Comparing adult cannabis treatment-seekers enrolled in a clinical trial with national samples of cannabis users in the United States.
BACKGROUND:
Cannabis use rates are increasing among adults in the United States (US) while the perception of harm is declining. This may result in an increased prevalence of cannabis use disorder and the need for more clinical trials to evaluate efficacious treatment strategies. Clinical trials are the gold standard for evaluating treatment, yet study samples are rarely representative of the target population. This finding has not yet been established for cannabis treatment trials. This study compared demographic and cannabis use characteristics of a cannabis cessation clinical trial sample (run through National Drug Abuse Treatment Clinical Trials Network) with three nationally representative datasets from the US; 1) National Survey on Drug Use and Health, 2) National Epidemiologic Survey on Alcohol and Related Conditions-III, and 3) Treatment: Episodes Data Set – Admissions.
METHODS:
Comparisons were made between the clinical trial sample and appropriate cannabis using sub-samples from the national datasets, and propensity scores were calculated to determine the degree of similarity between samples.
RESULTS:
showed that the clinical trial sample was significantly different from all three national datasets, with the clinical trial sample having greater representation among older adults, African Americans, Hispanic/Latinos, adults with more education, non-tobacco users, and daily and almost daily cannabis users.
CONCLUSIONS:
These results are consistent with previous studies of other substance use disorder populations and extend sample representation issues to a cannabis use disorder population. This illustrates the need to ensure representative samples within cannabis treatment clinical trials to improve the generalizability of promising findings.
PMID:28511033 DOI:10.1016/j.drugalcdep.2017.02.024
Source: Pubmed
McClure EA1, King JS2, Wahle A2, Matthews AG2, Sonne SC3, Lofwall MR4, McRae-Clark AL3, Ghitza UE5, Martinez M6, Cloud K7, Virk HS6, Gray KM3.