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Trajectories of marijuana use from adolescence to young adulthood: Predictors and outcomes

Published online by Cambridge University Press:  01 December 2004

MICHAEL WINDLE
Affiliation:
University of Alabama at Birmingham
MARGIT WIESNER
Affiliation:
University of Alabama at Birmingham

Abstract

Semiparametric group-based mixture modeling was used with data from an adolescent school sample (N = 1205) for three purposes. First, five trajectory groups were identified to characterize different patterns of change in the frequency of marijuana use across four waves of assessment during adolescence. These trajectory groups were labeled Abstainers, Experimental Users, Decreasers, Increasers, and High Chronics. Second, trajectory group comparisons were made across eight adolescent risk factors to determine distinctive predictors of the trajectory groups. Findings indicated, for example, that the High Chronic group, relative to the other trajectory groups, had higher levels of delinquency, lower academic performance, more drug using friends, and more stressful life events. Third, adolescent trajectory group comparisons were made across 10 risk behaviors in young adulthood (average subject age = 23.5 years) and the occurrence of psychiatric and substance abuse disorders. Findings indicated some consistency across adolescence to young adulthood with regard to risk factors, and specificity with regard to the prediction of disorders. Adolescent trajectory group membership was significantly associated in young adulthood with cannabis and alcohol disorders but not with major depressive disorders or anxiety disorders.This research was supported by a grant (R37-AA07861) awarded to Michael Windle from the National Institute on Alcohol Abuse and Alcoholism. An earlier version of this article was presented at the Michigan Symposium on Development and Psychopathology: Continuity and Discontinuity during the Transition to Adulthood, Ann Arbor, MI, June 14–15, 2002.

