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. Author manuscript; available in PMC: 2024 Jan 1.
Published in final edited form as: J Addict Med. 2022 Aug 24;17(2):e87–e93. doi: 10.1097/ADM.0000000000001059

Cannabis use disorder treatment preferences: a pilot survey in current users of cannabis

Joshua A Lile 1,2,3,✉, Brian W Turner 4, David H Cox 1, Marcel O Bonn-Miller 5, Ned R Katz 1, Thomas P Shellenberg 1, William W Stoops 1,2,3, Justin C Strickland 6
PMCID: PMC9950290  NIHMSID: NIHMS1826002  PMID: 36731101

Abstract

Objectives:

Highly effective treatments for cannabis use disorder (CUD) are lacking, and patient preferences have not been considered during treatment development. We therefore conducted an exploratory crowdsourced survey of individuals reporting current cannabis use and a willingness to cut down or quit their cannabis use, to determine their interest in various treatment aspects.

Methods:

Subjects (n=63) were queried about their willingness to take medications as a function of type, route and regimen and to participate in adherence monitoring. Subjects were also asked about their willingness to engage in behavioral/psychosocial interventions as a function of type, setting and duration. Measures theorized to be associated with treatment preferences were also collected, including cannabis use variables, readiness to change, reduction or cessation goal, perceived cessation barriers and medication use beliefs and behaviors.

Results:

Survey responses indicated that efforts to develop CUD medications should focus on non-synthetic compounds administered orally or by mouth spray no more than once per day to maximize patient acceptance. Remote adherence monitoring and one-on-one outpatient behavioral treatment approaches, especially contingency management, are also anticipated to enhance participation. Most subjects indicated a preference to reduce their cannabis use rather than quit.

Conclusions:

These data provide guidance for the development of CUD interventions based on the preferences of individuals interested in treatment for their cannabis use. Additional research is needed to confirm these results in a larger sample and determine if matching CUD patients with their preferred treatments improves success rates.

Keywords: marijuana, pharmacotherapy, medication, behavioral therapy, psychosocial, adherence

Introduction

Cannabis use disorder (CUD) remains a significant public health problem, but highly effective treatments are lacking. Recent survey data indicate that 11.8% of Americans aged 12 and older used cannabis in the past month, with 5.1% endorsing criteria for CUD.1 Moreover, cannabis was reported as the primary substance for 13% of recent US treatment admissions.2 Over 20 placebo-controlled, randomized clinical trials have evaluated the ability of medications to reduce cannabis use in treatment-seeking individuals; although some recent trials have yielded promising results,3,4,5 no medication has been approved.

The ongoing development of CUD medications provides an opportunity to consider patient preferences during the process. We are not aware of any prior studies that assessed preferences associated with pharmacological or other treatment modality in users of cannabis, and in general, limited research on preferences has been conducted in individuals with substance use disorders (SUDs). Related work in other clinical populations indicates that matching patients to their treatment preferences (e.g., type of treatment, treatment setting) can increase adherence and improve outcomes.6 A recent review7 of the SUD literature (n=25 trials) found that certain preferences varied by SUD, but the extent to which matching patients to their preferred treatments impacted treatment outcomes differed across studies.

Given the lack of information about treatment preferences in users of cannabis, we conducted an exploratory survey in individuals reporting current cannabis use and a willingness to cut down or quit their use. Subjects were queried about their willingness to take medications as a function of drug origin (e.g., synthetic, natural), route of administration and regimen (e.g., times per day, duration of treatment), and participate in adherence monitoring procedures. Several secondary measures theorized to be associated with medication preference were also collected (medication use beliefs and behaviors), as were measures of readiness to change, whether reduction or cessation was a goal and perceived barriers to cessation.

In addition, respondents were also asked about their willingness to engage in behavioral (psychosocial) interventions as a function of type, setting (e.g., group or individual; online, outpatient or inpatient) and duration. Motivational enhancement treatment, cognitive behavioral therapy, contingency management (CM) and combinations of these techniques reduce cannabis use relative to minimal treatment controls;8 however, behavioral therapies are only modestly effective and have some practical limitations. Determining behavioral treatment preferences in users of cannabis could inform tailored therapy programs that might improve their effectiveness.

Methods

Subjects

Subjects were sampled using the crowdsourcing website Amazon Mechanical Turk (mTurk). Crowdsourcing is an effective and efficient means of recruiting research subjects in addiction science.9,10 Subjects had to be US residents with a ≥ 95% approval rating on ≥ 100 previously approved human intelligence tasks to be included.11 The consent document and protocol were approved by the University of Kentucky Institutional Review Board (IRB# 45052).

