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Sexual Assault at Indiana Colleges and Universities

Sexual Assault at Indiana Colleges and Universities. Edgardo R. Pimentel, M.S. INCSAPP/ICAN Workshop September 7, 2006. The Core Institute. Assess the nature, scope, and consequences of alcohol and other drug use on college campuses.

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Sexual Assault at Indiana Colleges and Universities

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  1. Sexual Assault at Indiana Colleges and Universities Edgardo R. Pimentel, M.S. INCSAPP/ICAN Workshop September 7, 2006

  2. The Core Institute • Assess the nature, scope, and consequences of alcohol and other drug use on college campuses. • To date, the CORE Survey has been administered to 1,675,391 students at about 1,567 American universities and colleges.

  3. Purpose • To find potential predictors of Sexual Assault and Rape • Examine the relationship of those predictors to Sexual Assault and Rape

  4. Background • Negative consequences are what we really try to reduce • Sexual assault is qualitatively different from other types of negative consequences • Requires separate analysis

  5. Outline • Items • Indiana – Sexual Assault • Analysis • Model • Results of Assault • Results of Rape • Exploration • Model • Results of Assault • Results of Rape • Relationships of the Predictors • Discussion

  6. Items • Questions 25e and 25f - Forced sexual touching or fondling - Unwanted sexual intercourse

  7. Indiana – Sexual Assault

  8. Indiana – Sexual Assault

  9. Analysis • Logistic Regression on two conditions - No Assault vs. Assault - Touching vs. Rape

  10. Analysis • Estimates the odds of being classified as a victim of Assault or of Rape • Provides an R square equivalent value

  11. Model • Classification • Age • Ethnic origin • Gender • Marital status • Working • Living arrangements • GPA • Heavy drinking • Average drinks per week

  12. Model • All variables had significant differences on the dependent variables of Assault and Rape except for question 7 “Working”

  13. Results of Assault • Overall model is significant (Wald = 3125.17, 1 df, p.<.05) • Predictions for Step 6 of 7 are not significantly different from observations (Chi-square = 14.45, 8 df, p. = .07)

  14. Results of Assault • Significant predictors were being single (OR = .21), married (OR = .06), divorced (OR = .06), GPA (OR = .8), Heavy Drinking (OR = 1.3) and Average Drinks per Week (OR = 1.0) • R Square = .10

  15. Results of Rape • Overall model is not significant (Wald = 1.57, 1 df, p. = .21 • Predictions for Step 2 of 2 are not significantly different from observations (Chi-square = 4.23, 8 df, p. = .84)

  16. Results of Rape • Significant predictor was Average Drinks per Week (OR = 1.0) • R Square = .08

  17. Exploration • Ran correlations on all items on the survey against Assault and Rape • Highest correlations belonged to AOD Use, Use at residence halls and Greek houses, other negative consequences • Lowest correlations belonged to never using AOD at any locations

  18. Model • Heavy drinking • Average drinks per week • Annual AOD rates • 30-day AOD rates • Locations of AOD use • Change in drug use • Alcohol last time they had sex • Bragged about AOD use

  19. Results of Assault • Overall model is significant (Wald = 1843.39, 1 df, p.<.05) • Predictions for Step 6 of 6 are not significantly different from observations (Chi-square = 3.14, 4 df, p. = .53)

  20. Results of Assault • Significant predictors were annual cocaine use (OR = 1.3), alcohol use at fraternities (OR = 2.1), amphetamine use at residence halls (OR = 2.6), never using “other” drugs at any location (OR = 0.6), alcohol prior to sex (OR = 1.8) and bragging about AOD use (OR = 1.2) • R Square = .10

  21. Results of Rape • Overall model is not significant (Wald = 3.60, 1 df, p. = .06 • Predictions for Step 3 of 3 are not significantly different from observations (Chi-square = 4.14, 4 df, p. = .39)

  22. Results of Rape • Significant predictors were 30 day use of sedatives (OR = 2.9) and bragging about AOD use (OR = 1.3) • R Square = .13

  23. Relationships of the Predictors • GLM on Assault and Rape for the predictors found through the Logistic Regressions • Tested for between-subjects differences and interactions for gender

  24. Relationships of the Predictors • All between subjects test were significant • All but two gender differences were significant (Marital Status, Alcohol use at Greek house)

  25. Relationships of the Predictors • Five gender interactions were significant - Average Drinks per Week - Cocaine Use Last Year - Amphetamine Use in Residence Halls - Sedative Use Past 30 Days

  26. Discussion • Warning signs exist and should be used to monitor or educate potential victims • Victims of assault can serve as the next best source of information for increasing our ability to predict

  27. Discussion • There are several interesting and telling relationships • We did not find a good way to predict Sexual Assault • Need to look at some other facets of their lives that may prove informative

  28. Discussion • Items such as Sedative use may be indicators of other issues in their lives or a result of being victimized • Bragging about AOD use may be related to the peer relationships maintained

  29. Discussion • These items can serve as launching points to look at the other facets of the individual’s environment

  30. Closing • We are a resources available to you. • Questions are free.

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