Journal of Psychoactive Drugs, 47 (1), 1–9, 2015 Copyright © Taylor & Francis Group, LLC ISSN: 0279-1072 print / 2159-9777 online DOI: 10.1080/02791072.2014.991008

Frequency and Risk of Marijuana Use among Substance-Using Health Care Patients in Colorado with and without Access to State Legalized Medical Marijuana Melissa K. Richmond, Ph.D.a ; Fred C. Pampel, Ph.D.b ; Laura S. Rivera, Ph.D.c ; Kerryann B. Broderick, B.S.N., M.D.d ; Brie Reimann, M.P.A.e & Leigh Fischer, M.P.H.f

Abstract — With increasing use of state legalized medical marijuana across the country, health care providers need accurate information on patterns of marijuana and other substance use for patients with access to medical marijuana. This study compared frequency and severity of marijuana use, and use of other substances, for patients with and without state legal access to medical marijuana. Data were collected from 2,030 patients who screened positive for marijuana use when seeking health care services in a large, urban safety-net medical center. Patients were screened as part of a federally funded screening, brief intervention, and referral to treatment (SBIRT) initiative. Patients were asked at screening whether they had a state-issued medical marijuana card and about risky use of tobacco, alcohol, and other illicit substances. A total of 17.4% of marijuana users had a medical marijuana card. Patients with cards had higher frequency of marijuana use and were more likely to screen at moderate than low or high risk from marijuana use. Patients with cards also had lower use of other substances than patients without cards. Findings can inform health care providers of both the specific risks of frequent, long-term use and the more limited risks of other substance use faced by legal medical marijuana users. Keywords — marijuana, medical marijuana, prevention, SBIRT

Marijuana use has been increasing in the US population since 2007 and an estimated 7.6 million persons aged 12 or older use marijuana daily or almost daily (SAMHSA 2013). NIDA (2002) estimates that 9% of people who a Director

use marijuana will become dependent. In the US, marijuana disorders were the most prevalent of illicit substance use disorders (Compton et al. 2004). Nationally, 24% of those seeking treatment for substance use problems did e Director of Integrated Care Programs, Access Management Services, LLC, Colorado Access, Denver, CO. f Director, SBIRT Colorado, Peer Assistance Services, Inc., Denver, CO. Please address correspondence to Melissa K. Richmond, OMNI Institute, 899 Logan St., Denver, CO 80203; phone: 303-839-9422; email: [email protected]

of Research and Evaluation, OMNI Institute, Denver,

CO. b Research Professor and Director, Population Center, University of Colorado Boulder, Boulder, CO. c Senior Researcher, OMNI Institute, Denver, CO. d Associate Professor of Emergency Medicine, Denver Health Medical Center, Denver, CO.

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so for marijuana use, and marijuana users made up 59% of those with an illicit drug dependence (SAMHSA 2013, Figures 7.2 and 7.8). As states legalize marijuana for medical or recreational purposes, availability, access, and use are likely to increase (Cerdá et al. 2012). Interventions to prevent harm from dependence, driving risk, and respiratory disease associated with long-term use become increasingly important. However, efforts to identify and treat problematic marijuana use through public health programs face a changing population of users. At the federal level, marijuana remains a Schedule I Controlled substance with no recognized medical value; yet, 23 states and the District of Columbia have approved medical marijuana programs (NCSL 2014), and two states (Colorado and Washington) have legalized marijuana for recreational use. The Pew Research Center reports that 52% of Americans favor legalization and 60% oppose enforcement of federal laws in states that allow marijuana use (Pew Research 2013). The legalization and public support for medical marijuana use suggest that substantial numbers of marijuana users have legal access to the drug for medical reasons. According to the Pew poll, among those having used marijuana in the last year, 53% reported doing so for a medical issue (30% solely for medical use; 23% for medical and recreational reasons). In California, 250,000-350,000 adults possess physician recommendations for medical use of marijuana (Kleber & DuPont 2012). In Colorado, more than 100,000 patients possess valid ID cards for use of medical marijuana (CDPHE 2013). Among this population, 67% are male, the average age is 42, and 94% report severe pain as the debilitating condition. About 800 (5%) of Colorado’s licensed physicians authorize cards. Despite the growing number of medical marijuana users, studies say little about how they differ from other users in level of risk, negative consequences, and use of other substances. Most research on legalization has focused on whether the laws have the unintended side-effect of increasing illicit marijuana use among youth (Friese & Grube 2013; Lynne-Landsman, Livingston & Wagenaar 2013; Harper, Strumpf & Kaufman 2012; SalomonsenSautel et al. 2012; Wall et al. 2011), rather than on the consequences for lawful use. A study of 350 patients at a medical marijuana dispensary in Oakland, California, found that 88% reported daily marijuana use (Janichek & Reiman 2012). Another study of patients at a dispensary in Berkeley, California, found that 40% reported using marijuana as a substitute for alcohol, 26% as a substitute for illicit drugs, and 66% as a substitute for prescription drugs (Reiman 2009). Several other studies similarly describe medical marijuana users (Bottorff et al. 2011; Reinarman et al. 2011; Aggarwal et al. 2009; Reiman 2007; O’Connell & Bou-Matar 2007). Ilgen et al. (2013) compared use of marijuana and other substances among returning medical marijuana users to those applying for a medical marijuana Journal of Psychoactive Drugs

