Prevalence and correlates of nonmedical use of prescription opioids in patients seen in a residential drug and alcohol treatment program

Journal of Substance Abuse Treatment 41 (2011) 208 – 214

Brief article

Prevalence and correlates of nonmedical use of prescription opioids in patients seen in a residential drug and alcohol treatment program Amanda M. Price, (B.A.) a , Mark A. Ilgen, (Ph.D.) a,b,⁎, Amy S.B. Bohnert, (Ph.D.) a,b b

a Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109 Department of Veterans Affairs, Health Services Research & Development, Ann Arbor, MI, 48105

Received 26 August 2010; received in revised form 3 February 2011; accepted 7 February 2011

Abstract Population-based data indicate that rates of nonmedical use of prescription opioids (POs) have increased dramatically over the past decade. However, data are lacking on nonmedical use of POs in individuals seeking treatment for substance use disorders. Patients (N = 351) seeking treatment from a residential drug and alcohol treatment program were assessed for nonmedical use of POs prior to treatment entry. Approximately 68% (65% men and 78% women) of patients reported at least some nonmedical PO use in the 30 days prior to treatment. Our results indicate that nonmedical PO use was more common in those with higher levels of depressive symptoms and pain intensity and in those with lower physical functioning. Treatment programs should consider actively screening participants for nonmedical PO use and consider how nonmedical use of pain medications might influence their treatment planning for patients. Published by Elsevier Inc. Keywords: Opioid dependence; Nonmedical prescription opioid use; Pain medications

1. Introduction The nonmedical use of prescription opioids (POs) is a substantial and growing problem that is just beginning to be understood (Compton & Volkow, 2006; SAMHSA, 2009). Existing estimates indicate that not only has the rate of prescribing opioids by U.S. health care providers increased dramatically since 1995 (Paulozzi, 2006; Paulozzi & Ryan, 2006), but also, during this period, the estimated rate of nonmedical use of these medications has also increased more than sevenfold (Compton & Volkow, 2006; SAMHSA, 2009). For the purpose of this article, nonmedical use of POs is defined as patient use of POs that is not indicated by a prescribing health care practitioner (Anthony, Warner, & Kessler, 1994). In 2008, an estimated 4.7 million Americans older than 12 years (or approximately 1.8% of the U.S. population) reported the nonmedical use of POs within the past month (SAMHSA, 2009). In subgroups of individuals with an established non-PO substance use disorder (SUD), ⁎ Corresponding author. 4250 Plymouth Rd, Ann Arbor, MI 481092700. Tel.: +1 734 232 0424; fax: +1 734 615 8739. E-mail address: [email protected] (M.A. Ilgen). 0740-5472/11/$ – see front matter. Published by Elsevier Inc. doi:10.1016/j.jsat.2011.02.003

rates of nonmedical PO use are likely higher. Havens et al. (2009) found that more than half (53%) of rural stimulant users reported misusing POs in the previous 6 months. In addition, in a sample of New York street drug users, Davis and Johnson (2008) found that 34% of the sample reported using POs within the past month, and 26% reported use within the past week. A small number of studies indicate that nonmedical use of POs is particularly common in pain or SUD treatment settings (Chabal, Erjavec, Jacobson, Mariano, & Chaney, 1997; Hoffmann, Olofsson, Salen, & Wickstrom, 1995; Jonasson, Jonasson, Wickstrom, Andersson, & Saldeen, 1998; Kouyanou, Pither, & Wessely, 1997; Rosenblum et al., 2007). In patients seeking treatment for chronic pain, 23.4% met criteria for a current SUD, and an additional 9.4% met criteria for a SUD in remission (Hoffman et al., 1995). Chabal et al. (1997) found similar results among another group of patients experiencing chronic pain, with 27.6% meeting criteria for a SUD. In one large national study of methadone maintenance patients, 69% of primary heroin users reported lifetime nonmedical PO use, and 39% reported past 30-day nonmedical use (Rosenblum et al., 2007). Brands, Blake, Sproule, Gourlay, and Busto, (2004) conducted a chart review of patients

