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Background: Craving is a core clinical feature of cannabis use disorder (CUD) and a predictor of treatment outcomes, yet its temporal course during treatment is not well characterized. This study aimed to identify latent classes of cannabis craving trajectories among adults with CUD and examine associated baseline predictors and cannabis use outcomes.

Methods: This was a secondary analysis of the National Drug Abuse Treatment Clinical Trials Network’s CTN-0053 trial, a 12-week, multisite randomized controlled trial of N-acetylcysteine versus placebo for adults with CUD (N = 302). Cannabis craving was measured using the Marijuana Craving Questionnaire–Short Form at six treatment timepoints (weeks 1–5, 9 and 12) and one 5-week post-treatment follow-up (week 17). Urine cannabinoid tests were conducted twice weekly throughout treatment and follow-up. Latent class growth analysis identified craving trajectories. The present study aimed to identify latent classes of cannabis craving over 12 weeks of treatment and examine baseline predictors of class membership.

Results: A four-class solution provided the best fit: low craving (41%), moderate-decreasing craving (38%), moderate-stable craving (11%), and high craving (10%). Participants in higher craving classes exhibited greater baseline anxiety, depression, and obsessive-compulsive symptoms related to cannabis use. The high craving class had the greatest proportion of cannabis positive urine tests (96%) and the lowest urine test completion rate.

Conclusions: Craving follows heterogeneous trajectories during CUD treatment and is associated with co-occurring mental health symptoms and poorer outcomes. Dynamic craving assessment may support personalized treatment and strategies to prevent return to use.

Related protocols: CTN-0053

While approximately one in five Americans with substance use disorder (SUD) receives treatment in addiction treatment programs, a majority have seen a primary care medical provider in the past year. Recognizing the critical role of primary care in addressing prevention and treatment of unhealthy substance use, for over a decade the National Drug Abuse Treatment Clinical Trials Network (CTN) has supported research to build the tools and evidence needed to support the integration of SUD care, while remaining realistic about the barriers to doing so. Authored by primary care and addiction medicine physician researchers, this commentary provides an overview of CTN primary care-focused research, from developing and implementing substance use screening tools to advancing evidence-based SUD treatment delivery in primary care settings. We identify three priority areas for research and practice innovations: 1) identifying effective treatment interventions to address polysubstance use; 2) improved screening and treatment for cannabis use; and 3) building the evidence base for substance use interventions among non-treatment seeking patients who have unhealthy drug use identified through screening. Addressing these areas can help primary care fulfill its potential as a key component of the substance use services continuum of care.

Objectives: Assessment and counseling are recommended for individuals with prenatal cannabis use. We examined characteristics that predict prenatal substance use assessment and counseling among individuals who screened positive for prenatal cannabis use in prenatal settings.

Methods: Electronic health record data from Kaiser Permanente Northern California’s Early Start perinatal substance use screening, assessment, and counseling program was used to identify individuals with =1 pregnancies positive for prenatal cannabis use. Outcomes included completion of a substance use assessment and among those assessed, attendance in Early Start counseling only or Addiction Medicine Recovery Services (AMRS) treatment. Predictors included demographics and past-year psychiatric and substance use disorder diagnoses evaluated with GEE multinomial logistic regression.

Results: The sample included 17,782 individuals with 20,398 pregnancies positive for cannabis use (1/2011-12/2021). Most pregnancies (80.3%) had an assessment. Individuals with Medicaid, anxiety, depression and tobacco use disorders, compared to those without, had higher odds and those with greater parity, older age (=35) and in later trimesters, had lower odds of assessment. Among 64% (n = 10,469) pregnancies needing intervention based on assessment, most (88%) attended Early Start counseling only or AMRS (with or without Early Start). Greater parity and later trimester assessment was associated with lower odds, while Medicaid was associated with higher odds of Early Start counseling. Nearly all diagnosed psychiatric and substance use disorders were associated with higher odds of AMRS treatment.

Conclusions: A comprehensive prenatal substance use program engaged most pregnant individuals with prenatal cannabis use in substance use assessment and counseling. Opportunities to improve care gaps remain.

Related protocols: CTN-0140

Aims: Cannabis use is highly prevalent in patients seeking treatment for opioid use disorder. Studies have shown mixed results on the association between cannabis use and opioid use as well as the impact of MOUD on cannabis use. The current study aims to investigate the effects of buprenorphine versus naltrexone on cannabis use outcomes in treatment seeking individuals with Opioid Use Disorder (OUD).

