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. Author manuscript; available in PMC: 2026 Apr 7.
Published in final edited form as: J Atten Disord. 2025 May 17;29(9):757–765. doi: 10.1177/10870547251336841

ADHD Symptoms and Medical Cannabis Use Among Adults With Chronic Pain

David C Saunders 1,2, Deepika Slawek 3, Chenshu Zhang 4, Nancy Sohler 5, Chinazo Cunningham 3, Haruka Minami 6, Joanna Starrels 3, Julia Arnsten 3, Frances Levin 1,7
PMCID: PMC13051552  NIHMSID: NIHMS2138864  PMID: 40380798

Abstract

Objective:

We examined whether medical cannabis (MC) use was associated with change in ADHD symptoms across time in a sample of adults with chronic pain.

Methods:

We conducted a longitudinal cohort study (N = 223) across 12 months, assessing ADHD symptoms and MC use. We used mixed-effects linear regression to test whether MC use (vs. no use) and high THC (vs. low THC) MC was associated with change in ADHD symptoms from baseline to follow-up at quarterly intervals. We stratified by baseline ADHD symptoms and pain catastrophizing.

Results:

MC use was not associated with change in ADHD symptoms in the full sample or those with moderate/severe ADHD symptoms. Among those with minor/no baseline ADHD symptoms, high-THC MC (vs. low-THC) was associated with a decrease in ADHD symptoms.

Conclusions:

The null findings among participants with moderate/severe ADHD symptoms suggests that cannabis is unlikely to be a good treatment for ADHD. The preliminary findings in those with mild ADHD symptoms should be interpreted with caution given the small sample, the modest result, and all participants had chronic pain. These results may temper enthusiasm for MC as a treatment for ADHD, but further studies in larger and more generalizable samples may be justified.

Keywords: ADHD, substance related disorders, cannabis, chronic pain

Introduction

Attention-deficit/hyperactivity disorder (ADHD) is a widely prevalent neurodevelopmental condition characterized by inattention, impulsivity, and hyperactivity (American Psychiatric Association, 2013). Critically, untreated ADHD is associated with impairment in both childhood/adolescence and adulthood, such as adverse educational, social, health, and economic outcomes, including increased mortality (Barry et al., 2002; Dalsgaard, Leckman, et al., 2015; Dalsgaard, Østergaard, et al., 2015; Gordon & Moore, 2005; Huggins et al., 2015; Loe & Feldman, 2007).

Cannabis use is common and access is increasing due to policy changes (Klieger et al., 2017). Interestingly, the prevalence of ADHD is higher among people seeking treatment for cannabis use disorders than in the general population, ranging from 34% to 46% (Francisco et al., 2022; Notzon et al., 2020). Among people with ADHD, cannabis use is more prevalent and initiated earlier in comparison to those without ADHD (Brandt et al., 2018).

Individuals have reported that cannabis reduces their ADHD symptoms and/or ADHD medication side effects (Mitchell et al., 2016, 2018; Stueber & Cuttler, 2022; Wilens et al., 2007), perhaps via the perceived calming effects of cannabis (Dernbach et al., 2023). While one study provided preliminary evidence that cannabis may mitigate ADHD-related executive dysfunction, including hyperactivity and impulsivity (Stueber & Cuttler, 2022), outside of this study, there is little empirical evidence that cannabis improves ADHD symptoms (Harty et al., 2015). Rather, several recent studies suggest that chronic cannabis use may be associated with deficits in attention and concentration, (Meier et al., 2012; Parlar et al., 2021; Petker et al., 2020) and cannabis may exacerbate pre-existing ADHD symptoms or even precipitate ADHD-like symptoms (Parlar et al., 2021; Petker et al., 2020). Other evidence suggests that higher concentrations of tetrahydrocannabinol (THC) relative to the concentration of cannabidiol (CBD) in cannabis may impair cognition more than lower THC:CBD ratios (Colizzi & Bhattacharyya, 2017), suggesting that ratio of THC:CBD may differentially affect ADHD symptoms. However, studies have not been done in individuals with ADHD.

