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Natural course of cannabis use disorders

Published online by Cambridge University Press:  12 May 2014

R. F. Farmer ,
D. B. Kosty ,
J. R. Seeley ,
S. C. Duncan ,
M. T. Lynskey ,
P. Rohde ,
D. N. Klein  and
P. M. Lewinsohn
R. F. Farmer*
Affiliation:
Oregon Research Institute, Eugene, OR 97403, USA
D. B. Kosty
Affiliation:
Oregon Research Institute, Eugene, OR 97403, USA
J. R. Seeley
Affiliation:
Oregon Research Institute, Eugene, OR 97403, USA
S. C. Duncan
Affiliation:
Oregon Research Institute, Eugene, OR 97403, USA
M. T. Lynskey
Affiliation:
Addictions Department, Institute of Psychiatry, King's College London, London, UK
P. Rohde
Affiliation:
Oregon Research Institute, Eugene, OR 97403, USA
D. N. Klein
Affiliation:
Department of Psychology, Stony Brook University, Stony Brook, NY, USA
P. M. Lewinsohn
Affiliation:
Oregon Research Institute, Eugene, OR 97403, USA
*
* Address for correspondence: R. F. Farmer, Oregon Research Institute, 1776 Millrace Drive, Eugene, OR 97403, USA. (Email: [email protected])
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Abstract

Background

Despite its importance as a public health concern, relatively little is known about the natural course of cannabis use disorders (CUDs). The primary objective of this research was to provide descriptive data on the onset, recovery and recurrence functions of CUDs during the high-risk periods of adolescence, emerging adulthood and young adulthood based on data from a large prospective community sample.

Method

Probands (n = 816) from the Oregon Adolescent Depression Project (OADP) participated in four diagnostic assessments (T1–T4) between the ages of 16 and 30 years, during which current and past CUDs were assessed.

Results

The weighted lifetime prevalence of CUDs was 19.1% with an average onset age of 18.6 years. Although gender was not significantly related to the age of initial CUD onset, men were more likely to be diagnosed with a lifetime CUD. Of those diagnosed with a CUD episode, 81.8% eventually achieved recovery during the study period. Women achieved recovery significantly more quickly than men. The recurrence rate (27.7%) was relatively modest, and most likely to occur within the first 36 months following the offset of the first CUD episode. CUD recurrence was uncommon after 72 months of remission and recovery.

Conclusions

CUDs are relatively common, affecting about one out of five persons in the OADP sample prior to the age of 30 years. Eventual recovery from index CUD episodes is the norm, although about 30% of those with a CUD exhibit a generally persistent pattern of problematic use extending 7 years or longer.

Keywords

Cannabis use disordersgender differencesmarijuananatural courseonsetrecoveryrecurrence
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 1 , January 2015 , pp. 63 - 72
Copyright
Copyright © Cambridge University Press 2014 