Methods: The current study was based on data from the CTN-0051 X:BOT trial, which compared the opioid relapse-free survival outcomes of two treatment seeking groups, one receiving Extended-Release Naltrexone (XR-naltrexone) (N=283) versus another receiving Buprenorphine-Naloxone (N=287) for OUD. A mixed-effects logistic regression model including treatment assignment (buprenorphine-naloxone vs XR-naltrexone), time, and a time by treatment interaction was run on the sample with the odds of cannabis use as the outcome, as well as two cross-lagged mediation models to explore the prospective mediation of cannabis use on opioid use outcomes (and opioid use on cannabis use outcomes) by treatment assignment during the trial.

Results: There was a significant effect of buprenorphine treatment on reduced cannabis use. Participants receiving buprenorphine treatment were 39% less likely to use cannabis than those receiving naltrexone over all the timepoints (p=.0499). No significant mediation was found between treatment assignment and opioid use on cannabis use outcomes or between treatment assignment and cannabis use on opioid use outcomes in this trial.

Conclusion: Participants in this trial receiving buprenorphine treatment for OUD used less cannabis than those receiving naltrexone treatment.

Related protocols: CTN-0051

Background: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored.

Objective: Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey.

Participants: Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019-9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included.

Main measures: We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies.

Key results: Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3-19.2%) and 0.9% (0.0-2.7%) for < monthly to 44.6% (41.4-47.7%) and 20.3% (17.8-22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey.

Conclusions: Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.

Related protocols: CTN-0077-Ot

Objective: This secondary analysis evaluated the validation results of the Tobacco, Alcohol, Prescription Medication, and Other Substance Use (TAPS) tool for older adults.

Methods: Researchers performed a subgroup analysis of older adults aged =65 (n = 184) from the TAPS tool validation study conducted in 5 primary care clinics (CTN-0059). They compared the interviewer and self-administered versions of the TAPS tool at a cutoff of =1 for identifying problem use with a reference standard measure, the modified World Mental Health Composite International Diagnostic Interview.

Results: The mean age was 70.6 ± 5.9 years, 52.7% were female, and 49.5% were non-Hispanic Black. For identifying problem use, the self-administered TAPS tool had sensitivity of 0.91 (95% CI: 0.75–0.98) and specificity of 0.91 (95% CI: 0.85–0.95) for tobacco; sensitivity of 0.68 (95% CI: 0.45–0.86) and specificity of 0.88 (95% CI: 0.82–0.93) for alcohol; and sensitivity 0.86 (95% CI: 0.42–1.00) and specificity 0.94 (95% CI: 0.90–0.97) for cannabis. The interviewer-administered TAPS tool had similar results. Researchers were unable to evaluate its performance for identifying problem use of individual classes of drugs other than cannabis in this population due to small sample sizes.

Conclusions: While the TAPS had excellent sensitivity and specificity for identifying tobacco use among older adults, the results for other substances lack precision, and we were unable to evaluate its performance for prescription medications and individual illicit drugs in this sample. This analysis underlines the critical need to adapt and validate screening tools for unhealthy substance use, specifically for older populations who have unique risks.

Related protocols: CTN-0059

This population-based cross-sectional study, supported by CTN-0140, analyzed electronic health record data of pregnant individuals in an integrated health care delivery system in California to examine changes in prenatal cannabis use through self-report and urine toxicology testing during standard prenatal care between 2012 (n=33,546) and 2022 (n=43,415) and to test whether trends differed by race and ethnicity or age. The prevalence of prenatal cannabis use increased from 5.5% in 2012 to 9% in 2022, with similar increases by toxicology test and self-report. The increase in prevalence varied significantly across racial and ethnic and age groups, with the highest prevalence among Black individuals and those aged 13-24 across years. Although rates increased more slowly among groups with the highest prevalence of use, disparities persisted over time. These increases highlight the need to inform all pregnant individuals of the potential risks associated with prenatal cannabis use and connect them with nonjudgmental, culturally sensitive interventions, as needed.

Related protocols: CTN-0140

The goal of this study, part of CTN-0140 (Cannabis Use Among Pregnant Women with Polysubstance Use and Psychiatric Problems), was to estimate the strength of association between psychiatric disorders and substance use disorders (SUD), and cannabis use and cannabis use disorder (CUD) during early pregnancy. Participants were 299,496 pregnancies from 227,555 individuals screened for cannabis use by self-report and a urine toxicology test at entrance to prenatal care in Kaiser Permanente Northern California during January 2011-December 2021 (excepting year 2020). The sample was 62.5% non-White, with a mean (standard deviation) age of 31.1 (5.5) years; 6.8% used cannabis; 0.2% had a CUD.

