Journal of Quantitative Criminology

, Volume 21, Issue 1, pp 73–102 | Cite as

Measurement Properties of the Communities That Care® Youth Survey Across Demographic Groups

  • Renita R. Glaser
  • M. Lee Van. Horn
  • Michael W. ArthurEmail author
  • J. David. Hawkins
  • Richard F. Catalano

Prevention science has produced information about risk and protective factors that predict adolescent drug use and related problem behaviors. This paper investigates the Communities That Care Youth Survey that measures multiple risk and protective factors. Using a sample of 172,628 students who participated in surveys administered in seven states in 1998, analyses were conducted to test the factor structure of these risk and protective factors and to test the equivalence of the factor models across five racial/ethnic groups (African Americans, Asians or Pacific Islanders, Caucasians, Hispanic Americans, and Native Americans), four grade levels (6th, 8th, 10th, and 12th) and both gender groups. Results support the construct validity of the survey’s risk and protective factor scales and indicate that the measures are equally reliable across males and females and five racial/ethnic groups. Implications of these findings for science-based prevention planning are discussed.


risk and protective factors youth survey validity measurement drug use prevention 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Arthur, M. W., Blitz, C. 2000Bridging the gap between science and practice in drug abuse prevention through needs assessment and strategic community planningJ. Community Psychol.28241255Google Scholar
  2. Arthur, M. W., and Hawkins, J. D. (in press). Needs assessment for drug abuse prevention services. J. Prim. Prev.Google Scholar
  3. Arthur, M. W., Hawkins, J. D., Pollard, J. A., Catalano, R. F., Baglioni, A. J.,Jr. 2002Measuring risk and protective factors for substance use, delinquency, and other adolescent problem behaviors: The Communities That Care Youth SurveyEval. Rev.26575601Google Scholar
  4. Browne, M. W., Cudeck, R. 1993Alternative ways of assessing model fitBollen, K. A.Long, J. S. eds. Testing Structural Equation ModelsSageNewbury Park, CA136162Google Scholar
  5. Bry, B. H., McKeon, P., Pandina, R. J. 1982Extent of drug use as a function of number of risk factorsJ. Abnorm. Psychol.91273279Google Scholar
  6. Byrne, B. 1989A Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic ModelsSpringer VerlagNew YorkGoogle Scholar
  7. Catalano, R. F., Arthur, M. W., Hawkins, J. D., Berglund, L., Olson, J. J. 1998Comprehensive community and school based interventions to prevent antisocial behaviorLoeber, R.Farrington, D. P. eds. Serious and Violent Juvenile Offenders: Risk Factors and Successful InterventionsSageThousand Oaks, CA248283Google Scholar
  8. Cheung, G. W., Rensvold, R. B. 2002Evaluating goodness-of-fit indexes for testing measurement invarianceStruct. Equation Model.9233255Google Scholar
  9. Coie, J. D., Watt, N. F., West, S. G., Hawkins, J. D., Asarnow, J. R., Markman, H. J., Ramey, S. L., Shure, M. B., Long, B. 1993The science of prevention. A conceptual framework and some directions for a national research programAm. Psychol.4810131022Google Scholar
  10. Dryfoos, J. G. 1990Adolescents at Risk: Prevalence and PreventionOxford University PressNew YorkGoogle Scholar
  11. Durlak, J. A. 1998Common risk and protective factors in successful prevention programsAm. J. Orthopsychiat.68512520Google Scholar
  12. Fergusson, D. M., Horwood, L. J., Lynskey, M. T. 1994The childhoods of multiple problem adolescents: a 15-year longitudinal studyJ. Child Psychol. Psychiatry3511231140Google Scholar