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References

Agrawal, A, Lynskey, MT (2006). The genetic epidemiology of cannabis use, abuse and dependence. Addiction 101, 801–812.Google Scholar
APA (1987). Diagnostic and Statistical Manual of Mental Disorders, 3rd edn, revised. American Psychiatric Association: Washington, DC.Google Scholar
APA (1994). Diagnostic and Statistical Manual of Mental Disorders, 4th edn. American Psychiatric Association: Washington, DC.Google Scholar
APA (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th edn. American Psychiatric Association: Washington, DC.Google Scholar
Arnett, JJ (2007). Emerging adulthood: what is it, and what is it good for? Child Development Perspectives 1, 68–73.Google Scholar
Beseler, CL, Hasin, DS (2010). Cannabis dimensionality: dependence, abuse and consumption. Addictive Behaviors 35, 961–969.CrossRefGoogle ScholarPubMed
Blanco, C, Harford, TC, Nunes, E, Grant, B, Hasin, D (2007). The latent structure of marijuana and cocaine use disorders: results from the National Longitudinal Alcohol Epidemiologic Survey (NLAES). Drug and Alcohol Dependence 91, 91–96.CrossRefGoogle ScholarPubMed
Boden, JM, Fergusson, DM, Horwood, LJ (2006). Illicit drug use and dependence in a New Zealand birth cohort. Australian and New Zealand Journal of Psychiatry 40, 156–163.Google Scholar
Brook, JS, Kessler, RC, Cohen, P (1999). The onset of marijuana use from preadolescence and early adolescence to young adulthood. Development and Psychopathology 11, 901–914.CrossRefGoogle ScholarPubMed
Brook, JS, Lee, JY, Finch, SJ, Koppel, J, Brook, DW (2011 a). Psychosocial factors related to cannabis use disorders. Substance Abuse 32, 242–251.Google Scholar
Brook, JS, Zhang, C, Brook, DW (2011 b). Antisocial behavior at age 37: developmental trajectories of marijuana use extending from adolescence to adulthood. American Journal on Addictions 20, 509–515.Google Scholar
Calabria, B, Degenhardt, L, Briegleb, C, Vos, T, Hall, W, Lynskey, M, Callaghan, B, Rana, U, McLaren, J (2010). Systematic review of prospective studies investigating “remission” from amphetamine, cannabis, cocaine or opioid dependence. Addictive Behaviors 35, 741–749.Google Scholar
Chambers, WJ, Puig-Antich, J, Hirsch, M, Paez, P, Ambrosini, PJ, Tabrizi, MA, Davies, M (1985). The assessment of affective disorders in children and adolescents by semistructured interview: test–retest reliability of the Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present Episode version. Archives of General Psychiatry 42, 696–702.Google Scholar
Chen, CY, O'Brien, MS, Anthony, JC (2005). Who becomes cannabis dependent soon after onset of use? Epidemiological evidence from the United States: 2000–2001. Drug and Alcohol Dependence 79, 11–22.Google Scholar
Chen, K, Kandel, DB (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
Chung, T, Maisto, SA (2006). Relapse to alcohol and other drug use in treated adolescents: review and reconsideration of relapse as a change point in clinical course. Clinical Psychology Review 26, 149–161.Google Scholar
Clark, DB (2004). The natural history of adolescent alcohol use. Addiction 99 (Suppl. 2), 5–22.Google Scholar
Coffey, C, Carlin, JB, Lynskey, MT, Li, N, Patton, GC (2003). Adolescent precursors of cannabis dependence: findings from the Victorian Adolescent Health Cohort Study. British Journal of Psychiatry 182, 330–336.Google Scholar
Cohen, P, Cohen, J, Kasen, S, Velez, CN, Hartmark, C, Johnson, J, Rojas, M, Brook, J, Streuning, EL (1993). An epidemiological study of disorders in late childhood and adolescence: age- and gender-specific prevalence. Journal of Child Psychology and Psychiatry 34, 851–867.Google Scholar
Copeland, J, Swift, W (2009). Cannabis use disorder: epidemiology and management. International Review of Psychiatry 21, 96–103.Google Scholar
Farmer, RF, Kosty, DB, Seeley, JR, Olino, TM, Lewinsohn, PM (2013). Aggregation of lifetime Axis I psychiatric disorders through age 30: incidence, predictors, and associated psychosocial outcomes. Journal of Abnormal Psychology 122, 573–586.Google Scholar
