Drug and Alcohol Dependence 2018;182:1-7. [doi: 10.1016/j.drugalcdep.2017.09.035]
Rachel L. Tomko, PhD, Nathaniel L. Baker, MS, Erin A. McClure, PhD, Susan C. Sonne, PharmD, Aimee L. McRae-Clark, PharmD, Brian J. Sherman, PhD, Kevin M. Gray, MD (all from Medical University of South Carolina, SC Node).
Quantifying cannabis use is complex due to a lack of a standardized packaging system that contains specified amounts of constituents. A laboratory procedure has been developed for estimating physical quantity of cannabis use by utilizing a surrogate substance to represent cannabis, and weighing the amount of the surrogate to determine typical use in grams. This secondary analysis used data from a multi-site, randomized, controlled pharmacological trial for adult cannabis use disorder (N=300), sponsored by the National Drug Abuse Treatment Clinical Trials Network (protocol CTN-0053), to test the incremental validity of this procedure. In conjunction with the Timeline Followback, this physical scale-based procedure was used to determine whether average grams per cannabis administration predicted urine cannabinoid levels (11-nor-9-carboxy-delta-9-tetrahydrocannabinol) and problems due to use, after accounting for self-reported number of days use (in the past 30 days) and number of administrations per day in a 12-week clinical trial for cannabis use disorder.
Likelihood ratio tests suggest that model fit was significantly improved when grams per administration and relevant interactions were included in the model predicting urine cannabinoid level and in the model predicting problems due to cannabis use, relative to a model that contained only simpler measures of quantity and frequency.
Conclusions: This study provides support for the use of a scale-based method for quantifying cannabis use in grams. This methodology may be useful when precise quantification is necessary, for example, for researchers to begin to establish meaningful cut-offs for high-risk cannabis use. Researchers may use grams per episode to determine clinical cut-offs for high-risk episodic use in terms of "standard joints," similar to cut-offs developed in the alcohol literature. Precise quantification of cannabis use also offers some advantages over urine cannabinoid biomarker data, as it can be adapted for remote data collection and is better suited to detect variability in use patterns. (Article (Peer-Reviewed), PDF, English, 2017)
Keywords: CTN platform/ancillary study | Data collection | Timeline Follow-Back (TLFB) | Marijuana | Drug and Alcohol Dependence (journal)
Document No: 1295.
Submitted by CTN Dissemination Librarians, 1/5/2017.