Procedures

Potential subjects completed a screening questionnaire. To qualify, respondents had to 1) be ≥ 18 years old, 2) report using cannabis within the last 30 days, 3) endorse a history of trying, being willing to try, or currently trying to reduce or quit their cannabis use, and 4) indicate interest in employing at least one form of behavioral therapy or medication to change their cannabis use. Qualifying subjects who completed the entire survey received US $10.05. Median time to complete the survey was 27 min (range 11–124).

Measures

Subjects completed questionnaires designed to measure preferences for aspects of medication- and behavior-based treatments, as well as various secondary outcomes. Survey items that were locally developed or significantly modified for this study are provided in the Supplemental Material.

Treatment Preferences Survey

Primary outcome data were collected using a locally developed Treatment Preferences Survey (TPS) (see Supplemental Materials). Subjects were asked to rate, on a 5-point Likert scale ranging from “Completely Against” to “Very Willing”, their willingness to participate in treatment involving prescription medication derived from a synthetic chemical or from a natural product, dietary supplement or other natural over-the-counter (OTC) treatment, hallucinogen, “talk” therapy, and incentive reinforcement for evidence of recent abstinence (i.e., contingency management). Subjects who endorsed any degree of willingness to receive a medication were presented with additional preference questions regarding route of administration (Y/N; oral pill/tablet/capsule, oromucosal spray, inhaled, nasal spray, skin cream/patch, depot injection), times per day (0–4; select one), duration of treatment (1, 2, 3, 6, 12 and 24 months, or rest of life; select one), and medication adherence monitoring methods (Y/N; offline or online medication containers that record openings, pen-and-paper or digital diaries, clinician pill counts, urine or blood testing, digital or in-person observation). Subjects were also asked whether they would participate in a treatment program that combined medication and behavioral therapies, preferences regarding type of behavioral treatment (inpatient then outpatient or outpatient only; for outpatient sessions: in-person or online one-on-one sessions with a clinician, in-person or online group sessions, or computerized therapy), and how long they would be willing to stay in an inpatient facility (1, 2, 4, 8 or 12 weeks; select one).

Secondary Measures

Subjects completed basic demographic information and health history questions; sex (M,F), current or previous use of a prescription medication (Y/N) and diagnosis of at least one mental health disorder (anxiety, depression, bipolar, schizophrenia, attention deficit/hyperactivity or post-traumatic stress disorders) are reported. Whether mental health disorders were diagnosed by a clinician was not determined.

Current and past substance use was characterized, with more detailed information collected about subjects’ cannabis use. Subjects completed a modified version of the Daily Sessions, Frequency, Age of Onset, and Quantity of Cannabis Use Inventory (DFAQ-CU12). Whether or not subjects used daily (i.e., >24/30 days past month use) was also determined and subjects estimated what percent of their cannabis use was recreational (relative to medicinal). Problematic use of cannabis was assessed using the Cannabis Use Disorders Identification Test Revised (CUDIT-R13) and 11 Cannabis Use Disorder questions derived from the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM–514). Problematic alcohol and tobacco use was assessed using the Alcohol Use Disorders Identification Test (AUDIT15) and the Fagerstrom Test for Nicotine Dependence (FTND16), respectively.

Subjects were also asked “if you have tried, are currently trying, or would be willing to try to reduce or quit your cannabis use, is/was your goal to reduce your use or completely quit?”. In addition, readiness to change cannabis use behaviors was assessed using the Marijuana Ladder,17 revised for adults with cannabis access (see Supplemental Materials). The Barriers to Cannabis Cessation Scale was also collected (rated on a 0–3 scale ranging from “not a barrier/not applicable” to “large barrier”; adapted from the tobacco smoking version in Garey et al.,18 by the authors of that report, personal communication19). Subjects were asked whether they had engaged in prior CUD treatment attempts in the past year (Y/N for the treatment categories listed above); whether these treatments were directed by a clinician was not determined. The Adherence to Refills and Medications-Modified questionnaire (ARMS-Mod20; ranked on a 1–4 scale ranging from “none of the time” to “all of the time”; see Kripalani et al.21 for original scale validation) and Beliefs about Medicines Questionnaire (BMQ22; ranked on a 1–5 scale ranging from “strongly agree” to “strongly disagree”) were also administered. The BMQ was modified for cannabis; BMQ-cannabis refers to the subscale specific to a CUD medication and BMQ-general refers to the subscale that includes general questions about medication beliefs (see Supplemental Materials).

