Academic journal article
By Golub, Andrew; Liberty, Hilary James; Johnson, Bruce D.
Journal of Drug Issues , Vol. 35, No. 4
This study provides a comprehensive multivariate analysis of drug use disclosure among arrestees interviewed between 2000 and 2001 at 37 sites across the U.S. served by the Arrestee Drug Abuse Monitoring (ADAM) Program. Rates varied widely by drug and across sites. The marijuana disclosure rate varied from 68% in Fort Lauderdale to 93% in Spokane. The cocaine/crack disclosure rate varied from 28% in Chicago to 70% in Kansas City. Moreover, covariates of disclosure differed across drugs. This wide variation in disclosure suggests extreme caution be used when comparing self-reports of prevalence across drugs, locations, and individual characteristics - certainly at least for arrestees.
An extensive literature continually examines the prevalence of illicit drug use and its variation over time and across different subpopulations. Much of this literature depends on self-reports of use. However, self-reports of drug use reflect both the underlying prevalence of use and respondents' accurate reporting of that use. The prevalence of self-reported use underestimates prevalence to the extent that respondents do not report their use. Furthermore, comparisons of the use of different drugs (e.g., marijuana and heroin) or the use by different subpopulations (e.g., males and females) will be biased to the extent that some respondents are more willing to disclose use. Hence, there has been continual research into the extent of drug use disclosure and its covariates (for reviews, see Harrison, 1997, and Magura & Kang, 1996). Much of this validity literature has examined drug use among high-risk populations including persons in drug treatment and in the criminal justice system. Administrators and analysts associated with these and related agencies hold great interest in drug use within these populations.
This study set out to systematically document the variation in disclosure of drug use among American arrestees over time and across drugs, locations, and respondent characteristics. The analysis was made possible by the extensive data collected by the Arrestee Drug Abuse Monitoring Program (ADAM, formerly the Drug Use Forecasting or DUF Program). Starting in 1987, the program obtained urine samples and self-reports of drug use from arrestees at numerous sites across the United States. Since January 29, 2004, the ADAM program has been on hiatus as a Federal cost-saving measure (National Institute of Justice [NIJ], 2004). The combined 1987-2001 public-release dataset contains data from over 400,000 arrestees, and typically more than half the respondents each year are detected as recent users of at least one illicit drug. Hence, the ADAM data provides much opportunity to analyze disclosure and its covariates among the illicit drug users that come to the attention of the criminal justice system. As an exploratory analysis, the project ran several logistic regressions to identify covariates of disclosure using the complete 1987-2001 ADAM dataset. These analyses are not reported here due to substantial methodological and interpretive difficulties associated with the results. However, that analysis provided an initial indication that interview year and site were two of the strongest covariates of disclosure.
This paper focuses on the massive variation in drug use disclosure across sites. It also examines variation across drugs and demographic characteristics. We prepared a separate paper on the impact of nondisclosure on drug use trends (Golub, Liberty & Johnson, 2005). Local policy makers primarily concern themselves with drug use and its associated problems in their jurisdictions. Hence, they tend to be interested in local data. The massive variation across locations reported in this paper suggests that they may be poorly served by national estimates for drug use disclosure. Moreover, the value of nationwide prevalence estimates based on self-report data may be questionable given the extent of nondisclosure and its geographic variation. …