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Arrestee Drug Abuse Monitoring (ADAM) Program in the United States, 2000

Version
v0
Resource Type
Dataset : administrative records data, clinical data, medical records, survey data
Creator
  • United States Department of Justice. Office of Justice Programs. National Institute of Justice
Other Title
  • Archival Version (Subtitle)
Collective Title
  • Arrestee Drug Abuse Monitoring (ADAM) Program/Drug Use Forecasting (DUF) Series
Publication Date
2001-12-21
Funding Reference
  • United States Department of Justice. Office of Justice Programs. National Institute of Justice
Language
English
Free Keywords
ADAM/DUF Program; alcohol abuse; arrests; crime patterns; demographic characteristics; drug dependence; drug offenders; drug related crimes; drug testing; drug treatment; drug use; drugs; substance abuse; trends
Description
  • Abstract

    Beginning in 1996, the National Institute of Justice (NIJ) initiated a major redesign of its multisite drug-monitoring program, the Drug Use Forecasting (DUF) system (DRUG USE FORECASTING IN 24 CITIES IN THE UNITED STATES, 1987-1997 [ICPSR 9477]). The program was retitled Arrestee Drug Abuse Monitoring (ADAM) (see ARRESTEE DRUG ABUSE MONITORING (ADAM) PROGRAM IN THE UNITED STATES, 1998 [ICPSR 2628] and 1999 [ICPSR 2994]). ADAM extended DUF in the number of sites and improved the quality and generalizability of the data. The redesign was fully implemented in all sites beginning in the first quarter of 2000. The ADAM program implemented a new and expanded adult instrument in the first quarter of 2000, which was used for both the male (Part 1) and female (Part 2) data. The juvenile data for 2000 (Part 3) used the juvenile instrument from previous years. The ADAM program also moved to probability-based sampling for the adult male population during 2000. Therefore, the 2000 adult male sample includes weights, generated through post-sampling stratification of the data. The shift to sampling of the adult male population in 2000 required that all 35 sites move to a common catchment area, the county. The core instrument for the adult cases was supplemented by a facesheet, which was used to collect demographic and charge information from official records. Core instruments were used to collect self-report information from the respondent. Both the adult and juvenile instruments were administered to persons arrested and booked on local or state charges relevant to the jurisdiction (i.e., not federal or out-of-county charges) within the past 48 hours. At the completion of the interview the arrestee was asked to voluntarily provide a urine specimen. An external lab used the Enzyme Multiplied Immunoassay Testing (EMIT) protocols to test for the presence of ten drugs or metabolites of the drug in the urine sample. All amphetamine positives were confirmed by gas chromatography/mass spectrometry (GC/MS) to determine whether methamphetamine was used. For the adult data, variables from the facesheet include arrest precinct, ZIP code of arrest location, ZIP code of respondent's address, respondent's gender and race, three most serious arrest charges, sample source (stock, flow, other), interview status (including reason the individual selected in the sample was not interviewed), language of instrument used, and the number of hours since arrest. Demographic information from the core instrument includes respondent's age, ethnicity, residency, education, employment, health insurance coverage, marital status, housing, and telephone access. Variables from the calendar provide information on inpatient and outpatient substance abuse treatment, inpatient mental health treatment, arrests and incarcerations, heavy alcohol use, use of marijuana, crack/rock cocaine, powder cocaine, heroin, methamphetamine, and other drug (ever and previous 12 months), age of first use of the above six drugs and heavy alcohol use, drug dependency in the previous 12 months, characteristics of drug transactions in past 30 days, use of marijuana, crack/rock cocaine, powder cocaine, heroin, and methamphetamine in past 30 days, 7 days, and 48 hours, heavy alcohol use in past 30 days, and secondary drug use of 15 other drugs in the past 48 hours. Urine test results are provided for 11 drugs -- marijuana, cocaine, opiates, phencyclidine (PCP), benzodiazepines (Valium), propoxyphene (Darvon), methadone, methaqualone, barbiturates, amphetamines, and methamphetamine. The adult data files include several derived variables. The male data also include four sampling weights, and stratum identifications and percents. For the juvenile data, demographic variables include age, race, sex, educational attainment, employment status, and living circumstances. Data also include each juvenile arrestee's self-reported use of 15 drugs (alcohol, tobacco, marijuana, powder cocaine, crack, heroin, PCP, amphetamines, barbiturates, quaaludes, methadone, crystal methamphetamine, Valium, LSD, and inhalants). For each drug type, arrestees reported whether they had ever used the drug, age of first use, whether they had used the drug in the past 30 days and past 72 hours, number of days they used the drug in past month, whether they tried to cut down or quit using the drug, if they were successful, whether they felt dependent on the drug, whether they were receiving treatment for the drug, whether they had received treatment for the drug in the past, and whether they thought they could use treatment for that drug. Additional variables include whether juvenile respondents had ever injected drugs, whether they were influenced by drugs when they allegedly committed the crime for which they were arrested, whether they had been to an emergency room for drug-related incidents, and if so, whether in the past 12 months, and information on arrests and charges in the past 12 months. As with the adult data, urine test results are also provided. Finally, variables covering precinct (precinct of arrest) and law (penal law code associated with the crime for which the juvenile was arrested) are also provided for use by local law enforcement officials at each site.
  • Abstract