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presenting for methadone maintenance treatment from 1997 to 1999. They found that 82% of patients had used POs, either with or without additional heroin use, at higher than therapeutic dosages. Twenty-four percent of methadone maintenance patients in this study had used POs only. In a study that examined the rates and correlates of OxyContin use and nonmedical use among individuals admitted to 157 different SUD treatment centers from 2001 to 2004, Carise et al. (2007) found that those individuals who reported OxyContin use also reported nonmedical PO use and primarily used it recreationally to “get high” and not for chronic pain. Consistent with research on the general population (Becker et al., 1997; Blazer & Wu, 2009; Boyd, Teter, West, Morales, & McCabe, 2009; Grau et al., 2007; Martins, Storr, Zhu, & Chilcoat, 2009; McCabe, West, Morales, Cranford, & Boyd, 2007; Sullivan, Edlund, Zhang, Unützer, & Wells, 2006; Sung, Richter, Vaughan, Johnson, & Thom, 2005; Tetrault et al., 2008; Wu, Ringwalt, Mannelli, & Patkar, 2008), studies of treated samples consistently indicate that those who engage in nonmedical PO use have more other-substance-related, legal, psychiatric, and other health-related problems than others without nonmedical PO use (Chabal et al., 1997; Hoffmann et al., 1995; Jonasson et al., 1998; Kouyanou et al., 1997; Reid et al., 2002; Romach, Sproule, Sellers, Somer, & Busto, 1999; Rosenblum et al., 2007). These limited data indicate that the prevalence of nonmedical PO use is noticeably higher in treatment populations relative to the prevalence of nonmedical use seen in the general population, and nonmedical PO use may be a marker of greater substance-related and other problems even when compared with other treatment-seeking substance users. However, to the best of our knowledge, the bulk of the research on nonmedical PO use in adults presenting to SUD treatment has been conducted in settings specifically focused on treating opioid dependence (i.e., either those treated specifically for heroin or PO dependence; Brands et al. 2004; Rosenblum et al., 2007). The prevalence and associated problems of nonmedical PO use in the broader samples of SUD treatment patients are unknown. Thus, the aims of this study were to describe (1) the rates of recent nonmedical PO use in a large residential SUD treatment setting, (2) the characteristics of those who engage in nonmedical use of POs, and (3) the association with other substance use and overall functioning. We hypothesize that the prevalence of nonmedical PO use will be elevated compared with the general population, and those with decreased functioning will have increased nonmedical PO use.

2. Materials and methods

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of patients from the surrounding Flint and Detroit, MI, areas. For this study, men and women 18 years and older were recruited by research staff in person via presentations made at didactic groups at the treatment site. Those who expressed interest in participating were informed of the study protocol, provided written consent, and completed the initial screening questionnaire. Participants took 45 minutes to 1 hour to complete the questionnaire. Participants were excluded from participation if they were unable to speak or understand English, were unable to provide voluntary written consent, or exhibited any acute psychotic symptoms. All screening measures were self-administered, and participants were compensated for their time. Study protocols and materials were approved by the University of Michigan Medical School Institutional Review Board. 2.2. Participants Three-hundred fifty-one participants completed the screening questionnaire. The sample was 76.1% male, aged 35.6 years (SD = 10.8) on average, and was predominantly Caucasian (64.7%), 26.8% African American, 2.0% Hispanic/Latino, 1.7% Asian or American Indian, and 4.8% “other.” On average, participants had completed 11.8 years of education (SD = 2.1), 84.3% reported they were currently unemployed, and only 17.9% of participants endorsed being married or currently living with a partner. 2.3. Measures The screening questionnaire consisted of self-administered surveys designed to measure demographic information such as age, race/ethnicity, gender, education level, marital status, and current employment status, as well as chronic pain, mental and physical health functioning, and substance use. Race/Ethnicity, marital status, and current employment status were all dichotomized for these analyses. Race/ Ethnicity was coded as Caucasian or non-Caucasian (including African American, Hispanic/Latino, American Indian, Asian, and other). Marital status was coded as “partnered,” which included those participants who reported they were currently married or living with someone as if married, or “not partnered,” which included those who selfidentified as never married, divorced, separated, or widowed. Employment status was coded as “employed,” including those employed part- and full-time, or “unemployed,” which represented those looking for work, those uninterested in returning to work, and those who were currently with disability or retired. Years of educational attainment and age were included as continuous variables for these analyses.