Farmer, RF, Seeley, JR, Kosty, DB, Lewinsohn, PM (2009). Refinements in the hierarchical structure of externalizing psychiatric disorders: patterns of lifetime liability from mid-adolescence through early adulthood. Journal of Abnormal Psychology 118, 699–710.CrossRefGoogle ScholarPubMed
First, MB, Spitzer, RL, Gibbon, M, Williams, JBW (1994). Structured Clinical Interview for Axis I DSM-IV Disorders – Non-Patient Edition. Biometrics Research Department: New York.Google Scholar
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
Frank, E, Prien, RF, Jarrett, RB, Keller, MB, Kupfer, DJ, Lavori, PW, Rush, AJ, Weissman, MM (1991). Conceptualization and rationale for consensus definitions of terms in major depressive disorder: remission, recovery, relapse, and recurrence. Archives of General Psychiatry 48, 851–855.CrossRefGoogle ScholarPubMed
Gillespie, NA, Neale, MC, Kendler, KS (2009). Pathways to cannabis abuse: a multi-stage model from cannabis availability, cannabis initiation and progression to abuse. Addiction 104, 430–438.CrossRefGoogle ScholarPubMed
Griffith-Lendering, MF, Wigman, JT, Prince van Leeuwen, A, Huijbregts, SC, Huizink, AC, Ormel, J, Verhulst, FC, van Os, J, Swaab, H, Vollebergh, WAM (2012). Cannabis use and vulnerability for psychosis in early adolescence – a TRAILS study. Addiction 108, 733–740.Google Scholar
Hartman, CA, Gelhorn, H, Crowley, TJ, Sakai, JT, Stallings, M, Young, SE, Rhee, SH, Corley, R, Hewitt, JK, Hopfer, CJ (2008). An item response theory analysis of DSM-IV cannabis abuse and dependence criteria in adolescents. Journal of the American Academy of Child and Adolescent Psychiatry 47, 165–173.Google Scholar
Hicks, BM, Blonigen, DM, Kramer, MD, Krueger, RF, Patrick, CJ, Iacono, WG, McGue, M (2007). Gender differences and developmental change in externalizing disorders from late adolescence to early adulthood: a longitudinal twin study. Journal of Abnormal Psychology 116, 433–447.Google Scholar
Hicks, BM, Krueger, RF, Iacono, WG, McGue, M, Patrick, CJ (2004). The family transmission and heritability of externalizing disorders: a twin-family study. Archives of General Psychiatry 61, 922–928.CrossRefGoogle ScholarPubMed
Johnston, LD, O'Malley, PM, Bachman, JG, Schulenberg, JE (2013). Monitoring the Future National Survey Results on Drug Use, 1975–2012: Volume I, Secondary School Students. Institute for Social Research, University of Michigan: Ann Arbor.Google Scholar
Kandel, DB, Chen, K (2000). Types of marijuana users by longitudinal course. Journal of Studies in Alcohol 61, 367–378.Google Scholar
Keller, MB, Lavori, PW, Friedman, B, Nielsen, E, Endicott, J, McDonald-Scott, PA (1987). The Longitudinal Interval Follow-Up Evaluation: a comprehensive method for assessing outcome in prospective longitudinal studies. Archives of General Psychiatry 44, 540–548.CrossRefGoogle ScholarPubMed
Kessler, RC, Berglund, P, Demler, O, Jin, R, Merikangas, KR, Walters, EE (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 593–602.CrossRefGoogle ScholarPubMed
Krueger, RF, Markon, KE (2006). Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annual Review of Clinical Psychology 2, 111–133.Google Scholar
Langenbucher, JW, Labouvie, E, Martin, CS, Sanjuan, PM, Bavly, L, Kirisci, L, Chung, T (2004). An application of item response theory analysis to alcohol, cannabis, and cocaine criteria in DSM-IV. Journal of Abnormal Psychology 113, 72–80.Google Scholar
Lewinsohn, PM, Hops, H, Roberts, RE, Seeley, JR, Andrews, JA (1993). Adolescent psychopathology: I. Prevalence and incidence of depression and other DSM-III-R disorders in high school students. Journal of Abnormal Psychology 102, 133–144.Google Scholar
Lynskey, MT, Grant, JD, Nelson, EC, Bucholz, KK, Madden, PAF, Statham, DJ, Martin, NG, Heath, AC (2006). Duration of cannabis use – a novel phenotype? Addictive Behaviors 31, 984–994.Google Scholar