Exposure variables included electronic health record-based psychiatric diagnoses of attention deficit hyperactivity, anxiety, bipolar, depressive, personality, posttraumatic stress and psychotic disorders; and alcohol, opioid, stimulant and tobacco use disorders, during the two years prior to pregnancy up to the day before the prenatal substance use screening date. Outcome variables were any cannabis use, frequency of self-reported cannabis use and CUD during early pregnancy.

Psychiatric disorder prevalence ranged from 0.2% (psychotic) to 14.3% (anxiety), and SUD ranged from 0.3% (stimulant/opioid) to 3.8% (tobacco). Psychiatric disorders were associated with cannabis use and CUD, with the strongest association for any use found for bipolar disorder (adjusted odds ratio [aOR] = 2.83; 95% confidence interval [CI] = 2.53-3.17) and the strongest association for CUD found for psychotic disorders (aOR = 10.01, 95% CI = 6.52-15.37). SUDs were associated with cannabis use and CUD, with the strongest association for any use found for tobacco use disorder (aOR = 4.03, 95% CI = 3.82-4.24) and the strongest association for CUD found for stimulant use disorder (aOR = 21.99, 95% CI = 16.53-29.26). Anxiety, bipolar, depressive disorders and tobacco use disorder were associated with greater odds of daily than monthly or less cannabis use.

Conclusions: Psychiatric disorders and substance use disorders appear to be associated with elevated odds of any and frequent cannabis use as well as cannabis use disorder during early pregnancy. In most cases, the associations with cannabis outcomes were stronger for substance use disorders than other psychiatric disorders.

Related protocols: CTN-0140

In their complementary presentations, Drs. Hammond and Hinckley discuss the association between cannabis use and suicide-related outcomes among youth and young adults. Dr. Hammond presents findings from a study that used 20 years of national mortality data to examine the impact of medical and recreational cannabis legalization on suicide-related mortality among US 12-to-25-year-olds, focusing on variations by age, sex, race, and ethnicity. These findings are discussed within the context of current medical literature on cannabis policy effects and health disparities, with an emphasis on mechanisms, vulnerable
subgroups, and legislative reform. Dr. Hinckley presents data from a secondary analysis of the National Comorbidity Survey-Adolescent Supplement, involving youth aged 13-18. This study explores the association between cannabis use, major depressive disorder, and suicidal behavior. Findings are considered within existing literature to further understand how cannabis use and depression together may increase suicide risk among youth.

The prevalence of cannabis use disorder (CUD) is increasing in the US and primary care providers need tools to identify patients with moderate-severe CUD to facilitate treatment. A single-item screen for cannabis (SIS-C) has outstanding discriminative validity for CUD. However, because the prevalence of moderate-severe CUD is typically low, the probability that an average patient who screens positive for daily cannabis has moderate-severe cannabis use disorder is low, making follow-up assessment important.

This study, part of CTN-0077-Ot, reports the discriminative validity of a DSM-5 Substance Use Symptom Checklist (“Checklist”) for moderate-severe CUD among 498 primary care patients who reported daily cannabis use on the SIS-C. We evaluated the performance of the Checklist (score 0–11) completed during routine care, compared to =4 DSM-5 CUD symptoms (moderate-severe CUD) on the Composite International Diagnostic Interview Substance Abuse Module from a confidential survey (reference standard). We estimated areas under receiver operating curve (AUROC), sensitivities, specificities, and post-test probabilities.

Of 498 eligible patients, 17% met diagnostic criteria for moderate-severe CUD. The Checklist’s AUROC for moderate-severe CUD was 0.77 (95% CI: 0.71–0.83), and Checklist scores of 1–2 balanced sensitivity and specificity. Among patients from a population with average prevalence of CUD before screening (~6% prevalence) and daily use on the SIS-C, a Checklist score of 3 indicated a post-test probability of 82.1%.

Conclusions: Overall performance of the Checklist was good and the high specificity made it useful for identifying patients likely to have moderate-severe CUD among those at average risk.

Related protocols: CTN-0077-Ot

Substance use disorders (SUDs) are underdiagnosed in healthcare settings. The Substance Use Symptom Checklist (SUSC) is a practical, patient-report questionnaire that has been used to assess SUD symptoms based on Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria. This study evaluates the test-retest reliability of SUSCs completed in primary and mental health care settings.