2.1. Procedures All participants were recruited over the course of a year during 2008–2009 from a large residential SUD treatment center located in Waterford, MI, which serves a wide variety

2.3.1. Nonmedical PO use Items from the Current Opiate Misuse Measure (COMM; Butler et al., 2007) were used to measure nonmedical PO use within the sample. Items use a Likert-type scale with answer

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choices ranging from 0 (never) to 4 (very often) and are designed to assess the frequency of a particular thought or behavior pertaining to prescription medication over the past 30 days. The COMM has good internal consistency and test– retest reliability (Butler et al., 2007). For this study, six specific core items of the COMM were chosen to develop our nonmedical PO use variable based on their ability to map onto the core domains of nonmedical prescription medication use identified by Anthony et al. (1994) and directly address nonmedical use behaviors associated with POs. Items included the following: “How often have you taken your medications differently from how they are prescribed?” “How often have you needed to take pain medications belonging to someone else?” “How often have you had to go to someone other than your prescribing physician to get sufficient pain relief from your medications?” “How often have you had to take more of your medication than prescribed?” “How often have you borrowed pain medication from someone else?” and “How often have you used your pain medication for symptoms other than for pain?” These items had a strong reliability in this sample (Cronbach's α = .934). A positive endorsement, or rating of 1 or more on any of these six items, was used as an indicator of any recent nonmedical PO use. Participant responses for these specific items were summed to create a dichotomous (yes/no) “nonmedical PO use” variable, which served as the primary dependent variable in all analyses. 2.3.2. Substance use Information about participant's recent alcohol and drug use was obtained using the alcohol and drug sections of the Addiction Severity Index (ASI; McLellan, Luborsky, O'Brien, & Woody, 1980). Using the self-report version of the ASI (Rosen, Henson, Finney, & Moos, 2000), participants were asked to indicate how many days in the past 30 days before treatment they used a variety of nonprescribed legal and illegal substances, including alcohol to intoxication, heroin, methadone, other opiates/analgesics (including prescription pain medications), barbiturates, sedative/ tranquilizers (including Valium, Xanax, and Ketamine), cocaine, amphetamines, cannabis, hallucinogens, inhalants, and tobacco. For drugs with therapeutic applications, participants were asked about nonprescribed use, for example, “How many days in the 30 days before treatment have you used nonprescribed opiates/analgesics?” For these analyses, the measure of days in the past 30 days of use of each substance was dichotomized into no or yes. 2.3.3. Pain Chronic pain prevalence and intensity were assessed using the Numeric Rating Scale of pain intensity (NRS-I; Farrar, Young, LaMoreaux, Werth, & Poole, 2001), an 11-point numeric rating scale ranging from 0 (no pain) to 10 (worst pain imaginable). This single-item measure is a good indicator of pain-related functioning. In a study using the NRS-I to measure changes in pain among patients experi-

encing chronic pain, Farrar et al.'s (2001) results suggest good external validity. For this study, participants were asked to rate their average level of pain during the past week. 2.3.4. Health status The Patient Health Questionnaire (Kroenke, Spitzer, & Williams, 2001) is a nine-item, self-administered measure of depressive symptoms based on the Diagnostic and Statistical Manual, Fourth Edition diagnostic criteria for major depressive disorder. For each of the nine items, scores range from 0 (not at all) to 3 (nearly every day). Participant responses were summed to produce a total scale score ranging from 0 to 27, with score ranges indicating the following severity of depressive symptoms: minimal (0–4), mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27). The Short Form 12 Health Survey (SF-12; Ware, Kosinski, & Keller, 1996) was also used to determine levels of physical and mental health functioning. Participants receive composite scores on both the Physical Component Summary (PCS) and Mental Component Summary (MCS; Ware, Kosinski, & Keller, 1995). For this study, the PCS scores ranged from 12.6 to 67.9, with higher scores indicating better physical functioning; the MCS scores ranged from 14.2 to 67.9, with higher scores indicating better mental functioning. The SF-12 has been shown to have good test–retest reliability, as well as good construct and criterion validity (Ware et al., 1996). Among our sample specifically, these measures had good reliability (PCS Cronbach's α = .647; MCS Cronbach's α = .940). 2.4. Data analyses After describing the rates of nonmedical PO use, we conducted bivariate analyses (chi-square and t tests) of the association between substance use, pain, and health status and the report of any past 30-day nonmedical PO use. Then, these same variables were entered into a multivariable logistic regression model to determine the relative impact of these variables on the log odds of endorsing nonmedical PO use. In conducting the regression model, we excluded indicators of past 30-day methadone, barbiturate, amphetamine, hallucinogen, and inhalant use due to low response rates (i.e., for each of these substances less than 10% of the total sample endorsing using these drugs within the past 30 days). We also excluded the variable for any opiate/analgesic use in the 30 days from the regression model because this was redundant with our indicator of any nonmedical PO use. However, we did conduct a supplementary analysis describing the association between the ASI item measuring nonmedical PO use and our primary indicator of nonmedical PO use. 3. Results More than two thirds (68%) of the sample reported the nonmedical use of POs in the past 30 days; 78.3% of women