card for the first time. However, none of these studies compare patterns of marijuana use for those who have access to the substance through a medical program to those who do not. The health care community lacks background knowledge to determine how, if at all, interventions should differ for marijuana users when they have access through state-approved medical programs. More research is needed to understand the heterogeneous population of marijuana users and provide information that can help reduce the uncertainty of the health care community in responding to use of medical marijuana. Marijuana use—particularly when problematic or combined with use of other substances—can be addressed through screening, brief intervention, and referral to treatment (SBIRT). The SBIRT process is part of the nation’s strategy to combat drug abuse (ONDCP 2013), addressing the continuum of care by identifying and intervening with individuals who are engaging in risky patterns of use. Consistent with a public health approach, services are implemented in non-substance-use treatment settings such as emergency departments, primary care offices, trauma units, and community health centers (SAMHSA 2011). While additional research is needed (Saitz et al. 2010), several studies support the promise of SBIRT to identify and reduce harmful marijuana use (Bernstein et al. 2009; Madras et al. 2008; WHO 2008; McCambridge & Strang 2004). SBIRT has been part of Colorado’s strategy to address the continuum of care for substance abuse since 2006, when the state was awarded a Substance Abuse and Mental Health Services Administration (SAMHSA) grant to disseminate universal screening as a standard of health care. SBIRT Colorado takes a comprehensive approach and screens for abuse of multiple types of substances. In response to the proliferation of Colorado’s medical marijuana industry in the late 2000s, SBIRT Colorado incorporated screening for medical marijuana users as part of its protocol. This screening assesses whether patients have a card to access medical marijuana along with questions about use of tobacco, alcohol, and other illicit drugs. This was done to identify patients who may be using marijuana in unhealthy ways, even if accessed through a state-sanctioned program. The current study was designed to compare marijuana users with and without a medical marijuana card. However, in 2012, Colorado voters approved a referendum to legalize limited recreational use of marijuana. The recent change in the law makes it difficult for screening tools to distinguish legal and illegal use of marijuana or to screen for casual recreational marijuana users who began using in response to legalization. The data nonetheless remain valuable for comparing marijuana users with and without a card among those screening positive under the SBIRT Colorado protocol. 2

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The goal of the present study is to examine whether severity of risk of marijuana and other substance use differed for patients in Colorado with and without state-issued medical marijuana cards. The study used data from SBIRT Colorado to answer the following questions: (1) What proportion of patients screening positive and using marijuana had access through the state’s medical marijuana program? (2) Do positive-screened patients with medical marijuana cards use marijuana more frequently or at higher risk levels than positive-screened patients without cards? (3) Do positive-screened patients with medical marijuana cards use other substances at risky levels more frequently than positive-screened patients without cards?

question on having a medical marijuana card should accurately identify those who have applied for and received a physician’s approval and state certification for use of marijuana for medical purposes. However, the question on illicit drug use may miss casual marijuana users who do not consume other substances. Non-cardholding marijuana users, if they view their use as legal or non-problematic, may have answered negatively to all questions and been missed by the screen. The brief screen thus has special value for comparing marijuana users with and without a card who are polysubstance users or also use tobacco, alcohol to excess, or other illicit drugs. Health educators at each of the sites approached patients at bedside or in the examination room and obtained verbal consent to participate in the study. The health educator then obtained demographic information using Section A of the Government Performance and Results Act (GPRA) tool as a part of grant funding requirements (CSAT 2010). When patients had a negative brief screen, health educators verified their responses. When patients had a positive brief screen, health educators administered the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST v3.0) to assess the degree of risky use across multiple substances (Humeniuk et al. 2010). Health educators also administered Section B of the GPRA as part of funding requirements, which includes a question on the number of days in the past 30 that the patient used marijuana (CSAT 2010). When patient volume was heavy, health educators prioritized approaching patients who screened positive on the brief screen. The ASSIST measures problem use of 10 substance categories, including cannabis (Humeniuk et al. 2010; WHO 2002). Patients are assigned a risk score for each substance category from 0 to 39. Patients who screened negative on the brief screen were assigned a score of 0 on the ASSIST. ASSIST scores are derived from seven questions that ask about past 90-day use and associated consequences (e.g., led to health, social, legal, or financial problems; failing to do what is normally expected; a relative or friend expressing concern about use; trying and failing to control, cut down, or stop use). Patients are classified into three levels of risk (no/low, moderate, or high) for each substance area. To be scored high risk, users must endorse items that indicate experiencing negative consequences from use. The three levels are used to identify type of intervention needed, with no or low risk requiring no intervention, moderate risk requiring brief intervention, and high risk requiring a brief intervention accompanied with a referral for specialized services. Health educators used an electronic tablet or desktop computer to record patient data, which were uploaded to a secure database. Patients were assigned a unique identifier to protect confidentiality. All protocols were approved by the Colorado Multiple Institutional Review Board.

