1 / 11

Using General Growth Mixture Modeling to Study the First Year of College Student Drinking

Using General Growth Mixture Modeling to Study the First Year of College Student Drinking. Greenbaum, P. E., Del Boca, F. K., Darkes, J., and Goldman, M. S. Alcohol and Substance Use Research Institute.

laurieh
Download Presentation

Using General Growth Mixture Modeling to Study the First Year of College Student Drinking

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Using General Growth Mixture Modeling to Study the First Year of College Student Drinking Greenbaum, P. E., Del Boca, F. K., Darkes, J., and Goldman, M. S. Alcohol and Substance Use Research Institute Funded by NIAAA R37AA08333-10, “Alcohol Expectancies: Mediators of Biopsychological Risk,” (PI: Mark S. Goldman).

  2. Background • Prior research has documented heavy drinking on college campuses (e.g., 29% were drunk 3 or more times in past month; 44% were binge drinkers, Wechsler et al., 2000). • During this period, many individuals experience their personal peak consumption and individual drinking trajectories begin to diverge; some individuals continue to increase their drinking, while others asymptote or decline (Muthén & Muthén, 2000; Schulenberg et al., 1996). • Little attention has been given to drinking changes that occur during the academic year or to factors that are associated with these temporal changes.

  3. Method • Sample : • ·  308 freshmen recruited in three successive years. • ·    Randomly selected. • ·    Abstinent participants were omitted, N = 229. • ·    Sample characteristics. • Males-- 47% • Age range 17-20 years (M = 18.4, SD = 0.47) • Caucasian, 71%; African American, 12%; Hispanic, 8%; Other, 8%

  4. Method • Procedure : • ·Alcohol consumption was measured at eight times during the academic year using the Timeline Follow-Back interview (Sobell & Sobell, 1992). • ·Daily drinking measures were aggregated to provide weekly estimates (t = 32). • ·Risk factor variables in the current analyses, obtained at the beginning of the study, included:   • Gender • Sensation-seeking • Alcohol expectancies • Living arrangement (off-campus/home, dorm) • Ethnicity/race

  5. Figure 1. Alcohol Consumption During the First Year of College

  6. Figure 2. Alcohol Consumption During the First Year of College Mean Log Drinks

  7. Table 1 Selecting the Baseline Latent Growth Curve Model: Likelihood Ratio Tests Note.a Fixed effect for the slope growth factor not significant at p < .05. bHoliday loadings were freely estimated. cCorrelated errors for weeks 1 to 4. * p < .001

  8. Table 2 Selecting the Baseline Latent Growth Curve Model: Fit Indices Note.a Fixed effect for the slope growth factor not significant at p < .05. bHoliday loadings were fixed to 1.00. cHoliday loadings were freely estimated.

  9. Figure 3. Latent Growth Curve Model Mean Log Drinks (100%)

  10. Figure 4. 5 Class Solution Log Mean Drinks/Week (8%) (10%) (20%) (54%) (7%)

  11. Table 3 Predictors of Latent Class Membership Note: Within a column, significant mean differences (p < .05) between classes are noted by different superscripted letters.

More Related