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Journal of Youth and Adolescence

, Volume 42, Issue 4, pp 566–580 | Cite as

Predictors of Latent Trajectory Classes of Physical Dating Violence Victimization

  • Ashley Brooks-RussellEmail author
  • Vangie A. Foshee
  • Susan T. Ennett
Empirical Research

Abstract

This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9 % female). Growth mixture models were used to identify trajectory classes of physical dating violence victimization separately for girls and boys. Logistic and multinomial logistic regressions were used to identify situational and target vulnerability factors associated with the trajectory classes. For girls, three trajectory classes were identified: a low/non-involved class; a moderate class where victimization increased slightly until the 10th grade and then decreased through the 12th grade; and a high class where victimization started at a higher level in the 8th grade, increased substantially until the 10th grade, and then decreased until the 12th grade. For males, two classes were identified: a low/non-involved class, and a victimized class where victimization increased slightly until the 9th grade, decreased until the 11th grade, and then increased again through the 12th grade. In bivariate analyses, almost all of the situational and target vulnerability risk factors distinguished the victimization classes from the non-involved classes. However, when all risk factors and control variables were in the model, alcohol use (a situational vulnerability) was the only factor that distinguished membership in the moderate trajectory class from the non-involved class for girls; anxiety and being victimized by peers (target vulnerability factors) were the factors that distinguished the high from the non-involved classes for the girls; and victimization by peers was the only factor distinguishing the victimized from the non-involved class for boys. These findings contribute to our understanding of the heterogeneity in physical dating violence victimization during adolescence and the malleable risk factors associated with each trajectory class for boys and girls.

Keywords

Adolescent dating violence Physical victimization Trajectories Growth mixture model 

Notes

Acknowledgments

This research was supported in part by the Intramural Program of the Eunice Kennedy Shriver National Institute of Child Health and Child Development. The studies that provided the data for this research were funded by the National Institute on Drug Abuse (R01DA16669, S. T. Ennett, PI) and the Centers for Disease Control and Prevention (R49CCV423114, V. A. Foshee, PI).

ABR, VF, and SE participated in the study design, interpretation of the data, and drafting of the manuscript. ABR conducted the statistical analysis. All authors read and approved the final manuscript.