METHODS Participants and Setting Data were collected from June 2012 through August 2013 at Denver Health Medical Center (DHMC), a public safety net serving the city and county of Denver and its surrounding metropolitan areas. DHMC is an SBIRT Colorado implementation site through funding from SAMHSA. This site utilizes nurses/medical assistants who are trained to conduct a brief screen as part of standard intake and health educators who are trained in follow-up screening, motivational interviewing, and referral for substance use disorders. DHMC health educators screened 7,875 unduplicated adult patients during the study period in participating sites within DHMC. Sites included the dental clinic (n = 1,208), adult urgent care clinic (AUCC; n = 3,529), emergency department (ED; n = 2,773), and a primary care clinic (n = 365). The mean age of patients screened was 41 years (SD 14.0; range 18-94); 49.2% were female; 47.8% identified as White, 42.2% as Hispanic, and 15.5% as Black (patients could indicate more than one race/ethnicity category). The DHMC patient care population is 52% female, and 31% White, 48% Hispanic, and 14% Black (DHMC 2013). Procedures and Measures At each site, patients were administered six questions on substance use as part of standard intake protocols. In the AUCC and ED, nurses administered the brief screen at triage. In the primary care and dental clinic, medical assistants administered the brief screen at admission. A brief screen was positive when patients indicated current tobacco use, alcohol use that exceeded the daily or weekly limits (using the National Institute on Alcohol Abuse and Alcoholism guidelines of no more than 3/4 drinks per day for women/men and no more than 7/14 drinks per week for women/men), any illegal drug use or nonmedical use of prescription drugs, concern of self or others about prescription drug use, or having a medical marijuana card. The Journal of Psychoactive Drugs


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TABLE 1 Percentages and Means for Sociodemographic Variables by Marijuana (MJ) Use and Cardholding

Cardholder Female White Black Hispanic Other AUCC Dental ED Primary Care Mean Age (SD) N % ∗p

Full Sample (N = 7875) No MJ Use MJ Use 0.50% 17.4% 54.0% 35.7% 35.5% 44.1% 14.3% 17.7% 45.3% 33.4% 4.9% 4.7% 46.0% 41.3% 17.5% 9.2% 31.7% 45.4% 4.8% 4.1% 42.0 (14.3) 36.8 (12.5) 5845 74.2%

MJ Users (n = 2030) No Card Cardholder ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗

2030 25.8%

35.5% 43.8% 17.4% 33.8% 4.9% 41.8% 6.3% 46.9% 5.0% 36.5 (12.5)

36.9% 45.6% 19.0% 31.4% 4.0% 38.8% 23.0% 38.2% 0.0% 38.6 (12.7)

1677 82.6%

353 17.4%

∗ ∗ ∗ ∗

< .05 for difference-of-proportions t-test between No MJ Use/MJ Use and No Card and Cardholder.

Analysis Descriptive statistics were calculated to describe the study sample and to address the first research question (What proportion of patients screening positive through SBIRT and using marijuana had access through the state’s medical marijuana program?). All subsequent analyses were conducted on the sample of marijuana users (who indicated any use in the past 90 days on the ASSIST). To address the second question (Do positive-screened patients with medical marijuana cards use marijuana more frequently or at higher risk levels than positive-screened patients without cards?), two regression models were tested. First, to examine frequency of use, negative binomial regression, appropriate for count data, was used. This analysis tested whether cardholder status (1 = cardholder; 0 = non-cardholder) was associated with the number of days used marijuana in the past 30 (assessed on the GPRA). Second, to examine severity of use from the ASSIST marijuana substance risk level, multinomial logistic regression for outcomes with three categories was used. This analysis tested whether cardholder status was associated with degree of risky cannabis use (moderate risk served as the reference category). To address the third question (Do positive-screened patients with medical marijuana cards use other substances at risky levels more frequently than positive-screened patients without cards?), separate logistic regression models were conducted. These analyses examined whether cardholder status was associated with risky use (1 = moderate/high risk; 0 = no/low risk) on eight ASSIST substance categories (tobacco, alcohol, amphetamines, cocaine, hallucinogens, inhalants, opioids, sedatives), and

