Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Apr 12.
Published in final edited form as: Subst Use Misuse. 2022 Apr 11;57(7):1104–1110. doi: 10.1080/10826084.2022.2063899

Prevalence of Cannabis Use and Cannabis Route of Administration among Massachusetts Adults in Buprenorphine Treatment for Opioid Use Disorder

Joanna M Streck 1,2,3, Susan Regan 1,3, Benjamin Bearnot 1,3, Priya S Gupta 1,3, Sara Kalkhoran 1,3, Kelly M Kalagher 1, Sarah Wakeman 1,3, Nancy A Rigotti 1,3
PMCID: PMC10091221  NIHMSID: NIHMS1885330  PMID: 35410577

Abstract

Background:

Recent prevalence estimates of cannabis use among individuals receiving medication treatment for OUD (MOUD) are lacking, and no study has characterized cannabis route of administration (cROA) in this population. These knowledge gaps are relevant because cannabis’ effects and health outcomes vary by cROA and the availability and perceptions of cROA (e.g., vaping devices) are changing.

Methods:

The Vaping In Buprenorphine-treated patients Evaluation (VIBE) cross-sectional survey assessed the prevalence and correlates of cannabis use and cROA among adults receiving buprenorphine MOUD from 02/20 to 07/20 at five community health centers in Massachusetts, a state with legal recreational and medical cannabis use.

Results:

Among the 92/222 (41%) respondents reporting past 30-day cannabis use, smoking was the most common cROA (75%), followed by vaping (38%), and eating (26%). Smoking was more often used as a single cROA vs. in combination others (p=0.01), whereas vaping, eating, and dabbing were more often used in combination with another cROA (all p <0.05). Of the 39% of participants reporting multiple cROA, smoking and vaping (61%), and smoking and eating (50%), were the most prevalent combinations. Non-white race (vs. white) and current cigarette smoking (vs. no nicotine use) were associated with past 30-day cannabis use in multiple logistic regression.

Conclusions:

Prevalence of past 30-day cannabis use among individuals receiving buprenorphine MOUD in Massachusetts in 2020 was nearly double the prevalence of cannabis use in Massachusetts’ adult general population in 2019 (21%). Our data are consistent with state and national data showing smoking as the most common cROA.

Keywords: Cannabis, marijuana, route of administration, mode of cannabis use, buprenorphine, opioid use disorder

1.1. INTRODUCTION

Many states are moving to legalize cannabis and the landscape continues to rapidly evolve with each state taking a unique approach to designing legal cannabis laws (Borodovsky & Budney, 2018; NCSL, 2021). As of May 18, 2021, 36 states and four territories allow for the medical use of cannabis products, and as of November 29, 2021, 18 states, two territories and the District of Columbia have enacted legislation to regulate cannabis for nonmedical use (NCSL, 2021). In Massachusetts for example, both medical and nonmedical cannabis use is legal (NCSL, 2021). This rapidly evolving landscape has resulted in increased patient access to novel cannabis products that have yet to be thoroughly studied and has subsequently posed challenges for treatment providers such as how to address patient questions about potential clinical benefits of cannabis and to make recommendations (Borodovsky & Budney, 2018; Suzuki & Weiss, 2021; Wilkinson et al., 2016). For individuals with opioid use disorder (OUD), there has also been growing attention and debate around the potential clinical benefits of cannabis and cannabinoids as an alternative treatment for OUD, though scientists have argued there is insufficient evidence to recommend cannabis as an evidence-based treatment for OUD (Suzuki & Weiss, 2021).

National estimates suggest that past-year cannabis use is increasing in the United States (US) (Compton et al., 2019; Hasin, 2018), with a higher prevalence observed among vulnerable populations such as those with anxiety, depression, and substance use disorders (SUDs) (Hasin, 2018; Pacek et al., 2020; Weinberger et al., 2020). Among adults who are receiving medication treatment for opioid use disorder (MOUD) in clinical trials, the reported prevalence of cannabis use ranges from 28 to 79% at treatment baseline or throughout the study period, compared to ~8.5% past month prevalence in the general adult population (Dai & Richter, 2019; Hasin, 2018; Lake & St Pierre, 2020). It has been hypothesized that the increased prevalence of cannabis use in those receiving MOUD may be due to patients using cannabis as a supplement to self-manage symptoms of opioid craving or withdrawal, pain, or related symptoms such as anxiety (Hurd et al., 2019; Scavone et al., 2013). However, recent prevalence estimates of cannabis use among adults receiving MOUD are lacking, and most prevalence data derives from clinical trials rather than from community samples (Lake & St Pierre, 2020). Consequently, there are few high-quality data to assess the prevalence of cannabis use among community samples receiving MOUD, particularly buprenorphine, in states with legalized medical or recreational cannabis.