References

  1. Ackard, D. M., Eisenberg, M. E., & Neumark-Sztainer, D. (2007). Long-term impact of adolescent dating violence on the behavioral and psychological health of male and female youth. The Journal of pediatrics, 151, 476–481.PubMedCrossRefGoogle Scholar
  2. Ackard, D. M., Neumark-Sztainer, D., & Hannan, P. (2003). Dating violence among a nationally representative sample of adolescent girls and boys: Associations with behavioral and mental health. Journal of Gender-Specific Medicine, 6, 39–48.PubMedGoogle Scholar
  3. Akaike, H. (1987). Factor Analysis and AIC. Psychometrika, 52, 317–322.CrossRefGoogle Scholar
  4. Angold, A., Costello, E. J., Messer, S. C., & Pickles, A. (1995). Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5, 237–249.Google Scholar
  5. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.PubMedCrossRefGoogle Scholar
  6. Bauer, D. J., & Curran, P. J. (2003). Distributional assumptions of growth mixture models: Implications for overextraction of latent trajectory classes. Psychological Methods, 8, 338–363.PubMedCrossRefGoogle Scholar
  7. Bloom, B. L. (1985). A factor analysis of self-report measured of family functioning. Family Process, 24, 225–239.PubMedCrossRefGoogle Scholar
  8. Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equations perspective. Hoboken, New Jersey: Wiley.Google Scholar
  9. Capaldi, D. M., Knoble, N. B., Shortt, J. W., & Kim, H. K. (2012). A systematic review of risk factors for intimate partner violence. Partner Abuse, 3, 231–280.PubMedCrossRefGoogle Scholar
  10. Centers for Disease Control and Prevention (2011). Youth risk behavior surveillanceUnited States [Rep. no. 61 (no. 4)]. Atlanta, GA: Office of Surveillance, Epidemiology and Laboratory Services.Google Scholar
  11. Chase, K. A., Treboux, D., & O’Leary, K. D. (2002). Characteristics of high-risk adolescents’ dating violence. Journal of Interpersonal Violence, 17, 33–49.CrossRefGoogle Scholar
  12. Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 52, 170–183.CrossRefGoogle Scholar
  13. Coker, A. L., McKeown, R. E., Sanderson, M., Davis, K. E., Valois, R. F., & Huebner, E. S. (2000). Severe dating violence and quality of life among South Carolina high school students. American Journal of Preventive Medicine, 19, 220–227.PubMedCrossRefGoogle Scholar
  14. Colder, C. R., Campbell, R. T., Ruel, E., Richardson, J. L., & Flay, B. R. (2002). A finite mixture model of growth trajectories of adolescent alcohol use: Predictors and consequences. Journal of Consulting and Clinical Psychology, 70, 976–985.PubMedCrossRefGoogle Scholar
  15. Colder, C. R., Mehta, P., Balanda, K., Campbell, R. T., Mayhew, K., Stanton, W. R., et al. (2001). Identifying trajectories of adolescent smoking: An application of latent growth mixture modeling. Health Psychology, 20, 127–135.PubMedCrossRefGoogle Scholar
  16. Cudeck, R., & Henly, S. J. (2003). A realistic perspective on pattern representation in growth data: Comment on Bauer and Curran (2003). Psychological Methods, 8, 378–383.PubMedCrossRefGoogle Scholar
  17. Dahlberg, L. L., Toal, S. B., Swahn, M., & Behrens, C. B. (2005). Measuring violence-related attitudes, behaviors, and influences among youths: A compendium of assessment tools (2nd ed.). Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control.Google Scholar
  18. DiClemente, R., Wingood, G. M., Crosby, R., Sionean, C., Cobb, B. K., Harrington, K., et al. (2001). Parental monitoring: Association with adolescents’ risk behaviors. Pediatrics, 6, 1363–1368.CrossRefGoogle Scholar
  19. Ellis, W. E., Crooks, C. V., & Wolfe, D. A. (2009). Relational aggression in peer and dating relationships: Links to psychological and behavioral adjustment. Social Development, 18, 253–269.CrossRefGoogle Scholar
  20. Ennett, S. T., Bauman, K. E., Hussong, A., Faris, R., Foshee, V. A., Cai, L., et al. (2006). The peer context of adolescent substance use: Findings from social network analysis. Journal of Research on Adolescence, 16, 159–186.CrossRefGoogle Scholar
  21. Finkelhor, D., & Asdigian, N. L. (1996). Risk factors for youth victimization: Beyond a lifestyles theoretical approach. Violence and Victims, 11, 3–20.PubMedGoogle Scholar
