33 risk factors independently associated with both

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3.3. Risk Factors Independently Associated with Both Gambling and Substance Use
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14     Involvement in Greek organizations had significant direct effects on both gambling and two of the five substance use variables tested, and these effects were not appreciably different between the two models (see Table 3). In the model in which gambling was the intermediary variable, the direct effect of Greek involvement on gambling was positive (b=.35, SE=.13). A very similar result was obtained in the model where gambling was the outcome (b=.28, SE=.13), even accounting for the modest indirect effect of Greek involvement via substance use (b=.094, SE=.026). Similarly, Greek involvement’s direct effect on alcohol use frequency was significant when alcohol was the intermediary variable (b=12.39, SE=4.00) or the outcome (b=9.92, SE=3.96), and its indirect effect on alcohol use via gambling was much more modest by comparison (b=2.13, SE=.86). By contrast, across the two models, the effects of Greek involvement on AUD, marijuana use frequency, and number of other drugs used were completely accounted for by gambling. Interestingly, Greek involvement functioned as a protective factor for tobacco use frequency, again via mechanisms that appeared to be distinct from its contribution to gambling, as evidenced by its direct association with less frequent tobacco use in both models (b=-15.58, SE=6.00, and b=-18.52, SE=5.97, respectively). Athletics involvement had independent contributions to gambling, alcohol use frequency, and AUD risk, as evidenced by significant direct paths that were not attenuated by the inclusion of indirect paths. For example, athletics involvement had significant direct effects on gambling in both models (b=.50, SE=.14 and b=.47, SE=.14, respectively), but its indirect effect on gambling via substance use was much smaller (b=.062, SE=.025). Similarly, its direct effect on AUD risk (b=.23, SE=.08 in both models) was unchanged regardless of the modest indirect effect via gambling (b=.040, SE=.014), and the pattern was similar for alcohol use frequency. By
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15     contrast, the effects of athletics involvement on tobacco and marijuana use frequency, and number of other drugs used were entirely accounted for by gambling. 3.4. Risk Factors Accounting for “Shared” Variance in Gambling and Substance Use Four of the hypothesized risk factors we tested (i.e., sex, race/ethnicity, sensation- seeking, behavioral dysregulation) exhibited direct associations with both gambling and substance use that were accounted for, partially or completely, by each other, respectively. For example, male sex was directly associated with gambling in both models (b=1.65, SE=.13, and b=1.58, SE=.13, respectively), and had an additional indirect effect on gambling via alcohol use frequency and number of other drugs used (b=.10, SE=.03). Although male sex was also directly and independently associated with each of the substance use variables, these effects were all partially (for marijuana use frequency) or completely (for AUD risk, alcohol use frequency, number of other drugs used) attenuated in the model that included the indirect effect of sex via gambling. The sole exception to this pattern was tobacco use frequency, for which sex had an
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  • Fall '17
  • Amelia M. Arria

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