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Table 3 Linear regression for the rejection of health warning labels (HWLs) on wine and vodka bottles

From: How health warning labels on wine and vodka bottles influence perceived risk, rejection, and acceptance

 

Wine (n = 255)

Vodka (n = 250)

 

Unstandardized B

[95% CI]

SE (B)

Beta

t

Unstandardized B

[95% CI]

SE (B)

Beta

t

Constant

2.39 [0.07, 4.70]

1.18

 

2.03

1.42 [-0.88, 3.73]

1.17

 

1.22

HWLs’ effectivenessa

-0.38 [-0.52, -0.24]

0.07

-0.32

-5.41**

-0.41 [-0.53, -0.28]

0.06

-0.36

-6.31**

Social normsa

0.17 [0.01, 0.33]

0.08

0.15

2.15*

0.20 [-0.03, 0.43]

0.12

0.13

1.73

Positive health effectsa

0.22 [0.05, 0.39]

0.09

0.17

2.60*

0.19 [-0.01, 0.40]

0.10

0.13

1.87

Benefits of drinking alcohol

0.13 [0.00, 0.27]

0.07

0.12

1.94

0.11 [-0.04, 0.26]

0.08

0.09

1.43

Individualistic values

0.20 [0.04, 0.36]

0.08

0.15

2.52*

0.31 [0.16, 0.45]

0.07

0.24

4.13**

Alcohol consumptiona

0.00 [-0.01, 0.01]

0.01

-0.01

-0.14

0.00 [-0.03, 0.03]

0.02

-0.01

-0.15

Genderb

0.01 [-0.35, 0.38]

0.18

0.00

0.07

0.08 [-0.28, 0.43]

0.18

0.02

0.43

Age

0.00 [-0.01, 0.01]

0.01

0.02

0.41

0.01 [0.00, 0.02]

0.01

0.08

1.42

Education

0.07 [-0.12, 0.26]

0.10

0.04

0.71

0.03 [-0.16, 0.21]

0.10

0.01

0.27

  1. * p < 0.05, ** p < 0.01
  2. a These variables referred to beverage types. For example, participants in the wine groups were asked about HWLs’ effectiveness on wine bottles, whereas participants in the vodka groups were asked about HWLs’ effectiveness on vodka bottles
  3. b Dummy-coded gender: 0 = male, 1 = female