Abstract
In this study, we randomly assigned 123 sixth and seventh grade classrooms from seven middle schools in the greater Cleveland area to one of two five-session curricula addressing gender violence/sexual harassment (GV/SH) or to a no-treatment control group. A baseline survey and two follow-up surveys were administered immediately after the treatment (Wave 2) and about six months post-treatment (Wave 3). In an earlier paper, we demonstrated the effectiveness of two approaches to youth GV/SH prevention programming (a fact-based, law and justice curriculum and an interaction-based curriculum). In this paper, we explored whether these largely positive findings remain for both girls and boys, including whether girls experience higher levels of GV/SH than boys. Most of our statistical models proved to be non-statistically significant. However, in 2 of our 48 victimization/perpetration (any violence, sexual violence and non-sexual violence) models (across two post-intervention follow-up points), we observed that the interventions reduced peer (male or female, non-dating partner) sexual violence victimization and reduced peer perpetration, but another outcome model indicated that the interventions increased dating perpetration. These mixed findings will need to be explored further in future research. Regarding our primary research question, we observed no statistically significant differences for the treatment multiplied by gender interaction terms for any of the perpetration or victimization outcome models, suggesting that the treatment had similar effects on girls and boys. However, we did observe that boys are more involved in violence than girls: both as victims and perpetrators. Boys experienced significantly more of three types of victimization from peers and dating partners compared to what girls experienced at the hands of their peers and dating partners. As perpetrators, boys committed more sexual victimization against peers (immediately post-intervention only) and more sexual victimization against dating partners than girls. The implications of these results are discussed.
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Notes
We defined “dating” in the following manner: “girls or boys you are going with, dating, going steady with, or have gone out with, dated, or gone steady with for at least one week. This group includes anyone who is or was your boyfriend/girlfriend for at least one week.”
While there are other potential demographic variables to examine (e.g., ethnicity), we focus on the topic of gender differences. Gender and the greater physical strength of males over females is a key aspect of dating violence (Stein 1995) and can be used by boys to control young girls. We believe the topic of gender is too complex to present with other demographic variables and would interfere with our goal of a parsimonious presentation. Given our use of a RCT design, we found that we have a balance across our treatment/control groups on the issue of ethnicity and other demographic variables. Given this balance, we are able to assess the independent effects of gender without simultaneously examining other demographic variables.
The Jaycox et al. (2006) study is very different than our study in that it involved high school students, included three intervention sessions and was taught by lawyers.
A detailed description of the interventions and the roles of our project team members and project partners are provided in the project final report (see Taylor et al. 2008).
Due to resource constraints, our main interest was in detecting small to medium effect sizes, for anything below that level (given the time and resources to implement the program) might possibly be considered less meaningful for policy making purposes.
Logistically, it would not have been possible to take students out of their regular schedule and randomly assign them on an individual basis to new classes. Also, the funding necessary to assign a large number of schools (e.g., over 50 schools) randomly to our study conditions was not available.
Although not strictly necessary, pre-stratification helps ensure that groups start out with some identical characteristics and assure that we have adequate numbers of classrooms in each of the cells for each participating school (see Boruch 1997).
School scheduling precluded us from doing all of the surveys at the six-month follow-up point in time.
This was defined for students as, “People about the same age as you. They may be your classmates, kids in your school, neighborhood/community, and are both girls and boys the same age as you. You might or might not know them or think of them as your friends.”
This was defined for students as, “People who you are ‘going with’, ‘dating,’ ‘going steady with’ or have ‘gone out with,’ ‘dated,’ or ‘gone steady with’ for at least a week. This group also includes anyone who is or was your boyfriend/girlfriend for at least a week.”
As discussed earlier, not all the respondents completed all of the questions on the survey. For example, 47 students did not answer the gender question on the survey.
Prevalence of “any” violence was the sum of all student responses for one domain, with a possible score of 7 for survey items a through g. Prevalence of sexual violence was the sum of all student responses for sexual violence, with a possible score of 2 for items d and f. Prevalence of non-sexual (physical) violence was the sum of all student responses for one domain, with a possible score of 5 for items a, b, c, e, and g. Each outcome measure represents a sum of the different types of violence individuals face/perpetrate.
If a student scored “0”, they had 0 victimizations; 1 = 1-– victimizations; 2 = 4-– victimizations; 3 = 10+ victimizations. Each frequency measure represents a sum of the number of times students face violence on those measures.
Site 1 = Ford MS (Berea), Site 2 = Roehm MS (Berea), Site 3 = Monticello MS (CHUH), Site 4 = this planned site did not participate in the experiment and was dropped from the analysis, Site 5 = Wiley MS (CHUH), Site 6 = Shaker Heights MS (Shaker Heights), and Site 7 = Woodbury School (Shaker Heights) which served as the reference category.
That is, for each school, the intercept of the level 1 model is adjusted for the linear regression of the test scores on that variable. In a sense, that puts all school means on an equal footing with respect to that variable. In the HLM setting, the adjusted intercepts can be described as “adjusted school means.” The variation among adjusted means will usually be less than the variation among the unadjusted means (see Raudenbush and Bryk, chapter 5 [2002]).
Coded as female = 1 and male = 0.
Coded as treatment = 1 and control condition = 0.
Conversely, our findings also demonstrate our interventions to be equally as ineffective on all of our other non-significant victimization outcome measures.
As stated in the measures section, our definition of sexual violence includes a range of very serious forms of sexual assault plus behaviors such as “butt grabbing.”
Students were asked the following two questions regarding sexual violence: “Have any of your PEERS ever done any of the following things to you? Pushed, grabbed, shoved, or kicked you in your private parts? Made you touch their private parts or touched yours when you did not want them to?
More specifically, boys experienced more sexual victimization, “any” victimization (Wave 3 only) and non-sexual victimization (Wave 3 only) from peers, and more “any” victimization, non-sexual victimization, and sexual victimization (Wave 3 only) from dating partners than girls.
Based on data from the National Crime Victimization Survey (NCVS) from 1973 to 2006, males have experienced higher rates of victimization for violence than females for all types of violent crime except rape/sexual assault (see http://www.ojp.usdoj.gov/bjs/glance/vsx2.htm). Also, males perpetrate much more crime than females regardless of whether the data analyzed are arrest rates, victimization reports on characteristics of offenders, or self-reports of criminal behavior (Heimer 2000).
However, this will be a real challenge. Based on our experience working in schools, districts are very concerned about including sexual assault measures on surveys due to the potential negative feedback they may receive from parents. Researchers may need to work with parent groups to explain the rationale for these measures and carefully work through the wording of these items on surveys to get approval for more detailed items.
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This project was supported by Grant No. 2005–WT–BX–0002 awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. Points of view in this document are those of the author and do not necessarily represent the official position or policies of the U.S. Department of Justice or any other organization. The authors wish to acknowledge the substantial contributions of Dr. Amy R. Mack, ICF International, and Mr. Thomas Horwood, ICF International, for their roles in the research project.
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Taylor, B.G., Stein, N. & Burden, F.F. Exploring gender differences in dating violence/harassment prevention programming in middle schools: results from a randomized experiment. J Exp Criminol 6, 419–445 (2010). https://doi.org/10.1007/s11292-010-9103-7
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DOI: https://doi.org/10.1007/s11292-010-9103-7