An additional knowledge gap is that most existing studies of cannabis use, including studies among individuals receiving MOUD, do not assess cannabis route of administration (cROA)(Lake & St Pierre, 2020; Medicine et al., 2017). cROA is clinically relevant because cannabis’ effects (e.g., onset, intensity, duration) and associated health outcomes vary widely by cROA (NASEM, 2017; Russell et al., 2018; Suzuki & Weiss, 2021). cROA among individuals receiving MOUD is particularly relevant due to recent attention on cannabis as a potential alternative treatment for OUD (Russell et al., 2018; Suzuki & Weiss, 2021) and because of ongoing shifts in the use, availability, and perceptions of cannabis and various cROA products (i.e., vaping devices)(Lake & St Pierre, 2020; Pearson & Villanti, 2020; Spindle et al., 2019). A prior cohort study of cannabis users reported that use of more vs. fewer cROA in the past year was associated with more problematic cannabis use and increased other non-medical substance use (Baggio et al., 2014). The number of cROA used by individuals receiving MOUD may hold particular relevance due to concerns about maintenance of OUD treatment stability in this population. Existing reviews suggest that cannabis use by patients receiving MOUD may not negatively impact MOUD treatment outcomes or stability, but the overall evidence is of low quality (Lake & St Pierre, 2020), and no data are available on the association of different cROA with MOUD outcomes.

Using data from a cross-sectional survey study of adults receiving buprenorphine for OUD across community health centers in eastern Massachusetts, a state where recreational and medical cannabis use is currently legal, we aimed to conduct a prevalence study to quantify the current (past 30-day) prevalence of cannabis use and cROA and examine correlates of current cannabis use and single vs. poly cROA among a community sample of current cannabis users receiving buprenorphine for OUD.

2.1. MATERIALS AND METHODS

2.2. Design and Participants

The Vaping In Buprenorphine-treated patients Evaluation (VIBE) study was a cross-sectional survey conducted from February to July 2020, among adults (≥18 years) who were receiving buprenorphine treatment for OUD (i.e., received a buprenorphine prescription in the past 2 months) at five community health centers (CHCs) affiliated with a large Boston, Massachusetts, health care system (N=222). Current buprenorphine treatment status was determined based on a report extracted from the electronic health record and confirmed by email communication with the prescribing CHC clinician at the time of enrollment. The study methods have previously been published (Streck et al., 2021). The primary goal of the VIBE study was to assess smoking and electronic cigarette use patterns. The present investigation represents a secondary analysis of the VIBE survey study examining cannabis use prevalence and patterns. All VIBE study participants provided informed consent and the study was approved by the MassGeneral Brigham institutional review board. At the MGH CHCs, in the office-based buprenorphine treatment programs, cannabis use is not included as part of the standard urine drug screening and not routinely monitored, thus it is the provider’s discretion to ask/assess cannabis use if they deem appropriate.

2.3. Measures

2.3.1. Demographic, Psychiatric, Substance Use and Treatment Characteristics

Demographic factors assessed age, gender, race, ethnicity, employment, and education level. The Generalized Anxiety Disorder (GAD-7) scale (Spitzer et al., 2006) was used to assess anxiety symptomatology in the past two weeks and the Patient Health Questionnaire (PHQ-8)(Kroenke et al., 2009) assessed depressive symptoms in the past 2-weeks. Response options on the GAD-7 and PHQ-8 ranged from 0–3 with scores on each scale summed to form total scores with higher scores indicating more severe symptomatology (Kroenke et al., 2009; Spitzer et al., 2006). The AUDIT-C was used to screen for alcohol use in the past 6 months with response options ranging from 0 to 4 and higher total summary scores indicating more problematic use (Bush et al., 1998). Participants self-reported past month intravenous drug use (yes/no). Nicotine use was assessed by querying participants about their past 30-day cigarette and electronic cigarette (e-cigarette) use (yes/no) and time to first cigarette and e-cigarette in the morning for those endorsing past 30-day use of cigarettes and e-cigarettes, respectively (Fagerström, 2012). The total daily dose of buprenorphine (in milligrams), and the length of time in current buprenorphine treatment were extracted from the electronic health record.

2.3.2. Cannabis Use and Route of Administration

For the VIBE study, cannabis was defined as “marijuana/cannabis products, such as tetrahydrocannabinol (THC), hashish, or cannabidiol (CBD).” THC and CBD were combined in the present survey as the focus of the VIBE study was on nicotine use and thus, we sought to reduce response burden by limiting the length of our survey instrument for other substances. The survey assessed self-reported ever and past 30-day use of cannabis (yes/no) as well as past 30-day cannabis route of administration (cROA) using a single item adapted from the Behavioral Risk Factor Surveillance System (BRFSS)(CDC, 2020) which asked participants how they used marijuana, THC, hashish or CBD in the past 30 days. Participants could check as many response options as applicable. Response options assessed smoke, vaporize, ate, drank, dabbed or used cannabis in some other way. “Dabbing” refers to the inhalation of highly concentrated THC (Mullins, 2021).