    Beginning in 1996, the National Institute of Justice (NIJ) initiated a major redesign of its multisite drug-monitoring program, the Drug Use Forecasting (DUF) system (DRUG USE FORECASTING IN 24 CITIES IN THE UNITED STATES, 1987-1997 [ICPSR 9477]). The program was retitled Arrestee Drug Abuse Monitoring (ADAM) (see ARRESTEE DRUG ABUSE MONITORING (ADAM) PROGRAM IN THE UNITED STATES, 1998 [ICPSR 2628] and 1999 [ICPSR 2994]). ADAM extended DUF in the number of sites and improved the quality and generalizability of the data. The redesign was fully implemented beginning in the first quarter of 2000. The original goal remained the same -- to determine the extent of drug use in the arrestee population in a defined area at specified points each year. However, the redesigned sampling protocol and instrument extended ADAM's goals in the following ways: (1) to provide a suitable probability-based sample of jails and arrestees to support prevalence estimates of drug use and related behaviors in each county included in the ADAM program, (2) to provide accurate estimates with confidence intervals that permit tests of the significance of drug use trends, (3) to create a standardized dataset on arrestees in multiple jurisdictions to allow cross-site comparisons, (4) to expand the scope of DUF data to include other areas of concern (treatment history, dependency/abuse assessment, drug markets), (5) to provide a platform for distinguishing between arrest and drug use practices and for drawing inferences about the total population of hardcore or heavy drug users, including those not in the current ADAM sample, (6) to provide data for policy responses to substance abuse issues both locally and nationally, (7) to investigate drug markets or purchases, including data on characteristics of the market, conditions of purchase or exchange, and prices paid, (8) to assess risk of alcohol and/or drug dependency, drug and mental health treatment experiences, and (9) to use common definitions and, where possible, identical questions and response categories to allow meaningful links between ADAM and other national data systems.
  • Abstract

