Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-17T19:45:06.133Z Has data issue: false hasContentIssue false
  • English
  • Français

Heterogeneity in men's marijuana use in the 20s: Adolescent antecedents and consequences in the 30s

Published online by Cambridge University Press:  14 July 2014

Isaac J. Washburn  and
Deborah M. Capaldi
Isaac J. Washburn*
Affiliation:
Oklahoma State University
Deborah M. Capaldi
Affiliation:
Oregon Social Learning Center
*
Address correspondence and reprint requests to: Isaac J. Washburn, Human Development & Family Science, Oklahoma State University, 320 Human Sciences, Stillwater, OK 74078; E-mail: isaac.washburn@okstate.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

Adolescent psychopathology is commonly connected to marijuana use. How changes in these adolescent antecedents and in adolescent marijuana use are connected to patterns of marijuana use in the 20s is little understood. Another issue not clearly understood is psychopathology in the 30s as predicted by marijuana use in the 20s. This study sought to examine these two issues and the associations with marijuana disorder diagnoses using a longitudinal data set of 205 men with essentially annual reports. Individual psychopathology and family characteristics from the men's adolescence were used to predict their patterns of marijuana use across their 20s, and aspects of the men's psychopathology in their mid-30s were predicted from these patterns. Three patterns of marijuana use in the 20s were identified using growth mixture modeling and were associated with diagnoses of marijuana disorders at age 26 years. Parental marijuana use predicted chronic use for the men in adulthood. Patterns of marijuana use in the 20s predicted antisocial behavior and deviant peer association at age 36 years (controlling for adolescent levels of the outcomes by residualization). These findings indicate that differential patterns of marijuana use in early adulthood are associated with psychopathology toward midlife.