2.4. Statistical Methods

Demographic, psychiatric, and substance use and treatment characteristics were compared across past 30-day cannabis use status (i.e., use vs. no use) as well as across single vs. poly (>1) cROA using chi-squared tests and t-tests. Variables that differed in bivariate testing for past 30-day cannabis use status (i.e., p≤0.10) were included in an adjusted logistic regression model which tested participant factors associated with past 30-day cannabis use (vs. no use). Race was dichotomized for adjusted analyses (white vs. other race) due to cell size limitations because of low prevalence of non-white races. For participants with partially completed GAD-7 or PHQ-8 questionnaires (n=2 participants for GAD-7 and n=1 for PHQ-8), we imputed their scores with the mean of non-missing values. One participant did not complete any items on the GAD-7 or PHQ-8; their summary score could not be imputed and was not included in analyses.

All analyses were conducted in STATA version 16 (StataCorp. 2019, College Station, TX: StataCorp LLC) and significance set at p<0.05.

3.1. RESULTS

The VIBE study attempted to contact 520 patients and reached 323 (62%). Of those reached, 222 (69%) completed a survey. Survey completers evidenced stability in OUD treatment (mean of 3 years duration in current treatment; Streck et al., 2021) and non-prescribed opioid use based on toxicology at the last CHC visit did not differ by past 30-day cannabis use nor by cROA. Additional details of VIBE survey completion (and non-response) and OUD treatment stability have been previously published (Streck et al., 2021).

3.1.1. Prevalence of Cannabis Route of Administration (cROA)

Ever and past 30-day cannabis use was reported by 87% (193/222) and 41% (92/222) of survey respondents, respectively. Among past 30-day cannabis users, smoking cannabis was the most common cROA (69/92, 75%), followed by vaping (35/92, 38%) and eating (24/92, 26%) (Figure 1). While 61% (56/92) of past 30-day cannabis users reported using a single cROA in the past 30 days, a substantial minority (36/92, 39%) reported using multiple cROA. Smoking was more likely to be used as a single cROA vs. in combination with another cROA in the past 30-days (p=0.01), whereas vaping, eating and dabbing were each more likely to be used as a poly (vs. single) cROA (all p’s<.05; Figure 1). Among those reporting use of multiple cROA in the past 30 days, the most frequent combinations of cROA were smoking and vaping (22/36, 61%), followed by smoking and eating (18/36, 50%) and then vaping and eating (11/36, 31%).

Figure 1.

Figure 1.

Open in a new tab

Prevalence of past 30-day cannabis route of administration among Massachusetts adults in Buprenorphine treatment for opioid use disorder who report past 30-day cannabis use (N=92/222)

Key. cROA, cannabis route of administration.

Note. Listed in parentheses on x axis are the overall n and percent of participants reporting use of each cROA of the past 30-day cannabis users. Bar labels represent percentages. Poly cROA represents those reporting >1 cROA. Cannabis was defined for participants as marijuana, marijuana concentrates or waxes, THC, hashish or CBD oils. CBD, cannabidiol. “Other” routes of administration endorsed were dronabinol (n=1), topical (e.g., lotion) (n=3), oral drops (n=4).

*In chi square testing, smoking was more likely to be used as a single vs. poly cROA (p=0.01), and vaping, eating and dabbing were each more likely to be used as a poly vs. single cROA (all p’s<.05).

3.1.2. Correlates of Past 30-day Cannabis Use and cROA

In bivariate analyses, race was the only factor examined that differed significantly by past 30-day cannabis use status (Table 1). Participants identifying as white race were less likely to report past 30-day cannabis use (70/92, 76%) vs. no past 30-day cannabis use (116/130, 89%) (p<.01) and participants identifying as Black or multiple races were more likely to reported past 30-day cannabis use compared to no past 30-day use (Table 1). Participant’s average daily dose of buprenorphine was significantly associated with single vs. poly cROA use, with those using multiple cROA (vs. a single mode) in the past 30-days on a higher daily dose of buprenorphine (Mean=20 vs. 17 milligrams, p=0.01). Additional associations of variables (p≤10) with past 30-day cannabis use (e.g., AUDIT-C, past 30-day nicotine use) and single vs. poly cROA (e.g., ethnicity; Table 1) were included in multivariable regression analyses detailed below (see statistical methods section for details).

