Co-morbid pain and psychopathology in males and females admitted to treatment for opioid analgesic abuse q

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1 Pain 139 (2008) Co-morbid pain and psychopathology in males and females admitted to treatment for opioid analgesic abuse q Theodore J. Cicero a,, Michael Lynskey a, Alexandre Todorov a, James A. Inciardi b, Hilary L. Surratt b a Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8134, St. Louis, MO , USA b University of Delaware Research Center, Coral Gables, FL, USA Received 4 October 2007; received in revised form 12 March 2008; accepted 17 March 2008 Abstract The purpose of this study was to identify co-morbidity in a national sample (N = 1408) of males and females entering treatment for opioid abuse. Our sample was primarily white, lived in small urban, suburban or rural locations (80%), and was well-educated. Chronic pain was a symptomatic feature in over 60% of all subjects. Furthermore, 79% of male and 85% of female prescription opioid abusers indicated that their first exposure to an opioid was a legitimate prescription for pain which subsequently led 60 70% to misuse to get high. Our data also indicate that the use of prescription opioids to get high represents the end stage on a continuum of substance abuse, beginning at a very early age. The age of first alcohol use, getting drunk, smoking, use of marijuana, stimulants and other non-opioid prescription or illicit drugs occurred very early (13 19) in prescription opioid misusers/abusers, whose first use of opioids did not occur, on average, until age 22. Finally, most of the sample had sought treatment 3 or more times for substance abuse prior to the treatment admission in which the survey was completed. Physical and mental health were very poor in both male and female prescription opioid abusers, but females were more ill and dysfunctional than males in all physical and particularly emotional domains. Our results suggest that a small number of at risk opioid naive pain patients, who might abuse their therapeutically appropriate opioid analgesics, can be identified by assessing pre- and co-morbid substance abuse and significant psychopathology. Ó 2008 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. Keywords: TEDS; Co-morbid; Psychopathology; Misusers/abusers; Substance use; Pain 1. Introduction q Supported in part by NIH Grant DA Corresponding author. Tel.: ; fax: address: Cicerot@wustl.edu (T.J. Cicero). Numerous studies have found a surge in the abuse of prescribed opioid analgesics in the United States over the past decade [6 10,12,16,22,23]. For example, in data collected in the Treatment Episode Data Set (TEDS), a survey mandated by the Substance Abuse and Mental Health Services Administration (SAMHSA) for all publicly funded treatment centers [12], admissions related to prescribed opioid analgesics rose from 15,611 in 1994 to 63,243 by This rate of increase dwarfed that for any other prescribed or illicit drug. Although there is some evidence to indicate that illicit (i.e., heroin) opioid abuse and problem use of opioid analgesics are correlated with poly-substance abuse, pain and mental health problems [13,24,25], we know of no studies of co-morbidity in individuals with a diagnosis of opioid abuse/or dependence, whose misuse has progressed to the need for in-patient or out-patient treatment. In addition, we are unaware of any studies of prescription opioid abuse in which gender differences /$34.00 Ó 2008 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. doi: /j.pain

2 128 T.J. Cicero et al. / Pain 139 (2008) in co-morbidity have been examined. In the present studies, we examined several important questions in 1408 patients admitted to one of 95 treatment programs across the country: first, is chronic pain an important co-morbid factor in prescription opioid abusers?; second, is early licit and illicit drug use/misuse a predictor of subsequent opioid use?; third, was the first exposure to opioid analgesics the result of a legitimate prescription for pain?; fourth, did this initial therapeutic exposure to opioids lead to their non-medical use to get high?; and, finally, is there evidence of other co-morbid physical and mental health problems and are these gender dependent? The most fundamental question in any study of moderate to severe pain, requiring opioid analgesics for relief, is whether and/or to what extent iatrogenic dependence develops. The existing literature is contradictory [1] with estimates ranging from less than 1% to over 30% of pain patients treated with opiate analgesics. Our studies do not directly address this