We conducted the Medical Marijuana and Opioids (MEMO) Study, a longitudinal cohort study (n = 223) to examine medical cannabis (MC) use among adults with chronic pain (Cunningham et al., 2020). Participants of the MEMO Study are all certified for MC for chronic pain. Notably, elevated ADHD symptom scores are associated with extreme pain (Battison et al., 2023), and high ADHD symptom scores (vs. moderate or low) are associated with higher risk of extreme pain (Stickley et al., 2016), widespread pain (Stray et al., 2013), and chronic pain (Kessler et al., 2009), as well as increased use of pain medications (Vingilis et al., 2015), and worse health-related quality of life (Lensing et al., 2015). The mechanism(s) underpinning these associations are poorly understood, but may be related to differences in neuroinflammation or other mechanisms (Battison et al., 2023). These findings suggest that ADHD symptom scores may be higher in the MEMO cohort than the general population.

Cannabis is commonly used to manage severe and chronic pain (Haroutounian et al., 2016; Lucas, 2012; Martín-Sánchez et al., 2009; Nugent et al., 2017; Romero-Sandoval et al., 2018). Interestingly, a recent systematic review concluded that cannabis with equal parts THC and CBD was associated with short-term improvement in chronic pain, noting that further studies are needed on long-term outcomes and other formulations (McDonagh et al., 2022).

Given increased ADHD scores among individuals with chronic pain, and that all MEMO Study participants are certified to receive MC, the cohort presents an opportunity to study the impact of cannabis use on ADHD symptoms.

Study Objectives

In the following study, we examined whether MC use was associated with change in ADHD symptoms across 12 months in a sample of individuals with chronic pain who were recommended MC for their chronic pain symptoms. We hypothesized that (1) use of MC (vs. none) would be associated with an increase in ADHD symptoms across 12 months; and (2) use of MC with a high-THC:CBD ratio (vs. low) would be associated with a greater increase in ADHD symptoms.

Methods

Study Background

As described in Cunningham et al. (2020), the Medical Marijuana and Opioids (MEMO) Study is an 18-month longitudinal cohort study examining how MC impacts opioid use in adults with chronic pain who are newly certified for MC use in New York (Cunningham et al., 2020; Ross et al., 2021). The protocol was approved by the Montefiore Medical Center/Albert Einstein College of Medicine (Montefiore) institutional review board (IRB# 2017-7857).

Recruitment

Participants were recruited from Montefiore and four MC dispensaries in New York City from November 2018 to January 2022. Study participants were adults who were fluent in English or Spanish, received a new certification for MC use within the past 90 days, and had an MC-qualifying condition of “chronic pain,” “pain that degrades health and functional capability as an alternative to opioid use,” or “severe or chronic pain resulting in substantial limitations of function.” More details on inclusion/exclusion criteria are available in Cunningham et al. (2020).

Data Sources

This is a secondary data analysis of data from the first 12 months of the MEMO Study. We collected data via four methods. First, we conducted research visits at baseline and every 3 months from November 2018 to January 2023. Research visits took place in-person until March 2020, when they transitioned to phone or video because of the Covid-19 pandemic. These interviews were conducted using Audio Computer-Assisted Self-Interview (ACASI) technology. The current study uses baseline, 3, 6, 9, and 12-month visit data. Pain medication data were collected from pharmacy records and from New York State’s Prescription Monitoring Program (PMP) over the same period described above. Web-based surveys using TelASK Technologies (Nepean, Ontario, Canada) were conducted every 2 weeks across 12 months to collect data on use of MC.

Dependent Variable

The primary outcome was change in ADHD symptoms as measured by the Adult ADHD Self-Report Rating Screening Scale for DSM-5 (ASRS-5; Ustun et al., 2017) score, collected at baseline and three-month intervals until 12-month follow-up. The scale consists of six items, with scores ranging from 0 to 25. The ASRS-5 is a validated screening instrument for DSM-5 ADHD, with high sensitivity, specificity and positive predictive value (91.4%, 96.0%, and 67.3%, respectively). We dichotomized ADHD symptom scores, with a score of ≥14 classified as “moderate/severe ADHD symptoms,” and <14 as “minor/no ADHD symptoms.” For each three-month interval, we computed a change score of ADHD symptoms compared to that at baseline and used it as the dependent variable.

