Age differences in patterns of cannabis use among an online US sample of adults who consume cannabis frequently.

Background: Cannabis use is increasing among middle-aged and older US adults, populations that are particularly vulnerable to the adverse effects of cannabis. Risks for adverse effects differ by cannabis use patterns, which have become increasingly heterogeneous. Nevertheless, little is known about age differences in such patterns.Objective: To investigate age differences in cannabis use patterns, comparing younger (age 18-49), middle-aged (age 50-64), and older adults (age ≥65).Methods: A total of 4,151 US adults with past 7-day cannabis consumption completed an online survey (35.1% male; 60.1% female; 4.8% identified as "other"). Regression models examined age differences in cannabis use patterns.Results: Compared to younger adults, middle-aged and older adults were more likely to consume cannabis during evening hours (50-64: adjusted odds ratio [aOR] = 2.98, 95% CI 2.24-3.96; ≥65: aOR = 4.23, 95 CI 2.82-6.35); by only one method (50-64: aOR = 1.67, 95% CI 1.34-2.09; ≥65: aOR = 3.38, 95 CI 2.24-5.09); primarily by smoking as the only method (50-64: aOR = 1.52, 95% CI 1.29-1.78; ≥65: aOR = 2.12, 95 CI 1.64-2.74); but less likely to consume concentrated cannabis products (concentrates) with extremely high %THC (50-64: aOR = 0.71, 95% CI 0.54-0.93; ≥65: aOR = 0.30, 95 CI 0.16-0.55). Age differences in cannabis use patterns were also observed between middle-aged and older adults.Conclusion: Findings suggest that middle-aged and older adults may engage in less risky cannabis use patterns compared to younger groups (e.g. lower likelihood of consuming highly potent concentrates). However, findings also underscore the importance of recognizing risks unique to these older demographics, such as smoking-related health events. Consequently, prevention strategies targeting such use patterns are needed.

HealthCall: Smartphone Enhancement of Brief Interventions to Improve HIV Medication Adherence Among Patients in HIV Care.

Heavy drinking among people living with HIV (PLWH) reduces ART adherence and worsens health outcomes. Lengthy interventions are not feasible in most HIV care settings, and patients infrequently follow referrals to outside treatment. Utilizing visual and video features of smartphone technology, we developed HealthCall as an electronic means of increasing patient involvement in a brief intervention to reduce drinking and improve ART adherence. The objective of the current study is to evaluate the efficacy of HealthCall to improve ART adherence among PLWH who drink heavily when paired with two brief interventions: the National Institute on Alcoholism and Alcohol Abuse (NIAAA) Clinician's Guide (CG) or Motivational Interviewing (MI). Therefore, we conducted a 1:1:1 randomized trial among 114 participants with alcohol dependence at a large urban HIV clinic. Participants were randomized to one of three groups: (1) CG only (n = 37), (2) CG and HealthCall (n = 38), or (3) MI and HealthCall (n = 39). Baseline interventions targeting drinking reduction and ART adherence were ~ 25 min, with brief (10-15 min) booster sessions at 30 and 60 days. The outcome was ART adherence assessed using unannounced phone pill-count method (possible adherence scores: 0-100%) at 30-day, 60-day, 3, 6, and 12 months. Analyses were conducted using generalized linear mixed models with pre-planned contrasts. Of the 114 enrolled patients, 58% were male, 75% identified as Black/African American, 28% were Hispanic, and 62% had less than a high school education. The mean age was 47.5 years (standard deviation [SD] 10 years) and the mean number of years since they were diagnosed with HIV was 18.6 (SD 7.6). Participants assigned to HealthCall to extend the CG had increased levels of ART adherence at 60-day and 6-month follow-up (compared to CG only), although there was no statistically significant difference by 12-month follow-up. Participants who were assigned to HealthCall to extend the MI never had statistically significant higher levels of ART adherence. These results suggest that the use of a smartphone app can be used to initially extend the reach of a brief drinking intervention to improve ART adherence over a short period of time; however, sustained long-term improvements in ART adherence after intervention activity ends remains a challenge.

An Intervention to Reduce Drinking Among Individuals With HIV and Hepatitis C: A Pilot Randomized Controlled Trial.

OBJECTIVE: Heavy drinking poses serious risks to individuals with HIV, hepatitis C virus (HCV), and especially HIV/HCV coinfection. We adapted the National Institute on Alcohol Abuse and Alcoholism Clinician's Guide to address HIV/HCV coinfection and paired this with the "HealthCall" smartphone app to create an intervention tailored to HIV/HCV. After formative work and pretesting with HIV/HCV coinfected heavy drinkers, we conducted a pilot trial to determine potential of this new intervention for decreasing drinking. METHOD: A sample of 31 HIV/HCV coinfected heavy drinkers were randomly assigned to either intervention (n = 16) or control (n = 15; psychoeducation and brief advice) conditions. All participants completed a 60-day program consisting of approximately 25-minute-long baseline sessions and brief 5-10-minute booster sessions at 30 and 60 days, as well as an assessment-only follow-up at 90 days. Outcomes were measured using the Timeline Followback at baseline, 30, 60, and 90 days. Generalized linear models were used for analysis. RESULTS: Intervention participants drank fewer mean drinks per drinking day at 60 days (incidence rate ratio [IRR] = 0.43, p = .03) and 90 days (IRR = 0.34, p < .01). Intervention participants also reported fewer drinking days at 90 days (mean difference = 34.5%; p < .01). Self-efficacy differed between groups during intervention (p < .05). CONCLUSIONS: Although our sample was small, our results suggested lower drinking among participants who received a modified Clinician's Guide intervention plus use of the smartphone app HealthCall, in comparison with education and advice alone. A larger study is indicated to further examine this brief, disseminable intervention for HIV/HCV coinfected drinkers.