In this study, researchers identified 1194 patients who completed two SUSCs 1–21 days apart as part of routine care after reporting daily cannabis use and/or any past-year other drug use on behavioral health screens. Test-retest reliability of SUSC scores was evaluated within the full sample, subsamples who completed both checklists in primary care (n=451) or mental health clinics (n=512) where SUSC implementation differed, and subgroups defined by sex, insurance status, age, and substance use reported on behavioral health screens.

In the full sample, test-retest reliability was high for indices reflecting the number of SUD symptoms endorsed (ICC=0.75, 95% CI:0.72–0.77) and DSM-5 SUD severity (kappa=0.72, 95% CI:0.69–0.75). These reliability estimates were higher in primary care (ICC=0.81, 95% CI:0.77–0.84; kappa=0.79, 95% CI:0.75–0.82, respectively) than in mental health clinics (ICC=0.74, 95% CI:0.70–0.78; kappa=0.73, 95% CI:0.68–0.77). Reliability differed by age and substance use reported on behavioral health screens, but not by sex or insurance status.

Conclusions: The SUSC has good-to-excellent test-retest reliability when completed as part of routine primary or mental health care. Symptom checklists can reliably measure symptoms consistent with DSM-5 SUD criteria, which may aid SUD-related care in primary care and mental health settings.

Related protocols: CTN-0113

Medical cannabis is commonly used for chronic pain, but little is known about differences in characteristics, cannabis use patterns, and perceived helpfulness among primary care patients who use cannabis for pain versus nonpain reasons.

Among 1688 patients who completed a 2019 cannabis survey administered in a health system in Washington state, where recreational use is legal, participants who used cannabis for pain (n = 375) were compared with those who used cannabis for other reasons (n = 558) using survey and electronic health record data. We described group differences in participant characteristics, use patterns, and perceptions and applied adjusted multinomial logistic and modified Poisson regression.

Participants who used cannabis for pain were significantly more likely to report using applied (50.7% vs 10.6%) and beverage cannabis products (19.2% vs 11.6%), more frequent use (47.1% vs 33.1% for use =2 times per day; 81.6% vs 69.7% for use 4 to 7 days per week), and smoking tobacco cigarettes (19.2% vs 12.2%) than those who used cannabis for other reasons. They were also significantly more likely to perceive cannabis as very/extremely helpful (80.5% vs 72.7%), and significantly less likely to use cannabis for nonmedical reasons (4.8% vs 58.8%) or report cannabis use disorder symptoms (51.7% vs 61.1%).

Conclusions: Primary care patients who use cannabis for pain use it more frequently, often in applied and ingested forms, and have more co-use of tobacco, which may differentially impact safety and effectiveness. These findings suggest the need for different approaches to counseling in clinical care.

Related protocols: CTN-0077-Ot

Medical and nonmedical cannabis use and cannabis use disorders (CUD) have increased with increasing cannabis legalization. However, the prevalence of CUD among primary care patients who use cannabis for medical or nonmedical reasons is unknown for patients in states with legal recreational use.

The goal of this study, a secondary analysis of data from CTN-0077-Ot, was to estimate the prevalence and severity of CUD among patients who report medical use only, nonmedical use only, and both reasons for cannabis use in a state with legal recreational use.

This cross-sectional survey study took place at an integrated health system in Washington State. Among 108 950 adult patients who completed routine cannabis screening from March 2019 to September 2019, 5000 were selected for a confidential cannabis survey using stratified random sampling for frequency of past-year cannabis use and race and ethnicity. Among 1688 respondents, 1463 reporting past 30-day cannabis use were included in the study.

Patient responses to the Composite International Diagnostic Interview-Substance Abuse Module for CUD, corresponding to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition CUD severity (0-11 symptoms) were categorized as any CUD (=2 symptoms) and moderate to severe CUD (=4 symptoms). Adjusted analyses were weighted for survey stratification and nonresponse for primary care population estimates and compared prevalence of CUD across reasons for cannabis use.

Of 1463 included primary care patients (weighted mean [SD] age, 47.4 [16.8] years; 748 [weighted proportion, 61.9%] female) who used cannabis, 42.4% (95% CI, 31.2%-54.3%) reported medical use only, 25.1% (95% CI, 17.8%-34.2%) nonmedical use only, and 32.5% (95% CI, 25.3%-40.8%) both reasons for use. The prevalence of CUD was 21.3% (95% CI, 15.4%-28.6%) and did not vary across groups. The prevalence of moderate to severe CUD was 6.5% (95% CI, 5.0%-8.6%) and differed across groups: 1.3% (95% CI, 0.0%-2.8%) for medical use, 7.2% (95% CI, 3.9%-10.4%) for nonmedical use, and 7.5% (95% CI, 5.7%-9.4%) for both reasons for use (P=.01).