Journal of Psychoactive Drugs

on whether patients were at risk for any substance or for any controlled substance (i.e., excluding alcohol and tobacco). To account for multiple tests, significance levels were evaluated with probabilities adjusted by the Hochberg step-up method (Hochberg & Benjamini 1990), which is suitable for mildly correlated outcomes (Blakesley et al. 2009). A second set of analyses were conducted excluding patients who used marijuana and no other substances (also adjusting for multiple tests). The focus on polysubstance users defines a more homogenous sample and adjusts for the possibility that individuals without medical marijuana cards were missed in the screening if they used no other substances besides marijuana. If the sample includes too many non-cardholding marijuana users who screened positive for other substances and too few who only used marijuana, the sample selection could exaggerate the use of other substances among non-cardholding marijuana users and bias comparisons with cardholders. Thus, we conducted a subsample analysis to minimize this bias by examining only marijuana cardholders and non-cardholders who used additional substances. All regression models controlled for gender, age, race/ethnicity, and site. Models predicting other substances additionally controlled for marijuana risk level. RESULTS Table 1 describes characteristics of marijuana users (any use in the last three months) in comparison to nonmarijuana users. Marijuana users make up 25.8% of the full sample, and differ significantly from non-users on most measures. They are more likely to be White (44.1%


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TABLE 2 Negative Binomial Regression Results for Number of Days Using Marijuana in the Past 30 (N = 2002)

Predictors Intercept Cardholder Female Black Hispanic Other Age Dental ED Primary Care ∗p

B 2.97 0.41 −0.09 0.01 0.06 0.01 −0.01 0.01 0.06 0.29

Number of Days using Marijuana in Past 30 SE (B) OR (95% CI) 0.09 19.45 (16.3, 23.3) 0.07 1.51 (1.32, 1.73) 0.05 0.91 (.82, 1.01) 0.07 1.01 (.88, 1.17) 0.06 1.07 (.95, 1.20) 0.12 1.01 (.79, 1.28) 0.00 0.99 (.986, .994) 0.10 1.01 (.83, 1.22) 0.05 1.06 (.95, 1.18) 0.13 1.34 (1.03, 1.74)

Wald 1046.5∗∗ 35.8∗∗ 3.01 .019 1.16 .00 21.3∗∗ 0.01 1.07 4.88∗

< .05; ∗∗ p < .01.

v. 35.5%) and come from the ED (45.4% v. 31.7%). They are also younger than non-users (mean 36.8 v. 42.0) and less likely to be female (35.7% v. 54.0%) and Hispanic/Latino (33.4% v. 45.3%). Based on ASSIST scores for the sample of marijuana users over the past three months, 79% were at risk from use of another substance. The most common risk came from tobacco (71%), followed by excess alcohol use (18%). About 18% of the sample of marijuana users was at risk for use of a controlled substance, including cocaine (9%), amphetamines (7%), opioids (7%), and hallucinogens, sedatives, and inhalants (each less than 3%).

with cardholders using about 1.5 times more days than non-cardholders on average. With respect to risk, most cardholders (94.6%) were in the moderate risk category (4.8% were low risk; 0.6% were high risk). Three-quarters (74.7%) of noncardholders were in the moderate risk category, just under one quarter (22.5%) were low risk, and 2.7% were high risk. Controlling for socio-demographic variables, results of multinomial logistic regression show that, compared to non-cardholders, cardholders were significantly more concentrated in the moderate risk level rather than the no/low or high risk levels (see Table 3). Although based on relatively few cases, when looking at those with the highest risk, cardholders were 80% less likely than non-cardholders to be in the high than moderate risk category. Thus, in answer to question 2, cardholders were more frequent users of marijuana than non-cardholders, but were more “moderate” than non-cardholders with respect to risk level.

Q1: What proportion of patients screening positive through SBIRT and using marijuana had access through the state’s medical marijuana program? Table 1 also compares cardholders and noncardholders among the subsample of marijuana users. In answer to question 1, 17.4% of marijuana users had access to marijuana through the state’s medical marijuana program. In addition, significant differences emerge for age (cardholders are slightly older on average) and site (cardholders are more likely to come from the dental clinic and less likely to come from the ED and primary care).

Q3: Do positive-screened patients with medical marijuana cards use other substances at risky levels more frequently than positive-screened patients without cards? To answer question 3, Table 4 examines the association between being a cardholder and the risk for use of other drugs. The logistic regression models for these outcomes control for marijuana risk category (no/low, moderate, high) and sociodemographic variables. The results reveal that cardholders have significantly lower odds than noncardholders, adjusted for multiple tests, for moderate/high risk of alcohol (OR = .55, CI .40, .75, p < .001), tobacco (OR = .40, CI .31, .52, p < .001), any substance (OR = .35, CI .27, .46, p < .001), and any controlled substance (OR = .59, CI, .41, .85, p < .004). In answer to question 3,

Q2: Do positive-screened patients with medical marijuana cards use marijuana more frequently or at higher risk levels than positive-screened patients without cards? The median number of days used in the past 30 for cardholders was 30 and for non-cardholders it was 10. The modal response for cardholders and non-cardholders alike was 30 days. Controlling for socio-demographic variables, results of negative binomial regression (see Table 2) reveal a significant and positive association between being a cardholder and the number of days used in the past 30,

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TABLE 3 Multinomial Logistic Regression Relative Risks (RR) for Marijuana (MJ) Risk Level (N = 2022) MJ Risk Level Predictors Intercept Cardholder Female Black Hispanic Other Age Dental ED Primary Care a Relative

