Trajectory Analysis of the Campus Serial Rapist Assumption | Adolescent Medicine | JAMA Pediatrics | JAMA Network
[Skip to Navigation]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address Please contact the publisher to request reinstatement.
Obama  B; Office of the Press Secretary; White House. Memorandum—establishing a White House task force to protect students from sexual assault. Published January 22, 2014. Accessed January 23, 2014.
White House Council on Women and Girls.  Rape and sexual assault: a renewed call to action. Published January 21, 2014. Accessed January 23, 2014.
Gordon  C.  Why don’t we talk about all the serial rapists?Aljazeera America Flagship Blog. March 14, 2014. Accessed May 11, 2014.
Hostler  MJ.  Making campuses safer for women: sexual predators often blend in easily at college, their criminal intent seemingly unthinkable.Wall Street Journal (Opinion). February 24, 2014. Accessed February 26, 2014.
Starecheski  L.  The power of the peer group in preventing campus rape.National Public Radio. August 8, 2014. Accessed August 8, 2014.
Schafran LH, Bayliff CJ, Vris T, et al; National Judicial Education Program. The challenges of adult victim sexual assault cases. Accessed December 15, 2014.
Rape, Abuse, & Incest National Network. Letter to White House task force to protect students from sexual assault. Published February 28, 2014. Accessed July 15, 2014.
Lonsway  KA.  Trying to move the elephant in the living room.  Violence Against Women. 2010;16(12):1356-1371.PubMedGoogle ScholarCrossref
Lisak  D.  Understanding the predatory nature of sexual violence.Sexual Assault Rep. 2011;14(4):49-64. Accessed July 15, 2014.
Lisak  D, Miller  PM.  Repeat rape and multiple offending among undetected rapists.  Violence Vict. 2002;17(1):73-84.PubMedGoogle ScholarCrossref
Graney  DJ, Arrigo  BA.  The Power Serial Rapist: A Criminology-Victimology Typology of Female Victim Selection. Springfield, IL: Charles C Thomas Publishers; 2002.
Beauregard  E, Proulx  J, Rossmo  K, Leclerc  B, Allaire  J.  Script analysis of the hunting process of serial sex offenders.  Crim Justice Behav. 2007;34(8):1069-1084. doi:10.1177/0093854807300851.Google ScholarCrossref
Douglas  J, Burgess  AW, Burgess  AG, Ressler  RK.  Crime Classification Manual: A Standard System for Investigating and Classifying Violent Crime. Hoboken, New Jersey: Wiley; 2013.
US Department of Justice Office of Public Affairs.  Attorney General Eric Holder announces revisions to the Uniform Crime Report’s definition of rape: data reported on rape will better reflect state criminal codes, victim experiences. Published January 6, 2012. Accessed February 12, 2014.
Moffitt  TE.  Adolescence-limited and life-course-persistent antisocial behavior.  Psychol Rev. 1993;100(4):674-701.PubMedGoogle ScholarCrossref
Moffitt  TE. Natural histories of delinquency. In:  Cross-National Longitudinal Research on Human Development and Criminal Behavior. Heidelberg, Netherlands: Springer; 1994:3-61.
Moffit  TE.  Adolescence-limited and life-course-persistent offending.  Developmental Theories Crime Delinquency.1997;7:11-54.Google Scholar
White  JW, Smith  PH.  Sexual assault perpetration and reperpetration.  Crim Justice Behav. 2004;31(2):182-205. doi:10.1177/0093854803261342.Google ScholarCrossref
Thompson  MP, Swartout  KM, Koss  MP.  Trajectories and predictors of sexually aggressive behaviors during emerging adulthood.  Psychol Violence. 2013;3(3):247-259.PubMedGoogle ScholarCrossref
Koss  MP, Gidycz  CA, Wisniewski  N.  The scope of rape.  J Consult Clin Psychol. 1987;55(2):162-170.PubMedGoogle ScholarCrossref
Koss  MP, Abbey  A, Campbell  R,  et al.  Revising the SES: a collaborative process to improve assessment of sexual aggression and victimization.  Psychol Women Q. 2007;31(4):357-370. doi:10.1111/j.1471-6402.2007.00385.x.Google ScholarCrossref
Koss  MP, Oros  CJ.  Sexual Experiences Survey.  J Consult Clin Psychol. 1982;50(3):455-457.PubMedGoogle ScholarCrossref
Krebs  C.  Measuring sexual victimization.  Trauma Violence Abuse. 2014;15(3):170-180. PubMedGoogle ScholarCrossref
Muthén  BO. Latent variable mixture modeling. In: Marcoulides GA, Schumacker RE, eds. New Developments and Techniques in Structural Equation Modeling. Lawrence Erlbaum Associates, Inc; 2001:1-33.
