Skip to main content
SpringerLink
Log in

Predicting Bystander Behavior to Prevent Sexual Assault on College Campuses: The Role of Self-Efficacy and Intent

  • Original Article
  • Published:
American Journal of Community Psychology

Abstract

Bystander intervention has been increasingly applied to prevent sexual violence on college campuses. Its underlying theory assumes unidirectional relationships between variables, predicting that bystander behaviors (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 question for theory is whether a reciprocal relationship exists between BI and BE. We used structural equation modeling (SEM) with longitudinal data to test unidirectional and reciprocal causal relations between BI and BE. Participants (n = 1390) were students at a northeastern US university. 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 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 for theory and practice are described, and directions for future research discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Ahrens, C., Rich, M., & Ullman, J. (2011). Rehearsing for real life: The impact of the InterACT sexual assault prevention program on self-reported likelihood of engaging in bystander interventions. Violence Against Women, 17(6), 760–776.

    Article  PubMed  Google Scholar 

  • Ajzen, I. (1988). Attitudes, personality, and behavior. Chicago: Dorsey Press.

    Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

    Article  Google Scholar 

  • Arbuckle, J. L. (2007). Amos (Version 7.0) [Computer Program]. Chicago: SPSS.

  • Armijo-Olivo, S., Warren, S., & Magee, D. (2009). Intention to treat analysis, compliance, drop-outs and how to deal with missing data in clinical research: A review. Physical Therapy Reviews, 14(1), 36–49.

    Article  Google Scholar 

  • Banyard, V. (2008). Measurement and correlates of prosocial bystander behavior: The case of interpersonal violence. Violence and Victims, 23(1), 83–97.

    Article  PubMed  Google Scholar 

  • Banyard, V. L. (2011). Who will help prevent sexual violence: Creating an ecological model of bystander intervention. Psychology of Violence, 1(3), 216–229.

    Article  Google Scholar 

  • Banyard, V. L. (2014). Improving college campus–based prevention of violence against women a strategic plan for research built on multipronged practices and policies. Trauma, Violence, & Abuse, 15(4), 339–351.

    Article  Google Scholar 

  • Banyard, V., & Moynihan, M. (2011). Variation in bystander behavior related to sexual and intimate partner violence prevention: Correlates in a sample of college students. Psychology of Violence, 1(4), 287–301.

    Article  Google Scholar 

  • Banyard, V. L., Moynihan, M. M., & Plante, E. G. (2007). Sexual violence prevention through bystander education: An experimental evaluation. Journal of Community Psychology, 35(4), 463–481.

    Article  Google Scholar 

  • Banyard, V. L., Plante, E., & Moynihan, M. M. (2004). Bystander education: Bringing a broader community perspective to sexual violence prevention. Journal of Community Psychology, 32(1), 61–79.

    Article  Google Scholar 

  • Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21, 230–258. doi:10.1177/0049124192021002005.

    Article  Google Scholar 

  • Black, B., Weisz, A., Coats, S., & Patterson, D. (2000). Evaluating a psychoeducational sexual assault prevention program incorporating theatrical presentation, peer education, and social work. Research on Social Work Practice, 10(5), 589–606.

    Google Scholar 

  • Burn, S. (2009). A situational model of sexual assault prevention through bystander intervention. Sex Roles, 60(11–12), 779–792.

    Article  Google Scholar 

  • Cappadocia, M. C. (2012). Individual motivations and characteristics associated with bystander intervention during bullying episodes among children and youth. Canadian Journal of School Psychology, 27(3), 201–216.

    Article  Google Scholar 

  • Casey, E., & Lindhorst, T. (2009). Toward a multi-level, ecological approach to the primary prevention of sexual assault: Prevention in peer and community contexts. Trauma Violence & Abuse, 10(2), 91–114.

    Article  Google Scholar 

  • Coker, A., Cook-Craig, P. G., Williams, C. M., Fisher, B. S., Clear, E. R., Garcia, L. S., et al. (2011). Evaluation or green dot: An active bystander intervention to reduce sexual violence on college campuses. Violence Against Women, 17, 777–796.

    Article  PubMed  Google Scholar 

  • Christensen, M. C. (2013). Using theater of the oppressed to prevent sexual violence on college campuses. Trauma, Violence, & Abuse, 14(4), 282–294.

    Article  Google Scholar 

  • Darley, J. M., & Latane, B. (1968). Group inhibition of bystander intervention. Journal of Personality and Social Psychology, 10, 215–221.

    Article  PubMed  Google Scholar 

  • Department of Education. (2014). Violence Against Women Act; Final Rule. Federal Register, 79(202), 62752–62790.

  • Exner, D., & Cummings, N. (2011). Implications for sexual assault prevention: College students as prosocial bystanders. Journal of American College Health, 59(7), 655–657.

    Article  PubMed  Google Scholar 

  • Fabiano, P. M., Perkins, H. W., Berkowitz, A., Linkenbach, J., & Stark, C. (2003). Engaging men as social justice allies in ending violence against women: Evidence for a social norms approach. Journal of American College Health, 52(3), 105–112.

    Article  PubMed  Google Scholar 

  • Fischer, P., Krueger, J. I., Greitemeyer, T., Vogrincic, C., Kastenmüller, A., Frey, D., et al. (2011). The bystander-effect: A meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. Psychological Bulletin, 137(4), 517.

