No abstract

Public awareness of sexual assault and initiatives aimed at preventing sexual assault continue to increase over the years. However, whether rates of sexual assault have diminished because of such cultural shifts remains unclear. The purpose of this study was to assess if rates of sexual assault (i.e., forced sex) have changed over the past 18 years for adolescent girls and boys as well as potential differences across racial/ethnic identities. Using nationally representative data from the Youth Risk Behavioral Surveillance Survey from 2001 to 2019, we conducted logistic regressions to assess rates of experiences of forced sex by sex and by sex and racial/ethnic identity, while accounting for grade level. Participants included 135,837 high school students. From 2001 to 2019, rates of forced sex maintained for girls; however, there was a decrease over time for boys. For girls, there were inconsistent differences in rates of forced sex by racial/ethnic identities. However, boys who identified as Black, Hispanic, Multi-Racial, and Other Race/Ethnicity were at higher risk to report forced sex than their White peers, until 2015; only Other Race/Ethnicity was at higher risk in 2019. As girls and boys aged, the risk of forced sex increased. Despite prevention efforts, rates of forced sex did not decrease from 2001 to 2019 for adolescent girls disregarding race/ethnicity, and for racial/ethnic minority boys. That rates of forced sex continue to be high is problematic as experiencing sexual assault at an earlier age is associated with myriad consequences. Further, results suggest current prevention initiatives may be inadequate at addressing risk factors for forced sex, and more broadly, sexual assault. Moving forward, researchers and educators may want to re-evaluate the strategies used to address and measure sexual assault experiences.

The R package DIFSIB provides a direct translated version of the SIBTEST, Crossing- SIBTEST, and POLYSIBTEST procedures that were last updated and released in 2005. Having these functions directly written from Fortran into R code will allow researchers and practitioners to easily access the most recent versions of these procedures when they are conducting differential item functioning analysis and continue to improve the software more easily.

A study was conducted to implement the use of a standardized effect size and corresponding classification guidelines for polytomous data with the POLYSIBTEST procedure and compare those guidelines with prior recommendations. Two simulation studies were included. The first identifies new unstandardized test heuristics for classifying moderate and large differential item functioning (DIF) for polytomous response data with three to seven response options. These are provided for researchers studying polytomous data using POLYSIBTEST software that has been published previously. The second simulation study provides one pair of standardized effect size heuristics that can be employed with items having any number of response options and compares true-positive and false-positive rates for the standardized effect size proposed by Weese with one proposed by Zwick et al. and two unstandardized classification procedures (Gierl; Golia). All four procedures retained false-positive rates generally below the level of significance at both moderate and large DIF levels. However, Weese’s standardized effect size was not affected by sample size and provided slightly higher true-positive rates than the Zwick et al. and Golia’s recommendations, while flagging substantially fewer items that might be characterized as having negligible DIF when compared with Gierl’s suggested criterion. The proposed effect size allows for easier use and interpretation by practitioners as it can be applied to items with any number of response options and is interpreted as a difference in standard deviation units.

A simulation study was conducted to investigate the heuristics of the SIBTEST procedure and how it compares with ETS classification guidelines used with the Mantel–Haenszel procedure. Prior heuristics have been used for nearly 25 years, but they are based on a simulation study that was restricted due to computer limitations and that modeled item parameters from estimates of ACT and ASVAB tests from 1987 and 1984, respectively. Further, suggested heuristics for data fitting a two-parameter logistic model (2PL) have essentially went unused since their original presentation. This simulation study incorporates a wide range of data conditions to recommend heuristics for both 2PL and three-parameter logistic (3PL) data that correspond with ETS’s Mantel–Haenszel heuristics. Levels of agreement between the new SIBTEST heuristics and Mantel–Haenszel heuristics were similar for 2PL data and higher than prior SIBTEST heuristics for 3PL data. The new recommendations provide higher true-positive rates for 2PL data. Conversely, they displayed decreased true-positive rates for 3PL data. False-positive rates, overall, remained below the level of significance for the new heuristics. Unequal group sizes resulted in slightly larger false-positive rates than balanced designs for both prior and new SIBTEST heuristics, with rates less than alpha levels for equal ability distributions and unbalanced designs versus false-positive rates slightly higher than alpha with unequal ability distributions and unbalanced designs.