  13. Furstenberg, F. F.,Jr., Cook, T. D., Eccles, J., Elder, G. H.,Jr., Sameroff, A. J. 1998Managing to Make it: Urban Families and Adolescent SuccessThe John D. and Catherine T. MacArthur Foundation Series on Mental Health and Development, Studies on Successful Adolescent Development, University of Chicago PressChicagoGoogle Scholar
  14. Glantz, M. D.Pickens, R. W. eds. 1992Vulnerability to Drug AbuseAmerican Psychological AssociationWashington, DCGoogle Scholar
  15. Gottfredson, D. C., Koper, C. S. 1997Race and sex differences in the measurement of risk for drug useJ. Quant. Criminol.13325347Google Scholar
  16. Hawkins, J. D. 1999Preventing crime and violence through communities that careEur. J. Criminal Policy Res.7443458Google Scholar
  17. Hawkins, J. D., Arthur, M. W., Catalano, R. F. 1995Preventing substance abuseTonry, M.Farrington, D. eds. Crime and Justice: Vol. 19. Building a Safer Society: Strategic Approaches to Crime PreventionUniversity of Chicago PressChicago343427Google Scholar
  18. Hawkins, J. D., Arthur, M. W., Catalano, R. F. 1997Six State Consortium for Prevention Needs Assessment Studies: Final ReportSocial Development Research, Group University of WashingtonSeattle, WAGoogle Scholar
  19. Hawkins, J. D., Catalano, R. F., Miller, J. Y. 1992Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance-abuse preventionPsychol. Bull.11264105Google Scholar
  20. Hawkins, J. D., Herrenkohl, T., Farrington, D. P., Brewer, D., Catalano, R. F., Harachi, T. W. 1998A review of predictors of youth violenceLoeber, R.Farrington, D. P. eds. Serious and Violent Juvenile Offenders: Risk Factors and Successful Interventions.SageThousand Oaks, CA106146Google Scholar
  21. Hu, L.t., Bentler, P. M. 1998Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecificationPsychol. Meth.3424453Google Scholar
  22. Hu, L.t., Bentler, P. M. 1999Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternativesStruct. Equation Model.6155Google Scholar
  23. Jöreskog, K. G., Sörbom, D. 1994Lisrel 8 and Prelis 2: Comprehensive Analysis of Linear Relationships in Multivariate Data, Lisrel 8 User’s GuideLawrence Erlbaum AssociatesChicago, ILGoogle Scholar
  24. Kansas Department of Social and Rehabilitation Services/Alcohol and Drug Abuse Services1996Kansas Communities That Care Regional Planning Resource GuideAuthorTopeka, KSGoogle Scholar
  25. Kellam, S. G., Koretz, D., Moscicki, E. K. 1999Core elements of developmental epidemiologically based prevention researchAm. J. Community Psychol.27463482Google Scholar
  26. Lipsey, M. W., Derzon, J. H. 1998Predictors of violent or serious delinquency in adolescence and early adulthood: a synthesis of longitudinal researchLoeber, R.Farrington, D. P. eds. Serious and Violent Juvenile Offenders: Risk Factors and Successful InterventionsSageThousand Oaks, CA86105Google Scholar
  27. Little, R. J.A., Rubin, D. B. 1987Statistical Analysis with Missing DataJohn Wiley and SonsNew YorkGoogle Scholar
  28. Loeber, R., Stouthamer-Loeber, M. 1987PredictionQuay, H. C. eds. Handbook of Juvenile DelinquencyWileyNew York325382Google Scholar
  29. Mrazek, P. J.Haggerty, R. J. eds. 1994Committee on Prevention of Mental Disorders, Institute of Medicine Reducing Risks for Mental Disorders: Frontiers for Prevention Intervention ResearchNational Academy PressWashington, DCGoogle Scholar
  30. Muthen, B. 1983Latent variable structural equation modeling with categorical dataJ.␣Econometrics224865Google Scholar
  31. Muthen, B. 1984A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicatorsPsychometrika49115132Google Scholar
  32. Muthen, B., Kaplan, D. 1992A comparison of some methodologies for the factor analysis of non-normal Likert variables: a note on the size of the modelBr. J. Math. Stat. Psychol.451930Google Scholar
