The Cannabis Withdrawal Scale development: Patterns and predictors of cannabis withdrawal and distress

Allsop, DJ; Norberg, MM; Copeland, J; Fu, S; Budney, AJ

The Cannabis Withdrawal Scale development: Patterns and predictors of cannabis withdrawal and distress

Allsop, DJ Norberg, MM Copeland, J Fu, S

Budney, AJ

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Publication Type:: Journal Article
Citation:: Drug and Alcohol Dependence, 2011, 119 (1-2), pp. 123 - 129
Issue Date:: 2011-12-01

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Field	Value	Language
dc.contributor.author	Allsop, DJ	en_US
dc.contributor.author	Norberg, MM	en_US
dc.contributor.author	Copeland, J	en_US
dc.contributor.author	Fu, S https://orcid.org/0000-0002-6238-3612	en_US
dc.contributor.author	Budney, AJ	en_US
dc.date.available	2011-06-05	en_US
dc.date.issued	2011-12-01	en_US
dc.identifier.citation	Drug and Alcohol Dependence, 2011, 119 (1-2), pp. 123 - 129	en_US
dc.identifier.issn	0376-8716	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18592
dc.description.abstract	Background: Rates of treatment seeking for cannabis are increasing, and relapse is common. Management of cannabis withdrawal is an important intervention point. No psychometrically sound measure for cannabis withdrawal exists, and as a result treatment developments cannot be optimally targeted. The aim is to develop and test the psychometrics of the Cannabis Withdrawal Scale and use it to explore predictors of cannabis withdrawal. Methods: A volunteer sample of 49 dependent cannabis users provided daily scores on the Cannabis Withdrawal Scale during a baseline week and 2 weeks of abstinence. Results: Internal reliability (Cronbach's alpha=0.91), test-retest stability (average intra-class correlation=0.95) and content validity analysis show that the Cannabis Withdrawal Scale has excellent psychometric properties. Nightmares and/or strange dreams was the most valid item (Wald χ 2=105.6, P<0.0001), but caused relatively little associated distress (Wald χ 2=25.11, P=0.03). Angry outbursts were considered intense (Wald χ 2=73.69, P<0.0001) and caused much associated distress (Wald χ 2=45.54, P<0.0001). Trouble getting to sleep was also an intense withdrawal symptom (Wald χ 2=42.31, P<0.0001) and caused significant associated distress (Wald χ 2=47.76, P<0.0001). Scores on the Severity of Dependence Scale predicted cannabis withdrawal. Conclusions: The Cannabis Withdrawal Scale can be used as a diagnostic instrument in clinical and research settings where regular monitoring of withdrawal symptoms is required. © 2011 Elsevier Ireland Ltd.	en_US
dc.relation.ispartof	Drug and Alcohol Dependence	en_US
dc.relation.isbasedon	10.1016/j.drugalcdep.2011.06.003	en_US
dc.subject.classification	Substance Abuse	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Cannabis	en_US
dc.subject.mesh	Marijuana Abuse	en_US
dc.subject.mesh	Substance Withdrawal Syndrome	en_US
dc.subject.mesh	Tetrahydrocannabinol	en_US
dc.subject.mesh	Psychotropic Drugs	en_US
dc.subject.mesh	Questionnaires	en_US
dc.subject.mesh	Reproducibility of Results	en_US
dc.subject.mesh	Psychiatric Status Rating Scales	en_US
dc.subject.mesh	Psychometrics	en_US
dc.subject.mesh	Forecasting	en_US
dc.subject.mesh	Adult	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Dronabinol	en_US
dc.subject.mesh	Surveys and Questionnaires	en_US
dc.title	The Cannabis Withdrawal Scale development: Patterns and predictors of cannabis withdrawal and distress	en_US
dc.type	Journal Article
utslib.citation.volume	1-2	en_US
utslib.citation.volume	119	en_US
utslib.for	1103 Clinical Sciences	en_US
utslib.for	1115 Pharmacology and Pharmaceutical Sciences	en_US
utslib.for	11 Medical and Health Sciences	en_US
utslib.for	17 Psychology and Cognitive Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CFS - Centre for Forensic Science
utslib.copyright.status	closed_access
pubs.issue	1-2	en_US
pubs.publication-status	Published	en_US
pubs.volume	119	en_US

Abstract:

Background: Rates of treatment seeking for cannabis are increasing, and relapse is common. Management of cannabis withdrawal is an important intervention point. No psychometrically sound measure for cannabis withdrawal exists, and as a result treatment developments cannot be optimally targeted. The aim is to develop and test the psychometrics of the Cannabis Withdrawal Scale and use it to explore predictors of cannabis withdrawal. Methods: A volunteer sample of 49 dependent cannabis users provided daily scores on the Cannabis Withdrawal Scale during a baseline week and 2 weeks of abstinence. Results: Internal reliability (Cronbach's alpha=0.91), test-retest stability (average intra-class correlation=0.95) and content validity analysis show that the Cannabis Withdrawal Scale has excellent psychometric properties. Nightmares and/or strange dreams was the most valid item (Wald χ 2=105.6, P<0.0001), but caused relatively little associated distress (Wald χ 2=25.11, P=0.03). Angry outbursts were considered intense (Wald χ 2=73.69, P<0.0001) and caused much associated distress (Wald χ 2=45.54, P<0.0001). Trouble getting to sleep was also an intense withdrawal symptom (Wald χ 2=42.31, P<0.0001) and caused significant associated distress (Wald χ 2=47.76, P<0.0001). Scores on the Severity of Dependence Scale predicted cannabis withdrawal. Conclusions: The Cannabis Withdrawal Scale can be used as a diagnostic instrument in clinical and research settings where regular monitoring of withdrawal symptoms is required. © 2011 Elsevier Ireland Ltd.

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http://hdl.handle.net/10453/18592