Measuring cannabis consumption: Psychometric properties of the Daily Sessions, Frequency, Age of Onset, and Quantity of Cannabis Use Inventory (DFAQ-CU)

Abstract

ObjectiveWe created the Daily Sessions, Frequency, Age of Onset, and Quantity of Cannabis Use Inventory (DFAQ-CU) because the current lack of psychometrically sound inventories for measuring these dimensions of cannabis use has impeded research on the effects of cannabis in humans.MethodA sample of 2,062 cannabis users completed the DFAQ-CU and was used to assess the DFAQ-CU’s factor structure and reliability. To assess validity, a subsample of 645 participants completed additional measures of cannabis dependence and problems (Marijuana Smoking History Questionnaire [MSHQ], Timeline Followback [TLFB], Cannabis Abuse Screening Test [CAST], Cannabis Use Disorders Identification Test Revised [CUDIT-R], Cannabis Use Problems Identification Test [CUPIT], and Alcohol Use Disorder Identification Test [AUDIT]).ResultsA six-factor structure was revealed, with factors measuring: daily sessions, frequency, age of onset, marijuana quantity, cannabis concentrate quantity, and edibles quantity. The factors were reliable, with Cronbach’s alpha coefficients ranging from .69 (daily sessions) to .95 (frequency). Results further provided evidence for the factors’ convergent (MSHQ, TLFB), predictive (CAST, CUDIT-R, CUPIT), and discriminant validity (AUDIT).ConclusionsThe DFAQ-CU is the first psychometrically sound inventory for measuring frequency, age of onset, and quantity of cannabis use. It contains pictures of marijuana to facilitate the measurement of quantity of marijuana used, as well as questions to assess the use of different forms of cannabis (e.g., concentrates, edibles), methods of administering cannabis (e.g., joints, hand pipes, vaporizers), and typical THC levels. As such, the DFAQ-CU should help facilitate research on frequency, quantity, and age of onset of cannabis use.

The Relationship Between Social Anxiety and Alcohol and Marijuana Use Outcomes Among Concurrent Users: A Motivational Model of Substance Use

“…Despite using a validated measure of marijuana use quantity, the MUG focused on amount of grams participants’ used without querying the various forms of marijuana (e.g., leaf, concentrates, and edibles). Future researchers should query about marijuana use more comprehensively to obtain quantity estimates for the varying forms of marijuana (Cuttler and Spradlin, ). Relatedly, despite the psychometric support for the substance use motive measures (Chabrol et al., ; Grant et al., ), the coping subscales across these measures contained different item content, preventing us from examining whether these motives differ between alcohol and marijuana use.…”

Cannabis Use and Cognition in Adults Prescribed Opioids for Persistent Pain

“…Studies have found that self-report of cannabis use is generally more accurate than other substances such as alcohol or methamphetamines (Arfer et al, 2018), and in the state where this study occurred, recreational cannabis is legal and well labeled in shops. Yet, at the time of this study, no well-validated and reliable instruments were available to measure cannabis consumption; therefore we modeled our items from those that were used by other cannabis researchers (Cuttler & Spradlin, 2017). Because our regression models examining frequency of cannabis alone were nonsignificant, it is possible that important differences exist depending on the type of cannabis products used.…”

Patterns and perceptions of cannabis use with physical activity

“…Using skip logic, questions were further divided into three categories based on participant self-reported primary form of cannabis use, including flower or bud, concentrates (i.e., oils, wax, shatter, dabs), and edibles. In assessing the quantity of the flower or bud, a visual aid and terminology were adapted from the Daily Sessions, Frequency, Age of Onset, and Quantity of Cannabis Use Inventory (DFAQ-CU) (18).…”