Independent Variables

Our primary independent variables were (1) MC use and (2) cannabinoid content of MC used. We collected data on MC use every 2 weeks via web-based surveys between baseline and 12-month follow-up. We generated two dichotomous MC use variables for each participant at quarterly intervals (3, 6, 9, and 12 months from baseline): (1) MC use (vs. no use); and (2) predominantly high-THC product use (vs. use of other MC products). MC use was defined as reporting MC use during any 2-week period preceding each quarterly visit. “Predominantly high-THC use” was defined as using high-THC products (THC:CBD ratio ≥2:1) on more days across the preceding 3 months than the number of days using other MC products (THC:CBD ratio <2:1).

We collected sociodemographic data at baseline, including gender (male, female, transgender, other), age, race/ethnicity, years of education, employment status, poverty (annual income less than poverty level versus not [Department of Health and Human Services, 2023]), and health insurance status. We assessed physical and mental health symptoms at baseline, dichotomizing moderate/severe versus not: pain catastrophizing (Pain Catastrophizing Scale, range 0 to 52, moderate/severe ≥ 30; Cronbach’s α = .93 [Sullivan et al., 1995]), anxiety (General Anxiety Disorder −7 scale, range 0 to 21; moderate/severe ≥ 14; Cronbach’s α = .87 [Spitzer et al., 2006]), and depression, (Patient Health Questionnaire-9, range 0 to 27, moderate/severe≥10, Cronbach’s α = .84 [Kroenke et al., 2001]). We asked participants to report medication and substance use in the 30 days prior to baseline assessment including prescription opioid use (yes/no), unregulated cannabis use (yes/no), and MC use (days using MC in the past 2 weeks, continuous). Finally, we assessed health-related quality of life (EuroQOL Instrument 5D 5L, continuous [The EuroQol Group, 1990]).

Analyses

Baseline demographic and clinical characteristics of the sample are reported using descriptive statistics. To examine associations between baseline characteristics and severity of ADHD symptoms, we conducted chi-square tests (for categorical variables) and t-tests (for continuous variables). We used mixed-effects linear regression to test whether measures of MC use in the 3 months prior to each quarterly visit were associated with change in ADHD symptoms from baseline to each corresponding quarterly visit. Participants’ four quarterly visits were the units of analysis (months 3, 6, 9, and 12), with time as a control variable. This longitudinal approach allowed us to account for hierarchical data (repeated measures within participants).

All analyses above adjusted for baseline scores of known predictors of ADHD symptoms, including anxiety (Biederman et al., 2006; Katzman et al., 2017; GAD-7 score), depression (Katzman et al., 2017; Meizner, 2014; PHQ-9 score), and opioid use (Lugoboni et al., 2017; daily use vs. not daily use). We repeated analyses with stratified samples based on ADHD symptoms at baseline (moderate/severe [ADHD-RS score ≥ 14] vs. minor/no symptoms [ADHD-RS score < 14]). In sensitivity analyses, results were further stratified by pain catastrophizing (Slawek et al., 2021; moderate/severe vs. mild/none). We stratified by pain catastrophizing because (1) pain is a hallmark feature of this- sample, as all study participants have chronic pain conditions; and (2) we previously found that pain catastrophizing was associated with ADHD symptoms in this cohort (Slawek et al., 2021).

Finally, for missing data on the dependent variable (change in ADHD symptoms from baseline), we conducted multiple imputations (n of imputations = 5) using Markov Chain Monte Carlo imputation methods. For missing data on the independent variables (MC use), we conducted multiple imputations by applying a logistic regression model. We then conducted mixed effect linear regression analyses for each imputed data set and pooled the results into a single final result using Rubin’s (1987) method. We conducted analyses using SAS 9.4.