    The ADAM program implemented a new and expanded adult instrument in the first quarter of 2000, which was used for both the male (Part 1) and female (Part 2) data. The juvenile data for 2000 (Part 3) used the juvenile instrument from previous years. The ADAM program also moved to a probability-based sampling for the adult male population during 2000. Therefore, the 2000 adult male sample includes weights, generated through post-sampling stratification of the data. The shift to sampling of the adult male population in 2000 required that all 35 sites move to a common catchment area, the county. ADAM sites in 2000 included Albuquerque (Bernalillo County), Anchorage (Anchorage Borough), Atlanta (Fulton and DeKalb Counties), Birmingham (Jefferson County), Capital Area (Albany County, New York), Charlotte-Metro (Mecklenburg County), Chicago (Cook County), Cleveland (Cuyahoga County), Dallas (Dallas County), Denver (Denver County), Des Moines (Polk County), Detroit (Wayne County), Ft. Lauderdale (Broward County), Honolulu (Oahu County), Houston (Harris County), Indianapolis (Marion County), Laredo (Webb County), Las Vegas (Clark County), Los Angeles (Los Angeles County), Miami (Miami-Dade County), Minneapolis (Hennepin County), New Orleans (Orleans Parish), New York (Manhattan Borough), Oklahoma City (Oklahoma County), Omaha (Douglas County), Philadelphia (Philadelphia County), Phoenix (Maricopa County), Portland (Multnomah County), Sacramento (Sacramento County), Salt Lake City (Salt Lake County), San Antonio (Bexar County), San Diego (San Diego County), San Jose (Santa Clara County), Seattle (King County), Spokane (Spokane County), and Tuscon (Pima County). The core instrument for the adult cases was supplemented by a facesheet, which was used to collect demographic and charge information from official records. Core instruments were used to collect self-report information from the respondent. Both the adult and juvenile instruments were administered to persons arrested and booked on local or state charges relevant to the jurisdiction (i.e., not federal or out-of-county charges) within the past 48 hours. Trained interviewers used a paper and pencil instrument in a face-to-face setting in a secure and reasonably private area of the booking facility. The adult interview took an average of 20 minutes. The juvenile interview took an average of 5 minutes. Responses were recorded by the interviewer at the time of the interview. At the completion of the interview, the arrestee was asked to voluntarily provide a urine specimen. The adult male and female data reflect all the arrestees selected for an interview from the booking logs, including those for whom only facesheet information was collected. The final sample for each adult data file, however, is the subset of arrestees that accepted and completed an interview. An external lab used the Enzyme Multiplied Immunoassay Testing (EMIT) protocols to test for the presence of ten drugs or metabolites of the drug in the urine sample. All amphetamine positives were confirmed by gas chromatography/mass spectrometry (GC/MS) to determine whether methamphetamine was used. Local booking facilities provide a census of all adult males arrested in each facility collecting data for the time period of data collection in the target county. The census data are not in the public file but were used to develop sampling weights for the male data.
  • Abstract

    For the adult data, variables from the facesheet include arrest precinct, ZIP code of arrest location, ZIP code of respondent's address, respondent's gender and race, three most serious arrest charges, sample source (stock, flow, other), interview status (including reason the individual selected was not interviewed), language of instrument used, and the number of hours since arrest. Demographic information from the core instrument includes respondent's age, ethnicity, residency, education, employment, health insurance coverage, marital status, housing, and telephone access. Variables from the calendar provide information on inpatient and outpatient substance abuse treatment, inpatient mental health treatment, arrests and incarcerations, heavy alcohol use, use of marijuana, crack/rock cocaine, powder cocaine, heroin, methamphetamine, and other drug (ever and previous 12 months), age of first use of the above six drugs and heavy alcohol use, drug dependency in the previous 12 months, characteristics of drug transactions in past 30 days, use of marijuana, crack/rock cocaine, powder cocaine, heroin, and methamphetamine in past 30 days, 7 days, and 48 hours, heavy alcohol use in past 30 days, and secondary drug use of 15 other drugs in the past 48 hours. Urine test results are provided for 11 drugs -- marijuana, cocaine, opiates, phencyclidine (PCP), benzodiazepines (Valium), propoxyphene (Darvon), methadone, methaqualone, barbiturates, amphetamines, and methamphetamine. The adult data files include several derived variables. The male data also include four sampling weights, and stratum identifications and percents. For the juvenile data, demographic variables include age, race, sex, educational attainment, employment status, and living circumstances. Data also include each juvenile arrestee's self-reported use of 15 drugs (alcohol, tobacco, marijuana, powder cocaine, crack, heroin, PCP, amphetamines, barbiturates, quaaludes, methadone, crystal methamphetamine, Valium, LSD, and inhalants). For each drug type, arrestees reported whether they had ever used the drug, age of first use, whether they had used the drug in the past 30 days and past 72 hours, number of days they used the drug in past month, whether they tried to cut down or quit using the drug, if they were successful, whether they felt dependent on the drug, whether they were receiving treatment for the drug, whether they had received treatment for the drug in the past, and whether they thought they could use treatment for that drug. Additional variables include whether juvenile respondents had ever injected drugs, whether they were influenced by drugs when they allegedly committed the crime for which they were arrested, whether they had been to an emergency room for drug-related incidents, and if so, whether in the past 12 months, and information on arrests and charges in the past 12 months. As with the adult data, urine test results are also provided. Finally, variables covering precinct (precinct of arrest) and law (penal law code associated with the crime for which the juvenile was arrested) are also provided for use by local law enforcement officials at each site.
  • Methods

    ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes..
  • Methods

    Presence of Common Scales: None.
  • Methods

    Response Rates: The ability to provide a true response rate will not be available until the 2002 data collection. However, the data do contain information on interview and urine specimen status. For the male data, 56.3 percent agreed to an interview, 13.6 percent declined, 22.8 percent were not available at the time of their selection, and 7.3 percent were not approached. Of the male arrestees who were interviewed, 89.9 percent provided a urine sample. For the female data, 61.9 percent agreed to be interviewed, 14.6 percent declined, 14.8 percent were not available, and 8.7 percent were not approached. Of the female arrestees who were interviewed, 89.4 percent provided a urine specimen. For the juvenile data, only those who agreed to an interview and provided a urine sample are included in the file. Response rates vary across sites but generally fall in the 80 percent to 85 percent range. This includes agreement to the interview and providing a urine sample.
  • Table of Contents

    Datasets:

    • DS0: Study-Level Files
    • DS1: Adult Male Arrestee Data with Weights
    • DS2: Adult Female Arrestee Data
    • DS3: Juvenile Arrestee Data
Temporal Coverage
  • 2000-01-01 / 2000-12-31
    Time period: 2000-01-01--2000-12-31
  • 2000-01-01 / 2000-12-31
    Collection date: 2000-01-01--2000-12-31
Geographic Coverage
  • United States
Sampled Universe
All persons arrested and booked on local and state charges in the 35 ADAM counties in the United States during 2000.
Sampling
Part 1: Probability-based sampling, Parts 2-3: Convenience samples.
Collection Mode
  • Users are strongly encouraged to obtain copies of the "Methodology Guide for ADAM" and the "Analytic Guide for ADAM" from the ADAM Web site at http://www.adam-nij.net/.

    The ADAM program changes implemented in 2000 will continue during the 2001 collection. Because of the above changes to the ADAM program, analysts must be careful when comparing previous DUF and ADAM data to the 2000 data, especially for male arrestees.

    Local area estimates, national estimates, and inferences about the total population of hardcore or heavy drug users, including those not in the current ADAM sample, are possible with the new ADAM sampling design. The latter two items will be described in detail in forthcoming publications.

