Skip to main content
SpringerLink
Log in

Examining School-Based Bullying Interventions Using Multilevel Discrete Time Hazard Modeling

  • Published:
Prevention Science Aims and scope Submit manuscript

Abstract

Although schools have been trying to address bulling by utilizing different approaches that stop or reduce the incidence of bullying, little remains known about what specific intervention strategies are most successful in reducing bullying in the school setting. Using the social-ecological framework, this paper examines school-based disciplinary interventions often used to deliver consequences to deter the reoccurrence of bullying and aggressive behaviors among school-aged children. Data for this study are drawn from the School-Wide Information System (SWIS) with the final analytic sample consisting of 1,221 students in grades K – 12 who received an office disciplinary referral for bullying during the first semester. Using Kaplan-Meier Failure Functions and Multi-level discrete time hazard models, determinants of the probability of a student receiving a second referral over time were examined. Of the seven interventions tested, only Parent-Teacher Conference (AOR = 0.65, p < .01) and Loss of Privileges (AOR = 0.71, p < .10) were significant in reducing the rate of the reoccurrence of bullying and aggressive behaviors. By using a social-ecological framework, schools can develop strategies that deter the reoccurrence of bullying by identifying key factors that enhance a sense of connection between the students’ mesosystems as well as utilizing disciplinary strategies that take into consideration student’s microsystem roles.

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

Similar content being viewed by others

References

  • Barber, J. S., Murphy, S. A., Axinn, W. G., & Maples, J. (2000). Discrete-time multilevel hazard analysis. Sociological Methodology, 30, 201–235.

    Article  Google Scholar 

  • Bauman, S., Rigby, K., & Hoppa, K. (2008). US teachers and school counselors’ strategies for handling school bullying incidents. Educational Psychology, 28, 837–856.

    Article  Google Scholar 

  • Biggs, B. K., Vernberg, E. M., Twemlow, S. W., Fonagy, P., & Dille, E. J. (2008). Adherence and its relation to teacher attitudes and student outcomes in an elementary school-based violence prevention program. School Psychology Review, 37, 533–549.

    Google Scholar 

  • Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Burns, S., Maycock, B., Cross, D., & Brown, G. (2008). The power of peers: Why some students bully others to conform. Qualitative Health Research, 18, 1704–1716.

    Article  PubMed  Google Scholar 

  • Chase, B. (March 25, 2001). Bullyproofing our schools. Retrieved July 15th, 2010, from http://www.nea.org/columns/bc010325.html

  • Coatsworth, J. D., Pantin, H., McBride, C., Briones, E., Kurtines, W., & Szapocznik, J. (2002). Ecodevelopmental correlates of behavior problems in young Hispanic females. Applied Developmental Science, 6, 126–143.

    Article  Google Scholar 

  • Coloroso, B. (2003). The bully, the bullied, and the bystander. New York: Harper-Resource.

    Google Scholar 

  • Cowie, H., & Hutson, N. (2005). Peer support: a strategy to help bystanders challenge school bullying. Pastoral Care in Education, 23, 40–44.

    Article  Google Scholar 

  • Cowie, H., & Jennifer, D. (2008). New perspectives on bullying. New York: McGraw-Hill.

    Google Scholar 

  • Craig, W. M., Pepler, D., & Atlas, R. (2000). Observations of bullying in the playground and in the classroom. School Psychology International, 21, 22–36.

    Article  Google Scholar 

  • Epstein, J. L. (1995). School/family/community partnerships: Caring for the children we share. Phi Delta Kappan, 76, 701–712.

    Google Scholar 

  • Espelage, D. L., & Swearer, S. M. (2003). Research on school bullying and victimization: What have we learned and where do we go from here? School Psychology Review, 32, 365–383.

    Google Scholar 

  • Farmer, T. W. (2000). The social dynamic of aggressive and disruptive behavior in school: Implications for behavior consultation. Journal of Educational and Psychological Consultation, 11, 299–321.

    Google Scholar 

  • Farrington, D. P., & Ttofi, M. M. (2009). How to reduce school bullying. Victims and Offenders, 4, 321–326.

    Article  Google Scholar 

  • Fekkes, M., Pijpers, F. I. M., & Vereloove-Vanhorick, S. P. (2005). Bullying: Who does what, when and where? Involvement of children, teachers and parents in bullying behavior. Health Education Research, 20, 81–91.

    Article  PubMed  CAS  Google Scholar 

  • Grolnick, W. S., & Ryan, R. M. (1989). Parent styles associated with children’s regulation and competence in schools. Journal of Educational Psychology, 81, 143–154.