Moffitt, TE, Caspi, A, Kokaua, J, Milne, BJ, Polanczyk, G, Poulton, R (2010). How common are common mental disorders? Evidence that lifetime prevalence rates are doubled by prospective versus retrospective ascertainment. Psychological Medicine 40, 899–909.CrossRefGoogle ScholarPubMed
Newcomb, MD, Galaif, ER, Locke, TF (2001). Substance use diagnosis within a community sample of adults: distinction, comorbidity, and progression over time. Professional Psychology: Research and Practice 32, 239–247.Google Scholar
Orvaschel, H, Puig-Antich, J, Chambers, WJ, Tabrizi, MA, Johnson, R (1982). Retrospective assessment of prepubertal major depression with the Kiddie-SADS-E. Journal of the American Academy of Child Psychiatry 21, 392–397.Google Scholar
Perkonigg, A, Goodwin, RD, Fiedler, A, Behrendt, S, Beesdo, K, Lieb, R, Wittchen, H-U (2008). The natural course of cannabis use, abuse, and dependence during the first decades of life. Addiction 103, 439–449.CrossRefGoogle ScholarPubMed
Poulton, R, Moffitt, TE, Harrington, H, Milne, BJ, Caspi, A (2001). Persistence and perceived consequences of cannabis use and dependence among young adults: implications for policy. New Zealand Medical Journal 114, 544–547.Google Scholar
Rohde, P, Andrews, J (2006). Substance use disorders. In Child and Adolescent Psychopathology: Theoretical and Clinical Implications (ed. Essau, C. A.), pp. 184–220. Routledge: New York.Google Scholar
Roxburgh, A, Hall, WD, Degenhardt, L, McLaren, J, Black, E, Copeland, J, Mattick, RP (2010). The epidemiology of cannabis use and cannabis-related harm in Australia 1993–2007. Addiction 105, 1071–1079.Google Scholar
Rush, AJ, Kraemer, HC, Sackeim, HA, Fava, M, Trivedi, MH, Frank, E, Ninan, PT, Thase, ME, Gelenberg, AJ, Kupfer, DJ, Regier, DA, Rosenbaum, JF, Ray, O, Schatzberg, AF (2006). Report by the ACNP Task Force on response and remission in major depressive disorder. Neuropsychopharmacology 31, 1841–1853.Google Scholar
Singer, JD, Willett, JB (1991). Modeling the days of our lives: using survival analysis when designing and analyzing longitudinal studies of duration and the timing of events. Psychological Bulletin 110, 268–290.Google Scholar
Sobell, LC, Ellingstad, TP, Sobell, MB (2000). Natural recovery from alcohol and drug problems: methodological review of the research with suggestions for future directions. Addiction 95, 749–764.Google Scholar
Substance Abuse and Mental Health Services Administration (2012). Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings (NSDUH Series H-44; HHS Publication No. (SMA) 12-4713). Substance Abuse and Mental Health Services Administration: Rockville, MD.Google Scholar
ter Bogt, T, Schmid, H, Gabhainn, SN, Fotiou, A, Vollebergh, W (2006). Economic and cultural correlates of cannabis use among mid-adolescents in 31 countries. Addiction 101, 241–251.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
Wittchen, HU, Behrendt, S, Höfler, M, Perkonigg, A, Rehm, J, Lieb, R, Beesdo, K (2009). A typology of cannabis-related problems among individuals with repeated illegal drug use in the first three decades of life: evidence for heterogeneity and different treatment needs. Drug and Alcohol Dependence 102, 151–157.Google Scholar
Wittchen, HU, Fröhlich, C, Behrendt, S, Günther, A, Lieb, R, Perkonigg, A, Rehm, J, Zimmermann, P (2007). Cannabis use and cannabis use disorders and their relationship to mental disorders: a 10-year prospective-longitudinal study in adolescents. Drug and Alcohol Dependence 88, 60–70.Google Scholar
Young, SE, Stallings, MC, Corley, RP, Krauter, KS, Hewitt, JK (2000). Genetic and environmental influences on behavioral disinhibition. American Journal of Medical Genetics: Neuropsychiatric Genetics 96, 684–695.Google Scholar
Zucker, RA, Donovan, JE, Masten, AS, Mattson, ME, Moss, HB (2008). Early developmental processes and the continuity of risk for underage drinking and problem drinking. Pediatrics 121, S252–S272.Google Scholar