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and 64.4% of men reported nonmedical PO use. The associations between demographic characteristics, alcohol and drug use variables, and nonmedical PO use are shown in Table 1, and the distributions of responses to the nonmedical PO use indicators among those with use are shown in Fig. 1. In bivariate analyses, those who reported the nonmedical use of POs in the past 30 days were more likely to be female, Caucasian, with lower levels of educational attainment, and currently partnered (married or living with someone as if married) compared with those who did not report recent nonmedical PO use. Age was not significantly related to nonmedical PO use. In terms of alcohol and drug use variables, for most of the substances examined, those who reported nonmedical PO use were more likely to report using alcohol or other drugs in the past 30 days than those who did not report nonmedical PO use. The only substances that were not significantly associated with nonmedical PO use were amphetamines, inhalants, and tobacco. Those who reported nonmedical PO use had significantly higher levels of depressive symptoms and pain intensity when compared with those who did not report nonmedical PO use in the previous 30 days. In addition, those who reported nonmedical PO use had significantly poorer physical and mental health functioning compared with those who reported no nonmedical PO use.

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regression model (see Table 2). As noted in Table 2, all analyses adjust for the simultaneous entry of all predictors within a single model, and subsequently, we report the adjusted odds ratios (AORs). These results indicate that those who were partnered were more likely to engage in nonmedical use of POs when compared with those who were not currently partnered (AOR = 2.51, 95% confidence interval [CI] = 1.07–5.92). Those individuals who had fewer average years of education were more likely to report nonmedical PO use compared with those with more years of education on average (AOR = 0.80, 95% CI = 0.68–0.95). Compared with those who did not report using any sedatives, hypnotics, or tranquilizers in the past 30 days, those who did report use were more likely to engage in nonmedical use of POs (AOR = 7.65, 95% CI = 2.02–28.91). Greater depressive symptoms were associated with a significantly increased likelihood of misusing POs (AOR = 1.09, 95% CI = 1.01–1.18). Nonmedical PO use was more likely in those who reported higher levels of pain intensity (AOR = 1.25, 95% CI = 1.09–1.42). In addition, as physical functioning (AOR = 0.94, 95% CI = 0.91–0.98) increased, the likelihood of nonmedical use of POs decreased. Gender, race, age, alcohol use to intoxication, heroin use, cocaine use, cannabis use, tobacco use, and mental health functioning were not significantly related to nonmedical PO use.

3.1. Multivariable analyses 3.2. Supplementary descriptive analyses The comparative associations of demographic, substance use, and functioning-related variables with nonmedical PO use were examined using a single multiple logistic

To compare our estimated prevalence of nonmedical PO use with what would be obtained using more traditional

Table 1 Association between participant characteristics and nonmedical use of prescription opiates among patients currently receiving residential substance abuse treatment (N = 351) Characteristic

Nonmedical use of prescription opiates (n = 238) M or %

No nonmedical use of prescription opiates (n = 113), M or %

Chi-square or t test

p

Gender (female) Race (non-Caucasian) Marital status (partnered) Age Years of education Any alcohol use to intoxication Any heroin use Any methadone use Any opiate/analgesic use Any cocaine use Any barbiturate use Any sedative/hypnotic/tranquilizer use Any cannabis use Any amphetamine use Any hallucinogen use Any inhalant use Any tobacco use Depressive symptoms Pain intensity Physical health functioning Mental health functioning

27.7% 29.0% 20.8% 35.2 (10.7) 11.6 (1.8) 52.1% 26.1% 9.2% 34.0% 46.2% 10.1% 29.0% 39.9% 5.0% 8.0% 2.5% 66.8% 12.18 (6.72) 4.71 (2.77) 45.73 (11.00) 38.28 (12.26)

16.1% 48.7% 11.7% 36.5 (11.2) 12.3 (2.7) 30.1% 12.4% 0% 7.1% 23.9% 1.8% 2.7% 16.8% 0.9% 1.8% 0% 60.2% 6.11 (5.86) 2.25 (2.59) 52.77 (8.28) 47.13 (12.37)

5.60 12.99 4.21 1.05 2.68 15.00 8.43 11.14 29.41 16.05 7.72 32.60 18.65 3.71 5.26 2.90 1.47 8.24 7.96 6.04 6.30

b.05 b.001 b.05 .294 b.01 b.001 b.01 .001 b.001 b.001 b.01 b.001 b.001 .54 b.05 .09 .23 b.001 b.001 b.001 b.001

Note. Measures of alcohol and drug use represent an indicator of whether participants used the substance within the past 30 days.