  22. Foshee, V. A. (1996). Gender differences in adolescent dating violence abuse prevalence, types and injuries. Health Education Research, 11, 275–286.CrossRefGoogle Scholar
  23. Foshee, V. A., Benefield, T. S., Ennett, S. T., Bauman, K. E., & Suchindran, C. (2004). Longitudinal predictors of serious physical and sexual dating violence victimization during adolescence. Preventive Medicine, 39, 1007–1016.PubMedCrossRefGoogle Scholar
  24. Foshee, V. A., Benefield, T., Suchindran, C., Ennett, S. T., Bauman, K. E., Karriker-Jaffe, K. J., et al. (2009). The development of four types of adolescent dating abuse and selected demographic correlates. Journal of Research on Adolescence, 19, 380–400.CrossRefGoogle Scholar
  25. Foshee, V. A., & Reyes, H. L. M. (2009). Primary prevention of dating abuse: When to begin, whom to target, and how to do it. In J. Lutzker & D. Whitaker (Eds.), Preventing partner violence: Research and evidence-based intervention strategies (pp. 141–168). Washington, DC: American Psychological Association.Google Scholar
  26. Foshee, V. A., & Reyes, H. L. M. (2012a). Adolescent dating abuse: Primary prevention efforts. In J. R. Levesque (Ed.), Encyclopedia of adolescence. Berlin: Springer.Google Scholar
  27. Foshee, V. A., & Reyes, H. L. M. (2012b). Dating abuse: Prevalence, consequences, and predictors. In J. R. Levesque (Ed.), Encyclopedia of adolescence (pp. 602–615). Berlin: Springer.Google Scholar
  28. Foshee, V. A., Reyes, H. L. M., Ennett, S. T., Suchindran, C., Mathias, J., Karriker-Jaffe, K. J., et al. (2011). Risk and protective factors distinguishing profiles of adolescent peer and dating violence perpetration. Journal of Adolescent Health, 48, 344–350.PubMedCrossRefGoogle Scholar
  29. Fritz, P. A. T., & Slep, A. M. S. (2009). Stability of physical and psychological adolescent dating aggression across time and partners. Journal of Clinical Child and Adolescent Psychology, 38, 303–314.Google Scholar
  30. Goodman, E. (1999). The role of socioeconomic status gradients in explaining differences in US adolescents’ health. American Journal of Public Health, 89, 1522–1528.PubMedCrossRefGoogle Scholar
  31. Halpern, C. T., Oslak, S. G., Young, M. L., Martin, S. L., & Kupper, L. L. (2001). Partner violence among adolescents in opposite-sex romantic relationships: Findings from the national longitudinal study of adolescent health. American Journal of Public Health, 91, 1679–1685.PubMedCrossRefGoogle Scholar
  32. Hill, K. G., White, H. R., Chung, I. J., Hawkins, J. D., & Catalano, R. F. (2000). Early adult outcomes of adolescent binge drinking: Person- and variable-centered analyses of binge drinking trajectories. Alcoholism, Clinical and Experimental Research, 24, 892–901.PubMedCrossRefGoogle Scholar
  33. Hindelang, M. S., Gottfredson, M., & Garofalo, J. (1978). Victims of personal crime. Cambridge, MA: Ballinger.Google Scholar
  34. Howard, D., Qiu, Y., & Boekeloo, B. (2003). Personal and social contextual correlates of adolescent dating violence. Journal of Adolescent Health, 33, 9–17.PubMedCrossRefGoogle Scholar
  35. Howard, D. E., & Wang, M. Q. (2003a). Risk profiles of adolescent girls who were victims of dating violence. Adolescence, 38, 1–14.PubMedGoogle Scholar
  36. Howard, D. E., & Wang, M. Q. (2003b). Psychosocial factors associated with adolescent boys’ reports of dating violence. Adolescence, 38, 519–533.PubMedGoogle Scholar
  37. Howard, D. E., Wang, M. Q., & Yan, F. (2008). Psychosocial factors associated with reports of physical dating violence victimization among US adolescent males. Adolescence, 43, 449–460.PubMedGoogle Scholar
  38. Jackson, C., Henriksen, L., & Foshee, V. A. (1998). The authoritative parenting index: Predicting health risk behaviors among children and adolescents. Health Education and Behavior, 25, 319–337.PubMedCrossRefGoogle Scholar
  39. Lehrer, J. A., Buka, S., Gortmaker, S., & Shrier, L. A. (2006). Depressive symptomatology as a predictor of exposure to intimate partner violence among US female adolescents and young adults. Archives of Pediatrics and Adolescent Medicine, 160, 270–276.PubMedCrossRefGoogle Scholar