Type
Research Article
Copyright
© 2004 Cambridge University Press

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References

REFERENCES

Armor, D. J., & Polich, J. M. (1982). Measurement of alcohol consumption. In E. M. Pattison & E. Kaufman (Eds.), Encyclopedic handbook of alcoholism (pp. 7281). New York: Gardner Press.
Bailey, S. L., Flewelling, R. L., & Rachal, J. V. (1992). Predicting continued use of marijuana among adolescents: The relative influence of drug-specific and social contextual factors. Journal of Health and Social Behavior 33, 5166.Google Scholar
Bauer, D. J., & Curran, P. J. (2003). Distributional assumptions of growth mixture models: Implications for overextraction of latent trajectory classes. Psychological Methods 8, 338363.Google Scholar
Block, J., & Robins, R. W. (1993). A longitudinal study of consistency and change in self-esteem from early adolescence to early adulthood. Child Development 64, 909923.Google Scholar
Bryant, K., Windle, M., & West, S. G. (1997). The science of prevention: Methodological advances from alcohol and substance abuse research. Washington, DC: American Psychological Association.
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models for social and behavioral research: Application and data analysis methods. Newbury Park, CA: Sage.
Butters, J. E. (2002). Family stressors and adolescent cannabis use: A pathway to problem use. Journal of Adolescence 25, 645654.Google Scholar
Cairns, R. B., Bergman, L. R., & Kagan, J. (Eds.). (1998). Methods and models for studying the individual. Thousand Oaks, CA: Sage.
Chassin, L., Pitts, S. C., & Prost, J. (2002). Binge drinking trajectories from adolescence to emerging adulthood in a high-risk sample: Predictors and substance abuse outcomes. Journal of Consulting and Clinical Psychology 70, 6778.Google Scholar
Chassin, L., Presson, C. C., Sherman, S. J., & Edwards, D. A. (1994). The natural history of cigarette smoking and young adult social roles. Journal of Health and Social Behavior 33, 328347.Google Scholar
Cicchetti, D. (1993). Developmental psychopathology: Reactions, reflections, projections. Developmental Review 13, 471502.Google Scholar
Coffey, C., Carlin, J. B., Lynskey, M., Li, N., & Patton, G. C. (2003). Adolescent precursors of cannabis dependence: Findings from the Victorian Adolescent Health Cohort Study. British Journal of Psychiatry 182, 330336.Google Scholar
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. (1993). The science of prevention: A conceptual framework and some directions for a national research program. American Psychologist 48, 10131022.Google Scholar
Colder, C. R., Mehta, P., Balanda, K., Campbell, R. T., Mayhew, K. P., Stanton, W. R., Pentz, M. A., & Flay, B. R. (2001). Identifying trajectories of adolescent smoking: An application of latent growth mixture modeling. Health Psychology 20, 127135.Google Scholar
Collins, L. M., & Sayer, A. G. (2001). New methods for the analysis of change. Washington, DC: American Psychological Association.
Elliott, D. S., Huizinga, D., & Menard, S. (1989). Multiple problem youth: Delinquency, substance use, and mental health problems. New York: Springer–Verlag.
Flory, K., Lynam, D., Milich, R., Leukefeld, C., & Clayton, R. (2004). Early adolescent through young adulthood alcohol and marijuana use trajectories: Early predictors, young adult outcomes, and predictive utility. Development and Psychopathology 16, 193213.Google Scholar
Forman, B. D., Eidson, K., & Hagan, B. J. (1983). Measuring perceived stress in adolescents: A cross validation. Adolescence 18, 573576.Google Scholar
Glantz, M. D., & Pickens, R. W. (Eds.). (1992). Vulnerability to drug abuse: Introduction and overview. Washington, DC: American Psychological Association.
Goldstein, H. (1995). Multilevel statistical models (2nd ed.). London: Edward Arnold.
Gou, J., Chung, I. J., Hill, K. G., Hawkins, J. D., Catalano, R. F., & Abbott, R. D. (2002). Developmental relationships between adolescent substance use and risky sexual behavior in young adulthood. Journal of Adolescent Health 31, 354362.Google Scholar
Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin 112, 64105.Google Scholar
Hinde, R. A., & Dennis, A. (1986). Categorizing individuals: An alternative to linear analysis. International Journal of Behavioral Development 9, 105119.Google Scholar
Holmes, T. H., & Rahe, R. H. (1967). The social readjustment rating scale. Journal of Psychosomatic Research 11, 213218.Google Scholar
Johnston, L. D., O'Malley, P. M., & Bachman, J. G. (2002). The Monitoring the Future national results on adolescent drug use: Overview of key findings, 2001 (NIH Publication No. 02-5105). Washington, DC: US Government Printing Office.
Jones, B. L., Nagin, D. S., & Roeder, K. (2001). A SAS procedure based on mixture models of estimating developmental trajectories. Sociological Methods & Research 29, 374393.Google Scholar
Kandel, D. B. (1984). Marijuana users in young adulthood. Archives of General Psychiatry 41, 200209.Google Scholar
Kandel, D. B., & Chen, K. (2000). Types of marijuana users by longitudinal course. Journal of Studies on Alcohol 61, 367378.Google Scholar
Kass, R. E., & Raftery, A. E. (1995). Bayes factor. Journal of the American Statistical Association 90, 773795.Google Scholar
Kessler, R. C., McGonagle, K. A., Zhao, S., Nelson, C. B., Hughes, M., Eshleman, S., Wittchen, H. U., & Kendler, K. S. (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Archives of General Psychiatry 51, 819.Google Scholar
Lambert, D. (1992). Zero-inflated Poisson regressions: With an application to defects in manufacturing. Technometrics 34, 113.Google Scholar
Magnusson, D., & Bergman, L. R. (1988). Individual and variable-based approaches to longitudinal research on early risk factors. In M. Rutter (Ed.), Studies of psychosocial risks: The power of longitudinal data (pp. 4561). New York: Cambridge University Press.
Magnusson, D., & Bergman, L. R. (1990). A pattern approach to the study of pathways from childhood to adulthood. In L. Robins & M. Rutter (Eds.), Straight and devious pathways from childhood to adulthood (pp. 101115). New York: Cambridge University Press.
