Development and Reliability of Items Measuring the Nonmedical Use of Prescription Drugs for the Youth Risk Behavior Survey: Results From an Initial Pilot Test

Howard, Melissa; Weiler, Robert M.; Haddox, J. David

doi:10.1111/j.1746-1561.2009.00448.x

Cited by 14 publications

(9 citation statements)

References 15 publications

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“…The growing prevalence of prescription opioid use disorder (Blanco et al, 2007; Howard et al, 2009), and its association with psychosocial impairment (Huang et al, 2006), overdose death (Bohnert et al, 2011), and substantial health care costs, make it desirable to improve the detection of prescription opioid use disorders to facilitate access to treatment and more integrated care.…”

Section: Discussionmentioning

confidence: 99%

Probability and predictors of treatment-seeking for prescription opioid use disorders: A National Study

Blanco

Iza

Schwartz

et al. 2013

Drug and Alcohol Dependence

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Background Prescription opioid use disorders are the second most common drug use disorder behind only cannabis use disorders. Despite this, very little is known about the help-seeking behavior among individuals with these disorders. Methods The sample included respondents of the Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) with a lifetime diagnosis of prescription drug use disorders (N= 623). Unadjusted and adjusted hazard ratios are presented for time to first treatment-seeking by sociodemographic characteristics and comorbid psychiatric disorders. Results The lifetime cumulative probability of treatment seeking was 42% and the median delay from prescription drug use disorder onset to first treatment was 3.83 years. Having an earlier onset of prescription opioid use disorder and a history of bipolar disorder, major depression disorder, specific phobia and cluster B personality disorders predicted shorter delays to treatment. Conclusions Although some comorbid psychiatric disorders increase the rate of treatment-seeking and decrease delays to first-treatment contact rates of treatment-seeking for prescription drug use disorder are low, even when compared with rates of treatment for other substance use disorders. Given the high prevalence and adverse consequences of prescription drug use disorder, there is a need to improve detection and treatment of prescription opioid use disorder.

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Section: Discussionmentioning

confidence: 99%

Probability and predictors of treatment-seeking for prescription opioid use disorders: A National Study

Blanco

Iza

Schwartz

et al. 2013

Drug and Alcohol Dependence

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“…Overall, most reports describing the development or characterization of a new drug outcome measure are in response to a new need or a new area of research (2, 3). However, questions remain regarding the appropriate choice of measures when planning a study, and very few, if any studies have been conducted making direct comparisons of outcome measures in large datasets.…”

Section: Discussionmentioning

confidence: 99%

Assessing Drug Use during Follow-Up: Direct Comparison of Candidate Outcome Definitions in Pooled Analyses of Addiction Treatment Studies

Korte

Magruder

Chiuzan

et al. 2011

The American Journal of Drug and Alcohol Abuse

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Background Selection of appropriate outcome measures is important for clinical studies of drug addiction treatment. Researchers use various methods of collecting drug use outcomes and must consider substances to be included in a urine drug screen (UDS); accuracy of self-report; use of various instruments and procedures for collecting self-reported drug use; and timing of outcome assessments. Objectives We sought to define a set of candidate measures to 1) assess their inter-correlation, and 2) identify any differences in results. Methods Data were combined from completed protocols in the National Institute on Drug Abuse Clinical Trials Network (CTN), with a total of 1897 participants. We defined nine outcome measures based on UDS, self-report, or a combination. Multivariable, multilevel GEE models were used to assess subgroup differences in intervention success, controlling for baseline differences and accounting for clustering by CTN protocols. Results There were high correlations among all candidate outcomes. All outcomes showed consistent overall results with no significant intervention impact on drug use during follow-up. However, with most UDS variables, but not with self-report or “corrected self-report”, we observed a significant gender-ethnicity interaction with benefit shown in African American women, white women, and Hispanic men. Conclusion Despite strong associations between candidate measures, we found some important differences in results. Scientific Significance In this study, we demonstrated the potential utility and impact of combining UDS and self-report data for drug use assessment. Our results suggest possible differences in intervention efficacy by gender and ethnicity, but highlight the need to cautiously interpret observed interactions.

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“…6 In another survey published in 2009, the non-medical use of prescription drugs ranked fourth among most abused class of drugs by adolescents after alcohol, tobacco, and marijuana, respectively. 7 In a 2005 survey of 1,086 high school–aged adolescents, 12% reported engaging in non-medical use of opioid pain medications, and 2% reported engaging in nonmedical use of stimulant medications in the last 12 months. 8 In a large national survey published in 2008, 7%of 12- to 17-year-olds reported nonprescribed prescription pain reliever use in the last year, and 1% met DSM-IV criteria for past-year abuse or dependence.…”

mentioning

confidence: 99%

Characterization of Adolescent Prescription Drug Abuse and Misuse Using the Researched Abuse Diversion and Addiction-Related Surveillance (RADARS®) System

Zosel

Bartelson

Bailey

et al. 2013

Journal of the American Academy of Child & Adolescent Psych

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Objective To describe the characteristics and health effects of adolescent (age 13–19 years) prescription drug abuse and misuse using the Researched Abuse Diversion and Addiction-Related Surveillance (RADARS®) System. Method Secondary analysis of data collected from RADARS System participating poison centers was performed. Data for all intentional exposures from 2007 through 2009 were used to describe adolescent prescription opioid (oxycodone, fentanyl, hydrocodone, hydromorphone, morphine, methadone, buprenorphine, and tramadol) and stimulant (methylphenidate and amphetamines) exposures. Results A total of 16,209 intentional adolescent exposures to prescription drugs were identified, 68% to opioids and 32% to stimulants. The mean age was 16.6 years (SD ± 1.7 years). Slightly more than half (52.4%) of drug mentions involved females. The five most frequently misused or abused drugs were hydrocodone (32%), amphetamines (18%), oxycodone (15%), methylphenidate (14%), and tramadol (11%). Of all exposures, 38%were classified as suspected suicidal. Of adolescents who intentionally exposed themselves to prescription drugs, 30% were treated in a health care facility, 2,792 of whom were admitted to the hospital, including 1,293 to the intensive care unit. A total of 17.2% of intentional exposures were associated with no effect, 38.9% minor effects, 23.3% moderate effects, 3.6% major effects, and 0.1% were associated with death. Oxycodone and methadone were associated with the most deaths. No deaths were associated with exposures to stimulants. Conclusions Prescription drug misuse and abuse poses an important health problem and results in thousands of hospitalizations of adolescents per year. Further work is needed to develop focused interventions and educational programs to prevent prescription drug abuse and misuse by adolescents.

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Development and Reliability of Items Measuring the Nonmedical Use of Prescription Drugs for the Youth Risk Behavior Survey: Results From an Initial Pilot Test

Cited by 14 publications

References 15 publications

Probability and predictors of treatment-seeking for prescription opioid use disorders: A National Study

Probability and predictors of treatment-seeking for prescription opioid use disorders: A National Study

Assessing Drug Use during Follow-Up: Direct Comparison of Candidate Outcome Definitions in Pooled Analyses of Addiction Treatment Studies

Characterization of Adolescent Prescription Drug Abuse and Misuse Using the Researched Abuse Diversion and Addiction-Related Surveillance (RADARS®) System

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