  40. Li, F., Barrera, M., Hops, H., & Fisher, K. J. (2002). The longitudinal influence of peers on the development of alcohol use in late adolescence: A growth mixture analysis. Journal of Behavioral Medicine, 25, 293–315.PubMedCrossRefGoogle Scholar
  41. Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778.CrossRefGoogle Scholar
  42. Magdol, L., Moffitt, T. E., Caspi, A., & Silva, P. A. (1998). Developmental antecedents of partner abuse: A prospective-longitudinal study. Journal of Abnormal Psychology, 107, 375–389.PubMedCrossRefGoogle Scholar
  43. Malik, S., Sorenson, S. B., & Aneshensel, C. S. (1997). Community and dating violence among adolescents: Perpetration and victimization. Journal of Adolescent Health, 21, 291–302.PubMedCrossRefGoogle Scholar
  44. Miyazaki, Y., & Raudenbush, S. W. (2000). Tests for linkage of multiple cohorts in an accelerated longitudinal design. Psychological Methods, 5, 44–63.PubMedCrossRefGoogle Scholar
  45. Muthén, B. O. (2003). Statistical and substantive checking in growth mixture modeling: Comment on Bauer and Curran (2003). Psychological Methods, 8, 369–377.PubMedCrossRefGoogle Scholar
  46. Muthén, B. O., & Muthén, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism, Clinical and Experimental Research, 24, 882–891.PubMedCrossRefGoogle Scholar
  47. Muthén, L. K., & Muthén, B. O. (2011). Mplus users guide (6th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
  48. Muthén, B. O., & Shedden, K. (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics, 55, 463–469.PubMedCrossRefGoogle Scholar
  49. Nagin, D. S. (1999). Analyzing developmental trajectories: A semiparametric, group-based approach. Psychological Methods, 4, 139–157.CrossRefGoogle Scholar
  50. Nocentini, A., Menesini, E., & Pastorelli, C. (2010). Physical dating aggression growth during adolescence. Journal of Abnormal Child Psychology, 38, 353–365.PubMedCrossRefGoogle Scholar
  51. Odgers, C. L., Moffitt, T. E., Broadbent, J. M., Dickson, N., Hancox, R. J., Harrington, H., et al. (2008). Female and male antisocial trajectories: From childhood origins to adult outcomes. Development and Psychopathology, 20, 673–716.PubMedCrossRefGoogle Scholar
  52. O’Donnell, L., Stueve, A., Myint, U., Duran, R., Agronick, G., & Wilson-Simmons, R. (2006). Middle school aggression and subsequent intimate partner physical violence. Journal of Youth and Adolescence, 35, 693–703.CrossRefGoogle Scholar
  53. O’Leary, K. D., & Slep, A. M. S. (2003). A dyadic longitudinal model of adolescent dating aggression. Journal of Clinical Child & Adolescent Psychology, 32, 314–327.Google Scholar
  54. O’Leary, K. D., Slep, A. M. S., Avery-Leaf, S., & Cascardi, M. (2008). Gender differences in dating aggression among multiethnic high school students. Journal of Adolescent Health, 42, 473–479.PubMedCrossRefGoogle Scholar
  55. Orpinas, P., Nahapetyan, L., Song, X., Mcnicholas, C., & Reeves, P. M. (2012). Psychological dating violence perpetration and victimization: Trajectories from middle to high school. Aggressive Behavior, 38, 510–520.PubMedCrossRefGoogle Scholar
  56. Ozer, E. J., Tschann, J. M., Pasch, L. A., & Flores, E. (2004). Violence perpetration across peer and partner relationships: Co-occurrence and longitudinal patterns among adolescents. Journal of Adolescent Health, 34, 64–71.PubMedGoogle Scholar
  57. Petersen, A. C., Schulenberg, J. E., Abramowitz, R. H., Offer, D., & Jarcho, H. D. (1994). A self-image questionnaire for young adolescents (SIQYA): Reliability and validity studies. Journal of Youth and Adolescence, 13, 93–111.CrossRefGoogle Scholar
  58. Raiford, J. L., Wingood, G. M., & Diclemente, R. J. (2007). Prevalence, incidence, and predictors of dating violence: A longitudinal study of African American female adolescents. Journal of Women’s Health, 16, 822–832.PubMedCrossRefGoogle Scholar
  59. Reyes, H. L. M., Foshee, V. A., Bauer, D. J., & Ennett, S. T. (2011). The role of heavy alcohol use in the developmental process of desistance in dating aggression during adolescence. Journal of Abnormal Child Psychology, 39, 239–250.PubMedCrossRefGoogle Scholar