Table 1.

Correlates of past 30-day cannabis use and single vs. poly cannabis route of administration among Massachusetts adults in Buprenorphine treatment for opioid use disorder

Past 30-day Cannabis Use
(N=92, 41%)		 No Past 30-day Cannabis Use
(N=130, 59%)		 Bivariate p value Adjusted Odds Ratio (Confidence Interval), p value Past 30-day Single cROA
(N=56, 61%)		 Past 30-day Poly cROA
(N=36, 39%)		 Bivariate p value
Demographic
Age, M±SD 44±10 47±12 0.13 45±10 43±9 0.22
Gender 0.20 0.88
 Male 52 (57%) 62 (48%) 32 (57%) 20 (56%)
 Female 40 (43%) 68 (52%) 24 (43%) 16 (44%)
Race <.01 0.25
 White 70 (76%) 116(89%) 0.43 (0.20–0.93), p=0.03 45 (80%) 25 (69%)
 Black 6 (7%) 5 (4%) Ref 4 (7%) 2 (6%)
 Other racea 5 (5%) 7 (5%) 1 (2%) 4 (11%)
 Multiple races 11 (12%) 2 (2%) 6 (11%) 5 (14%)
Ethnicity 0.68 0.08
 Hispanic origin 9 (10%) 15 (12%) 3 (5%) 6 (17%)
 Non-Hispanic 83 (90%) 115(88%) 53 (95%) 30 (83%)
Employmentb 0.54 0.75
 Unemployed 53 (58%) 69 (53%) 33 (59%) 20 (56%)
 Employed full or part-time 39 (42%) 60 (47%) 23 (41%) 16 (44%)
Educationb 0.38 0.72
 ≤high school 43 (47%) 68 (53%) 27 (48%) 16 (44%)
 > high school 49 (53%) 61 (47%) 29 (52%) 20 (56%)
Psychiatric
PHQ-8, M±SD 9±7 8±7 0.21 9±7 9±6 0.72
GAD-7, M±SD 10±7 8±7 0.10 1.02 (0.98–1.07), p=0.28 10±7 9±6 0.45
Substance Use & Treatment
AUDIT-C, M±SD 2±3 1±2 0.08 1.06 (0.95–1.18), p=0.28 2±3 2±3 0.95
Time in BUP treatment, yrs, M±SD 3±1 3±1 0.10 0.91 (0.73–1.12), p=0.37 3±1 3±1 0.40
Daily dose of BUP, mg, M±SD 18±7 17±7 0.24 17±7 20±6 0.01
Past 30d injection drug use 0.79 0.97
 Yes 5 (5%) 6 (5%) 3 (5%) 2 (6%)
 No 87 (95%) 123(95%) 53 (95%) 34 (94%)
Nicotine
Past 30day nicotine use 0.08 0.14
 No use 11 (12%) 31 (24%) Ref 7 (13%) 4 (11%)
 Cigarettes only 53 (58%) 58 (45%) 2.43 (1.07–5.47), p=0.03 34 (61%) 19 (53%)
 Nicotine e-cigarettes only 10 (11%) 10 (8%) 3.15 (1.00–9.96), p=0.05 8 (14%) 2 (6%)
 Dual cigarette/e-cigarette use 18 (20%) 31 (24%) 1.80 (0.71–4.59), p=0.22 7 (13%) 11 (31%)
Smokes cigarette within 30m of waking 45 (64%) 51 (58%) 0.66 23 (58%) 22 (73%) 0.17
Vapes nicotine e-cigarette within 30m of waking 21 (81%) 28 (68%) 0.26 12 (86%) 9 (75%) 0.49
Open in a new tab

Key. cROA, cannabis route of administration. Poly cROA represents those reporting >1 cROA. BUP, buprenorphine. M, minute; D, day. Ref, reference group for multivariate analyses.

Note. Tabled values represent N (column percent) unless otherwise indicated. P value columns represents bivariate analyses using chi-squared testing or t-tests. Race was dichotomized for the multivariate analysis (white vs. other races) in order increase cell size. Variables that differed in bivariate analyses at p≤0.10 level were included in adjusted logistic regression analyses for past 30-day cannabis use. Adjusted analyses were not conducted for single vs. poly cROA due to insufficient cell sizes. Bolded p values represent p<0.05.

a

Other race included Asian (n=1), American Indian/Alaskan Native (n=2), “other” (n=9)

b

One participant responded, “don’t know” to this item and their data was excluded.

In a multivariable logistic regression analysis, white race (vs. other races) and past 30-day cigarette smoking (vs. no nicotine use) were each independently associated with past 30-day cannabis use (vs. no use), such that those who identified as other race and current cigarette smokers were more likely to report current cannabis use (p’s<0.05; Table 1).