issue because the only way to do so would be a very large and perhaps implausibly complex prospective study which would have to control for many variables. Rather, in this retrospective study, we have assumed that iatrogenic abuse occurs in some unknown percentage of pain patients. Furthermore, we postulate that pre-morbid health issues, particularly psychopathology, substance abuse/misuse at an early age (alcohol, nicotine, other non-opioid prescription drugs and illicit drugs), and a history of treatment for substance abuse, places these individuals at high risk for abuse of their therapeutically appropriate medicines. In contrast to the TEDS database, which samples only publicly funded treatment centers, we biased our sampling toward private, for pay treatment centers (70 80%) to provide not only a complementary data set to TEDS, but to provide access to individuals who have the resources to cover their care. Since past studies have shown that prescription opioid abusers are often more affluent, well-educated and employed- [6 11] presumably with employee provided medical insurance- it seems probable that many would seek treatment in private rather than publicly subsidized treatment centers. 2. Materials and methods 2.1. Recruitment of subjects As shown in Fig. 1, the treatment centers were balanced geographically [10,11] to cover most of the country with good representation of large urban, suburban and rural treatment centers. Each of the treatment specialists was asked to recruit as many patients as possible who had a diagnosis of Fig. 1. Location by 3 digit zip code (first 3 digits) of the treatment centers (red circles) and patients who completed the drug use survey (blue circles). The inset shows the distribution of patients filling out questionnaires (N = 1408) stratified by the population of their residential zip code.

3 T.J. Cicero et al. / Pain 139 (2008) prescription opioid analgesic abuse or dependence using the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) [2]. Inclusion criteria were very broad: first, those people who met DSM-IV criteria for substance abuse whose primary drug was a prescription opioid (i.e., not heroin); and, second, use of prescription opioid drugs to get high at least once in the past 30 days prior to treatment. The only exclusion criteria were those individuals who did not meet these criteria and any individual who listed heroin as their primary drug. Overall, 85% of the patients approached by the treatment counselors completed surveys and submitted them. The patients were asked to complete a detailed survey instrument, covering: demographics; licit and illicit patterns of drug use; diagnostic criteria for alcohol and opioid abuse or dependence (DSM-IV criteria; e.g., loss of control of drinking or drugging, disruption of everyday activities as a consequence of use, family and friend complaints about abuse, withdrawal, craving, and so forth); the Fagerström test for Nicotine Dependence [14]; general health status using the SF-36v2 Health Survey; chronic non-withdrawal bodily pain and its intensity (scale of 1 10 with 1 being none and 10 the worst possible pain); and, whether they were currently being treated for a psychiatric condition. Completed survey instruments were identified solely by a unique case number and were sent directly to Washington University School of Medicine. The treatment specialists did not see the detailed responses of their patients/clients Statistical analyses Given the fact that some clinics were very large and some much smaller, the number of surveys completed varied widely depending upon the size of the clinical practice. Thus, we used generalized Estimating Equations (GEEs), as a practical method, with reasonable statistical efficiency, to analyze clustered data with high correlation. SAS proc GENMOD procedure was used to run GEE models in this study. For binary data, Odds Ratios (ORs) were estimated in the GENMOD procedure. In all cases, the females/males ratio was defined as one. For continuous variables (e.g., age of first use), t-tests for independent samples were used. For scoring the SF-36v2, all but one of the 36 items (self-reported health transition) were used to score the eight SF-36v2 scales. Each item was used in scoring only one scale. The scales were pooled for the summary factors: physical component summary (PCS) and mental component summary (MCS). With the release of SF-36v2, norms were updated using data from the 1998 National Survey of Functional Health Status (NSFHS) and norm-based scoring (NBS) algorithms were introduced [15]. Norm-based scoring employs a linear T-score transformation with mean = 50 and standard deviation + 10, which makes it possible to meaningfully compare scores for physical and mental health summary measures in the same graph. 