Type
Special Section Articles
Information
Development and Psychopathology , Volume 27 , Issue 1: What Works for Whom? Genetic Moderation of Intervention Efficacy , February 2015 , pp. 279 - 291
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Achenbach, T. M. (1991). Manual for Teacher's Report Form and 1991 profile. Burlington, VT: University of Vermont, Department of Psychology.Google Scholar
Achenbach, T. M. (1993a). Young Adult Behavior Checklist. Burlington, VT: University of Vermont, Department of Psychology.Google Scholar
Achenbach, T. M. (1993b). Young Adult Self-Report. Burlington, VT: University of Vermont, Department of Psychology.Google Scholar
Achenbach, T. M., & Edelbrock, C. (1983). Manual for the Child Behavior Checklist and revised Child Behavior Profile. Burlington, VT: University of Vermont, Department of Psychiatry.Google Scholar
Asparouhouv, T., & Muthén, B. O. (2007). Wald test of mean equality for potential latent class predictors in mixture modeling. Retrieved from http://www.statmodel.com/download/MeanTest1.pdfGoogle Scholar
Bailey, J. A., Hill, K. G., Oesterle, S., & Hawkins, J. D. (2006). Linking substance use and problem behavior across three generations. Journal of Abnormal Child Psychology, 34, 263–282.CrossRefGoogle ScholarPubMed
Brook, J. S., Richter, L., Whiteman, M., & Cohen, P. (1999). Consequences of adolescent marijuana use: Incompatibility with the assumption of adult roles. Genetic, Social, and General Psychology Monographs, 115, 349–369.Google Scholar
Brook, J. S., Zhang, C., & Brook, D. W. (2011a). Antisocial behavior at age 37: Developmental trajectories of marijuana use extending from adolescence to adulthood. American Journal on Addictions, 20, 509–515.Google Scholar
Brook, J. S., Zhang, C., & Brook, D. W. (2011b). Developmental trajectories of marijuana use from adolescence to adulthood: Personal predictors. Archives of Pediatrics and Adolescent Medicine, 165, 55.Google Scholar
Capaldi, D. M., Chamberlain, P., Fetrow, R. A., & Wilson, J. E. (1997). Conducting ecologically valid prevention research: Recruiting and retaining a “whole village” in multimethod, multiagent studies. American Journal of Community Psychology, 25, 471–492.Google Scholar
Capaldi, D. M., Feingold, A., Kim, H. K., Yoerger, K., & Washburn, I. J. (2013). Heterogeneity in growth and desistance of alcohol use for men in their 20s: Prediction from early risk factors and association with treatment. Alcoholism: Clinical and Experimental Research, 37(Suppl. s1), E347–E355.CrossRefGoogle ScholarPubMed
Capaldi, D. M., King, J., & Wilson, J. (1992). Young Adult Adjustment Scale. Unpublished manuscript, Oregon Social Learning Center.Google Scholar
Capaldi, D. M., Shortt, J. W., & Kim, H. K. (2005). A life span developmental systems perspective on aggression toward a partner. In Pinsof, W. & Lebow, J. (Eds.), Family psychology: The art of the science (pp. 141–167). Oxford: Oxford University Press.Google Scholar
Capaldi, D. M., Stoolmiller, M., Kim, H. K., & Yoerger, K. (2009). Growth in alcohol use in at-risk adolescent boys: Two-part random effects prediction models. Drug and Alcohol Dependence, 105, 109–117.Google Scholar
Carroll, J. (2005). Who supports marijuana legalization? Gallup Poll Tuesday Briefing. Retrieved from http://www.gallup.com/poll/19561/who-supports-marijuana-legalization.aspxGoogle Scholar
Chen, K., & Kandel, D. B. (1995). The natural history of drug use from adolescence to the mid-thirties in a general population sample. American Journal of Public Health, 85, 41–47.Google Scholar
Coombs, R. H., Paulson, M. J., & Richardson, M. A. (1991). Peer versus parental influence in substance use among Hispanic and Anglo children and adolescents. Journal of Youth and Adolescence, 20, 73–88.CrossRefGoogle Scholar
Degenhardt, L., Hall, W., & Lynskey, M. (2003). Exploring the association between cannabis use and depression. Addiction, 98, 1493–1504.CrossRefGoogle ScholarPubMed
Dishion, T. J., & Capaldi, D. M. (1985). Peer Involvement and Social Skills Questionaire. Unpublished manuscript, Oregon Social Learning Center.Google Scholar
Dishion, T. J., Capaldi, D. M., Spracklen, K. M., & Li, F. (1995). Peer ecology of male adolescent drug use. Development and Psychopathology, 7, 803–824.Google Scholar
Dishion, T. J., Capaldi, D. M., & Yoerger, K. (1999). Middle childhood antecedents to progressions in male adolescent substance use: An ecological analysis of risk and protection. Journal of Adolescent Research, 14, 175–205.Google Scholar
Duncan, T. E., Tildesley, E., Duncan, S. C., & Hops, H. (1995). The consistency of family and peer influences on the development of substance use in adolescence. Addiction, 90, 1647–1660.Google Scholar
Ellickson, P. L., Martino, S. C., & Collins, R. L. (2004). Marijuana use from adolescence to young adulthood: Multiple developmental trajectories and their associated outcomes. Health Psychology, 23, 299–307.Google Scholar
Elliott, D. S., Ageton, S. S., Huizinga, D., Knowles, B. A., & Canter, R. J. (1983). The prevalence and incidence of delinquent behavior: 1976–1980. National estimates of delinquent behavior by sex, race, social class, and other selected variables (National Youth Survey Report No. 26). Boulder, CO: Behavioral Research Institute.Google Scholar
Fleming, C. B., Mason, W. A., Mazza, J. J., Abbott, R. D., & Catalano, R. F. (2008). Latent growth modeling of the relationship between depressive symptoms and substance use during adolescence. Psychology of Addictive Behaviors, 22, 186–197.CrossRefGoogle ScholarPubMed
Flory, K., Lynam, D., Milich, R., Leukefeld, C., & Clayton, R. (2004). Early adolescent through young adult alcohol and marijuana use trajectories: Early predictors, young adult outcomes, and predictive utility. Development and Psychopathology, 16, 193–213.Google Scholar
Griffin, K., Bang, H., & Botvin, G. (2010). Age of alcohol and marijuana use onset predicts weekly substance use and related psychosocial problems during young adulthood. Journal of Substance Use, 15, 174–183.Google Scholar