Evaluating age-related disparities in cannabis-related problems among LGBT+ versus non-LGBT+ adults.

LGBT+ adults demonstrate greater cannabis-related problems (e.g., Cannabis Use Disorder [CUD]) compared to non-LGBT+ counterparts. No study has explored age-related disparities in cannabis problems across the adult lifespan, nor have studies identified specific CUD criteria that contribute to elevated CUD among LGBT+ adults. The purpose of this study was to examine associations between LGBT+ identity and age with endorsement of CUD criteria in a sample of regular cannabis consumers. An online sample of N = 4334 (25.1% LGBT+) adults aged 18-64 residing in the U.S. completed an online survey about cannabis use behaviors and CUD diagnostic criteria. Bivariate contrasts revealed significantly greater CUD criteria endorsement among LGBT+ respondents, largely driven by differences at younger ages. However, this effect disappeared in the majority of adjusted logistic regression models. LGBT+ identity was associated with greater probability of use in larger amounts (adjOR = 2.10, 95% CI: 1.22-3.60) and use despite physical/mental health problems (adjOR = 2.51, 95% CI:1.23-5.03). No age*LGBT+ identity interactions were detected. Plotted trends depict more pronounced disparities in outcomes among LGBT+ adults under 35 years. Several potential risk and protective factors including employment, education, and reasons for use were identified. There were age-related differences in these characteristics among LGBT+ and non-LGBT+ respondents. Initial findings highlight the need for LGBT+ research examining trends in health outcomes and sociodemographic and cannabis characteristics across the lifespan. The study also provides a substantive contribution regarding specific cannabis-related problems that young LGBT+ cannabis consumers may be more likely to endorse than their non-LGBT+ counterparts.

Exploring survey methods for measuring consumption quantities of cannabis flower and concentrate products.

Background: Researchers need accurate measurements of cannabis consumption quantities to assess risks and benefits. Survey methods for measuring cannabis flower and concentrate quantities remain underdeveloped.Objective: We examined "grams" and "hits" units for measuring flower and concentrate quantities, and calculating milligrams of THC (mgTHC).Methods: Online survey participants (n = 2,381) reported preferred unit (hits or grams), past-week hits and grams for each product, and product %THC. Quantile regression compared mgTHC between unit-preference subgroups. Hits-based mgTHC calculations assumed a universal grams-per-hit ratio (GPHR). To examine individualized GPHRs, we tested a "two-item approach," which divided total grams by total hits, and "one-item approach," which divided 0.5 grams by responses to the question: "How many total hits would it take you to finish 1/2 g of your [product] by [administration method]?"Results: Participants were primarily daily consumers (77%), 50% female sex, mean age 39.0 (SD 16.4), 85% White, 49% employed full-time. Compared to those who preferred the hits unit, those who preferred the grams unit reported consuming more hits and grams, higher %THC products, and consequently, larger median mgTHC (flower-hits mgTHC: 32 vs. 91 (95%CI: 52-67); flower-grams mgTHC: 27 vs. 113 (95%CI: 73-95); concentrate-hits mgTHC: 29 vs. 59 (95%CI: 15-43); concentrate-grams mgTHC: 61 vs. 129 (95%CI: 43-94)). "Two-item" and "one-item" approach GPHRs were similar and frequently 50% larger or smaller than the universal GPHR.Conclusion: Allowing respondents to choose "hits" or "grams" when reporting cannabis quantities does not compromise mgTHC estimates. A low-burden, one-item approach yields individualized "hit sizes" that may improve mgTHC estimates.

Extending Gender- and Sex-Based Analyses in Cannabis Research: Findings from an Online Sample of Gender Diverse Young Adult Consumers.