3. Results 3.1. Demographics of the sample The demographics and drug use histories of the sample (N = 1408) are shown in Table 1. Males represented a higher proportion (55%) of the sample than females. Table 1 Demographics of national prescription opioid abusers (N = 1408) Total Male Female n = 1408 n = 773 n = 605 Racial preference White 85.48% 88.85% 81.49% Prior number of times 3.05 ± ± ± 0.31 treatment sought Age at current treatment ± ± ± 0.46 Education Some college 50.53% 45.25% 57.63% Source Dealer 69.40% 74.03% 63.48% Forged Rx 10.15% 9.73% 10.93% Stolen 23.47% 25.70% 21.18% Doctor 62.86% 58.80% 66.98% Friend/relative 68.39% 66.45% 70.75% ER 29.03% 27.06% 31.33% Internet 7.24% 7.80% 6.70% Diagnosed abuse Alcohol abuse a 43.24% 43.16% 43.10% Nicotine dependence b 69.36% 65.77% 73.61% Age of first psychotropic use Alcohol ± ± ± 0.25 Marijuana ± ± ± 0.28 First Intoxication ± ± ± 0.43 Nicotine ± ± ± 0.39 Powdered Cocaine/Crack ± ± ± 2.00 Stimulants c ± ± ± 1.40 Benzodiazepines ± ± ± 2.02 Prescription Opiates ± ± ± 0.66 Heroin ± ± ± 0.61 Heroin first opioid 8.77% 8.70% 8.33% a Alcohol abuse as defined by DSM-IV criteria. b Nicotine dependence as defined by Fagerstöm Nicotine Dependence Test [14]. c Stimulants include Adderall, Amphetamines, Methamphetamines and Ritalin. Females significantly different than males (p < 0.05). Females significantly different than males (p < 0.01). The vast majority of males and females identified themselves as white but females were significantly more racially diverse than males (OR = 1.80, Reference group = Male, Minority = 1, White = 0, p < 0.01). Females sought treatment at a significantly (p < 0.01) older age than males. The vast majority of the population had sought substance abuse treatment 3 or more times (males significantly more often than females) prior to the admission to a treatment program at which time the survey was completed. About 92% of all males and females had at least a high school degree; over 57% of the females had some college, a college degree, or advanced degree, which was significantly higher (OR = 1.65, Reference group = Male, College = 1, No College = 0, p < 0.01) than males (45.25%). As shown in Fig. 1, despite the fact that treatment centers were equally represented in rural, suburban, small and large urban areas, almost 80% of the patients completing

4 130 T.J. Cicero et al. / Pain 139 (2008) surveys resided in zip codes in small urban (<250,000) or rural (<100,000) areas Drugs of choice and substance abuse histories Fig. 2A shows the licit opioid drugs and two representative other drug classes, benzodiazepines and stimulants (for the most part Ritalin/Adderall), used to get high in the last 30 days. Panel B shows the illicit drugs used for that purpose in this same time period. It is obvious that those individuals, with a primary diagnosis of opioid abuse, are poly-substance abusers of both licit and illicit drugs; males tended to use more drugs more often than females. In fact, over 90% of those who misused opioid drugs in the past 30 days also misused one or more other licit or illicit drug. Only 8% of the total population used only one opiate to get high and used no other licit and illicit drug Co-morbidity with alcohol abuse, nicotine dependence and other substances of abuse Table 1 shows that over 40% of both males and females satisfied DSM-IV criteria for alcohol abuse. Nearly 70% of the sample of prescription opioid users smoked regularly and most of these met criteria for nicotine dependence: 66% of all male and 74% of female prescription opioid abusers. As shown in Table 1, the age of first use of nicotine, alcohol, marijuana, licit (e.g., Adderall and Ritalin) and illicit (e.g., cocaine/crack) drugs occurred at a very early age (13 19) well before the initial use of prescription opioids (22 years of age). It also appears that prescription opioid abuse led to the initial use of heroin: over 90% of the total population of prescription opioid misusers that used heroin to get high indicated that their use of prescription opioids to get high led them to use heroin. Conversely only 8 9% of all subjects indicated that heroin was the first opioid they used to get high Source of drugs As shown in Table 1, friends/relatives, dealers, and doctor s prescriptions, respectively, were the most common source of drugs, with well over 60% of the population endorsing one or more of these sources (Table 1). However, there were substantial