Results

Baseline Sample Characteristics

Of the 888 participants screened for the MEMO study, 223 enrolled and completed the baseline research visit; 211 (94.6%) completed at least 1 follow-up survey; and 163 (73.1%) completed all 4 follow-up surveys. These resulted in a total of 766 completed follow-up surveys by month 12. Participant characteristics of the full sample are presented in Table 1. The mean age was 56 years with 121 (54%) identifying as female. Non-Hispanic white participants comprised the largest portion of the sample (n = 78, 35%).

Table 1.

Bivariate Models for Factors Associated With ADHD Symptoms.

Participant characteristics Whole sample (N = 223)
 Moderate/severe ADHD symptomsa (N = 89, 40.4%)
 Minor/no ADHD symptomsa (N = 134, 59.6%)
 p-Valueb
N (%) or mean (SD) N (%) or mean (SD) N (%) or mean (SD)
Demographic characteristics
Female, n (%)  121 (54.3)  51 (57.3)  70 (52.2)  .457
Age (in years), mean (SD) 55.8 (13.0) 52.0 (13.2) 58.3 (12.3) <.001
Race and ethnicity  .057
 Hispanic, n (%)  58 (26.0)  28 (31.5)  30 (22.4)
 Non-Hispanic White, n (%)  78 (35.0)  36 (40.5)  42 (31.3)
 Non-Hispanic Black, n (%)  72 (32.3)  21 (23.6)  51 (38.1)
 Non-Hispanic other races, n (%)  15 (6.7)  4 (4.5)  11 (8.2)
Less than 12 years of education, n (%)  35 (15.7)  16 (18.0)  19 (14.2)  .445
Not employed, n (%) 174 (78.0)  69 (77.5) 105 (78.4)  .883
Poverty, n (%)c 126 (56.5)  51 (57.3)  75 (56.0)  .844
Not having private insurance, n (%) 175 (78.5)  73 (82.0) 102 (76.1)  .294
Physical and mental health
 Moderate/Severe pain catastrophizing symptoms, n (%)d 101 (45.3)  48 (53.9)  53 (39.6)  .035
 Moderate/Severe anxiety symptoms, n (%)e  82 (36.8)  48 (53.9)  34 (25.4) <.001
 Moderate/Severe depressive symptoms, n (%)f 102 (45.7)  61 (68.5)  41 (30.6) <.001
 Daily prescription opioid use, n (%) 117 (52.5)  47 (52.8)  70 (52.2)  .934
 Unregulated cannabis use, n (%)  65 (29.2)  25 (28.1)  40 (29.9)  .777
 Number of days using MC in the past two weeks, mean (SD) 4.8 (5.7)  4.9 (5.6)  4.8 (5.8)   .936
 Health-related quality of life, mean (SD)g 0.57 (0.18) 0.53 (0.19) 0.60 (0.16)  .004
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a

Score of ≥14 on the Adult Attention-Deficit Hyperactivity Disorder Self-Report Screening Scale for DSM-5 (ASRS-5).

b

Chi-square tests were conducted for categorical variables and t-tests were conducted for continuous variables.

c

Annual income lower than Federal Poverty Level in the US.

d

Score of ≥30 on the Pain Catastrophizing Scale (PCS).

e

Score of ≥10 on the General Anxiety Disorder-7 (GAD-7) scale.

f

Score of ≥10 on the Patient Health Questionnaire-9 (PHQ-9) scale.

g

EuroQOL 5D 5L.

Significant effects (p<0.05) in bold.

A substantial minority of the sample reported moderate or severe pain catastrophizing (n = 101 [45.3%]), anxiety (n = 82 [36.8%]), and depression (n = 102 [45.7%]) symptoms at baseline. More than half of the participants reported daily prescription opioid use (n = 117 [52.5%]), and more than a quarter of the participants reported unregulated cannabis use (n = 65 [29.2%]). Participants reported MC use a mean of 4.8 (SD = 5.7) days in the past 2 weeks.