    Article  PubMed  Google Scholar 

  • Gini, G., Albiero, P., Benelli, B., & Altoe, G. (2008). Determinants of adolescents’ active defending and passive bystanding behaviour in bullying. Journal of Adolescence, 31(1), 93–105.

    Article  PubMed  Google Scholar 

  • Hollis, S., & Campbell, F. (1999). What is meant by intention to treat analysis? Survey of published randomised controlled trials. BMJ, 319(7211), 670–674.

    Article  PubMed Central  PubMed  Google Scholar 

  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. doi:10.1080/10705519909540118.

    Article  Google Scholar 

  • Huston, T. L., Ruggiero, M., Conner, R., & Geis, G. (1981). Bystander intervention into crime: A study based on naturally-occurring episodes. Social Psychology Quarterly, 44(1), 14–23.

  • Katz, J., & Moore, J. (2013). Bystander education training for campus sexual assault prevention: An initial meta-analysis. Violence and Victims, 28(6), 1054–1067.

    Article  PubMed  Google Scholar 

  • Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: Guilford Press.

    Google Scholar 

  • Latane, B., & Darley, J. M. (1970). The unresponsive bystander: Why doesn’t he help? Englewood Cliffs, NJ: Prentice-Hall, Inc.

    Google Scholar 

  • Latane, B., & Nida, S. (1981). Ten years of research on group size and helping. Psychological Bulletin, 89(2), 308–324.

    Article  Google Scholar 

  • Lonsway, K. A. (1996). Preventing acquaintance rape through education: What do we know. Psychology of Women Quarterly, 20(2), 229–265.

    Article  Google Scholar 

  • McMahon, S., Allen, C. T., Postmus, J. L., McMahon, S. M., Peterson, N. A., & Lowe Hoffman, M. (2014). Measuring bystander attitudes and behavior to prevent sexual violence. Journal of American College Health, 62(1), 58–66.

    Google Scholar 

  • McMahon, S., Banyard, V. L., Palmer, J. E., Murphy, M., & Gidcyz, C. A. (in press). Measuring bystander behavior in the context of sexual violence prevention: Lessons learned and new directions. Journal of Interpersonal Violence. doi:10.1177/0886260515591979.

  • McMahon, S., Winter, S., Palmer, J., Postmus, J. L., Peterson, N. A., Zucker, S., et al. (in press). A randomized control trial of a peer education theater bystander program to prevent sexual violence. Health Education Research. doi:10.1093/her/cyv022.

  • Moynihan, M., Banyard, V. J., Arnold, J. S., Eckstein, R. P., & Stapleton, J. G. (2011). Sisterhood may be powerful for reducing sexual and intimate partner violence: An evaluation of the bringing in the bystander in-person program with sorority members. Violence Against Women, 17(6), 703–719.

    Article  PubMed  Google Scholar 

  • Murphy, M. (2014). Sexual assault-specific bystander behavior: Accounting for opportunity in a prospective analysis of the effects of individual, social norms, and situational variables (Doctoral dissertation). Retrieved from OhioLink Dissertation and Theses Center. (Document No. ohiou1389008840).

  • Murphy, M. J., Dardis, C. M., Wilson, M. S., Gidycz, C. A., & Berkowitz, A. D. (in press). Predictors of sexual assault-specific prosocial bystander behavior and intentions: A prospective analysis. Violence Against Women.

  • Newman, D. A. (2003). Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques. Organizational Research Methods, 6(3), 328–362.

    Article  Google Scholar 

  • Schnell, R., Bachteler, T., & Reiher, J. (2010). Improving the use of self-generated identification codes. Evaluation Review, 34, 391–418.

    Article  PubMed  Google Scholar 

  • The White House. (2014). The first report of the White House task force to protect students from sexual assault. Retrieved May 9, 2014 from http://www.whitehouse.gov/sites/default/files/docs/report_0.pdf.

  • Thornberg, R., Tenenbaum, L., Varjas, K., Meyers, J., Jungert, T., & Vanegas, G. (2012). Bystander motivation in bullying incidents: To intervene or not to intervene? Western Journal of Emergency Medicine, 13(3), 247–252.

Download references

Acknowledgments

Preparation of this manuscript was supported by a Grant from the Centers for Disease Control and Prevention (Grant Number: 1R01CE001855-01, PI: McMahon, CO-PI: Postmus). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the CDC.

Author information

Authors and Affiliations

  1. Center on Violence Against Women and Children, School of Social Work, Rutgers University, New Brunswick, NJ, USA

    Sarah McMahon, N. Andrew Peterson, Samantha C. Winter & Judy L. Postmus

  2. Department of Public Administration and Policy, American University, Washington, DC, USA

    Jane E. Palmer

  3. Office for Violence Prevention and Victim Assistance, Rutgers University, New Brunswick, NJ, USA

    Ruth Anne Koenick

Authors
  1. Sarah McMahon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Andrew Peterson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Samantha C. Winter
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jane E. Palmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Judy L. Postmus
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ruth Anne Koenick
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sarah McMahon.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

McMahon, S., Peterson, N.A., Winter, S.C. et al. Predicting Bystander Behavior to Prevent Sexual Assault on College Campuses: The Role of Self-Efficacy and Intent. Am J Community Psychol 56, 46–56 (2015). https://doi.org/10.1007/s10464-015-9740-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10464-015-9740-0

Keywords

Search

Navigation