Data Analysis

Descriptive statistics were calculated for all survey measures. To ensure integrity, data were excluded if duplicate answers to a question about last weekend’s activities were provided, or if a subject said they did not take their time or they would be completely against an intervention to help reduce or quit their cannabis use. In addition, several questions were repeated with minor variations across the survey that were used for attention and validity checks. A subject’s data were excluded if their answers met two or more of the following criteria: discrepancy in age, no cannabis use reported in the past 30 days, endorsed using a fake drug (oxypentone), and/or self-reported cannabis use had >2 inconsistencies that could not be attributed to differences in question parameters or variability in recall.

Results

Sample

The total number of people who completed the screener was 1371. Of these, 118 subjects passed the screener and completed the survey. The filtering criteria outlined above removed 55 subjects for a final sample size of n = 63.

Demographics

The subject sample was comprised of 31 female and 32 male, predominantly White (78%, compared to 11% Black, 3% Southeast Asian and 6% Other) and not Hispanic/Latino (92%) subjects, with a median age of 34 years old (range = 18–68). The highest level of education (mode) was a bachelor’s degree (38%), followed by a master’s degree (24%), high school degree or equivalent (14%), some college credit (13%), an associate’s degree (8%) and vocational training (3%). Subjects resided in 28 different US states. 27% stated that they were not diagnosed with any mental health disorder, whereas the remaining subjects reported one or more, including anxiety (52%), depression (49%), attention deficit/hyperactivity disorder (ADHD; 16%), post-traumatic stress disorder (13%), bipolar disorder (11%) and schizophrenia (5%). Most subjects were employed full time (35+ hours per week; 84%). The mode annual household income was USD$50K-60K.

Substance Use

Key cannabis use characteristics are shown in Figure 1. The distribution of cannabis use frequencies indicated that the mode usage was more than once a day (27%) every day of the last 30 days (22%). The number of years of cannabis use ranged from <1 to 50, with a cluster between 1–6 years and a mean of 10 years. The primary form and route of cannabis administration was smoked flower (89%). 43% indicated that they had a physician’s recommendation for use, with 14% stating that they used medicinal access to obtain cannabis for recreational use. Conversely, 64% did not have physician’s recommendation but used cannabis for medicinal reasons. The relative percentage of recreational to medicinal use was 63%. Of those who used cannabis to manage a medical condition, 57% felt they were using too much or having associated problems. The mean number of DSM-5 CUD items endorsed was 5 (range = 0–11); 40% of subjects met criteria for mild/moderate CUD (2–5 items) and 54% had severe CUD (>5 items). Mean CUDIT score was 16 (range = 1–30); 85% surpassed the threshold for hazardous use (score>7). A majority (79%) expressed an interest in reducing their cannabis use instead of quitting completely (21%). 43% reported past-year treatment attempts for their cannabis use.

Figure 1.

Figure 1.

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Subject counts (x-axis) for cannabis use frequency (top left panel), past month days of cannabis use (bottom left panel) number of DSM-5 CUD criteria met (top right panel) and years of cannabis use (bottom right panel) (y-axes).

Some subjects also endorsed past 30-day use of alcohol (70%), prescription opioids (non-medical use; 17%), cocaine (11%) and heroin (n=8%), and 49% of subjects reported daily tobacco cigarette use. Mean score for the Alcohol Use Disorders Identification Test (AUDIT) was 11.7 (range = 1–25), suggestive of hazardous or harmful alcohol consumption. Mean score for the Fagerstrom Test for Nicotine Dependence (FTND) was 5.4 (range = 1–8), suggestive of moderate nicotine dependence.

Treatment Preferences Survey

Subjects preferred to participate in a combination of pharmacological and behavioral treatments (60%) relative to only behavioral therapy (25%), only a prescription medication (8%) or neither (6%). The mode response for willingness to participate in various types of treatments was “somewhat willing” for talk therapy (43%), prescription medication derived from a natural product (41%), contingency management (37%; tied with “very willing”), dietary supplement or other natural OTC product (35%) and a hallucinogen (30%), whereas the largest percentage (30%) of subjects were “neutral” about their willingness to take a synthetic prescription medication. When the “somewhat willing” and “very willing” categories were combined (Figure 2), the rank order of preferred treatment options were: contingency management (73%), talk therapy (59%), prescription medication derived from a natural product (56%), dietary supplement or other natural OTC product (52%), hallucinogen (47%) and synthetic prescription medication (33%).

Figure 2.

Figure 2.

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Number of subjects (x-axis) that endorsed a willingness to engage in different treatment options (y-axis).