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Fig. 1. Response distributions for individuals with positive screen for nonmedical PO use (n = 238).

measures of nonmedical PO use, we examined the overlap between our measure of past 30-day nonmedical PO use (using six items from the COMM) and the item focused on past 30 day nonmedical pain medication use in the ASI. Our six-item measure detected more nonmedical PO use than the ASI indicator; only 89 individuals (25.4% of the sample) endorsed nonmedical PO use for the ASI item. Only 81 Table 2 Multivariate logistic regression analysis for predicting nonmedical use of prescription opiates based on participant characteristics Characteristics

AOR a

95% CI

p

Gender: female vs. males Race: non-Caucasian vs. Caucasian Marital status: partnered vs. not-partnered Age Years of education Any alcohol use to intoxication Any heroin use Any sedative/hypnotic/tranquilizer use Any cocaine use Any cannabis use Any tobacco use Depressive symptoms Pain intensity Physical health functioning Mental health functioning

1.70 1.61 2.51 0.99 0.80 1.63 1.37 7.65 1.77 1.94 0.96 1.09 1.25 0.94 0.99

0.73–3.96 0.83–3.15 1.07–5.92 0.96–1.03 0.68–0.95 0.81–3.32 0.56–3.34 2.02–28.91 0.84–3.75 0.91–4.16 0.49–1.89 1.01–1.18 1.09–1.42 0.91–0.98 0.96–1.03

.215 .162 .035 .675 .010 .174 .486 .003 .135 .088 .899 .021 .001 .005 .665

Note. Measures of alcohol and drug use represent an indicator of whether participants used the substance within the past 30 days. a

Analyses adjusted for the simultaneous entry of all predictors within a single model.

(34%) of the 238 individuals who were coded as having nonmedical PO use with our measure also endorsed nonmedical opioid use on the ASI, with a remaining 157 (66%) whose nonmedical PO use was detected by our measure did not endorse nonmedical PO use on the ASI. Our measure detected nonmedical PO use for 91% of the 89 individuals positive for nonmedical PO use on the ASI, and only 8 (9%) of those who report nonmedical PO use on the ASI were not coded as having nonmedical PO use using items from the COMM.

4. Discussion A substantial portion (68%) of adults presenting to a large residential SUD treatment program in the upper Midwest reported past 30-day nonmedical PO use. In addition, those who report nonmedical PO use also endorse more pain, greater depressive symptoms, and poorer physical functioning. For the most part, individuals endorsing nonmedical PO use did not report differential patterns of nonmedical use of other substances, although they were more likely to report recent nonmedical sedative use. Finally, these data indicate that common measures of nonmedical PO use (i.e., the ASI) may fail to detect nonmedical PO use in many patients with SUDs. The prevalence of nonmedical PO use was high in this study and approaches levels previously reported in methadone maintenance treatment (Brands et al., 2004; Rosenblum