Given the association of cigarette smoking and past 30-day cannabis use in the multivariable analysis, we conducted additional bivariate post-hoc descriptive analyses probing the association between past 30-day cigarette smoking (vs. no cigarette smoking) and each cROA using chi-squared testing (data not pictured). Past 30-day cigarette smoking was significantly associated with past 30-day cannabis smoking such that past 30-day smokers had higher prevalence of past 30-day cannabis smoking (57/160, 36%) compared to non-cigarette smokers (12/62, 19%) (p=0.02). There were no other significant associations between past 30-day cigarette smoking and the other cROA examined.

4.1. DISCUSSION

This secondary analysis of a cross-sectional survey study examined the prevalence and patterns of past 30-day cannabis use and cROA among adults who were receiving MOUD with buprenorphine at five CHCs in metropolitan Boston, Massachusetts, a state in which medical and recreational cannabis use is legal. The prevalence of recent cannabis use (41%) was substantial and was higher among current cigarette smokers and nonwhite individuals. The majority of cannabis users reported only one cROA, which was most often smoking, but 39% used multiple cROA that combined cannabis vaping, smoking, and eating in various patterns.

The past 30-day 41% prevalence of current cannabis use among adults receiving MOUD in this study, which was conducted in 2020, is nearly double the past 30-day 21% prevalence found in a sample representative of the Massachusetts adult general population in 2019 by the Massachusetts Department of Public Health Marijuana Baseline Health Study (MBHS)(MDPH, 2019). Despite the difference in prevalence, the pattern of cannabis use in our study resembles that reported in the MBHS, which also found that smoking was the most commonly reported cROA among adults (51%) and that a substantial minority (43%) of Massachusetts adults used multiple cROA. The Massachusetts pattern matches recent systematic reviews (US and international) showing higher prevalence of cannabis use in patients receiving MOUD (Lake & St Pierre, 2020) vs. those without OUD, and smoking as the most common cROA in the general population (Spindle et al., 2019). Our investigation provides more recent (2020) cannabis prevalence estimates and novel cROA data showing that smoking is the most common cROA among patients receiving MOUD with buprenorphine.

We observed a high prevalence of cannabis use and cannabis vaping in our sample even though data were collected following events that might have lowered use. We collected data from February to July 2020, just following Massachusetts’ temporary total vaping product sales ban from September 25, 2019 to December 11, 2019. The ban was imposed due to the recognition of E-cigarette or Vaping-Product Use-Associated Lung Injury (EVALI) cases beginning in August 2019. The cases were eventually linked to contaminants in vaped THC products (King et al., 2020). Data have suggested that EVALI led to heightened risk perceptions of vaping (Dave et al., 2020). However, our prevalence of vaping cannabis (38%) was substantially higher than the prevalence observed in MBHS (3%) whose data were collected prior to EVALI suggesting that in our sample, EVALI may not have led to substantial concerns about vaping cannabis, however we did not directly assess participant’s cannabis vaping behavior in response to EVALI. Additionally, our data were collected during the height of the first wave of the COVID-19 pandemic in Massachusetts, which could have either increased or decreased cannabis use, though little work has investigated COVID-19’s impact on vaping behavior either in the general population or among those with OUD (Kalkhoran et al., 2021; Klemperer et al., 2020; Streck et al., 2021). In our prior work among individuals with OUD at the MGH CHCs, we found mixed effects of COVID-19 on self-reported nicotine vaping behavior, with 20% having attempted to quit nicotine vaping due to the pandemic and some participants increasing their amount vaped (27%), others decreasing the amount they vaped (16%), and the majority not reporting any changes in their nicotine vaping behavior (56%) (Streck et al., 2021). However, there is insufficient prior research on COVID’s impact on vaping cannabis in the general population or among individuals with OUD to draw conclusions from our data. Regardless, our data showed a substantial prevalence of cannabis vaping, which was higher than estimates observed recently in the general Massachusetts population, despite the context of EVALI and COVID-19.