gender and age-related differences in the use of dealers and doctor s prescriptions. As shown in Fig. 3, although dealers were used by nearly 90% of males and females under age 20, there was a significant drop to less than 50% of those in the oldest age group. Overall, males were more likely (OR = 1.64, reference group = female, dealer yes = 1, dealer no = 0, p < 0.01) than females to use a dealer to obtain prescription opioids. Doctor s prescriptions, as a source of drugs, displayed the opposite effect (Fig. 3). Females were more likely than males (OR = 1.71, reference group = male, doctor Rx yes = 1, doctor Rx no = 0, p < 0.01) to use doctor s prescriptions to obtain opioids across all age groups: over 40% of females under the age of 20 got a prescription for an opioid analgesic compared to only 21% of the males. The use of doctor s prescription increased with age such that it was a major source of drugs in both sexes over 40. Forged (10%) or stolen prescriptions (<25%) were used relatively infrequently as a source of drugs and the internet rarely (<8%) Mental and physical health status As shown in Fig. 4, male and female prescription opioid abusers had significantly poorer physical and mental health than their respective national norms on the SF-36v2. While this was true for both sexes, as shown in Fig. 4 and Table 2, for all 8 SF-36v2 domains, females were more ill and dysfunctional than males. A. PRESCRIPTION DRUGS B. ILLICIT DRUGS 70.00% 60.00% 50.00% 40.00% 30.00% Males Females 60.00% 50.00% 40.00% 30.00% Males Females 20.00% 10.00% 20.00% 10.00% 0.00% 0.00% Benzodiazepine Buprenorphine Fentanyl Hydrocodone Hydromorphone Methadone Morphine Oxycodone OxyContin Ritalin/Adderall Tramadol Amphetamine Crack Ecstasy Heroin Marijuana Methamphetamine Powdered Cocaine Fig. 2. Drugs used in the last 30 days expressed as percent of total. Females significantly lower than males (p < 0.05). Females significantly lower than males (p < 0.01).

5 T.J. Cicero et al. / Pain 139 (2008) A. DEALERS B. PHYSICIAN S PRESCRIPTION % 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 80.00% Males Males Females 70.00% Females 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% < AGE 0.00% < AGE Fig. 3. Percent of males and females who used a dealer (left panel) or a doctor s prescription as a source of drugs by age group. Significantly (p < 0.05) different than males. Significantly (p < 0.01) different than males Pain and first use of opioids As shown above and in Table 3, chronic bodily pain was a significant co-morbid factor in both males and females. Moreover, 79% of males and 85% of females indicated that their first exposure to an opioid was a legitimately prescribed opioid analgesic for pain. The average age was 21.5 (±0.72) for males and 22.3 (±0.68) for females. Over 62% of all males and 70% of females indicated that their first use of opioids for pain led them to use the drugs to get high even when their pain subsided Co-morbid psychopathology While the SF-36v2 health survey suggested poor general physical health in prescription opioid abusers, as shown in Fig. 4 and Tables 2 and 3, the most striking difference was the extremely poor mental health scores in all prescription opioid users compared to national norms (p < 0.001). However, females clearly had significantly (p < 0.01) more psychopathology than males. As shown in Table 3, 66% of females and 54% of the males self-reported that they had been treated for a psychiatric disorder in the past 12 months. Depression was the most frequent diagnosis followed by anxiety disorders, bipolar disorder and attention deficit disorders; females had much higher rates of anxiety disorders than males (OR = 1.74, reference group = male, anxiety yes = 1, anxiety no = 0, p < 0.05), while males had more attention deficit disorders than females (OR = 1.49, reference group = female, ADD yes = 1, ADD no = 0, p = 0.27) Comparison between those with pain vs. non-pain We asked a subset of 426 of our population (1408) to indicate the main reason for their first use of opioid Rx Males Rx Females National Norm Males National Norm Females Physical Functioning Role- Physical Body Pain General Health Vitality Social Functioning Role- Emotional Mental Health Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 Factor 8 Fig. 4. SF-36v2 standardized scores for males and females for both the national norms (lines) and males vs. females (bars). p values are shown in Table 2. Both males and females differed significantly (p < 0.001) from national norms. Females significantly worse than males (p < 0.05). Females significantly worse than males (p < 0.01).