    Article  Google Scholar 

  • Gupta, N., & da Costa Leite, I. (1999). Adolescent fertility behavior: Trends and determinants in Northeastern Brazil. International Family Planning Perspectives, 25, 125–130.

    Article  Google Scholar 

  • Hanish, L. D., & Guerra, N. G. (2000). Children who get victimized at school: What is known? What can be done? Professional School Counseling, 4, 113–146.

    Google Scholar 

  • Hong, J. S. (2009). Feasibility of the Olweus Bullying Prevention Program in low-income schools. Journal of School Violence, 8, 81–97.

    Article  Google Scholar 

  • Howe, E., Haymes, E., & Tenor, T. (2006). Bullying: Best practices for prevention and intervention in schools. In C. Franklin, M. B. Harris, & P. Allen-Meares (Eds.), The school services sourcebook: A guide for school-based professionals (pp. 461–467). Cambridge, MA: Oxford University Press.

    Google Scholar 

  • Jeffrey, L. R., Miller, D., & Linn, M. (2001). Middle school bullying as a context for the development of passive observers to the victimization of others. In R. A. Geffner, M. Loring, & C. Young (Eds.), Bullying behavior: Current issues, research, and interventions (pp. 143–156). New York: Haworth Press.

    Google Scholar 

  • Jensen, J. M., & Dieterich, W. A. (2007). Effects of a skills-based prevention program on bullying and bully victimization among elementary school children. Prevention Science, 8, 285–296.

    Article  Google Scholar 

  • Juvonen, J., Graham, S., & Schuster, M. A. (2003). Bullying among young adolescents: The strong, the weak, and the troubled. Pediatrics, 112, 1231–1237.

    Article  PubMed  Google Scholar 

  • Kaltiala-Heino, R., Rimpela, M., Marttunen, M., Rimpela, A., & Rantanen, P. (1999). Bullying, depression, and suicidal ideation in Finnish adolescents: School survey. British Medical Journal, 319, 348–351.

    Article  PubMed  CAS  Google Scholar 

  • Kaltiala-Heino, R., Rimpela, M., Rantanen, P., & Rimpela, A. (2000). Bullying at school: An indicator of adolescents at risk for mental disorders. Journal of Adolescence, 23, 661–674.

    Article  PubMed  CAS  Google Scholar 

  • Kevorkian, M., & D’Antona, R. D. (2008). 101 facts about bullying: What everyone should know. Lanham, MD: Rowman & Littlefield Education.

    Google Scholar 

  • Killip, S., Mahfoud, Z., & Pearce, K. (2004). What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. The Annals of Family Medicine, 2, 204–208.

    Article  Google Scholar 

  • Lee, C. (2010). An ecological systems approach to bullying behaviors among middle school students in the United States. Journal of Interpersonal Violence, 26, 1664–1693.

    Article  PubMed  Google Scholar 

  • Leff, S. S. (2007). Bullying and peer victimization at school: Considerations and future directions. School Psychology Review, 36, 406–412.

    Google Scholar 

  • Li, Q. (2006). Cyberbullying in schools: A research of gender differences. School Psychology International, 27, 157–170.

    Article  CAS  Google Scholar 

  • Luk, J. W., Wang, J., & Simons-Morton, B. G. (2010). Bullying victimization and substance use among U.S. adolescents: Mediation by depression. Prevention Science, 11, 355–359.

    Article  PubMed  Google Scholar 

  • May, S., Ard, W., Todd, A., Horner, R. H., Glasgow, A., Sugai, G., et al. (2003). School-wide information system. Eugene: Educational and Community Supports, University of Oregon.

    Google Scholar 

  • Mishna, F., Pepler, D., & Wiener, J. (2006). Factors associated with perceptions and responses to bullying situations by children, parents, teachers, and principals. Victims and Offenders, 1, 255–288.

    Article  Google Scholar 

  • Monks, C. P., Smith, P. K., Naylor, P., Barter, C., Ireland, J. L., & Coyne, I. (2009). Bullying in different contexts: Commonalities, differences and the role of theory. Aggression and Violent Behavior, 14, 146–156.

    Article  Google Scholar 

  • Nansel, T. R., Overpeck, M., Pilla, R. S., Ruan, W. J., Simons-Morton, B. G., & Scheidt, P. (2001). Bullying behaviors among U. S. youth: Prevalence and association with psychosocial adjustment. Journal of the American Medical Association, 285, 2094–2100.

    Article  PubMed  CAS  Google Scholar 

  • Nansel, T. R., Overpeck, M. D., Haynie, D. L., Ruan, W. J., & Scheidt, P. C. (2003). Relationship between bullying and violence among US youth. Archives of Pediatric and Adolescent Medicine, 157, 348–353.