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et al., 2007). The prior results are understandable given the fact that prescription pain medications are themselves opioids, and it is reasonable to expect that patients dependent on other opioids (e.g., heroin) may engage in nonmedical PO use from time to time. However, in the present sample (recruited from a treatment program designed for a mixed sample of substance users), the prevalence of nonmedical use of POs was also substantial, and nonmedical PO use, although more common in those using other opioids, was still prevalent in those who were not using heroin. Over 10 years of population-level data have documented the increasing rates of prescription of POs and the corresponding prevalence of nonmedical use in the general population (Paulozzi, 2006; Paulozzi & Ryan, 2006; SAMHSA, 2009). The high prevalence of nonmedical PO use in this study indicates that standard addictions treatment programs may find themselves on the “front lines” of this problem. In terms of clinical implications, treatment providers in residential addictions treatment settings should be aware that many patients could be using POs nonmedically, and our findings suggest that improved assessments with multiple questions to measure nonmedical PO use may identify a substantial number of individuals who could benefit from additional clinical interventions. On one hand, however, it is possible that among patients seeking treatment for SUDs, nonmedical PO use may not be associated with problems that exceed those that result from the nonmedical use of other substances. Nonetheless, the present data indicate that nonmedical PO use is associated with a pattern of more depressive symptoms, pain, and poorer physical functioning. This is consistent with the nonmedical use of POs as being a marker of greater severity in multiple domains of health and functioning. To better understand the clinical implications of the findings, it is crucial for future work to examine if SUD treatment patients who report baseline nonmedical use of POs report poorer treatment outcomes in terms of continued nonmedical PO use and other substance use than those who do not report nonmedical PO use. Until these data become available, SUD treatment providers should inquire about consumption of nonmedical POs and consider exploring with patients how their perception of POs relates to their motivation and self-efficacy to reduce substance use during and after treatment. Finally, the present findings highlight the importance of improving measurement of nonmedical PO use. This study utilized a number of items from the COMM (Butler et al., 2007) that were developed for the measurement of nonmedical PO use in pain treatment settings. These items could likely be improved for use in addictions treatment settings. However, we found that this measure identified nonmedical PO use in many more patients than were identified using a single item from the ASI, with few (∼9%) individuals who endorsed the ASI failing to endorse nonmedical PO use on the items from the COMM. Although further work is needed, these results suggest that, if patients are provided with a more detailed behavioral definition of

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nonmedical use than is currently used in most SUD-related measures, substantially more participants will endorse nonmedical use. This study has several limitations. First, data were collected at a single site that serves a mixture of urban and rural adults in Michigan. The extent to which these findings would apply to other addictions treatment programs in other locations is unknown. Although all participants were receiving long-term residential treatment, there are no data on type of treatment, disorder being treated, or length of treatment time for participants. In addition, no comprehensive measures of substance-specific, substance-related problems were available in this study. These measures are needed to examine if individuals who report nonmedical use of POs also report symptoms of a PO use disorder. All measures are self-report, and data were collected as part of a larger ongoing research project. It is possible that participants could be less likely to report nonmedical use of POs if asked about this during routine clinical care, particularly if they rely on the same health care system for a prescription for these medications. Despite these limitations, this descriptive study is the first of which we are aware of to document the high rates of nonmedical PO medication use in a residential addictions treatment program. The extent to which most residential addictions treatment programs are assessing for and directly addressing nonmedical PO use is unknown. However, these results highlight the importance of measuring nonmedical PO use in addictions treatment programs (particularly among women) and raise the possibility that treatment providers should consider how nonmedical PO use influences their treatment planning for their patients. References Anthony, J., Warner, L., & Kessler, R. (1994). Comparative epidemiology of dependence on tobacco, alcohol, controlled substances, and inhalants: Basic findings from the national comorbidity survey. Experimental and Clinical Psychopharmacology, 2, 244−268. Becker, N., Thomsen, A. B., Olsen, A. K., Sjogren, P., Bech, P., & Eriksen, J. (1997). Pain epidemiology and health related quality of life in chronic non-malignant pain patients referred to a Danish multidisciplinary pain center. Pain, 73, 393−400. Blazer, D. G., & Wu, L. T. (2009). Nonprescription use of pain relievers by middle-aged and elderly community-living adults: National survey on drug use and health. Journal of the American Geriatrics Society, 57, 1252−1257. Boyd, C. J., Teter, C., West, B. T., Morales, M., & McCabe, S. E. (2009). Non-medical use of prescription analgesics: A three-year national longitudinal study. Journal of Addictive Diseases, 28, 232−242. Brands, B., Blake, J., Sproule, B., Gourlay, D., & Busto, U. (2004). Prescription opioid abuse in patients presenting for methadone maintenance treatment. Drug and Alcohol Dependence, 73, 199−207. Butler, S. F., Budman, S. H., Fernandez, K. C., Houle, B., Benoit, C., Katz, N., et al. (2007). Development and validation of the Current Opioid Misuse Measure. Pain, 130, 144−156. Carise, D., Dugosh, K. L., McLellan, A. T., Camilleri, A., Woody, G. E., & Lynch, K. G. (2007). Prescription OxyContin abuse among patients entering addiction treatment. American Journal of Psychiatry, 164, 1750−1756.

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