The most commonly used quantification method is a calendar-based tool designed to enhance recall, the Timeline Followback (TLFB). However, this method is limited by an individual’s ability to recall specifics about his/her use, as well as difficulty estimating the amount of cannabis physically used in the first place.
Reliable quantification of cannabis use is particularly difficult because of all the different product preparations (edibles, extracts, whole plant, e.g.), variations in the amount used for each preparation, potency of the final product, and the number of others sharing the use of a particular administration.
Also, unlike with alcohol and tobacco, cannabis does not come in a standardized amount.
To overcome this, a surrogate substance (oregano) has been used in concert with a traditional 30-day TLFB to estimate how much cannabis individuals used during each episode of use.
This secondary analysis of data from CTN-0053 aimed to test this procedure’s predictive ability compared to other assessments and to determine whether average grams per cannabis administration predicted urine cannabinoid levels and problems due to use, after accounting for self-reported number of days used (in the past 30 days) and number of administrations per day in the 12 week study.
Statistical testing found that a model that included estimated grams per method of administration (e.g., joint, blunt) fit the data significantly better than a model including only self-reported number of days used and number of administrations per day when predicting both outcomes (urine cannabinoid level and problems due to use).
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, in working 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.
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Funding for this Addiction Science Made Easy project is provided by the Addiction Technology Transfer Center National Office, under the cooperative agreement from the Center for Substance Abuse Treatment of SAMHSA.
Articles were written based on the following published research:
Tomko RL, et al. Incremental Validity of Estimated Cannabis Grams as a Predictor of Problems and Cannabinoid Biomarkers: Evidence from a Clinical Trial. Drug and Alcohol Dependence 2018;182:1-7