McArdle, J. J., & Epstein, D. (1987). Latent growth curves within developmental structural equation models. Child Development 58, 110133.Google Scholar
Moffitt, T. E. (1993). Adolescence-limited and life-course persistent antisocial behavior: A developmental taxonomy. Psychological Review 100, 674701.Google Scholar
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, 882891.Google Scholar
Muthén, L. K., & Muthén, B. O. (2001). Mplus users guide (2nd ed.). Los Angeles: Author.
Nagin, D. S. (1999). Analyzing developmental trajectories: A semi-parametric, group-based approach. Psychological Methods 4, 139157.Google Scholar
Nagin, D. S., & Tremblay, R. E. (1999). Trajectories of boy's physical aggression, opposition, and hyperactivity on the path to physically violent and nonviolent juvenile delinquency. Child Development 70, 11811196.Google Scholar
Newcomb, M. D., & Bentler, P. M. (1988). Consequences of adolescent drug use: Impact on the lives of young adults. Newbury Park, CA: Sage.
Newcomb, M. D., & Bentler, P. M. (1989). Substance use and abuse among children and adolescents. American Psychologist 2, 242248.Google Scholar
NIDA Research Report Series. (2002). Marijuana abuse (NIH Publication Number 02-3859). Rockville, MD: NIDA.
Oetting, E. R., & Beauvais, F. (1990). Adolescent drug rise: Findings of national and local surveys. Journal of Consulting and Clinical Psychology 58, 385394.Google Scholar
Office of Applied Studies. (2002). Emergency department trends from the Drug Abuse Warning Network, final estimates 1999–2001 (DAWN Series D-21, DHHS Pub. No. SMA 02-3635). Rockville, MD: SAMSHA.
Olson, D., Portner, J., & Lavee, G. (1985). FACES-III. St. Paul, MN: University of Minnesota, Family Social Science Department.
Petraitis, J., Flay, B. R., & Miller, T. Q. (1995). Reviewing theories of adolescent substance use: Organizing pieces in the puzzle. Psychological Bulletin 117, 6786.Google Scholar
Procidano, M. E., & Heller, K. (1983). Measures of perceived social support from friends and family: Three validational studies. American Journal of Community Psychology 11, 124.Google Scholar
Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement 1, 385401.Google Scholar
Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology 25, 111164.Google Scholar
Reifman, A., & Windle, M. (1995). Adolescent suicidal behaviors as a function of depression, hopelessness, alcohol use, and social support: A longitudinal investigation. American Journal of Community Psychology 23, 329354.Google Scholar
Roberts, R. E., Andrews, J. A., Lewinsohn, P. M., & Hops, H. (1990). Assessment of depression in adolescents using the Center for Epidemiologic Studies Depression Scale. Psychological Assessment 2, 122128.Google Scholar
Roeder, K., Lynch, K. G., & Nagin, D. S. (1999). Modeling uncertainty in latent class membership: A case study in criminology. Journal of the American Statistical Association 94, 766776.Google Scholar
Schulenberg, J., & Maggs, J. (2002). A developmental perspective on alcohol use and heavy drinking during the transition to adulthood. Journal of Studies on Alcohol Supplement 14, 5470.Google Scholar
Schulenberg, J., Wadsworth, K. N., O'Malley, P. M., Bachman, J. G., & Johnston, L.D. (1996). Adolescent risk factors for binge drinking during the transition to young adulthood: Variable- and pattern-centered approaches to change. Developmental Psychology 32, 659674.Google Scholar
Sussman, S., Stacy, A. W., Dent, C. W., Simon, T. R., & Johnson, C. A. (1996). Marijuana use: Current issues and new research directions. Journal of Drug Issues 26, 695733.Google Scholar
Tashkin, D. P. (1990). Pulmonary complications of smoked substance abuse. Western Journal of Medicine 152, 525530.Google Scholar
von Sydow, K., Lieb, R., Pfister, H., Hofler, M., & Wittchen, H. U. (2002). What predicts incident use of cannabis and progression to abuse and dependence? A four year prospective examination of risk factors in a community sample of adolescents and young adults. Drug and Alcohol Dependence 68, 4964.Google Scholar
Willett, J. B., & Sayer, A. G. (1994). Using covariance structure analysis to detect correlates and predictors of individual change over time. Psychological Bulletin 116, 363381.Google Scholar
Windle, M. (1987). Stressful life events, general mental health, and temperament among late adolescent females. Journal of Adolescent Research 2, 1331.Google Scholar
Windle, M. (1996). An alcohol involvement typology for adolescents: Convergent validity and longitudinal stability. Journal of Studies on Alcohol 57, 627637.Google Scholar
Windle, M., & Davies, P. (1999). Developmental theory and research. In K. E. Leonard & H. T. Blane (Eds.), Psychological theories of drinking and alcoholism (2nd ed., pp. 164202). New York: Guilford Press.
Windle, M., & Miller–Tutzauer, C. (1992). Confirmatory factor analyses and concurrent validity of the Perceived Social Support–Family Measure among adolescents. Journal of Marriage and the Family 54, 777789.Google Scholar
Windle, R. C., & Windle, M. (1995). Longitudinal patterns of physical aggression: Associations with adult social, psychiatric, and personality functioning and testosterone levels. Development and Psychopathology 7, 563585.Google Scholar
Winters, K. C., Stinchfield, R. D., Henly, G. A., & Schwartz, R. H. (1991). Validity of adolescent self-reports of alcohol and other drug involvement. The International Journal of the Addictions 25, 13791395.Google Scholar
World Health Organization. (1997). Composite International Diagnostic Interview, version 2.0. Geneva: Author.
Yeaworth, R. C., York, J., Hussey, M. A., Ingle, M. E., & Goodwin, T. (1980). The development of an Adolescent Life Change Event Scale. Adolescence 15, 9197.Google Scholar
Zucker, R. A., Fitzgerald, H. E., & Moses, H. D. (1995). Emergence of alcohol problems and the several alcoholisms: A developmental perspective on etiologic theory and life course trajectory. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 2. Risk, disorder and adaptation (pp. 677711). New York: Wiley.