Our multivariate analyses demonstrated that past 30-day cigarette smoking and non-white race were each associated with past 30-day use of cannabis. This is consistent with prior literature, including nationally-representative data, which has established that there are higher rates of cannabis use in cigarette smokers (vs. nonsmokers) and in African-American individuals (vs. other races)(Goodwin et al., 2017; Hasin et al., 2017; Keyes et al., 2017; Pacek et al., 2012; Schauer et al., 2015), and we extend these findings to individuals receiving MOUD. However, our results for race should be interpreted with caution as our sample was predominantly white, and we had little racial diversity. In the general population, there are documented differences in cannabis use by sex, with men more likely to initiate cannabis use and develop a use disorder (Wagner & Anthony, 2007), and differences in cannabis use by anxiety and depression status with higher prevalence of cannabis use among those with these psychiatric symptoms (Gorfinkel et al., 2020). Very few studies have examined predictors of cannabis use among individuals with OUD, however a few emerging studies report that these differences in cannabis use by sex and anxiety/depression may extend to those with OUD (Lake & St Pierre, 2020; Parker et al., 2018). We found a non-significant difference in past 30-day cannabis use among men vs. women in our sample (46% vs. 37%). This is consistent with a prior report of Canadian individuals in methadone treatment using a larger sample size (N=777), surveyed during a time when cannabis was not legal, which reported significantly higher rates of past 3-month cannabis use in men (60%) vs. women (44%)(Zielinski et al., 2017). Finally, while not statistically significant, we did observer higher rates of anxiety among those using cannabis in the past 30 days vs. those not using cannabis in our sample.

Our study was limited in that we did not have biochemical data on cannabis use, collect data on how participants obtained cannabis (e.g., medical vs. recreational), nor assess the presence of a cannabis use disorder or other indicators of problematic use. Additionally, the sample sizes for various cROA limited our statistical ability to make comparisons among individual cROA or to investigate predictors of individual cROA. Our definition of cannabis use included both THC and CBD. We can’t disentangle use of THC vs. CBD, though our results are strengthened by use of a validated assessment of cROA from the BRFSS (CDC, 2020). The present investigation was a cross-sectional survey study and causality of associations cannot be inferred. Finally, our study surveyed participants in the Eastern Massachusetts area, thus our findings cannot be generalized to other regions where prevalence of cannabis and use of various cROAs may differ.

These limitations notwithstanding, to our knowledge, this is the first report to characterize cannabis routes of administration among adults receiving MOUD. Consistent with the Massachusetts and US general population, smoking was the most common cROA reported by adults receiving MOUD with buprenorphine. We also provide updated (2020) prevalence estimates of past 30-day cannabis use among individuals in buprenorphine treatment in a state that permits both recreational and medical cannabis use. Our data suggest a higher prevalence of cannabis use in patients with MOUD than the adult general population, even during events that might have discouraged cannabis use.

Role of Funding Source

This work was supported by the National Institute on Drug Abuse (NIDA K12 DA043490; Rigotti) and sundry funds provided by Dr. Rigotti. The funding organization had no role in the study design, collection, analysis, and interpretation of the data, preparation of the manuscript, or decision to submit the manuscript for publication.

Footnotes

Disclosures of interest

Dr. Rigotti receives royalties from UpToDate, has consulted for Achieve Life Sciences, and consulted (without pay) for Pfizer. Dr. Kalkhoran has received royalties from UpToDate. Dr. Wakeman receives royalties from UpToDate and has received salary support from OptumLabs, Celero Systems, and Alosa Health. No other authors have conflicts of interest to disclose.