Nagin  DS, Tremblay  RE.  Developmental trajectory groups.  Criminology. 2005;43(4):873-904. doi:10.1111/j.1745-9125.2005.00026.x.Google ScholarCrossref
Muthén  BO, Asparouhov  T. Growth mixture modeling: analysis with non-Gaussian random effects. In:  Longitudinal Data Analysis.Vol 3. Boca Raton, FL: Chapman & Hall/CRC Press; 2008:143-165.
Muthén  BO. Latent variable analysis: growth mixture modeling and related techniques for longitudinal data. In: Kaplan  D, ed.  Handbook of Quantitative Methodology for the Social Sciences. Newbury Park, CA: Sage Publications; 2004:345-368.
Muthén  B, Shedden  K.  Finite mixture modeling with mixture outcomes using the EM algorithm.  Biometrics. 1999;55(2):463-469.PubMedGoogle ScholarCrossref
Morgan-Lopez  AA, Cluff  LA, Fals-Stewart  W.  Capturing the impact of membership turnover in small groups via latent class growth analysis.  Gr Dyn: Theory, Res Pract.2009;13(2):120-132. doi:10.1037/a0014095.Google ScholarCrossref
Muthén  BO, Muthén  LM.  Mplus (Version 7.11). Los Angeles, CA: Muthén & Muthén; 2012.
Yuan  K, Bentler  PM.  Three likelihood-based methods for mean and covariance structure analysis with nonnormal missing data.  Sociol Methodol. 2008;30(1):165-200. doi:10.1111/0081-1750.00078.Google ScholarCrossref
Bollen  KA.  Overall fit in covariance structure models: .  Psychol Bull. 1990;107(2):256-259. doi:10.1037//0033-2909.107.2.256.Google ScholarCrossref
Preacher  KJ, Hayes  AF.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.  Behav Res Methods. 2008;40(3):879-891.PubMedGoogle ScholarCrossref
Jackson  KM, Sher  KJ, Schulenberg  JE.  Conjoint developmental trajectories of young adult alcohol and tobacco use.  J Abnorm Psychol. 2005;114(4):612-626.PubMedGoogle ScholarCrossref
Tucker  JS, Orlando  M, Ellickson  PL.  Patterns and correlates of binge drinking trajectories from early adolescence to young adulthood.  Health Psychol. 2003;22(1):79-87.PubMedGoogle ScholarCrossref
Tofighi  D, Enders  CK. Identifying the correct number of classes in a growth mixture models. In: Hancock  GR, Samuelsen  KM, eds.  Advances in Latent Variable Mixture Models. Greenwich, CT: Information Age; 2007.
Nylund  K, Asparouhov  T, Muthén  BO.  Deciding on the number of classes in latent class analysis and growth mixture modeling.  Struct Equ Modeling. 2007;14(4):535-569. doi:10.1080/10705510701575396.Google ScholarCrossref
Swartout  KM, Swartout  AG, White  JW.  A person-centered, longitudinal approach to sexual victimization.  Psychol Violence. 2011;1(1):29-40. doi:10.1037/a0022069.Google ScholarCrossref
Abbey  A, McAuslan  P.  A longitudinal examination of male college students’ perpetration of sexual assault.  J Consult Clin Psychol. 2004;72(5):747-756.PubMedGoogle ScholarCrossref
Wheeler  J, George  W, Dahl  B.  Sexually aggressive college males.  Pers Individ Dif. 2002;33(5):759-775. doi:10.1016/S0191-8869(01)00190-8.Google ScholarCrossref
Abbey  A, Wegner  R, Pierce  J, Jacques-Tiura  AJ.  Patterns of sexual aggression in a community sample of young men.  Psychol Violence. 2012;2(1):1-15.PubMedGoogle ScholarCrossref
Lussier  P, Davies  G.  A person-oriented perspective on sexual offenders, offending trajectories, and risk of recidivism.  Psychol Public Policy Law. 2011;17(4):530-561. doi:10.1037/a0024388.Google ScholarCrossref
Swartout  KM, Swartout  AG, Brennan  CL, White  JW.  Trajectories of male sexual aggression from adolescence through college.  Aggress Behav.PubMedGoogle Scholar
Bandura  A.  Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall; 1977.
Reiss  AJ.  Delinquency as the failure of personal and social controls.  Am Sociol Rev. 1951;16(2):196-207. doi:10.2307/2087693.Google ScholarCrossref
Swartout  KM.  The company they keep: how peer networks influence male sexual aggression.  Psychol Violence. 2013;3(2):157-171. doi:10.1037/a0029997.Google ScholarCrossref
DeGue  S, Valle  L, Holt  M, Massetti  G, Matjasko  J, Tharp  A.  A systematic review of primary prevention strategies for sexual violence perpetration.  Aggress Violent Behav. 2014;19(4):346-362. doi:10.1016/j.avb.2014.05.004.Google ScholarCrossref
Koss  MP, Wilgus  JK, Williamsen  KM.  Campus sexual misconduct.  Trauma Violence Abuse. 2014;15(3):242-257.PubMedGoogle ScholarCrossref
Original Investigation
Journal Club
December 2015