    Article  Google Scholar 

  • Nansel, T. R., Craig, W., Overpeck, M. D., Saluja, G., Ruan, W. J., & the Health Behaviour in School-aged Children Bullying Analyses Working Group. (2004). Cross-national consistency in the relationship between bullying behaviors and psychosocial adjustment. Archives of Pediatric and Adolescent Medicine, 158, 730–736.

    Article  Google Scholar 

  • NCES. (2010). U.S. Department of Education, Institute of Education Sciences. Washington, DC. Retrieved on September 13, 2010 from http://nces.ed.gov/about/.

  • Olweus, D. (1993). Bullying at school: What we know and what we can do. Cambridge, MA: Blackwell

    Google Scholar 

  • Olweus, D. (1997a). Tackling peer victimization with a school-based intervention program. In D. P. Fry & K. Bjorkqvist (Eds.), Cultural Variation in Conflict Resolution: Alternatives to Violence (pp. 215–231). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Olweus, D. (1997b). Bully/victim problems in schools: Knowledge base and an effective intervention program. The Irish Journal of Psychology, 18, 170–190.

    Google Scholar 

  • Olweus, D., & Limber, S. P. (2010). Bullying in school: Evaluation and dissemination of the Olweus Bullying Prevention Program. American Journal of Orthopsychiatry, 80, 124–134.

    Article  PubMed  Google Scholar 

  • Pellegrini, A. D., & Long, J. D. (2002). A longitudinal study of bullying, dominance, and victimization during the transition from primary school through secondary school. British Journal of Developmental Psychology, 20, 259–280.

    Article  Google Scholar 

  • Reardon, S. F., Brennan, R. T., & Buka, S. L. (2002). Estimating multi-level discrete-time hazard models using cross-sectional data: Neighborhood effects on the onset of adolescent cigarette use. Multivariate Behavioral Research, 37, 297–330.

    Article  Google Scholar 

  • Rigby, K. (2007). Bullying in schools: And what to do about it. Camberwell, Australia: ACER Press.

    Google Scholar 

  • Ross, S. W., & Horner, R. H. (2009). Bully prevention in Positive Behavior Support. Journal of Applied Behavior Analysis, 42, 747–759.

    Article  PubMed  Google Scholar 

  • Ryan, W., & Smith, J. D. (2009). Anti-bullying programs in schools: How effective are evaluation practices? Prevention Science, 10, 248–259.

    Article  PubMed  Google Scholar 

  • Scholte, E. M. (1992). Prevention and treatment of juvenile problem behavior: A proposal for a socio-ecological approach. Journal of Abnormal Child Psychology, 20, 247–262.

    Article  PubMed  CAS  Google Scholar 

  • Sheldon, S. B., & Epstein, J. L. (2002). Improving student behavior and school discipline with family and community involvement. Education and Urban Society, 35, 4–26.

    Article  Google Scholar 

  • Singer, J. D., & Willett, J. B. (1993). It’s about time: Using discrete-time survival analysis to study duration and the timing of events. Journal of Educational Statistics, 18, 155–195.

    Article  Google Scholar 

  • Skiba, R. J. (2000). Zero tolerance, zero evidence: An analysis of school disciplinary practice (Publication No. SRS2). Bloomington: Indiana Education Policy Center.

    Google Scholar 

  • Smith, J. D., Schneider, B. H., Smith, P. K., & Ananiadou, K. (2004). The effectiveness of whole-school antibullying programs: A synthesis of evaluation research. School Psychology Review, 33, 547–560.

    Google Scholar 

  • Smith, P. K. (2004). Bullying: Recent developments. Child and Adolescent Mental Health, 9, 98–103.

    Article  Google Scholar 

  • Song, S. Y., & Stoiber, K. C. (2008). Children exposed to violence at school: An evidence-based intervention agenda for the “real bullying” problem. Journal of Emotional Abuse, 8, 235–253.

    Article  Google Scholar 

  • Spaulding, S. A., & Frank, J. L. (2009). Comparison of office discipline referrals in U.S. schools by population densities: Do rates differ according to school location? Eugene: Educational and Community Supports, University of Oregon.

    Google Scholar 

  • Spriggs, A. L., Iannotti, R. J., Nansel, T. R., & Haynie, D. L. (2008). Adolescent bullying involvement and perceived family, peer and school relations: Commonalities and differences across race/ethnicity. Journal of Adolescent Health, 41, 283–293.

    Article  Google Scholar 

  • StataCorp. (2009). Stata Statistical Software: Release 10. College Station, MD: StataCorp LP.