B −1.85 −1.87 0.40 −0.25 −0.23 −0.20 0.02 −0.18 −0.17 −0.60

None/Lowa SE (B) RR 0.21 0.26 0.16 0.12 1.49 0.17 0.78 0.13 0.80 0.28 0.82 0.01 1.02 0.23 0.83 0.12 0.85 0.32 0.55

Higha Wald 78.1∗∗ 51.4∗∗ 11.1∗∗ 2.34 2.82 0.52 18.3∗∗ 0.60 1.80 3.56

B −2.63 −1.62 −0.35 0.44 0.30 −0.74 −0.02 −1.37 −0.40 0.74

SE (B) 0.53 0.73 0.33 0.41 0.34 1.04 0.01 1.03 0.32 0.54

RR 0.20 0.70 1.55 1.34 0.48 0.98 0.25 0.67 2.09

Wald 24.3∗∗ 4.90∗ 1.14 1.14 0.75 0.50 1.55 1.76 1.56 1.89

to moderate MJ risk category; ∗ p < .05; ∗∗ p < .01.

TABLE 4 Logistic Regression Odds Ratios (OR) for Substance Use Risk on Cardholder Status Full Sample: Marijuana Users (N = 2022) Alcohol Amphetamines Cocaine Hallucinogens Inhalants Opioids Sedatives Tobacco Any Substance Any Controlled

Logistic Regression B −0.60 −0.68 −0.19 −0.54 −0.41 −0.57 −0.39 −0.91 −1.04 −0.53

SE (B) 0.16 0.32 0.23 0.76 1.07 0.31 0.55 0.13 0.14 0.19

Subsample: Positive Brief Screen (n = 1945) Alcohol Amphetamines Cocaine Hallucinogens Inhalants Opioids Sedatives Tobacco Any Substance Any Controlled ∗p

OR (95% CI) 0.55 (.40, .75) 0.51 (.27, .94) 0.82 (.52, 1.30) 0.58 (.13, 2.59) 0.67 (.08, 5.38) 0.57 (.31, 1.03) 0.68 (.23, 1.99) 0.40 (.31, .52) 0.35 (.27, .46) 0.59 (.41, .85)

Wald 14.29∗∗ 4.69∗ 0.68 0.50 0.15 3.43 0.50 49.92∗∗ 58.21∗∗ 8.09∗∗


ˆ ˆ ˆ

Logistic Regression B −0.43 −0.55 −0.08 −0.46 −0.32 −0.50 −0.25 −0.54 −0.60 −0.39

SE (B) 0.16 0.32 0.24 0.76 1.07 0.32 0.55 0.14 0.15 0.19

OR 0.65 (.48, .90) 0.58 (.31, 1.07) 0.92 (.58, 1.47) 0.63 (.14, 2.82) 0.73 (.09, 5.89) 0.60 (.32, 1.12) 0.78 (.27, 2.28) 0.59 (.44, .77) 0.55 (.41, .74) 0.68 (.47, .98)

Wald 6.95∗∗ 3.03 0.11 0.36 0.09 2.53 0.21 14.37∗∗ ˆ 15.20∗∗ ˆ 4.22∗

< .05; ∗∗ p < .01; ˆ p < .05 with Hochberg adjustment for multiple tests.

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then, risky use of other substances generally appears lower among cardholders than non-cardholders. To check these findings, Table 4 also presents results including only the subsample of polysubstance-using patients who screened positive for tobacco, alcohol, other illegal drugs, or prescription medication misuse (i.e., excluding 60 cardholders and 10 non-cardholders who only used marijuana). The results in Table 4 show somewhat weaker differences between cardholders and noncardholders, but the pattern of results remains unchanged. The results suggest that sample selection bias did not distort the findings of greater use of other substances by non-cardholding marijuana users.

frequency of marijuana use among returning medical marijuana users in Michigan compared to first-time applicants for a medical marijuana card (Ilgen et al. 2013). On the other hand, use of marijuana by cardholders is less likely to be classified as high risk than for noncardholding marijuana users. In addition, use of marijuana by cardholders is not accompanied as often as with noncardholders by use of excess alcohol, tobacco, and illegal drugs. The lower use of other substances among cardholders is consistent with findings that medical marijuana serves as a substitute rather than a complement for the use of other substances (Janichek & Reiman 2012). Medical cannabis users in California report using marijuana to replace other drugs, including legitimate prescriptions as well as illicit drug use (Reiman 2007; 2009). Medical use appears to protect against the use of other substances rather than serve as a gateway to illegal drug use (O’Connell & Bou-Matar 2007). However, longitudinal comparisons of subjects before and after receiving approval for legal medical marijuana use are needed to test for substitution for marijuana for use of other substances. The intent of the current study was to examine screening data to identify whether those with legal medical access to marijuana differed in their patterns of use compared to those without access. The findings about the special characteristics of medical marijuana users can inform the practice of health care providers who implement SBIRT as part of standard practice. Practitioners may learn of the medical use of marijuana through screening, and then use the information about risks and benefits to help educate and potentially intervene with patients (Kleber & DuPont 2012). Patients report that medical marijuana helps with problems of chronic pain, discomfort, and psychological well-being (Bottorff et al. 2011; Nunberg et al. 2011; Aggarwal et al. 2009). In many cases, however, the long-term, regular use of marijuana may be a maladaptive coping strategy (Zvolensky et al. 2011), and alternative treatments need to be considered (Desai & Patel 2013). Critics note that medical marijuana use has no controlled dosage, standardized product, or FDA approval (Kleber & DuPont 2012). These problems deserve discussion, and additional information is needed on the health consequences associated with marijuana use. The sample for this study comes from four sites in a large, urban safety-net medical center. Patients who seek treatment at this center typically have high needs and often use the emergency and urgent care center as a form of primary care. Health educators were not always able to gather data for patients who screened negative, and the sample likely overrepresents substance users. Because of the nature of the patient population and the sample, the use of marijuana for both medical and non-medical purposes may be higher than for the general population. The sample figure of 25.8% using marijuana in the last three months likely does not generalize to use in the medical center, other Colorado