Trajectory Analysis of the Campus Serial Rapist Assumption

Journal Club PowerPoint Slide Download
Author Affiliations
  • 1Department of Psychology, Georgia State University, Atlanta
  • 2Department of Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson
  • 3Department of Psychology, University of North Carolina at Greensboro, Greensboro
  • 4Institute on Family and Neighborhood Life, Clemson University, Clemson, South Carolina
  • 5Department of Psychology, Wayne State University, Detroit, Michigan
JAMA Pediatr. 2015;169(12):1148-1154. doi:10.1001/jamapediatrics.2015.0707

Importance  Rape on college campuses has been addressed recently by a presidential proclamation, federal legislation, advocacy groups, and popular media. Many initiatives assume that most college men who perpetrate rape are serial rapists. The scientific foundation for this perspective is surprisingly limited.

Objective  To determine whether a group of serial rapists exists by identifying cohesive groups of young men, indicated by their trajectories of rape likelihood across high school and college.

Design, Setting, and Participants  Latent class growth analysis of the 2 largest longitudinal data sets of adolescent sexual violence on college campuses using 2 distinct groups of male college students. The first group was used for derivation modeling (n = 847; data collected from August 1990 through April 1995) and the second for validation modeling (n = 795; data collected from March 2008 through May 2011). Final data analyses were conducted from February 16, 2015, through February 20, 2015.

Main Outcomes and Measures  Rape perpetration assessed using the Sexual Experiences Survey.

Results  Across samples, 178 of 1642 participants (10.8%) reported having perpetrated at least 1 rape from 14 years of age through the end of college. A 3-trajectory model best fit both the derivation and validation data sets. Trajectories reflected low or time-limited (92.6% of participants), decreasing (5.3%), and increasing (2.1%) rape patterns. No consistently high trajectory was found. Most men who perpetrated a rape before college were classified in the decreasing trajectory. During college, the increasing trajectory included 14 men (15.2%) who reported having perpetrated a rape, the decreasing trajectory included 30 men (32.6%), and the low or time-limited included 48 men (52.2%). No participant in the low or time-limited trajectory reported perpetrating a rape during more than 1 period. Most men (67 [72.8%]) who committed college rape only perpetrated rape during 1 academic year.

Conclusions and Relevance  Although a small group of men perpetrated rape across multiple college years, they constituted a significant minority of those who committed college rape and did not compose the group at highest risk of perpetrating rape when entering college. Exclusive emphasis on serial predation to guide risk identification, judicial response, and rape-prevention programs is misguided. To deter college rape, prevention should be initiated before, and continue during, college. Child and adolescent health care professionals are well positioned to intervene during the early teenage years by informing parents about the early onset of nonconsensual sexual behavior.