    Google Scholar 

  • Sugai, G., & Horner, R. (2002). The evolution of discipline practices: School-wide positive behavior supports. Behavior Psychology in the Schools, 24, 23–50.

    Google Scholar 

  • Swearer, S. M., & Doll, B. (2001). Bullying in schools: An ecological framework. Journal of Emotional Abuse, 2, 7–23.

    Article  Google Scholar 

  • Swearer, S. M., Espelage, D. L., Vaillancourt, T., & Hymel, S. (2010). What can be done about school bullying? Linking research to educational practice. Educational Researcher, 39, 38–47.

    Article  Google Scholar 

  • Szapocznik, J., & Coatsworth, J. D. (1999). An ecodevelopmental framework for organizing the influences on drug abuse: A developmental model of risk and protection. In M. Glantz & C. R. Hartel (Eds.), Drug abuse: Origins and interventions (pp. 331–366). Washington, DC: American Psychological Association.

    Chapter  Google Scholar 

  • Tarshis, T. P., & Huffman, L. C. (2007). Psychometric properties of the peer interactions in primary school (PIPS) Questionnaire. Journal of Developmental & Behavioral Pediatrics, 28, 125–132.

    Article  Google Scholar 

  • Ttofi, M. M., & Farrington, D. P. (2011). Effectiveness of school-based programs to reduce bullying: A systematic and meta-analytic review. Journal of Experimental Criminology, 7, 27–56.

    Article  Google Scholar 

  • Yabiku, S. T. (2005). The effect of non-family experiences on age of marriage in a setting of rapid social change. Population Studies, 59, 339–354.

    Article  PubMed  Google Scholar 

  • Young, R., & Sweeting, H. (2004). Adolescent bullying, relationships, psychological well-being, and gender-atypical behavior: A gender diagnosticity approach. Sex Roles, 50, 525–534.

    Article  Google Scholar 

Download references

Acknowledgments

An earlier version of this paper was presented at the Society for Prevention Research conference (2010, June) in Denver, CO as part of the Sloboda and Bukoski SPR Cup Competition (Eddy & Martinez, 2008). The authors’ time was supported by funding from the National Institutes of Health/National Center on Minority Health and Health Disparities (NCMHD/NIH), award P20 MD002316-04 (F. Marsiglia, P.I.) to the Southwest Interdisciplinary Research Center at Arizona State University. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NCMHD or the NIH.

The authors would like to thank Dr. Robert H. Horner and Dr. Jennifer Frank of the Education and Community Supports research surveys unit within the College of Education at the University of Oregon for allowing us use of the data.

Author information

Authors and Affiliations

  1. Southwest Interdisciplinary Research Center, College of Public Programs, Arizona State University, Phoenix, AZ, USA

    Stephanie L. Ayers & Monica Bermudez-Parsai

  2. Arizona State University School of Social Work & Health Disparities Doctoral Intern, Southwest Interdisciplinary Research Center, Phoenix, AZ, USA

    M. Alex Wagaman & Jennifer Mullins Geiger

  3. Research Scientist, National Opinion Research Center, University of Chicago, Chicago, IL, USA

    E. C. Hedberg

  4. Southwest Interdisciplinary Research Center, Arizona State University, 411 N. Central Ave, Suite 720, Phoenix, AZ, 85004, 602-496-0700, USA

    Stephanie L. Ayers

Authors
  1. Stephanie L. Ayers
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Alex Wagaman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jennifer Mullins Geiger
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Monica Bermudez-Parsai
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. E. C. Hedberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stephanie L. Ayers.

Appendix A

Appendix A

Effective Sample Size

(Killip et al. 2004)

Because each school did not contribute the same number of students to the study, the harmonic mean was calculated using Stata 9.0 (H = 3.7).

$$ \matrix{{*{20}{c}} {{\text{ESS}} = {\text{mk}}/\left( {{1} + \rho \;\left( {{\text{m}} - {1}} \right)} \right)} \\ {{\text{ESS}} = \left( {{3}.{7}} \right)\left( {{122}} \right)/\left( {{1} + .0{5}\left( {{3}.{7} - {1}} \right)} \right)} \\ {{\text{ESS}} = {397}.{7}0} \\ } $$
ESS:

Effective Sample Size

m:

Average number of students who bullied per school based on the harmonic mean (H)

k:

Number of schools

ρ:

Intraclass correlation

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ayers, S.L., Wagaman, M.A., Geiger, J.M. et al. Examining School-Based Bullying Interventions Using Multilevel Discrete Time Hazard Modeling. Prev Sci 13, 539–550 (2012). https://doi.org/10.1007/s11121-012-0280-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11121-012-0280-7

Keywords

Search

Navigation