Table 3. Multivariate logistic regression results with demographic and psychological variables as predictors of past-month skin betting.
Advertisements Esports skin betting vs not (ref. = not) |
Qualtrics Esports skin betting vs not (ref. = not) |
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Variables | B | S.E. | Z | p | Odds Ratio [95% CI] | B | S.E. | Z | p | Odds Ratio [95% CI] |
Age (in years) | -.05 | .05 | -.99 | .324 | .95 [.86,1.05] | .18 | .08 | 2.35 | .020 | 1.20 [1.03,1.40] |
Gender | -.17 | .19 | -.92 | .359 | .84 [.58,1.22] | .30 | .26 | 1.17 | .240 | 1.35 [.82,2.23] |
ATSI | .78 | .18 | 4.25 | < .001 | 2.19 [1.52,3.14] | .53 | .33 | 1.57 | .116 | 1.69 [.88,3.26] |
Parents living together | .27 | .18 | 1.57 | .117 | 1.32 [.93,1.87] | .06 | .29 | .20 | .844 | 1.06 [.61,1.85] |
Wellbeing | -.05 | .03 | -1.63 | .104 | .95 [.90,1.01] | -.09 | .06 | -1.41 | .157 | .92 [.81,1.04] |
Impulsiveness | .07 | .02 | 3.06 | .002 | 1.07 [1.03,1.13] | -.01 | .03 | -.48 | .631 | .99 [.93,1.05] |
Problematic gaming | .30 | .18 | 1.70 | .089 | 1.35 [.95,1.91] | .79 | .25 | 3.11 | .002 | 2.21 [1.34,3.63] |
Played esports game | .43 | .18 | 2.39 | .017 | 1.53 [1.08,2.18] | 1.09 | .28 | 3.93 | < .001 | 2.96 [1.72,5.09] |
Watched esports | .66 | .18 | 3.65 | < .001 | 1.94 [1.36,2.78] | .62 | .28 | 2.21 | .027 | 1.86 [1.07,3.24] |
Competed in esports | 1.53 | .35 | 4.47 | < .001 | 4.60 [2.36,8.98] | 1.61 | .31 | 5.14 | < .001 | 5.01 [2.71,9.27] |
Intercept | -2.65 | .96 | -2.76 | .006 | .07 [.01,0.46] | -5.00 | 1.49 | -3.35 | < .001 | .01 [.004,.13] |
ATSI = Aboriginal and/or Torres Strait Islander. Age, Wellbeing, and Impulsiveness were measured on a continuous scale. All other variables were treated as categorical with the reference groups = No for Parents Living Together, Paid Job, Internet Gaming Disorder, Played esports, Watched esports, and Competed in esports. Other reference groups are Gender = Female and Indigenous = Non-Indigenous. Advertisements sample model fit: AIC = 854; R2 McF = .17. Qualtrics sample model fit: AIC = 520; R2 McF = .25.