Figure 3 summarizes subjects’ preferences for various aspects of pharmacological CUD treatment. 2/3rds expressed a willingness to take an oral pill, tablet or capsule daily to help reduce or quit their cannabis use, followed by daily use of mouth spray (53%), inhaler (34%), skin cream or patch (32%), nose spray (29%), or long-acting (e.g., 30-day) injection (18%). The majority (52%) expressed a preference for once-a-day administration, followed by 2x (30%), 3x (5%) and 4x (3%) a day, and unwillingness to take a medication daily (11%). The mode duration of treatment in which subjects would be willing to participate was tied at 3 and 6 months (39% of sample combined). Of the medication adherence monitoring methods, subjects were most willing to use a digital diary (52%) or medication container (48%) that could be reviewed online by a clinician, followed by direct observation at home by another person (32%); other options were chosen by less than 25% of the sample.

Figure 3.

Figure 3.

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Top panel: Number of subjects (x-axis) that endorsed a willingness to take a medication by different routes of administration (y-axis). Percentage of subjects that endorsed different medication administration frequencies each day (middle panel) and different medication treatment durations (bottom panel).

Figure 4 shows the types of behavioral therapy delivery methods preferred by individuals willing to participate in combined pharmacological and behavioral treatments (n = 45). The largest preference was for online one-on-one treatment appointments (49%). Combining categories revealed a preference for digital/online (47%) versus in-person (38%) treatments and one-on-one (59%) versus group sessions (36%). A small percentage (22%) preferred inpatient treatment (mode duration = 8 weeks).

Figure 4.

Figure 4.

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Number of subjects (x-axis) that endorsed a willingness to engage in different methods of behavioral treatment delivery (y-axis).

Marijuana Readiness to Change Ladder

The “rungs” of readiness to change ladders have been grouped conceptually as the pre-contemplation stage (rungs 1–3), contemplation stage (rungs 4–6), preparation stage (rungs 7–8), stage of action (rung 9) and maintenance stage (10). This subject sample fell largely within the preparation (37%) and contemplation (35%) stages, followed by pre-contemplation (24%), maintenance (2%) and action (1%) stages.

Barriers to Cannabis Cessation Scale

Subjects scored an average of 27 (range: 2–43) on this scale (maximum score = 54). Only the item “Having strong feelings such as anger, anxiety, sadness or feeling upset when alone” was ranked the highest in the large barrier category (41% of subjects). Discomfort (41%), the companionship of cannabis (40%), being addicted (35%) and withdrawal symptoms (35%) were ranked highest in the medium barrier category.

Adherence to Refills and Medications-Modified questionnaire (ARMS-Mod)

Subjects who endorsed regular current or past use of a prescription medication (n = 41) were asked how many prescription medications they were currently taking (mean = 4, mode = 2). Those individuals were also asked to complete the ARMS-Mod and scored an average of 12 (range: 0–23; maximum score = 40).

Beliefs about Medicines Questionnaire (BMQ)

Subjects scored an average of 32 (range: 17–46; maximum score = 50) on the BMQ-cannabis subscale. Collapsing across the “agree” and “strongly agree” categories, over half of the sample expressed concerns about immediate side effects (78%), cost (68%), long-term effects (65%) and becoming addicted to a medication for cannabis use disorder treatment (56%). Subjects scored an average of 26 (range: 11–39; maximum score = 45) on the BMQ-general subscale. Most subjects (71%) agreed that medications only work if they are taken as recommended.

Discussion

Prior research on SUD treatment preferences has relied on the opinions of current patients about existing treatment options.7 The only prior research that assessed preference for an SUD medication appears limited to the choice between methadone versus buprenorphine in patients with opioid use disorder.23,24 To inform future interventions for CUD, the present crowdsourced survey therefore examined hypothetical pharmacological and behavioral treatment preferences in individuals interested in cutting down or quitting their cannabis use, as well as responses on several measures theorized to be associated with treatment preferences.

Survey subjects were predominantly White, non-Hispanic, college educated and in their 30’s, consistent with subject demographics in other MTurk studies.25,26 Over half the sample reported at least one mental health disorder, with rates of individual disorders tending to being higher than what is observed in the general population. This increased frequency could be due to a greater propensity for MTurk subjects to endorse clinical symptoms,27,28 inaccurate self-diagnoses of these conditions by the subjects and/or the comorbidity between cannabis use disorder and various psychiatric conditions.29

Cannabis use outcomes indicated that the sample was appropriate for the intended purpose of the survey. Most subjects reported using multiple times daily, and the average duration of use was 10 years. In addition, all subjects endorsed having tried, currently trying, or being willing to try to quit or reduce their cannabis use, and 43% had used at least one prior treatment method. Readiness to change ratings on the Marijuana Ladder were also consistent with most subjects thinking about changing, and preparing to change, their cannabis use. A mix of recreational and medicinal use was reported, regardless of whether a physician’s recommendation for medicinal use was obtained. Further, of the subjects who used cannabis medicinally, 57% felt they were using too much or having problems associated with their medicinal cannabis use. 94% met DSM-5 criteria for CUD and 85% surpassed the CUDIT-R threshold for hazardous cannabis use.