DISCUSSION Colorado approved medical marijuana in 2000 and passed a referendum in 2012 to legalize the purchase, possession, and use of small amounts for adults aged 21 and over. The newest law adds some complexity to the context of our results and differentiates Colorado from all but one other state. Effective December 10, 2012, when the governor signed a proclamation that placed the legalization amendment in the constitution, adults could use marijuana legally, possess one ounce, and grow limited amounts at home. However, public sale of marijuana did not begin until January 2014 (after the study’s conclusion). Although our sample cannot precisely compare legal and illicit marijuana users, it can compare those with and without legally prescribed medical marijuana cards. The lack of a question specific to marijuana use means the sample likely misses casual marijuana users who do not smoke, use alcohol to excess, or use illicit drugs. Our sample thus applies more to polysubstance users. Although the sample does not generalize to all marijuana users in Colorado or elsewhere, this study offers new insights into the heterogeneity of marijuana users in a state that has a substantial number of individuals accessing marijuana through state-run medical programs, and is facing a changing population of marijuana users. The findings reveal that medical marijuana users in this sample differ from other users in several ways. On the one hand, they use marijuana on a more regular basis than others. Daily or chronic use creates greater risk of dependence and long-term harm on respiratory function, even when motivated by chronic pain or health problems and recommended by a physician (Hall & Pacula 2003). The risk of dependence can be heightened when chronic use has a component of emotional relief, which is common among those applying for medical marijuana access (O’Connell & BouMatar 2007). The results are consistent with the findings of Richmond et al. (2013) in which increases in overall marijuana use, and severity of use, coincided with increased numbers of medical marijuana users and dispensaries in Colorado. They are also consistent with findings of greater Journal of Psychoactive Drugs


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locations, or other states. However, the demographic figures for medical marijuana users in the sample are similar to those for the state of Colorado (37% in the sample are female compared to 33% in the state; the average age of our sample is 39 compared to 42; CDPHE 2013). The findings rely on cross-sectional comparisons of cardholders and non-cardholders. The ability to follow both groups longitudinally would give more insight into risk before and after obtaining a card. Similarly, we lack a strong set of control variables (e.g., substance use by peers and family members, attitudes and beliefs about substance use risks, or health problems for which medical marijuana is used) that would help account for differences in substance use patterns. We can say descriptively that cardholders use marijuana more regularly and use other substances less often, but we can say little in causal terms about the sources of these differences. For example, those going through the process of obtaining a card for medical marijuana may have more resources and stable life circumstances than those who continue to obtain marijuana through illegal means. Characteristics that precede obtaining a card may differentiate legal medical users from others. Although we know that 94% of approved applicants for medical marijuana cite severe pain as the condition (CDPHE 2013), we lack more detailed information on cardholder motives, medical conditions, personal problems, and socioeconomic status. Additional data are needed to more fully understand the process that leads to medical marijuana use. The results also depend on self-reported substance use. Although the ASSIST has demonstrated validity (Humeniuk et al. 2008), it was designed under the assumption that marijuana use is illegal. To the extent that cardholders and non-cardholders differ in the accuracy of their reports, it will bias comparisons between the groups. It is also possible that the two-phase screening procedure

missed some marijuana users. Our checks suggest that the influence of this bias is small, and a new version of the brief screen asks explicitly about marijuana use separately from questions about illegal drug use and a medical marijuana card. The change in the Colorado law to legalize recreational use of marijuana during the period of data gathering limits our ability to make inferences about legal and illegal use; the brief screen question on illicit drug use may miss non-cardholders who use no other substances besides marijuana. Although there were no Colorado establishments authorized to sell recreational marijuana during the study period, after the law passed, Colorado residents viewed marijuana as a legal substance. In response to these changes, the brief screen has been changed to include a specific question on marijuana use rather than mixing it with illicit drugs. Despite the limitations of the study, it offers original insights into the nature of medical marijuana use. Health care providers encounter increasing numbers of patients who access marijuana through state-run programs and need to better understand the unique characteristics and risks of these patients. Our findings can give some guidance in working with medical marijuana patients, but more research is needed to help health care providers address risk-prone marijuana use.

