TY - JOUR
T1 - The Cannabis Withdrawal Scale development
T2 - Patterns and predictors of cannabis withdrawal and distress
AU - Allsop, David J.
AU - Norberg, Melissa M.
AU - Copeland, Jan
AU - Fu, Shanlin
AU - Budney, Alan J.
PY - 2011/12/1
Y1 - 2011/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=80054982125&partnerID=8YFLogxK
U2 - 10.1016/j.drugalcdep.2011.06.003
DO - 10.1016/j.drugalcdep.2011.06.003
M3 - Article
C2 - 21724338
AN - SCOPUS:80054982125
VL - 119
SP - 123
EP - 129
JO - Drug and Alcohol Dependence
JF - Drug and Alcohol Dependence
SN - 0376-8716
IS - 1-2
ER -