REFERENCES

  1. Baggio S, Deline S, Studer J, Mohler-Kuo M, Daeppen J-B, & Gmel G (2014). Routes of administration of cannabis used for nonmedical purposes and associations with patterns of drug use. The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine, 54(2), 235–240. 10.1016/j.jadohealth.2013.08.013 [DOI] [PubMed] [Google Scholar]
  2. Borodovsky JT, & Budney AJ (2018). Cannabis regulatory science: Risk-benefit considerations for mental disorders. International Review of Psychiatry (Abingdon, England), 30(3), 183–202. 10.1080/09540261.2018.1454406 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bush K, Kivlahan DR, McDonell MB, Fihn SD, & Bradley KA (1998). The AUDIT alcohol consumption questions (AUDIT-C): An effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Archives of Internal Medicine, 158(16), 1789–1795. [DOI] [PubMed] [Google Scholar]
  4. CDC - BRFSS. (2020, August 31). https://www.cdc.gov/brfss/index.html
  5. Compton WM, Han B, Jones CM, & Blanco C (2019). Cannabis use disorders among adults in the United States during a time of increasing use of cannabis. Drug and Alcohol Dependence, 204, 107468. 10.1016/j.drugalcdep.2019.05.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Dai H, & Richter KP (2019). A National Survey of Marijuana Use Among US Adults With Medical Conditions, 2016–2017. JAMA Network Open, 2(9), e1911936. 10.1001/jamanetworkopen.2019.11936 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Dave D, Dench D, Kenkel D, Mathios A, & Wang H (2020). News that takes your breath away: Risk perceptions during an outbreak of vaping-related lung injuries. Journal of Risk and Uncertainty, 60(3), 281–307. 10.1007/s11166-020-09329-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Fagerström K (2012). Determinants of tobacco use and renaming the FTND to the Fagerstrom Test for Cigarette Dependence. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco, 14(1), 75–78. 10.1093/ntr/ntr137 [DOI] [PubMed] [Google Scholar]
  9. Goodwin RD, Pacek LR, Copeland J, Moeller SJ, Dierker L, Weinberger A, Gbedemah M, Zvolensky MJ, Wall MM, & Hasin DS (2017). Trends in Daily Cannabis Use Among Cigarette Smokers: United States, 2002–2014. American Journal of Public Health, 108(1), 137–142. 10.2105/AJPH.2017.304050 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Gorfinkel LR, Stohl M, & Hasin D (2020). Association of Depression With Past-Month Cannabis Use Among US Adults Aged 20 to 59 Years, 2005 to 2016. JAMA Network Open, 3(8), e2013802. 10.1001/jamanetworkopen.2020.13802 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Hasin DS (2018). US Epidemiology of Cannabis Use and Associated Problems. Neuropsychopharmacology, 43(1), 195–212. 10.1038/npp.2017.198 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hasin DS, Sarvet AL, Cerdá M, Keyes KM, Stohl M, Galea S, & Wall MM (2017). US Adult Illicit Cannabis Use, Cannabis Use Disorder, and Medical Marijuana Laws: 1991–1992 to 2012–2013. JAMA Psychiatry, 74(6), 579–588. 10.1001/jamapsychiatry.2017.0724 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Hurd YL, Spriggs S, Alishayev J, Winkel G, Gurgov K, Kudrich C, Oprescu AM, & Salsitz E (2019). Cannabidiol for the Reduction of Cue-Induced Craving and Anxiety in Drug-Abstinent Individuals With Heroin Use Disorder: A Double-Blind Randomized Placebo-Controlled Trial. The American Journal of Psychiatry, 176(11), 911–922. 10.1176/appi.ajp.2019.18101191 [DOI] [PubMed] [Google Scholar]
  14. Kalkhoran S, Levy DE, & Rigotti NA (2021). Smoking and Vaping Among a National Sample of U.S. Adults During the COVID-19 Pandemic. MedRxiv, 2021.03.18.21253902. 10.1101/2021.03.18.21253902 [DOI] [Google Scholar]
  15. Keyes KM, Wall M, Feng T, Cerda M, & Hasin D (2017). Race/ethnicity and marijuana use in the United States:Diminishing differences in the prevalence of use, 2006 to 2015. Drug and Alcohol Dependence, 179, 379–386. 10.1016/j.drugalcdep.2017.07.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. King BA, Jones CM, Baldwin GT, & Briss PA (2020). E-cigarette, or Vaping, Product Use-Associated Lung Injury: Looking Back, Moving Forward. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco, 22(Supplement_1), S96–S99. 10.1093/ntr/ntaa186 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Klemperer EM, West JC, Peasley-Miklus C, & Villanti AC (2020). Change in tobacco and electronic cigarette use and motivation to quit in response to COVID-19. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco. 10.1093/ntr/ntaa072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kroenke K, Strine TW, Spitzer RL, Williams JBW, Berry JT, & Mokdad AH (2009). The PHQ-8 as a measure of current depression in the general population. Journal of Affective Disorders, 114(1–3), 163–173. 10.1016/j.jad.2008.06.026 [DOI] [PubMed] [Google Scholar]
  19. Lake S, & St Pierre M (2020). The relationship between cannabis use and patient outcomes in medication-based treatment of opioid use disorder: A systematic review. Clinical Psychology Review, 82, 101939. 10.1016/j.cpr.2020.101939 [DOI] [PubMed] [Google Scholar]
  20. Massachusetts Department of Public Health (2019). Marijuana Baseline Health Study. Retrieved from https://www.mass.gov/doc/marijuana-based-health-study-final-report/download