Note
2006-03-30 File UG3270.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. Funding insitution(s): United States Department of Justice. Office of Justice Programs. National Institute of Justice (OJP-98-C-001).
Availability
Delivery
One or more files in this study are not available for download due to special restrictions; consult the study documentation to learn more on how to obtain the data.
Alternative Identifiers
  • 3270 (Type: ICPSR Study Number)
Relations
  • Is previous version of
    DOI: 10.3886/ICPSR03270.v1
Publications
  • Caulkins, Jonathan P., Kilmer, Beau, Reuter, Peter H., Midgette, Greg. Cocaine's fall and marijuana's rise: Questions and insights based on new estimates of consumption and expenditures in US drug markets. Addiction.110, (5), 728-736.2015.
    • ID: 10.1111/add.12628 (DOI)
  • Fox, Andrew M., Rodriguez, Nancy. Using a criminally involved population to examine the relationship between race/ethnicity, structural disadvantage, and methamphetamine use. Crime and Delinquency.60, (6), 833-858.2014.
    • ID: 10.1177/0011128710364825 (DOI)
  • Kilmer, Beau, Everingham, Susan S., Caulkins, Jonathan P., Midgette, Gregory, Pacula, Rosalie Liccardo, Reuter, Peter H., Burns, Rachel M., Han, Bing, Lundberg, Russell. What America's Users Spend on Illegal Drugs: 2000-2010. Santa Monica, CA: RAND Corporation. 2014.
    • ID: http://www.whitehouse.gov/sites/default/files/ondcp/policy-and-research/wausid_results_report.pdf (URL)
  • Parsons, Nicholas L.. Meth Mania: A History of Methamphetamine. Boulder, CO: Lynne Rienner Publishers. 2014.
  • Golub, Andrew, Brownstein, Henry H.. Drug generations in the 2000s: An analysis of arrestee data. Journal of Drug Issues.43, (3), 335-356.2013.
    • ID: 10.1177/0022042613475599 (DOI)
  • Caulkins, Jonathan P., Bond, Brittany M.. Marijuana price gradients: Implications for exports and export-generated tax revenue for California after legalization. Journal of Drug Issues.42, (1), 28-45.2012.
    • ID: 10.1177/0022042612436650 (DOI)
  • Cooper, Jonathon A., Fox, Andrew M., Rodriguez, Nancy. Race, structural disadvantage, and illicit drug use among arrestees. Criminal Justice Policy Review.23, (1), 18-39.2012.
    • ID: 10.1177/0887403410390508 (DOI)
  • Miller, Riane N., Kuhns, Joseph B.. Exploring the impact of medical marijuana laws on the validity of self-reported marijuana use among juvenile arrestees over time. Criminal Justice Policy Review.23, (1), 40-66.2012.
    • ID: 10.1177/0887403410392026 (DOI)
  • Pyrooz, David C., Fox, Andrew M., Katz, Charles M., Decker, Scott H.. Gang organization, offending, and victimization: A cross-national analysis. Youth Gangs in International Perspective: Results from the Eurogang Program of Research.New York, NY: Springer. 2012.
  • Griffin, Marie L., Rodriguez, Nancy. The gendered nature of drug acquisition behavior within marijuana and crack drug markets. Crime and Delinquency.57, (3), 408-431.2011.
    • ID: 10.1177/0011128708327955 (DOI)
  • Katz, Charles M., Webb, Vincent J., Fox, Kate, Shaffer, Jennifer N.. Understanding the relationship between violent victimzation and gang membership. Journal of Criminal Justice.39, (1), 48-59.2011.
    • ID: 10.1016/j.jcrimjus.2010.10.004 (DOI)
  • Bhati, Avinash Singh, Roman, John K.. Simulated evidence on the prospects of treating more drug-involved offenders. Journal of Experimental Criminology.6, (1), 1-113.2010.
    • ID: 10.1007/s11292-010-9088-2 (DOI)
  • Bond, Brittany M., Caulkins, Jonathan P.. Potential for Legal Marijuana Sales in California to Supply Rest of U.S.. RAND Working Paper.765, Santa Monica, CA: RAND Corporation. 2010.
  • Kposowa, Augustine Joseph, Adams, Michelle A., Tsunokai, Glenn T.. Citizenship status and arrest patterns in the United States: Evidence from the Arrestee Drug Abuse Monitoring program. Crime, Law and Social Change.53, (2), 159-181.2010.
    • ID: 10.1007/s10611-009-9224-y (DOI)