At baseline, the mean (SD) score on the ASRS-5 was 11.4 [5.5]. Eighty-nine participants (40%) had moderate/severe ADHD symptoms (16.9 [2.5]) versus minor/no symptoms (n = 134 [60%]; 7.8 [3.7]). Participants with moderate/severe ADHD symptoms (vs. minor/no ADHD symptoms) were younger (52 vs. 58.3 years, p < .001), more likely to be Non-Hispanic white (p < .057), displayed higher pain catastrophizing (p < .05), reported more anxiety symptoms (p < .001), and depressive symptoms (p < .001), and lower health-related quality of life scores (p = .004). Correlation analyses showed that the number of missed surveys was not associated with baseline ADHD symptoms or other study variables (p > .05).

Change in ADHD Symptoms From baseline to 12 months

Table 2 displays the results of the stratified multiple mixed-effects linear regression models of change in ADHD symptoms from baseline to each of the quarterly visits (months 3, 6, 9, and 12) for the whole sample and the stratified sample, with all analyses adjusted for baseline anxiety, depression, and opioid use.

Table 2.

Stratified Multiple Mixed Effects Linear Regression Models for Factors Associated With Change in ADHD Symptoms From Baseline.

Variables Change in ADHD symptoms
Whole sample
 Moderate/severe ADHD symptoms (ASRS-5 score ≥ 14)
 Minor/no ADHD symptoms (ASRS-5 score <14)
n, visit points (VP) β [95% CI] p-Value n, visit points (VP) β [95% CI] p-Value n, visit points (VP) β [95% CI] p-Value
MC use (vs. none)
 Whole Sample n = 211, VP = 766 −.50 [−1.47, 0.47] .315 N = 84, VP = 307 .54 [−.98, 2.07] .482 n = 127, VP = 459 −.40 [−1.58, .79] .512
 Participants with moderate/severe pain catastrophizing n = 96, VP = 341 −1.03 [−2.40, .34] .140 n = 46, VP = 166 −.18 [−2.17, 1.81] .860 n = 50, VP = 175 −1.12 [−3.02, .78] .245
 Participants with mild/no pain catastrophizing n = 115, VP = 425  .11 [−1.31, 1.52] .883 n = 38, VP = 141 1.87 [−.66, 4.40] .145 n = 77, VP = 284 .12 [−1.47, 1.70] .886
High-THC (vs. other)
 Participants who use MC n = 169, VP = 530 −.86 [−1.75, .02] .056 n = 72, VP = 235 .01 [−1.23, 1.24] .989 n = 97, VP = 295 −1.51 [−2.73, −.29] .016
 Participants MC use and moderate/severe pain catastrophizing n = 73, VP = 215 −.91 [−2.24, .42] .179 n = 37, VP = 117 −.16 [−1.68, 1.37] .840 n = 36, VP = 98 −2.13 [−4.54, .28] .082
 Participants with MC use and mild/no pain catastrophizing n = 96, VP = 315 −.87 [−2.09, .34] .159 n = 35, VP = 118 .23 [−1.81, 2.27] .823 n = 61, VP = 197 −1.48 [−2.94, −.02] .047
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Note. Multiple analyses: baseline anxiety, depression, and opioid use were controlled.

Significant effects (p<0.05) in bold.

In both the full sample and among those with moderate/severe baseline ADHD symptoms, neither MC use nor high-THC MC use (among MC users) were associated with change in ADHD symptoms over time. Stratifying by pain catastrophizing (moderate/severe vs. mild/none) did not change these associations. Among those with minor/no baseline ADHD symptoms, MC use was also not associated with change in ADHD symptoms. However, among participants with minor/no baseline ADHD symptoms who used MC, high-THC MC use (vs. other MC products use) was associated with a decrease in ADHD symptoms (−1.51, CI = −2.73 to −0.29, p < .05). This association was maintained for those with mild/no pain catastrophizing (−1.48; CI = −2.94 to −0.02, p < .05), but not those with moderate/severe pain catastrophizing. In the analyses using imputed missing data, findings remained similar.