6 132 T.J. Cicero et al. / Pain 139 (2008) Table 2 Results of SF-36v2 for males and females Mean difference (female male) Composite scores PCS (Physical Component Score) MCS (Mental Component Score) 95% CI p value (one-tailed) <0.001 Eight scales Factor 1 physical functioning Factor 2 roles, physical Factor 3 bodily pain Factor 4 general health Factor 5 vitality <0.001 Factor 6 social <0.001 functioning Factor 7 role, <0.001 emotional Factor 8 mental health <0.001 Females significantly more ill than males (p < 0.05). Females significantly more ill than males (p < 0.01). Table 4 Comparison of patients in which pain played a role in the initiation of opioid use (N = 426) PAIN NO PAIN Total n = 197 a Total n = 61 a Gender Male 47.21% 62.30% Female 51.27% 34.43% % Total 46.24% 14.32% population (N = 426) Age Opioid first use ± ± 0.60 Past 30 day use Opioids 77.16% 83.61% To get high Illicit drugs b 35.53% 65.57% Source Dealer 54.44% 86.67% Stolen 16.45% 28.26% Doctor 77.14% 38.00% SF-36v2 Physical component score Mental component score a Remainder of sample selected both pain and non-pain related reasons for first use (N = 168, 39.44% of total population). b Illicit drug use does not include marijuana. Females significantly different than males (p < 0.05). Females significantly different than males (p < 0.01). analgesics. As shown in Table 4, over 86% of the sample indicated that pain alone (45%) or pain and euphoria (40 45%) served as the motivation for their initial use (data not shown). Only 14% indicated that pain was not a factor in the first use of analgesics. Table 4 shows that there were many differences between those for whom pain served as the sole motivation for initial opioid use (pain group), and those in which pain was not a factor (non-pain group). Most prominently, females were a slight majority in the pain group, whereas in Table 3 Physical and mental co-morbidity in national opioid abusers Total Male Female Chronic pain 61.48% 65.84% 57.65% Self-reported pain score 5.41 ± ± ± 0.21 Reason for first use 81.84% 79.23% 84.74% pain Rx Age of first use of opioid ± ± ± 0.68 for pain First use of opioid for 65.81% 62.18% 69.79% pain led to misue Self-identified 60.70% 54.73% 66.15% psychopathology Depression 72.05% 68.14% 75.74% Anxiety 55.29% 47.37% 61.03% Bipolar disorder 27.53% 23.85% 30.08% Attention deficit 14.92% 17.12% 12.12% disorder Other 10.79% 11.32% 10.00% Females significantly different than males (p < 0.05). the non-pain group, males overwhelmingly dominated. In addition, those in the non-pain group were much younger and, as shown in Table 4, used many more drugs licit and illicit to get high than did the pain group. In terms of the source of drugs, the non-pain group used dealers and stole drugs much more frequently than those in the pain group, whereas the pain group used doctors prescriptions twice as often as those not in pain. Lastly, the non-pain group had average physical well-being compared to the national norms, whereas the pain group had much poorer physical health composite scores in the SF-36v2. Both groups showed relatively poor mental health composite scores, but those in pain had much poorer scores than those in the non-pain group. 4. Discussion We believe this is the first study in which co-morbidity has been examined in diagnosed prescription opioid abusers entering a treatment clinic, particularly in the fast growing population of females. Several previous studies have examined some of these issues in problem misusers of opioid analgesics [5,7,13,17,18,20,25 27], but diagnostic criteria were seldom used and sample sizes were too small to examine all variables, notably gender differences. In the present study, our sample size was very large and permitted meaningful comparisons across a large number of domains. We found that: First, a high percentage of prescription opioid abusers experi-

7 T.J. Cicero et al. / Pain 139 (2008) ence moderate to severe chronic pain (ffi60%) and have a low quality of life as reflected in very poor physical and mental health scores in the SF-36v2; second, in this context, approximately 45% of the total sample indicated that their pain was the sole factor in their initial use of opioids, and in nearly the same fraction of the patients it was at least a contributing factor; third a small subset of the population (14%) reported that factors other than pain motivated their first use of opioids (e.g. to get high and experimentation) and these people were vastly different than those in which pain was the primary factor in the first use of opioid analgesics; fourth 60 70% of those individuals who used opioids for pain reported that this led them to use the drugs to get high even when the pain was gone; and, finally, those individuals seeking treatment