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. 2024 Jun 18;9:38. doi: 10.1186/s41235-024-00566-6

Table 4.

Results of the multilevel logistic regression model predicting vaccination status

Fixed effects b SE z p OR 95% CI
Intercept 0.26 0.35 0.72 .469 1.29 [0.65, 2.58]
Age 0.28 0.04 7.74  < .001 1.32 [1.23, 1.42]
Gender (male) − 0.31 0.06 − 4.83  < .001 0.73 [0.65, 0.83]
Gender (non-binary) 0.32 0.22 1.44 .149 1.38 [0.89, 2.14]
Education level (no schooling) − 0.80 0.76 − 1.06 .287 0.45 [0.10, 1.97]
Education level (primary) 0.24 0.60 0.40 .691 1.27 [0.39, 4.13]
Education level (secondary) − 0.05 0.07 − 0.74 .459 0.95 [0.83, 1.09]
Education level (postgraduate) 0.33 0.09 3.60  < .001 1.39 [1.16, 1.66]
Relative income 0.08 0.03 2.41 .016 1.08 [1.02, 1.15]
Essential worker status 0.51 0.08 6.43  < .001 1.67 [1.43, 1.95]
Psychological distress − 0.01 0.04 − 0.31 .754 0.99 [0.92, 1.06]
Intolerance of uncertainty 0.04 0.04 1.27 .204 1.05 [0.98, 1.12]
Delay discounting (AuC) 0.14 0.03 4.52  < .001 1.15 [1.08, 1.22]
Random effects Estimate SD
Intercept error variance (country) 1.58 1.26

Note. The variable was standardized. AuC = Area-under-the-curve, CI = confidence interval; OR = odds ratio; SD = standard deviation; SE = standard error of the mean. Female was used as the reference category for gender. Undergraduate level of education was used as the reference category for level of education