Conclusions: In this cross-sectional study of primary care patients in a state with legal recreational cannabis use, CUD was common among patients who used cannabis. Moderate to severe CUD was more prevalent among patients who reported any nonmedical use. These results underscore the importance of assessing patient cannabis use and CUD symptoms in medical settings.

Related protocols: CTN-0077-Ot

Screening for substance use in rural primary care clinics faces unique challenges due to limited resources, high patient volumes, and multiple demands on providers. To explore the potential for electronic health record (EHR)-integrated screening in this context, researchers conducted an implementation feasibility study with a rural federally-qualified health center (FQHC) in Maine. This was an ancillary study to a NIDA Clinical Trials Network study of screening in urban primary care clinics (CTN-0062).

Researchers worked with stakeholders from three FQHC clinics to define and implement their optimal screening approach. Clinics used the Tobacco, Alcohol, Prescription Medication, and Other Substance (TAPS) Tool, completed on tablet computers in the waiting room, and results were immediately recorded in the EHR. Adult patients presenting for annual preventive care visits, but not those with other visit types, were eligible for screening. Data were analyzed for the first 12 months following implementation at each clinic to assess screening rates and prevalence of reported unhealthy substance use, and documentation of counseling using an EHR-integrated clinical decision support tool, for patients screening positive for moderate-high risk alcohol or drug use.

Screening was completed by 3749 patients, representing 93.4% of those with screening-eligible annual preventive care visits, and 18.5% of adult patients presenting for any type of primary care visit. Screening was self-administered in 92.9% of cases. The prevalence of moderate-high risk substance use detected on screening was 14.6% for tobacco, 30.4% for alcohol, 10.8% for cannabis, 0.3% for illicit drugs, and 0.6% for non-medical use of prescription drugs. Brief substance use counseling was documented for 17.4% of patients with any moderate-high risk alcohol or drug use.

Conclusions: Self-administered EHR-integrated screening was feasible to implement, and detected substantial alcohol, cannabis, and tobacco use in rural FQHC clinics. Counseling was documented for a minority of patients with moderate-high risk use, possibly indicating a need for better support of primary care providers in addressing substance use. There is potential to broaden the reach of screening by offering it at routine medical visits rather than restricting to annual preventive care visits, within these and other rural primary care clinics.

Related protocols: CTN-0062-Ot

Brief cannabis screening followed by standardized assessment of symptoms may support diagnosis and treatment of cannabis use disorder (CUD). This study tested whether the probability of a medical provider diagnosing and treating CUD increased with the number of substance use disorder (SUD) symptoms documented in patients’ EHRs.

This observational study from the Health Systems Node (related to CTN-0113) used EHR and claims data from an integrated healthcare system. Adult patients were included who reported daily cannabis use and completed the Substance Use Symptom Checklist, a scaled measure of DSM-5 SUD symptoms (0-11), during routine care 3/1/2015-3/1/2021. Logistic regression estimated associations between SUD symptom counts and: 1) CUD diagnosis; 2) CUD treatment initiation; and 3) CUD treatment engagement, defined based on Healthcare Effectiveness Data and Information Set (HEDIS) ICD-codes and timelines. We tested moderation across age, gender, race, and ethnicity.

Patients (N=13,947) were predominantly middle-age, male, White, and non-Hispanic. Among patients reporting daily cannabis use without other drug use (N=12,568), the probability of CUD diagnosis, treatment initiation, and engagement increased with each 1-unit increase in Symptom Checklist score (p’s<0.001). However, probabilities of diagnosis, treatment, and engagement were low, even among those reporting =2 symptoms consistent with SUD: 14.0% diagnosed (95% CI: 11.7-21.6), 16.6% initiated treatment among diagnosed (11.7-21.6), and 24.3% engaged in treatment among initiated (15.8-32.7). Only gender moderated associations between Symptom Checklist and diagnosis (p=0.047) and treatment initiation (p=0.012). Findings were similar for patients reporting daily cannabis use with other drug use (N=1,379).

Conclusions: This study highlights the need to improve diagnosis and treatment of CUD in general medical settings. While the probability of provider-documented CUD diagnosis and treatment increased with patient-report of symptoms, most patients with severe CUD did not receive diagnosis or treatment. The probability of CUD diagnosis and treatment could be even lower in other settings without routine cannabis assessment. There were missed opportunities across all sociodemographic subgroups, but women with severe CUD may be particularly less likely to initiate treatment. Further research should identify optimal approaches for initiating and engaging patients in CUD treatment in medical settings.

Related protocols: CTN-0113