for opioid abuse, had very high rates of alcoholism and nicotine dependence, 3 or more prior treatments for substance abuse, early exposure (13 19 years of age) to both licit and illicit and had significant psychopathology. We hypothesize that at risk pain patients, who might abuse their opioid analgesics, can be identified by assessing pre- and co-morbid substance abuse and significant psychopathology. Our finding that extensive use of alcohol, nicotine, marijuana, stimulants and other licit and illicit drugs preceded the first use of opioids lends support to the concept of gateway drugs. Furthermore, our data suggest that the use of heroin to get high is rarely the first drug to be used in this fashion: in fact, less than 8% of the entire sample indicated that their first use of any opioid to get high was heroin. Rather, of the total population who used heroin to get high, 90% indicated that opioid analgesics to get high represented their initial use which then led to the subsequent abuse of heroin. Our studies also indicate that there may be two separate populations of opioid analgesic abusers: those in which pain was a factor in the initiation of their use and misuse; and those in which euphoria served as the primary motivating factor from the onset. While our data are preliminary, they suggest: first, there are gender differences between the two groups females represent the majority of those in whom pain was the reported motivation for first use of opioids, while males overwhelmingly predominated in those in which euphoria was the motivating factor; second, those seeking euphoria had much better physical health (comparable to population norms) than those in which pain was the motivating factor in initial use; third, opioids were obtained from very different sources; and fourth, those in which euphoria was their goal in initial use also used more licit and illicit drugs for non-therapeutic purposes than those in pain. Based on these preliminary data we suggest that a large scale epidemiological study be carried out to assess the already identified and additional differences between these two groups. An unintended consequence of the studies reported in this paper is that physicians may become even more wary of using opioids in the appropriate treatment of pain thereby exacerbating the public health crisis of the massive under-treatment of pain because of fears of iatrogenic dependence. Viewed in an appropriate context, however, we believe our data actually should remove some of the fear in using these drugs by identifying risk factors which differentiate patients, in whom opioid use is not only appropriate but necessary, from those who may be at high risk for potential abuse. Obviously opioids need to be used carefully and monitored closely in those with prior histories of alcohol and substance abuse and significant psychopathology. Our studies also indicate that the rapidly growing population of female prescription drug abusers differs in many respects from males. They have much poorer general health and significantly greater psychopathology than males. Given that females, particularly older ones, also use doctor s prescriptions as a source of drugs much more frequently than males (Fig. 2), physicians need to be particularly attentive to abuse potential in women and may need to structure pain management programs somewhat differently for them. It needs to be strongly cautioned that we focused only on prescription opioid abusers in these studies and, consequently, our results cannot and should not be generalized to the entire population of individuals who have chronic pain and seek treatment for it. All our data suggest is that some persons in pain, who receive opioid analgesics, abuse them. From this observation alone, one cannot conclude anything about what percentage of the total population of pain patients treated with opioid analgesics evolve into substance abusers since we did not sample all pain patients. The literature regarding iatrogenic dependence is confusing and inconclusive and, as a result, the incidence of such therapeutically induced dependence ranges from significantly less than 1 to over 30% [1]. Our data shed no light on this contentious issue, but do provide physicians with some help in identifying high risk patients in whom opioids should be used carefully. The question left unanswered by our study is does the existence of pain and poor mental health lead to self-medication with opioid analgesics, or does the abuse of opioids cause a progressive decline in physical and mental health? While only prospective, longitudinal studies will be able to address this question, we favor the interpretation that pre-existing physical and psychiatric disturbances lead to self-medication with alcohol, nicotine, opioids and other prescribed and illicit drugs. The most significant observation supporting this conclusion is that 80% of the prescription opioid abusers claimed they first used opioids legitimately for pain, which suggests at the very least that,

