Schedule:
Friday, January 15, 2016
Ballroom Level-Grand Ballroom South Salon (Renaissance Washington, DC Downtown Hotel)
* noted as presenting author
Sarah McMahon, PhD,
Assistant Professor/Associate Director, Rutgers University, New Brunswick, NJ
N. Andrew Peterson, PhD, Associate Professor, Rutgers University, New Brunswick, NJ
Jane E. Palmer, PhD, Director, Community-Based Research Scholars program Professorial Lecturer, Department of Public Administration & Policy, American University, Washington, DC
Background: Bystander intervention has been increasingly applied to prevent sexual violence on college campuses. Social workers and others who are involved in the delivery and evaluation of campus sexual assault prevention efforts need to better understand how to design and measure the effects of their interventions on intended outcomes. Of particular interest is research that clarifies understanding of the direction of relationships between mediating variables – variables that describe the process through which interventions might achieve their effects. The underlying theory related to bystander intervention assumes unidirectional relationships between mediating variables, predicting that bystander behaviors (BB) (i.e., actions taken to intervene in sexual violence situations) will be influenced by bystander intentions (BI) (i.e., likelihood to intervene in the future), which in turn will be affected by bystander efficacy (BE) (i.e., confidence to intervene). One critical question for theory is whether a reciprocal relationship exists between BI and BE. No study to date has empirically addressed this question.
Methods: We used structural equation modeling (SEM) with longitudinal data to test unidirectional and reciprocal causal relations between BI and BE. Participants (n = 1,390) were students at a northeastern U.S. university. Students completed an online survey over a period of that included a number of validated scales. A total of four data points were used that spanned a one year period. Four models were examined using SEM: (1) a baseline model with autoregressive paths; (2) a model with autoregressive effects and BI predicting future BE; (3) a model with autoregressive effects and BE predicting future BI; and, (4) a fully cross-lagged model.
Results: Results indicated that reciprocal causality was found to occur between BI and BE. In addition, a final model demonstrated indirect effects of a bystander intervention program on bystander behaviors through both BI and BE at different time points.
Implications: The findings suggest that bystander intervention education programs would likely benefit from minimally addressing both bystander efficacy and behavioral intent, based on the premise that these work together in encouraging positive bystander behavior. The findings also indicate that as compared to receiving one session of bystander education training, additional sessions yield better outcomes.