  60. Reynolds, C. R., & Richmond, B. O. (1979). Factor structure and construct validity of “What I think and feel”: The revised children’s manifest anxiety scale. Journal of Personality Assessment, 43, 281–283.PubMedCrossRefGoogle Scholar
  61. Roberts, T. A., Klein, J. D., & Fisher, S. (2003). Longitudinal effect of intimate partner abuse on high-risk behavior among adolescents. Archives of Pediatrics and Adolescent Medicine, 157, 875–881.PubMedCrossRefGoogle Scholar
  62. Rothman, E. F., Reyes, H. L. M., Johnson, R. M., & LaValley, M. (2012). Does the alcohol make them do it? Dating violence perpetration and drinking among youth. Epidemiologic Reviews, 34, 103–119.PubMedCrossRefGoogle Scholar
  63. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.CrossRefGoogle Scholar
  64. SAS Institute (2010). Statistical analysis software (SAS) (Version 9.3) [Computer software]. Cary, NC: SAS Institute Inc.Google Scholar
  65. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461–464.CrossRefGoogle Scholar
  66. Sclove, S. L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52, 333–343.CrossRefGoogle Scholar
  67. Silverman, J. G., Raj, A., Mucci, L. A., & Hathaway, J. E. (2001). Dating violence against adolescent girls and associated substance use, unhealthy weight control, sexual risk behavior, pregnancy, and suicidality. Journal of the American Medical Association, 286, 572–579.PubMedCrossRefGoogle Scholar
  68. Smith, P. H., White, J. W., & Holland, L. J. (2003). A longitudinal perspective on dating violence among adolescent and college-age women. American Journal of Public Health, 93, 1104–1109.PubMedCrossRefGoogle Scholar
  69. Spriggs, A. L., Halpern, C. T., Herring, A. H., & Schoenbach, V. J. (2009). Family and school socioeconomic disadvantage: Interactive influences on adolescent dating violence victimization. Social Science and Medicine, 68, 1956–1965.PubMedCrossRefGoogle Scholar
  70. Steinberg, L., Fletcher, A., & Darling, N. (1994). Parental monitoring and peer influences on adolescent substance use. Pediatrics, 93, 1060–1064.PubMedGoogle Scholar
  71. Straus, M. A., & Gelles, R. J. (1986). Societal change and change in family violence from 1975 to 1985 as revealed by two national surveys. Journal of Marriage and the Family, 48, 465–479.CrossRefGoogle Scholar
  72. Swahn, M. H., Bossarte, R. M., & Sullivent, E. E. (2008). Age of alcohol use initiation, suicidal behavior, and peer and dating violence victimization and perpetration among high-risk, seventh-grade adolescents. Pediatrics, 121, 297–305.PubMedCrossRefGoogle Scholar
  73. Vicary, J. R., Klingaman, L. R., & Harkness, W. L. (1995). Risk factors associated with date rape and sexual assault of adolescent girls. Journal of Adolescence, 18, 289–306.CrossRefGoogle Scholar
  74. White, H. R., Bates, M. E., & Buyske, S. (2001). Adolescence-limited versus persistent delinquency: Extending Moffitt’s hypothesis into adulthood. Journal of Abnormal Psychology, 110, 600–609.PubMedCrossRefGoogle Scholar
  75. White, H. R., Pandina, R. J., & Chen, P. H. (2002). Developmental trajectories of cigarette use from early adolescence into young adulthood. Drug and Alcohol Dependence, 65, 167–178.PubMedCrossRefGoogle Scholar
  76. Wiesner, M., & Windle, M. (2004). Assessing covariates of adolescent delinquency trajectories: A latent growth mixture modeling approach. Journal of Youth and Adolescence, 33, 431–442.CrossRefGoogle Scholar
  77. Wolfe, D. A., Wekerle, C., Scott, K., Straatman, A. L., Grasley, C., & Reitzel-Jaffe, D. (2003). Dating violence prevention with at-risk youth: A controlled outcome evaluation. Journal of Consulting and Clinical Psychology, 71, 279–291.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside the USA) 2012

Authors and Affiliations

  • Ashley Brooks-Russell
    • 1
    Email author
  • Vangie A. Foshee
    • 2
  • Susan T. Ennett
    • 2
  1. 1.Prevention Research Branch, Division of Epidemiology, Statistics and Prevention ResearchEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBethesdaUSA
  2. 2.Department of Health Behavior, Gillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillUSA

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