Discussion

In a sample of adults with chronic pain who are prescribed opioids and are newly certified for MC, self-reported use of MC (vs. no use) was not associated with a change in ADHD symptoms over a 12-month follow-up period. This non-association was observed across the full sample and when stratifying by ADHD symptoms. As such, our hypothesis that MC use would be associated with an increase in ADHD symptoms over time was not supported. Further, the results suggest that cannabis is unlikely to be an effective treatment for ADHD.

However, among those with minor or no ADHD symptoms at baseline—but not moderate/severe ADHD symptoms—use of high-THC MC was associated with a decrease in ADHD symptoms. One possible preliminary interpretation of this finding might be that THC (or an elevated ratio of THC:CBD) could reduce inattention/hyperactivity among those without ADHD. However, given that ADHD is a heterogeneous disorder with multiple symptom domains, and the six-item ASRS does not have subscales, the finding raises questions about which symptoms might be driving the observed effect (e.g., hyperactivity vs. inattention). Additionally, reductions in ADHD symptoms were driven by those with minor/no pain catastrophizing (n = 61), whereas reduction in ADHD symptoms was not observed in the moderate/severe pain catastrophizing group. These preliminary and modest findings might suggest that high-THC MC reduces ADHD symptoms as long as pain catastrophizing is minimal; that said, given limitations of the study design, (discussed below) further study is needed.

Together, the findings suggest that MC does not benefit those with an ADHD diagnosis, but may improve subclinical inattention/hyperactivity, especially high-THC cannabis, and among those who do not have pain catastrophizing. The discrepancy in findings among subgroups may explain the mixed reports of cannabis reducing ADHD symptoms in the literature. That said, the findings are preliminary and modest. Further, they draw from a relatively small sample size and a specific subpopulation.

The findings also raise interesting questions about the differential impact of THC versus CBD on ADHD symptoms. Specifically, that MC with a higher ratio of THC:CBD was associated with decreased sub-clinical ADHD symptoms might indicate that THC could improve mild inattention and hyperactivity, whereas CBD could worsen them, or both. However, to our knowledge, the differential association of THC and CBD on ADHD symptoms has not been investigated. While these results are preliminary, they point to a need for mechanistic studies of the differential association of THC and CBD on ADHD symptoms. Understanding the neural and molecular pathways underpinning these associations could shed light on critical differences in how THC and CBD affect all mental health outcomes, not just ADHD symptoms.

In sum, these findings may have implications for clinicians and researchers alike, though they should be interpreted with caution given the modest findings, and limitations of the study design and sample. Clinically, the findings should temper enthusiasm for cannabis as a stand-alone treatment for ADHD. For researchers, the differential findings based on THC:CBD ratio and level of pain catastrophizing suggest further study is warranted.

This study has several limitations. It was not designed to investigate the impact of MC on ADHD symptoms, nor adequately powered to do so. Second, all participants have chronic pain conditions, are either currently or have previously taken opioids for chronic pain, and were prescribed MC to explicitly address pain. That said, in sensitivity analyses, we tested for an association between baseline ADHD and changes in pain severity and did not find a significant association (not shown). That said, any changes in ADHD symptoms must be interpreted in this context, which may limit generalizability Third, ADHD symptom change was assessed exclusively via a six-item self-report screening instrument. A scale with only six items may not be the ideal instrument to capture symptom change over time, nor does it allow us to investigate specific symptoms or symptom clusters within ADHD. A more comprehensive ADHD diagnostic assessment may have produced different results. Finally, the clinical relevance of this result may be limited, given the findings are only apparent in the group with lower baseline ADHD symptoms.