  • Kremling, Janine. An Analysis of the Influence of Sampling Methods on Estimation of Drug Use Prevalence and Patterns among Arrestees in the United States: Implications for Research and Policy. Dissertation, University of South Florida. 2010.
  • Pacula, Rosalie L., Kilmer, Beau, Grossman, Michael, Chaloupka, Frank J.. Risks and practices: The role of user sanctions in marijuana markets. B.E. Journal of Economic Analysis and Policy.10, (1), 1-36.2010.
  • Dave, Dhaval. Illicit drug use among arrestees, prices and policy. Journal of Urban Economics.63, (2), 694-714.2009.
    • ID: 10.1016/j.jue.2007.04.011 (DOI)
  • The White House. National Drug Control Strategy: Data Supplement 2009. NCJ 225448, Washington, DC: Office of National Drug Control Policy. 2009.
    • ID: http://www.whitehousedrugpolicy.gov/publications/policy/ndcs09/ndcs09_data_supl/09datasupplement.pdf (URL)
  • Zhang, Zhiwei. Modeling Nonresponse and Underreporting in Response Surveys of Arrestees. 2009 Joint Statistical Meeting.Washington, DC. 2009.
    • ID: http://www.amstat.org/sections/srms/proceedings/y2009/Files/305170.pdf (URL)
  • Decker, Scott H., Katz, Charles M., Webb, Vincent J.. Understanding the black box of gang organization: Implications for involvement in violent crime, drug sales, and violent victimization. Crime and Delinquency.54, (1), 153-172.2008.
    • ID: 10.1177/0011128706296664 (DOI)
  • The White House. National Drug Control Strategy. Data Supplement 2008.NCJ 221951, Washington, DC: Office of National Drug Control Policy. 2008.
    • ID: http://www.whitehousedrugpolicy.gov/publications/policy/ndcs08_data_supl/ndcs_suppl08.pdf (URL)
  • Wood, Darryl S.. Criterion validity of self-reported drug use among Alaska Native and non-Native arrestees in Anchorage, Alaska. Criminal Justice Studies.21, (1), 49-60.2008.
    • ID: 10.1080/14786010801972688 (DOI)
  • Brownstein, Henry H., Taylor, Bruce G.. Measuring the stability of illicit drug markets: Why does it matter?. Drug and Alcohol Dependence.90, (Supplement 1), 52-60.2007.
    • ID: 10.1016/j.drugalcdep.2006.11.010 (DOI)
  • Damphousse, Kelly R.. Start spreading the news: Understanding the drug problem in the mid-American states with the Arrestee Drug Abuse Monitoring Program. Free Inquiry.35, (1), 63-78.2007.
  • Golub, Andrew, Johnson, Bruce D., Dunlap, Eloise. The race/ethnicity disparity in misdemeanor marijuana arrests in New York City. Criminology and Public Policy.6, (1), 131-164.2007.
  • Gorman, Dennis M., Huber, J. Charles, Jr.. Do medical cannabis laws encourage cannabis use?. International Journal of Drug Policy.18, (3), 160-167.2007.
    • ID: 10.1016/j.drugpo.2006.10.001 (DOI)
  • Harcourt, Bernard E., Ludwig, Jens. Reaction Essay. Reefer madness: Broken windows policing and misdemeanor marijuana arrests in New York City, 1989-2000. Criminology and Public Policy.6, (1), 165-181.2007.
  • Pacula, Rosalie Liccardo, Kilmer, Beau, Grossman, Chaloupka, Frank J.. Risks and Prices: The Role of User Sanctions in Marijuana Markets. NBER Working Paper Series.NCJ 13415, Cambridge, MA: National Bureau of Economic Research. 2007.
    • ID: http://www.nber.org.proxy.lib.umich.edu/papers/w13415.pdf?new_window=1 (URL)
  • Rhodes, William, Hunt, Dana, Chapman, Meg, Kling, Ryan, Dyous, Christina, Fuller, Doug. Using ADAM Data to Investigate the Effectiveness of Law Enforcement. NCJ 221073, Cambridge, MA: Abt Associates Inc.. 2007.
    • ID: http://www.ncjrs.gov/pdffiles1/nij/grants/221073.pdf (URL)
  • Rhodes, William, Kling, Ryan, Johnston, Patrick. Using booking data to model drug user arrest rates: A preliminary to estimating the prevalence of chronic drug use. Journal of Quantitative Criminology.23, (1), 1-22.2007.
    • ID: 10.1007/s10940-006-9016-9 (DOI)
  • Capeheart, Loretta J., Sweet, Elizabeth L.. Condiciones, Drogas, y La Carcel: Latino Arrestees in Miami, New York, San Antonio, and San Jose. Criminal Justice Policy Review.17, (4), 428-450.2006.
    • ID: 10.1177/0887403406292684 (DOI)
  • Decker, Scott H., Katz, Charles M., Webb, Vincent J.. Assessing the validity of self-reports by gang members: Results from the Arrestee Drug Abuse Monitoring Program. Crime and Delinquency.52, (2), 232-252.2006.
  • Johnson, Bruce D., Golub, Andrew. Dependence on and treatment for street drugs among Manhattan arrestees. New Research on Street Drugs.Hauppauge, NY: Nova Science Publishers. 2006.
  • Ross, Michael W., Risser, Jan, Peters, Ronald J.. Cocaine use and syphilis trends: Findings from the Arrestee Drug Abuse Monitoring (ADAM) program and syphilis epidemiology in Houston. American Journal on Addictions.15, (6), 473-477.2006.
    • ID: 10.1080/10550490601000462 (DOI)
  • Beckett, Katherine, Nyrop, Kris, Pfingst, Lori, Bowen, Melissa. Drug use, drug possession arrests, and the question of race: Lessons from Seattle. Social Problems.52, (3), 419-441.2005.
    • ID: 10.1525/sp.2005.52.3.419 (DOI)
  • Golub, Andrew, Liberty, Hillary James, Johnson, Bruce D.. Inaccuracies in self-reports and urinalysis tests: Impacts on monitoring marijuana use trends among arrestees. Journal of Drug Issues.35, (4), 941-965.2005.
    • ID: 10.1177/002204260503500413 (DOI)
  • Golub, Andrew, Liberty, Hillary James, Johnson, Bruce D.. The variation in arrestees' disclosure of recent drug use across locations, drugs, and demographic characteristics. Journal of Drug Issues.35, (4), 917-940.2005.
    • ID: 10.1177/002204260503500412 (DOI)
  • Jones, Peter R.. Drug use trends across the DUF/ADAM divide: 1988-2002. Boston, MA. 2005.
  • Katz, Charles M., Webb, Vincent J., Decker, Scott H.. Using the Arrestee Drug Abuse Monitoring (ADAM) Program to further understand the relationship between drug use and gang membership. Justice Quarterly.22, (1), 58-88.2005.
    • ID: 10.1080/0741882042000333645 (DOI)
  • Lord, Vivian B., Friday, Paul C., Brennan, Pauline K.. The effects of interviewer characteristics on arrestees' responses to drug-related questions. Applied Psychology in Criminal Justice.1, (1), 36-55.2005.
  • Rodriguez, Nancy, Griffin, Marie L.. Gender Differences in Drug Market Activities: A Comparative Assessment of Men and Women’s Participation in the Drug Market. NCJ 211974, . 2005.
    • ID: https://www.ncjrs.gov/pdffiles1/nij/grants/211974.pdf (URL)
  • Rodriguez, Nancy, Katz, Charles, Webb, Vincent J., Schaefer, David R.. Examining the impact of individual, community, and market factors on methamphetamine use: A tale of two cities. Journal of Drug Issues.35, (4), 665-693.2005.
    • ID: 10.1177/002204260503500402 (DOI)
  • Rosenfeld, Richard, Fornango, Robert, Baumer, Eric. Did Ceasefire, Compstat, and Exile reduce homicide?. Criminology and Public Policy.4, (3), 419-450.2005.
  • Burke, Cynthia. Drug Use Among Adult Arrestees in San Diego County. CJ Bulletin.San Diego, CA: SANDAG, Criminal Justice Research Division. 2004.
    • ID: http://sandiegohealth.org/disease/drug/publicationid_1109_3506.pdf (URL)
  • Golub, Andrew, Johnson, Bruce D.. How Much Do Manhattan-Arrestees Spend on Drugs?. Final Report to the National Institute of Justice Regarding Monitoring Drug Markets in Manhattan with ADAM.NIJ 207147, New York, NY: National Development and Research Institutes, Inc.. 2004.
    • ID: http://www.ncjrs.gov/pdffiles1/nij/grants/207147.pdf (URL)
  • National Center on Addiction and Substance Abuse at Columbia University. Criminal Neglect: Substance Abuse, Juvenile Justice and The Children Left Behind. NCJ 207406, . 2004.
    • ID: http://www.casacolumbia.org/addiction-research/reports/substance-abuse-juvenile-justive-children-left-behind (URL)
  • Webb, Vincent J., Katz, Charles M., Decker, Scott H.. Assessing the Validity of Self-Reports by Gang Members: Results From the Arrestee Drug Abuse Monitoring Program. Conference of the Academy of Criminal Justice Sciences.Las Vegas, NV. 2004.
  • Yacoubian, George S., Jr., Peters, Ronald J.. Exploring the prevalence and correlates of methamphetamine use: Findings from Sacramento's ADAM program. Journal of Drug Education.34, (3), 281-294.2004.
    • ID: 10.2190/QBHY-ADHA-MYMW-HCMR (DOI)