FUNDING SBIRT Colorado is a statewide initiative funded by the Substance Abuse and Mental Health Services Administration (5U79TIO1802-02) through the Office of the Governor, administered by the Office of Behavioral Health and managed by Peer Assistance Services, Inc.,

REFERENCES Rockville, MD: Substance Abuse and Mental Health Services Administration. Available from: CSAT-GPRA/services/SAIS_GPRA_Client_Outcome_Instrument_ final.pdf Cerdá, M.; Wall, M.; Keyes, K.M.; Galea, S. & Hasin, D. 2012. Medical marijuana laws in 50 states: Investigating the relationship between state legalization of medical marijuana and marijuana use, abuse and dependence. Drug and Alcohol Dependence 120: 22–27. Colorado Department of Public Health and Environment (CDPHE). 2013, August. Center for Health and Environmental Information and Statistics: Medical Marijuana Registry Program Update. Available from: Compton, W.M.; Grant, B.F.; Colliver, J.D.; Glantz, M.D. & Stinson, F.S. 2004. Prevalence of marijuana use disorders in the United States: 1991-1992 and 2001-2002. Journal of the American Medical Association 291 (17): 2114–21.

Aggarwal, S.K.; Carter, G.T.; Sullivan, M.D.; ZumBrunnen, C.; Morrill, R. & Mayer, J.D. 2009. Characteristics of patients with chronic pain accessing treatment with medical cannabis in Washington State. Journal of Opioid Management 5 (5): 257–286. Bernstein, E.; Edwards, E.; Dorfman, D.; Heeren, T.; Bliss, C. & Bernstein, J. 2009. Screening and brief intervention to reduce marijuana use among youth and young adults in a pediatric emergency department. Academic Emergency Medicine 16 (11): 1174–1185. Blakesley, R.E.; Mazumdar, S.; Dew, M.A.; Houck, P.R.; Tang, G.; Reynolds III, C.F. & Butters, M.A. 2009. Comparisons of methods for multiple hypothesis testing in neuropsychological research. Neuropsychology 23 (2): 255–264. Bottorff, J.F.; Bissell, L.J.L.; Balneaves, L.G.; Oliffe, J.L.; Kang, H.B.K.; Capler, N.R.; Buxton, J.A. & O’Brien, R.K. 2011. Health effects of using cannabis for therapeutic purposes: A gender analysis of users’ perspectives. Substance Use & Misuse 46: 769–780. Center for Substance Abuse Treatment (CSAT). 2010. Sept. Government Performance and Results Act Client Outcome Instrument v2.6.

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characteristics, patterns of cannabis and other drug use of 4117 applicants. Harm Reduction Journal 4 (16): 1–7. Office of National Drug Control Policy. 2013. National Drug Control Strategy. Washington, DC: Executive Office of the President. Available from: ondcp/policy-and-research/ndcs_2013.pdf. Pew Research Center. 2013 April. Majority now supports legalizing marijuana. Available from: 04/majority-now-supports-legalizing-marijuana. Reiman, A. 2007. Medical cannabis patients: Patient profiles and health care utilization patterns. Journal of Evidence-Based Complementary and Alternative Medicine 12 (1): 31–50. Reiman, A. 2009. Cannabis as a substitute for alcohol and other drugs. Harm Reduction Journal 6 (35): 1–5. Reinarman, C.; Nunberg, H.; Lanthier, F. & Heddleston, T. 2011. Who are medical marijuana patients? Population characteristics from nine California assessment clinics. Journal of Psychoactive Drugs 43 (29): 128–135. Richmond, M.K.; Page, K.; Rivera, L.S.; Reimann, B. & Fischer L. 2013. Trends in detection rates of risky marijuana use in Colorado health care settings. Substance Abuse 34 (3): 248–255. Saitz, R.; Alford, D.P.; Bernstein, J.; Cheng, D.M.; Samet, J.; & Palfai, T. 2010. Screening and brief intervention for unhealthy drug use in primary care settings: Randomized clinical trials are needed. Journal of Addiction Medicine 4 (3): 123–130. Salomonsen-Sautel, S.; Sakai, J.T.; Thurstone, C.; Corley, R. & Hopfer, C. 2012. Medical marijuana use among adolescents in substance abuse treatment. Journal of the American Academy of Child & Adolescent Psychiatry 51 (7): 694–702. Substance Abuse and Mental Health Services Administration (SAMHSA). 2011 April. Screening, brief intervention and referral to treatment (SBIRT) in behavioral healthcare. Available from: Substance Abuse and Mental Health Services Administration (SAMHSA). 2013. Results from the 2012 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series H-46, HHS Publication No. (SMA) 13-4795. Rockville, MD: Substance Abuse and Mental Health Services Administration. Available from: NatFindDetTables/NationalFindings/NSDUHresults2012.htm Wall, M.M.; Poh, E.; Cerdá, M.; Keyes, K.M.; Galea, S. & Hasin, D.S. 2011. Adolescent marijuana use from 2002 to 2008: Higher in states with medical marijuana laws, cause still unclear. Annals of Epidemiology 21 (9): 714–7166. World Health Organization (WHO). 2008. The Effectiveness of a Brief Intervention for Illicit Drugs Linked to the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) in Primary Health Care Settings: A Technical Report of Phase III Findings of the WHOASSIST Randomized Controlled Trial. Geneva: World Health Organization. Available from: activities/assist technicalreport phase3 final.pdf. World Health Organization (WHO) ASSIST Working Group. 2002. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Development, reliability and feasibility. Addiction 97 (9): 1183–1194. Zvolensky, M.J.; Cougle, J.R.; Bonn-Miller, M.O.; Norberg, M.M; Johnson, K.; Kosiba, J. & Asmundson, G.J. 2011. Chronic pain and marijuana use among a nationally representative sample of adults. American Journal on Addictions 20 (6): 538–542.