One of the main findings from this study is an apparent bias against prescription medications in individuals reporting interest in reducing/quitting their cannabis use. For example, only 8% expressed a willingness to participate in treatment involving only a prescription medication. Most subjects were neutral about taking a synthetic pharmaceutical but were more favorable towards other treatment options. Moreover, taking a synthetic medication manufactured by a pharmaceutical company was ranked last among the treatment options presented. Further, the BMQ-cannabis revealed that the majority was apprehensive about various aspects of pharmacological CUD treatment, including immediate side effects, cost, long-term effects and becoming addicted to a CUD medication. These results suggest that providers could face challenges with initial acceptance of pharmacological treatment by patients.

Despite some apparent mistrust of prescription medications, about 2/3rd of subjects reported current or past use of them, with most currently taking two prescription medications. Adherence to obtaining and using medications was in line with other health conditions, with the mean ARMS-Mod score falling in the bottom third of the possible range.21 Of the adherence monitoring options, only those involving remote observation were acceptable to the majority. Related, rates of acceptance for dosing frequency declined sharply when increased beyond once per day, and most subjects were not willing to take a medication longer than 6 months. These findings suggest that adherence to a CUD medication would likely be comparable with other health conditions, and that treatment plans including once daily dosing, a short treatment duration and online monitoring methods could improve adherence.

This sample also preferred remote behavioral treatment delivery options, with little interest in inpatient treatment. These subjects’ inclination towards outpatient services is consistent with several other studies on SUD treatment preferences,30,31,32,33 though some patients with opioid use disorder have expressed a preference for inpatient services.34,35 Worth mentioning is that the preference for remote services could have been influenced by the COVID-19 pandemic, which was ongoing at the time of data collection. The present sample also preferred one-on-one treatment with a provider, consistent with prior work.23,33 When rank ordered, subjects were more willing to engage in the behavioral treatment options than any of the pharmacological treatments. These results support continued work to optimize and expand existing effective behavioral treatments that employ remote methods and technologies and could be combined with a medication. Indeed, prior work has demonstrated that combining multiple SUD treatments is more effective than single therapy approaches.36,37

An interesting finding was that nearly 80% of subjects preferred to reduce use rather than quit. The primary criterion for an SUD treatment to be considered effective has typically been its ability to engender sustained abstinence from the misused substance. However, there is a growing recognition that sustained abstinence could be too great of an expectation38 and that measures of function (e.g., cognitive, psychosocial, quality of life) or extent of the SUD (e.g., number of DSM-5 criteria met) might be more valuable for evaluating interventions instead of cannabis use.39,40 One notable caveat to this strategy is that quantifying reductions in ongoing cannabis use is difficult.40 Considering that reduced cannabis use is a treatment goal for many, determining its potential therapeutic value should be a priority for the field.

Limitations of the survey include the small sample size and use of an MTurk subject pool, so the results might not generalize to others who use cannabis. In addition, the small sample size prevented us from using more sophisticated analyses to explore the role of potential predictor variables on treatment preference, and the results presented here are only descriptive. Another limitation of a crowdsourced sample is that substance use cannot be biologically verified. Lastly, some of the questionnaires were modified for relevance to cannabis without accompanying validation. The extent to which these limitations influenced the results is unknown.

Conclusions

In summary, the present exploratory study indicated that efforts to develop CUD medications should focus on non-synthetic compounds that can be administered orally or via mouth spray no more than once per day in order to maximize patient acceptance. Incorporating remote adherence monitoring and one-on-one outpatient behavioral treatment approaches, especially CM, are also anticipated to enhance treatment participation. Another potentially valuable finding is that most subjects preferred to reduce their use, rather than quit. Future research is needed to determine if matching CUD patients with their preferred treatments improves rates of success.

Supplementary Material

Supplemental Data File (doc, pdf, etc.)

Funding:

This work was supported by R01 DA036550 and UL1TR001998.

Footnotes

Disclosures:

JAL is on a Scientific Review Board for Canopy Growth Corporation.

MBM is an employee of Canopy Growth Corporation, during which time he has received stock options. He was a previous member of the Board of Directors for AusCann Group Holdings Limited.

There are no other conflicts to report.

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