  • Yang, Y. Michael. Survey errors and survey costs: Experience from surveys of arrestees. Joint Statistical Methods.Toronto. 2004.
  • Brecht, Mary-Lynn, Anglin, M. Douglas, Lu, Tzu-Hui. Estimating Drug Use Prevalence Among Arrestees Using ADAM Data: An Application of a Logistic Regression Synthetic Estimation Procedure. NCJ 198829, Los Angeles, CA: UCLA Integrated Substance Abuse Programs [producer], National Institute of Justice [distributor]. 2003.
    • ID: http://www.ncjrs.gov/pdffiles1/nij/grants/198829.pdf (URL)
  • Falkowski, Carol L.. Drug Abuse Trends. Center City, MN: Hazelden Foundation. 2003.
  • Myrstol, Brad. Alcohol use among Anchorage Arrestees. Alaska Justice Forum.19, (4), 3-4.2003.
    • ID: http://justice.uaa.alaska.edu/forum/19/4winter2003/194.winter2003.pdf (URL)
  • Myrstol, Brad. Drug use trends among Anchorage arrestees: 1999-2001. Alaska Justice Forum.19, (4), 1, 10-12.2003.
    • ID: http://justice.uaa.alaska.edu/forum/19/4winter2003/194.winter2003.pdf (URL)
  • Taylor, Bruce, Brownstein, Henry H.. Toward the operationalization of drug market stability: An illustration using arrestee data from crack cocaine markets in four urban communities. Journal of Drug Issues.33, (1), 73-99.2003.
    • ID: 10.1177/002204260303300104 (DOI)
  • Yacoubian, George S., Jr.. Does the calendar method enhance drug use reporting among Portland arrestees?. Journal of Substance Use.8, (1), 27-32.2003.
    • ID: 10.1080/1465989031000067218 (DOI)
  • Yacoubian, George, Jr.. Measuring alcohol and drug dependence with New York City ADAM data. Journal of Substance Abuse Treatment.24, (4), 341-345.2003.
    • ID: 10.1016/S0740-5472(03)00044-8 (DOI)
  • Yang, Y. Michael, Gerstein, Dean R.. A comparison of two arrestee drug use estimation methods. Joint Statistical Meetings.San Francisco, CA. 2003.
  • Yacoubian, George S.. Estimating the prevalence of recent ecstasy use among national arrestees. Federal Probation.66, (3), 17-18.2002.
  • (author unknown). 2000 Annualized Site Reports, Research Report. Washington, DC: United States Department of Justice, National Institute of Justice. 2001.
  • (author unknown). Ecstasy surveillance in the United States: The time to monitor juvenile arrestees is now. Journal of Offender Monitoring.14, (3-4), 23-24.2001.
  • Giblin, Matthew J.. Aspects of drug use: Arrestees in Anchorage, 2000. Alaska Justice Forum.18, (3), 6-8.2001.
    • ID: http://justice.uaa.alaska.edu/forum/18/3fall2001/a_adam.html (URL)
  • Golub, Andrew, Johnson, Bruce D.. The Rise of Marijuana as the Drug of Choice Among Youthful Adult Arrestees. Research in Brief.NCJ 187490, Washington, DC: United States Department of Justice, National Institute of Justice. 2001.
    • ID: https://www.ncjrs.gov/pdffiles1/nij/187490.pdf (URL)
  • Heliotis, Joanna, Kuck, Sarah, Hunt, Dana. Analytic Guide for ADAM. Arrestee Drug Abuse Monitoring (ADAM) Program.Washington, DC: United States Department of Justice, National Institute of Justice. 2001.
    • ID: http://www.adam-nij.net/files/analguid.pdf (URL)
  • Taylor, Bruce G., Fitzgerald, Nora, Hunt, Dana, Reardon, Judy A., Brownstein, Henry H.. ADAM Preliminary 2000 Findings on Drug Use and Drug Markets -- Adult Male Arrestees. NCJ 189101, Washington, DC: United States Department of Justice, National Institute of Justice. 2001.
    • ID: http://www.ncjrs.gov/pdffiles1/nij/189101.pdf (URL)
  • Zhang, Zhiwei, et al. Drug and Alcohol Use and Related Matters among Arrestees, 2000. NCJ 212905, Washington, DC: United States Department of Justice, National Institute of Justice. 2001.
    • ID: http://www.ncjrs.gov/nij/adam/ADAM2000.pdf (URL)

Update Metadata: 2015-08-05 | Issue Number: 6 | Registration Date: 2015-06-15

United States Department of Justice. Office of Justice Programs. National Institute of Justice (2001): Arrestee Drug Abuse Monitoring (ADAM) Program in the United States, 2000. Archival Version. Arrestee Drug Abuse Monitoring (ADAM) Program/Drug Use Forecasting (DUF) Series. Version: v0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/ICPSR03270