Denver Health Medical Center (DHMC). 2013. Report to the City of Denver, 2013. Available from: 0/2013%20Report%20to%20the%20City.pdf Desai, U. & Patel, P. 2013. Medical marijuana: A public health perspective. International Journal of Basic & Clinical Pharmacology 2 (2): 136–143. Friese, B. & Grube, J.W. 2013. Legalization of medical marijuana and marijuana use among youths. Drugs: Education, Prevention and Policy 20 (1): 33–39. Hall, W.D. & Pacula, R.L. 2003. Cannabis Use and Dependence: Public Health and Public Policy. Cambridge, UK: Cambridge University Press. Harper, S.; Strumpf, E.C. & Kaufman, J.S. 2012. Do medical marijuana laws increase marijuana use? Replication study and extension. Annals of Epidemiology 22: 207–212. Hochberg, Y. & Benjamini Y. 1990. More powerful procedures for multiple significance testing. Statistics in Medicine 9: 811–818. Humeniuk, R.; Ali, R.; Babor, T.F.; Farrell, M.; Formigoni, M.L.; Jittiwutikarn, J; de Lacerda, R.B.; Ling, W.; Marsden, J.; Monteiro, M.; Nhiwatiwa, S.; Pal, H.; Poznyak, V. & Simon, S. 2008. Validation of the alcohol, smoking and substance involvement screening test (ASSIST). Addiction 103 (6): 1039–1047. Humeniuk, R.E.; Henry-Edwards, S.; Ali, R.L.; Poznyak, V. & Monteiro, M. 2010. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Manual for Use in Primary Care. Geneva: World Health Organization. Ilgen, M.A.; Bohnert, K.; Kleinberg, F.; Jannausch, M.; Bohnert, A.S.B.; Walton, M. & Blow, F.C. 2013. Characteristics of adults seeking medical marijuana certification. Drug and Alcohol Dependence 132 (3): 654–9. Janichek, J.L. & Reiman, A. 2012. Clinical service desires of medical cannabis patients. Harm Reduction Journal 9 (12): 1–6. Kleber, H.D. & DuPont, R.L. 2012. Physicians and medical marijuana. American Journal of Psychiatry 169: 564–8. Lynne-Landsman, S.D.; Livingston, M.D. & Wagenaar, A.C. 2013. Effects of state medical marijuana laws on adolescent marijuana use. American Journal of Public Health 103: 1500–1506. Madras, K.; Compton, W.; Avula, D.; Stegbauer, T.; Stein, J. & Clark, H. 2008. Screening, brief interventions, referral to treatment (SBIRT) for illicit drug and alcohol use at multiple healthcare sites: Comparison at intake and 6 months later. Drug and Alcohol Dependence 3357: 1–16. McCambridge, J. & Strang, J. 2004. The efficacy of single-session motivational interviewing in reducing drug consumption and perceptions of drug-related risk and harm among young people: Results from a multi-site cluster randomized trial. Addiction 99: 39–52. National Conference of State Legislatures (NCSL). 2014 June. State medical marijuana laws. Available from: National Institute on Drug Abuse (NIDA). 2002. Marijuana abuse. NIDA Research Report Series (NIH Publication No. 12-3859). Available from: Nunberg, H.; Kilmer, B.; Pacula, R.L. & Burgdorf, J.R. 2011. An analysis of applicants presenting to a medical marijuana specialty practice in California. Journal of Drug Policy Analysis 4 (1): 1–16. O’Connell, T.J. & Bou-Matar, C.B. 2007. Long term marijuana users seeking medical cannabis in California: Demographics, social

Journal of Psychoactive Drugs


Volume 47 (1), January – March 2015

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Frequency and Risk of Marijuana Use among Substance-Using Health Care Patients in Colorado with and without Access to State Legalized Medical Marijuana.

With increasing use of state legalized medical marijuana across the country, health care providers need accurate information on patterns of marijuana ...
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