Gutman, L. M., Eccles, J. S., Peck, S., & Malanchuk, O. (2011). The influence of family relations on trajectories of cigarette and alcohol use from early to late adolescence. Journal of Adolescence, 34, 119–128.Google Scholar
Henson, J. M., Reise, S. P., & Kim, K. H. (2007). Detecting mixtures from structural model differences using latent variable mixture modeling: A comparison of relative model fit statistics. Structural Equation Modeling, 14, 202–226.CrossRefGoogle Scholar
Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2011). Marijuana use continues to rise among U.S. teens, while alcohol use hits historic lows. Retrieved from http://www.monitoringthefuture.org on August 13, 2012.Google Scholar
Kandel, D. B., Griesler, P. C., Lee, G., Davies, M., & Schaffran, C. (2001). Parental influences on adolescent marijuana use and the baby boom generation: Findings from the 1979–1996 National Household Surveys on Drug Abuse (DHHS Publication SMA 01-3531, Analytic Series: A-13). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.Google Scholar
Khantzian, E. J. (1997). The self-medication hypothesis of substance use disorders: A reconsideration and recent applications. Harvard Review of Psychiatry, 4, 231–244.Google Scholar
Kirisci, L., Mezzich, A. C., Reynolds, M., Tarter, R. E., & Aytaclar, S. (2009). Prospective study of the association between neurobehavior disinhibition and peer environment on illegal drug use in boys and girls. American Journal of Drug and Alcohol Abuse, 35, 145–150.CrossRefGoogle ScholarPubMed
Lac, A., & Crano, W. D. (2009). Monitoring matters. Perspectives on Psychological Science, 4, 578.CrossRefGoogle ScholarPubMed
Lessem, J. M., Hopfer, C. J., Haberstick, B. C., Timberlake, D., Ehringer, M. A., Smolen, A., et al. (2006). Relationship between adolescent marijuana use and young adult illicit drug use. Behavior Genetics, 36, 498–506.Google Scholar
Li, C., Pentz, M. A., & Chou, C. P. (2002). Parental substance use as a modifier of adolescent substance use risk. Addiction, 97, 1537–1550.CrossRefGoogle ScholarPubMed
Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778.CrossRefGoogle Scholar
Martins, S. S., Storr, C. L., Alexandre, P. K., & Chilcoat, H. D. (2008). Adolescent ecstasy and other drug use in the National Survey of Parents and Youth: The role of sensation-seeking, parental monitoring and peer's drug use. Addictive Behaviors, 33, 919–933.Google Scholar
Mauricio, A. M., Little, M., Chassin, L., Knight, G. P., Piquero, A. R., Losoya, S. H., et al. (2009). Juvenile offenders' alcohol and marijuana trajectories: Risk and protective factor effects in the context of time in a supervised facility. Journal of Youth and Adolescence, 38, 440–453.Google Scholar
McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley.Google Scholar
Moore, T. H. M., Zammit, S., Lingford-Hughes, A., Barnes, T. R. E., Jones, P. B., Burke, M., et al. (2007). Cannabis use and risk of psychotic or affective mental health outcomes: A systematic review. Lancet, 370, 319–328.Google Scholar
Nylund, K., Asparouhov, T., & Muthén, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569.Google Scholar
Olsen, M. K., & Schafer, J. L. (2001). A two-part random-effects model for semicontinuous longitudinal data. Journal of the American Statistical Association, 96, 730–745.Google Scholar
Oregon Social Learning Center. (1982–2012). Peers Questionnaire. Unpublished manuscipt. Retrieved from http://www.oslc.org/unpublished_oslc_instruments.pdfGoogle Scholar
Radloff, L. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.Google Scholar
Reinherz, H. Z., Giaconia, R. M., Hauf, A. M. C., Wasserman, M. S., & Paradis, A. D. (2000). General and specific childhood risk factors for depression and drug disorders by early adulthood. Journal of the American Academy of Child & Adolescent Psychiatry, 39, 223–231.CrossRefGoogle ScholarPubMed
Schulenberg, J., Merline, A., Johnston, L., O'Malley, P., Bachman, J., & Laetz, V. (2005). Trajectories of marijuana use during the transition to adulthood: The big picture based on national panel data. Journal of Drug Issues, 35, 255.Google Scholar
Smith, L. B., & Thelen, E. (2003). Development as a dynamic system. Trends in Cognitive Sciences, 7, 343–348.Google Scholar
Snyder, J. (2002). Reinforcement and coercion mechanisms in the development of antisocial behavior: Peer relationships. In Reid, J. B., Patterson, G. R., & Snyder, J. (Eds.), Antisocial behavior in children and adolescents: A developmental analysis and model for intervention (pp. 101–122). Washington, DC: American Psychological Association.Google Scholar
Staff, J., Schulenberg, J. E., Maslowsky, J., Bachman, J. G., O'Malley, P. M., Maggs, J. L., et al. (2010). Substance use changes and social role transitions: Proximal developmental effects on ongoing trajectories from late adolescence through early adulthood. Development and Psychopathology, 22, 917.Google Scholar
Tarter, R. E., Kirisci, L., Ridenour, T., & Vanyukov, M. (2008). Prediction of cannabis use disorder between childhood and young adulthood using the Child Behavior Checklist. Journal of Psychopathology and Behavioral Assessment, 30, 272–278.Google Scholar
Walker, H. M., & McConnell, S. (1988). Walker–McConnell Scale of Social Competence and School Adjustment. Austin, TX: Pro-Ed.Google Scholar
Wang, C. P., Brown, C. H., & Bandeen-Roche, K. (2005). Residual diagnostics for growth mixture models. Journal of the American Statistical Association, 100, 1054–1076.Google Scholar
Windle, M., & Wiesner, M. (2004). Trajectories of marijuana use from adolescence to young adulthood: Predictors and outcomes. Development and Psychopathology, 16, 1007–1027.Google Scholar
World Health Organization. (1997). Programme on substance abuse. Cannabis: A health perspective and research agenda. Geneva: Author.Google Scholar