1 / 41

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.

pepin
Download Presentation

Sexual Assault at Indiana Colleges and Universities

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. 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.

More Related