  21. Medicine, N. A. of S., Engineering, and, Division, H. and M., Practice, B. on P. H. and P. H., & Agenda, C. on the H. E. of M. A. E. R. and R. (2017). The Health Effects of Cannabis and Cannabinoids: The Current State of Evidence and Recommendations for Research. National Academies Press. [PubMed] [Google Scholar]
  22. Mullins MF (2021). Cannabis dabbing: An emerging trend. Nursing, 51(5), 46–50. 10.1097/01.NURSE.0000743108.72528.d8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. NCSL. (2021). State Medical Cannabis Laws. Retrieved January 4, 2022, from https://www-ncsl-org.ezp-prod1.hul.harvard.edu/research/health/state-medical-marijuana-laws.aspx
  24. Pacek LR, Malcolm RJ, & Martins SS (2012). Race/Ethnicity Differences between Alcohol, Marijuana, and Co-Occurring Alcohol and Marijuana Use Disorders and their Association with Public Health and Social Problems using a National Sample. The American Journal on Addictions / American Academy of Psychiatrists in Alcoholism and Addictions, 21(5), 435–444. 10.1111/j.1521-0391.2012.00249.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Pacek LR, Weinberger AH, Zhu J, & Goodwin RD (2020). Rapid increase in the prevalence of cannabis use among people with depression in the United States, 2005–17: The role of differentially changing risk perceptions. Addiction (Abingdon, England), 115(5), 935–943. 10.1111/add.14883 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Parker MA, Streck JM, Bergeria CL, Bunn JY, Galeema DE, Davis DR, Barrows AJ, Sigmon SC, Tidey JW, Heil SH, & Higgins ST (2018). Reduced Nicotine Content Cigarettes and Cannabis Use in Vulnerable Populations. Tobacco Regulatory Science, 4(5), 84–91. 10.18001/TRS.4.5.8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Pearson JL, & Villanti AC (2020). It Is Past Time to Consider Cannabis in Vaping Research. Nicotine & Tobacco Research, 22(5), 597–598. 10.1093/ntr/ntaa012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Russell C, Rueda S, Room R, Tyndall M, & Fischer B (2018). Routes of administration for cannabis use - basic prevalence and related health outcomes: A scoping review and synthesis. The International Journal on Drug Policy, 52, 87–96. 10.1016/j.drugpo.2017.11.008 [DOI] [PubMed] [Google Scholar]
  29. Scavone JL, Sterling RC, Weinstein SP, & Van Bockstaele EJ (2013). Impact of cannabis use during stabilization on methadone maintenance treatment. The American Journal on Addictions, 22(4), 344–351. 10.1111/j.1521-0391.2013.12044.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Schauer GL, Berg CJ, Kegler MC, Donovan DM, & Windle M (2015). Assessing the overlap between tobacco and marijuana: Trends in patterns of co-use of tobacco and marijuana in adults from 2003–2012. Addictive Behaviors, 49, 26–32. 10.1016/j.addbeh.2015.05.012 [DOI] [PubMed] [Google Scholar]
  31. Spindle TR, Bonn-Miller MO, & Vandrey R (2019). Changing landscape of cannabis: Novel products, formulations, and methods of administration. Current Opinion in Psychology, 30, 98–102. 10.1016/j.copsyc.2019.04.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Spitzer RL, Kroenke K, Williams JBW, & Löwe B (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. 10.1001/archinte.166.10.1092 [DOI] [PubMed] [Google Scholar]
  33. Streck JM, Kalkhoran S, Bearnot B, Gupta PS, Kalagher KM, Regan S, Wakeman S, & Rigotti NA (2021). Perceived risk, attitudes, and behavior of cigarette smokers and nicotine vapers receiving buprenorphine treatment for opioid use disorder during the COVID-19 pandemic. Drug and Alcohol Dependence, 218, 108438. 10.1016/j.drugalcdep.2020.108438 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Suzuki J, & Weiss RD (2021). Cannabinoids for the Treatment of Opioid Use Disorder: Where is the Evidence? Journal of Addiction Medicine, 15(2), 91–92. 10.1097/ADM.0000000000000711 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Wagner FA, & Anthony JC (2007). Male-female differences in the risk of progression from first use to dependence upon cannabis, cocaine, and alcohol. Drug and Alcohol Dependence, 86(2–3), 191–198. 10.1016/j.drugalcdep.2006.06.003 [DOI] [PubMed] [Google Scholar]
  36. Weinberger AH, Zhu J, Levin J, Barrington-Trimis JL, Copeland J, Wyka K, Kim JH, & Goodwin RD (2020). Cannabis use among US adults with anxiety from 2008 to 2017: The role of state-level cannabis legalization. Drug and Alcohol Dependence, 214, 108163. 10.1016/j.drugalcdep.2020.108163 [DOI] [PubMed] [Google Scholar]
  37. Wilkinson ST, Yarnell S, Radhakrishnan R, Ball SA, & D’Souza DC (2016). Marijuana Legalization: Impact on Physicians and Public Health. Annual Review of Medicine, 67, 453–466. 10.1146/annurev-med-050214-013454 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Zielinski L, Bhatt M, Sanger N, Plater C, Worster A, Varenbut M, Daiter J, Pare G, Marsh DC, Desai D, MacKillop J, Steiner M, McDermid Vaz S, Thabane L, & Samaan Z (2017). Association between cannabis use and methadone maintenance treatment outcomes: An investigation into sex differences. Biology of Sex Differences, 8, 8. 10.1186/s13293-017-0130-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES