The influence of age and gender on the likelihood of endorsing cannabis abuse/dependence criteria

Addictive Behaviors

Volumn 42, Issue , 2015, Pages 172-175

  Delforterie, Monique J ^a   Creemers, Hanneke E ^a   Agrawal, Arpana ^b   Lynskey, Michael T ^c   Jak, Suzanne ^d   Huizink, Anja C ^a  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c KING'S COLLEGE LONDON   (United Kingdom)

^d UTRECHT UNIVERSITY   (Netherlands)

Author keywords

Age; Cannabis abuse dependence; DSM IV; Factor analysis; Gender; Measurement bias

Indexed keywords

CANNABIS;

ADULT; AGE DISTRIBUTION; AGED; ARTICLE; CANNABIS ADDICTION; DISEASE CLASSIFICATION; DSM-IV; FACTORIAL ANALYSIS; FEMALE; HEALTH SURVEY; HUMAN; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; POPULATION RESEARCH; PREVALENCE; SEX DIFFERENCE; YOUNG ADULT; ADOLESCENT; AGE; MARIJUANA ABUSE; UNITED STATES;

ADOLESCENT; ADULT; AGE FACTORS; AGED; FEMALE; HEALTH SURVEYS; HUMANS; MALE; MARIJUANA ABUSE; MIDDLE AGED; PREVALENCE; SEX FACTORS; UNITED STATES; YOUNG ADULT;

EID: 84913580930     PISSN: 03064603     EISSN: 18736327     Source Type: Journal    
DOI: 10.1016/j.addbeh.2014.11.029     Document Type: Article

References (23)

1. Agrawal A., Lynskey M.T. Does gender contribute to heterogeneity in criteria for cannabis abuse and dependence? Results from the national epidemiological survey on alcohol and related conditions. Drug and Alcohol Dependence 2007, 88:300-307.
2. Agrawal A., Lynskey M.T., Bucholz K.K., Kapoor M., Almasy L., Dick D.M., Hancock D.B. DSM-5 cannabis use disorder: A phenotypic and genomic perspective. Drug and Alcohol Dependence 2014, 134:362-369.
3. American Psychiatric Association Diagnostic and statistical manual of mental disorders 2013, American Psychiatric Association, Arlington, VA. 5th ed.
4. Barendse M., Oort F., Werner C., Ligtvoet R., Schermelleh-Engel K. Measurement bias detection through factor analysis. Structural Equation Modeling: A Multidisciplinary Journal 2012, 19:561-579.
5. Budney A.J., Vandrey R.G., Hughes J.R., Moore B.A., Bahrenburg B. Oral delta-9-tetrahydrocannabinol suppresses cannabis withdrawal symptoms. Drug and Alcohol Dependence 2007, 86:22-29.
6. Chung T., Martin C.S., Winters K.C., Cornelius J.R., Langenbucher J.W. Limitations in the assessment of DSM-IV cannabis tolerance as an indicator of dependence in adolescents. Experimental and Clinical Psychopharmacology 2004, 12:136-146.
7. Compton W.M., Grant B.F., Colliver J.D., Glantz M.D., Stinson F.S. Prevalence of marijuana use disorders in the United States: 1991-1992 and 2001-2002. Jama 2004, 291:2114-2121.
8. Copeland J., Rooke S., Swift W. Changes in cannabis use among young people: Impact on mental health. Current Opinion in Psychiatry 2013, 26:325-329.
9. Degenhardt L., Hall W., Lynskey M. The relationship between cannabis use and other substance use in the general population. Drug and Alcohol Dependence 2001, 64:319-327.
10. Dennis M., Babor T.F., Roebuck M.C., Donaldson J. Changing the focus: The case for recognizing and treating cannabis use disorders. Addiction 2002, 97:4-15.
11. Grant B.F., Harford T.C., Dawson D.A., Chou P.S., Pickering R.P. The Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS): Reliability of alcohol and drug modules in a general population sample. Drug and Alcohol Dependence 1995, 39:37-44.
12. Grant B.F., Moore T.C., Shepard J., Kaplan K. Source and accuracy statement: Wave 1 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) 2003, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD.
13. Grant J.D., Scherrer J.F., Neuman R.J., Todorov A.A., Price R.K., Bucholz K.K. A comparison of the latent class structure of cannabis problems among adult men and women who have used cannabis repeatedly. Addiction 2006, 101:1133-1142.
14. Grucza R.A., Abbacchi A.M., Przybeck T.R., Gfroerer J.C. Discrepancies in estimates of prevalence and correlates of substance use and disorders between two national surveys. Addiction 2007, 102:623-629.
15. Hartman C.A., Gelhorn H., Crowley T.J., Sakai J.T., Stallings M., Young S.E., Hopfer C.J. Item response theory analysis of DSM-IV cannabis abuse and dependence criteria in adolescents. Journal of the American Academy of Child & Adolescent Psychiatry 2008, 47:165-173.
16. Hasin D.S., Fenton M.C., Beseler C., Park J.Y., Wall M.M. Analyses related to the development of DSM-5 criteria for substance use related disorders: 2. Proposed DSM-5 criteria for alcohol, cannabis, cocaine and heroin disorders in 663 substance abuse patients. Drug and Alcohol Dependence 2012, 122:28-37.
17. Hu L.T., Bentler P.M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal 1999, 6:1-55.
18. Jak S., Oort F.J., Dolan C.V. Measurement bias and multidimensionality; an illustration of bias detection in multidimensional measurement models. AStA Advances in Statistical Analysis 2010, 94:129-137.
19. Langenbucher J.W., Labouvie E., Martin C.S., Sanjuan P.M., Bavly L., Kirisci L., Chung T. An application of item response theory analysis to alcohol, cannabis, and cocaine criteria in DSM-IV. Journal of Abnormal Psychology 2004, 113:72-80.
20. Mewton L., Teesson M., Slade T. "Youthful epidemic" or diagnostic bias? Differential item functioning of DSM-IV cannabis use criteria in an Australian general population survey. Addictive Behaviors 2010, 35:408-413.
21. Muthén L.K., Muthén B.O. Mplus user's guide 1998-2010, Muthén & Muthén, Los Angeles, CA. 5th ed.
22. Stinson F.S., Ruan W.J., Pickering R., Grant B.F. Cannabis use disorders in the USA: Prevalence, correlates and co-morbidity. Psychological Medicine 2006, 36:1447-1460.
23. Verweij K., Agrawal A., Nat N., Creemers H., Huizink A., Martin N., Lynskey M. A genetic perspective on the proposed inclusion of cannabis withdrawal in DSM-5. Psychological Medicine 2013, 43:1713-1722.