8 134 T.J. Cicero et al. / Pain 139 (2008) as shown in an earlier preliminary study [18], pain was a predisposing factor in introducing them to opioids which subsequently escalated to abuse. Our results are also consistent with literature indicating that preexisting psychopathology predicts, as we found, very early use of alcohol, first age of intoxication, nicotine and marijuana use [3,15,20,21]. It seems reasonable to postulate that opioid abuse, like misuse of other drugs, may also reflect pre-existing psychiatric conditions. However, certainly the abuse of alcohol, nicotine, opioids and other drugs can only further erode physical and mental health. Our finding that doctor s prescriptions play such a prominent role as a source of opioid analgesics to get high, particularly in women and older adults is disturbing. This may reflect the fact that primary care physicians, who prescribe most of the opioid analgesics in this country, are unable to distinguish legitimate patients from those trying to scam them. Compounding this problem, general health status decreases somewhat as a function of age, and hence to most practitioners it is intuitively obvious that older patients will require more medications than younger ones. In addition, older people are much more risk averse than younger ones and, thus, may shun illegal sources of drugs, such as dealers and theft, in favor of legitimate ones such as doctors. No matter the contributing factors, our findings strongly indicate that doctors are inadvertently serving as one significant source of abused prescription opioids, particularly in women of all ages and both men and women over the age of 40. There is clearly a strong need for more education about substance abuse, including the risk factors identified in our study. There are currently several available resources (for a recent review see [19]) for physicians regarding substance abuse in their pain patients, and the present results represent an extension of these efforts. Hopefully, a checklist of some sort can be developed for physicians to warn them about problematic use of opioids by their patients. There are many limitations in the approach we used in this study. Most notably, our sample reflects only those individuals who sought treatment for their abuse problems and had the financial resources to pay for their care. This no doubt contributes to the demographics we observed. However, when compared to the Treatment Episode Data Set (TEDS) [12], which is based on patients admitted to publicly funded treatment centers, there are many similarities in demographics and drug usage patterns. Obviously, neither system sheds any light on recreational users or those who do not opt for treatment, and, hence, are limited in this respect. Finally, our survey instruments were self-administered and thus all of the limitations of such methodology need to be recognized [3,4,15,21]. Acknowledgments Supported in part by NIH Grant (DA020791). Although Drs. Cicero, Inciardi and Surratt serve as consultants to a number of pharmaceutical firms that market opioid analgesics, there is no overlap at all in terms of areas of consultation and this research nor was any funding provided by a pharmaceutical firm. Theodore J. Cicero had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. References [1] Adams EH, Breiner S, Cicero TJ, Geller A, Inciardi JA, Schnoll SH, et al. A comparison of the abuse liability of tramadol, NSAIDs, and hydrocodone in patients with chronic pain. J Pain Symptom Manage 2006;31: [2] American Psychiatric Association. Diagnostic and statistical manual of mental disorders. Washington, DC: American Psychiatric Association; [3] Aquilino W. Interview mode effects in surveys of drug and alcohol use: a field experiment. Public Opin Q 1994;58: [4] Aquilino WWDL. Substance use estimates from rdd and area probability samples: impact of differential screening methods and unit non-response. Public Opin Q 1996;60: [5] Bourgois P, Martinez A, Kral A, Edlin BR, Schonberg J, Ciccarone D. Reinterpreting ethnic patterns among white and African American men who inject heroin: a social science of medicine approach. PLoS Med 2006;3:e452. [6] Cicero TJ, Adams EH, Geller A, Inciardi JA, Munoz A, Schnoll SH, et al. A postmarketing surveillance program to monitor Ultram (tramadol hydrochloride) abuse in the United States. Drug Alcohol Depend 1999;57:7 22. [7] Cicero TJ, Dart RC, Inciardi JA, Woody GE, Schnoll S, Munoz A. 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