.30
|
0.99
|
0.32
|
|
Need satisfaction†
|
0.48 [0.33, 0.63]
|
0.08
|
6.17
|
< 0.001*
|
|
Conformity†
|
0.15 [− 0.01, 0.31]
|
0.08
|
1.88
|
0.061
|
|
Exclusion†
|
0.14 [− 0.01, 0.29]
|
0.08
|
1.79
|
0.074
|
|
Dependence†
|
|
Intercept
|
− 0.29 [− 0.50, − 0.08]
|
0.11
|
− 2.72
|
0.007*
|
|
Age
|
0.00 [0.00, 0.01]
|
0.00
|
1.95
|
0.052
|
|
Male
|
0.20 [0.06, 0.35]
|
0.07
|
2.81
|
0.005*
|
|
Remote
|
0.16 [− 0.11, 0.44]
|
0.14
|
1.16
|
0.25
|
|
Need satisfaction†
|
0.13 [0.06, 0.21]
|
0.04
|
3.55
|
< 0.001*
|
|
Conformity†
|
0.17 [0.10, 0.25]
|
0.04
|
4.51
|
< 0.001*
|
|
Exclusion†
|
0.34 [0.26, 0.41]
|
0.04
|
8.98
|
< 0.001*
|
- *p < 0.05; †standardised variable; \(n\) = 597
- aStandard drinks per day was log-transformed, to interpret coefficients (\({\beta }_{i}\)) as percent increases for log-transformed outcomes (y) the following formula can be used: \(\Delta{\%}y=({e}^{{\beta }_{i}}-1)*100\). Dependence items were summed to create an aggregate measure (range 0–12)