Conclusion

In a sample of adults with chronic pain who were recently certified for MC, use of any MC was not associated with ADHD symptoms, regardless of severity of ADHD symptoms at baseline. These results suggest MC is unlikely to be an effective stand-alone treatment for ADHD. Among those with mild/no ADHD symptoms at baseline, use of high-THC-containing MC (vs. low-THC MC) was associated with a decrease in ADHD symptoms. However, these preliminary and modest findings preclude any recommendation that MC might be useful for ADHD, especially given that all participants have chronic pain. These results might temper enthusiasm for MC as a treatment for ADHD, but further studies in larger and more generalizable samples are needed.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institutes of Health’s National Institute on Drug Abuse (R01DA044171 [Arnsten], K23DA053997 [Slawek], K12DA000357 [Saunders]); by the National Center for Advancing Translational Sciences (UL1TR001073); and by the Einstein-Rockefeller-CUNY Center for AIDS Research (P30-AI124414), which is supported by the following NIH Co-Funding and Participating Institutes and Centers: NIAID, NCI, NICHD, NHBL, NIDA, NIMH, NIA, FIC, and OAR. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Biographies

David Saunders, MD PhD is an Assistant Professor of Psychiatry at New York State Psychiatric Institute/Columbia University, and child psychiatrist. His research focuses on mindfulness-based interventions for children and adolescents, including ADHD, as well as spirituality/religiosity and substance use disorders.

Deepika Slawek, MD, MS is an Associate Professor of Medicine at Montefiore Medical Center and Albert Einstein College of Medicine. She is board certified in Addiction Medicine and Infectious Diseases and her research to date has centered on the therapeutic uses of cannabinoids, treatment of opioid use disorder, and improving HIV outcomes in people living with HIV.

Chenshu Zhang, PhD, is a Research Associate Professor in the Department of Medicine at Albert Einstein College of Medicine. His research focuses on applied statistics and research design in medical research and behavioral science.

Nancy Sohler, PhD, MPH is an Associate Medical Professor at the CUNY School of Medicine. She is a psychiatric epidemiologist and mental health services researcher.

Chinazo Cunningham, MD, MS, is the Commissioner of the New York State Office of Addiction Services and Supports and Clinical Professor of Medicine, Family and Social Medicine, and Psychiatry and Behavioral Health at the Albert Einstein College of Medicine. Her areas of expertise include public health approaches to substance use disorders, opioid use disorder treatment, and the intersection between cannabis and opioid use.

Haruka Minami, PhD, is an Associate Professor in the Department of Psychology at Fordham University, New York. Her research interests lie in studying tobacco dependence and the process of smoking cessation/approaches to reduce harm from smoking among marginalized/underserved populations including individuals with medical and psychiatric disorders.

Joanna Starrels, MD, MS is a Professor of Medicine and Professor of Psychiatry & Behavioral Sciences at Albert Einstein College of Medicine and Montefiore Medical Center. Dr. Starrels’ research focuses on the intersection of substance use and pain.

Julia Arnsten, MD, MPH, is a physician, researcher, and division chief at Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY, USA. She has been funded since 1998 by the National Health Institutes of Health to study prevention and treatment of medical complications arising from opioid use disorder.

Frances Levin, MD, is the Kennedy-Leavy Professor of Psychiatry and an addiction psychiatrist at Columbia University, Vagelos College of Physicians and Surgeons and the New York State Psychiatric Institute. Her main areas of research are developing novel treatment interventions for individuals with substance use disorders with and without additional psychiatric comorbidities, and in particular adult attention-deficit hyperactivity disorder.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Statement

The protocol was approved by the Montefiore Medical Center/ Albert Einstein College of Medicine (Montefiore) institutional review board (IRB# 2017-7857). Oral informed consent is obtained prior to conducting screening questionnaires, and written informed consent is obtained at the time of enrollment into the study. Several steps are taken to protect participant confidentiality, including using a data management system that separates “name-based” and “study ID-based” documents, obtaining a Certificate of Confidentiality from the National Institute of Health, and using a two-step verification process to access the study database. We will disseminate study findings through presentations at scientific conferences, publications in peer-reviewed journals and presentations to medical cannabis stakeholders. Study findings will be reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology Statement.

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