  33. Muthén, B. O., du Toit, S. H. C., and Spisic, D. (1997). Robust Inference Using Weighted Least Squares and Quadratic Estimating Equations in Latent Variable Modeling with Categorical and Continuous Outcomes, Unpublished manuscript.Google Scholar
  34. Muthen, L. K., Muthen, B. O. 2001Mplus User’s GuideMuthen and MuthenLos AngelesGoogle Scholar
  35. Newcomb, M. D. 1995Identifying high-risk youth: prevalence and patterns of adolescent drug abuseRahdert, E.Czechowicz, D.Amsel, I. eds. Adolescent Drug Abuse: Clinical Assessment and Therapeutic InterventionNational Institute on Drug AbuseRockville, MD738Google Scholar
  36. Office of Juvenile JusticeDelinquency Prevention1995Guide for Implementing the Comprehensive Strategy for Serious, Violent, and Chronic Juvenile OffendersOffice of Juvenile Justice and Delinquency Prevention U. S. Department of JusticeWashington, DCGoogle Scholar
  37. Office of National Drug Control Policy2000National Drug Control Strategy: 2000 Annual ReportU. S. Government Printing OfficeWashington, DCGoogle Scholar
  38. Olsson, U. 1979Maximum likelihood estimation of the polychoric correlation coefficientPsychometrika44443460Google Scholar
  39. Peck, S., Sameroff, A. J., Ramey, S., and Ramey, C. (1999, April). Transition into school: Ecological risks for adaptation and achievement in a national sample. Paper presented at the Biennial Meeting of the Society for Research and Development, Albuquerque, NM.Google Scholar
  40. Pollard, J. A., Hawkins, J. D., Arthur, M. W. 1999Risk and protection: are both necessary to understand diverse behavioral outcomes in adolescence?Soc Work Res.23145158Google Scholar
  41. Rosay, A. B., Gottfredson, D. C., Armstrong, T. A., Harmon, M. A. 2000Invariance of measures of prevention program effectiveness: a replicationJ. Quant. Criminol.16341367Google Scholar
  42. Rutter, M. 1979Protective factors in children’s responses to stress and disadvantageKent, M. W.Rolf, J. E. eds. Primary Prevention of Psychopathology: Vol. 3. Social Competence in ChildrenUniversity Press of New EnglandHanover, NH4974Google Scholar
  43. Sameroff, A., Gutman, L. M. 2004Contributions of risk research to the design of successful interventionsFraser, M. W.Allen-Meares, P. eds. Intervention with Children and Adolescents: An Interdisciplinary PerspectiveAllyn & BaconBoston926Google Scholar
  44. Sameroff, A. J., Bartko, W. T., Baldwin, A., Baldwin, C., Seifer, R. 1998Family and social influences on the development of child competenceLewis, M.Feiring, C. eds. Families, Risk, and CompetenceLawrence Erlbaum Associates, IncMahwah, NJ161185Google Scholar
  45. Schafer, J. L. 1997Analysis of Incomplete Multivariate Data. Monographs on Statistics and Applied ProbabilityChapman and HallLondonGoogle Scholar
  46. Sloboda, Z., David, S. L. 1997Preventing Drug Use Among Children and Adolescents: A␣Research-based GuideNational Institute on Drug AbuseRockville, MDGoogle Scholar
  47. Vandenberg, R. J., Lance, C. E. 2000A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational researchOrgan. Res. Meth.3469Google Scholar
  48. Washington State Department of Social and Health Services2001Washington State Incentive Grant. State Substance Abuse Prevention SystemAuthorOlympia, WAGoogle Scholar
  49. Wasserman, G. A., Miller, L. S. 1998The prevention of serious and violent juvenile offendingLoeber, R.Farrington, D. P. eds. Serious and Violent Juvenile Offenders: Risk Factors and Successful InterventionsSageThousand Oaks, CA197247Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Renita R. Glaser
    • 1
  • M. Lee Van. Horn
    • 1
    • 2
  • Michael W. Arthur
    • 1
    Email author
  • J. David. Hawkins
    • 1
  • Richard F. Catalano
    • 1
  1. 1.Social Development Research GroupUniversity of WashingtonSeattleWA
  2. 2.Department of PsychologyUniversity of South CarolinaColumbia

Personalised recommendations