Background: Gender and sex can influence cannabis behaviors and consequences (Cannabis Use Disorder [CUD]). Research typically examines sex and gender independently. Gender analyses often exclude transgender and gender diverse (TGD) populations. The objectives of this study were to (a) replicate less frequent cannabis use among TGD young adults compared to cisgender counterparts (b) compare severity of CUD, and (c) examine the role of sex on cannabis outcomes. Method: Online survey participants between 18 and 34 (N=1213) from the United States who reported past-week cannabis consumption provided information on cannabis practices and CUD from February to April 2022. Bivariate analyses explored gender differences across frequency (daily frequency across routes of administration [ROAs]; daily use of 2+ ROAs, use throughout the day) and CUD. Adjusted regression models provided model-estimated marginal probabilities and means to examine differences across four gender-by-sex categories (cisgender men: n=385; cisgender women: n=681; male-at-birth TGD: n=26; female-at-birth TGD: n=121). Benjamini-Hochberg adjustments (10% false discovery rate) were applied. Results: Among past-week consumers, female-at-birth TGD participants demonstrated lower probability of daily flower smoking compared to cisgender men (0.54 vs. 0.67). Cisgender men reported greater probability of daily concentrate vaping (0.55) compared to cisgender women (0.45) and female-at-birth TGD participants (0.27); they were also more likely to report daily use of 2+ ROAs (cisgender men: 0.51 vs. cisgender women: 0.39 and female at-birth TGD: 0.27). TGD participants reported greater CUD severity compared to cisgender counterparts, t(1096)=-3.69, p=0.002. Model-estimated means found lower severity among cisgender women compared to cisgender men and female-at-birth TGD participants. Stratified regression models support positive associations between daily cannabis use and CUD in both TGD in cisgender groups. Among cisgender participants, greater severity was predicted by male sex, younger age, and younger age of onset. Conclusions: The present study replicates and extends a prior finding that among past-week cannabis consumers, TGD young adults report less frequent use than cisgender counterparts. Despite this, TGD participants demonstrated greater severity of CUD. While analyses were limited by the small sample of male-at-birth TGD participants, the article highlights the importance of expanding sex- and gender-focused analyses. Future work is expanding efforts to target hard-to-reach consumers.

Economic Cost of the HealthCall Smartphone Intervention to Reduce Heavy Alcohol Drinking in Adults With HIV.

OBJECTIVE: Alcohol use among people living with HIV (PLWH) can reduce adherence and worsen health outcomes. We evaluated the economic cost of an effective smartphone application (HealthCall) to reduce drinking and improve antiretroviral adherence among heavy-drinking PLWH participating in a randomized trial. METHOD: Participants were randomized to receive a brief drinking-reduction intervention, either (a) the National Institute on Alcohol Abuse and Alcoholism (NIAAA) Clinician's Guide (CG-only, n = 37), (b) CG enhanced by HealthCall to monitor daily alcohol consumption (CG+HealthCall, n = 38), or (c) motivational interviewing delivered by a nonclinician enhanced by HealthCall (MI+HealthCall, n = 39). We used micro-costing techniques to evaluate start-up costs and incremental costs per participant incurred from the health care sector perspective in 2018 U.S. dollars. We also investigated potential cost offsets using participant-reported health care utilization. RESULTS: Participants attended three intervention visits, and each visit cost on average $29 for CG-only, $32 for CG+HealthCall, and $15 for MI+HealthCall. The total intervention cost per participant was $94 for CG-only, $114 for CG+HealthCall, and $57 for MI+HealthCall; the incremental cost of CG+HealthCall compared with CG-only was $20 per participant, and the incremental savings of MI+HealthCall compared with CG-only was $37 per participant. No significant differences in health care utilization occurred among the three groups over 12 months. CONCLUSIONS: The cost of enhancing CG with the HealthCall application for heavy-drinking PLWH was modestly higher than using the CG alone, whereas MI enhanced with HealthCall delivered by a nonclinician had a lower cost than CG alone. HealthCall may be a low-cost enhancement to brief interventions addressing alcohol use and antiretroviral adherence among PLWH.

Evaluating cannabis exposure in survey items: Insights, strategies, and remaining challenges identified from cognitive interviewing.

Background: The diversity in characteristics of cannabis products and behavior patterns make evaluation of cannabis exposure in population-based, self-report surveys challenging. Accurate identification of cannabis exposure and related outcomes necessitates a thorough understanding of participants' interpretations of survey questions assessing cannabis consumption behaviors. Objectives: The current study utilized cognitive interviewing to gain insight on participants' interpretation of items in a self-reported survey instrument used to estimate the quantity of THC consumed in population samples. Methods: Cognitive interviewing was used to evaluate survey items assessing cannabis use frequency, routes of administration, quantity, potency, and perceived "typical patterns" of use. Ten participants ≥18 years (n = 4 cisgender-men; n = 3 cisgender-women; n = 3 non-binary/transgender) who had used cannabis plant material or concentrates in the past week were recruited to take a self-administered questionnaire and subsequently answer a series of scripted probes regarding survey items. Results: While most items presented no issues with comprehension, participants identified several areas of ambiguity in question or response item wording or in visual cues included in the survey. Generally, participants with irregular use patterns (i.e., non-daily use) reported more difficulty recalling the time or quantity of cannabis use. Findings resulted in several changes to the updated survey, including updated reference images and new quantity/frequency of use items specific to the route of administration. Conclusion: Incorporating cognitive interviewing into cannabis measurement development among a sample of knowledgeable cannabis consumers led to improvements in assessing cannabis exposure in population surveys, which may otherwise have been missed.

Dimensionality and differential functioning of DSM-5 cannabis use disorder criteria in an online sample of adults with frequent cannabis use.

The DSM-5 criteria for cannabis use disorder (CUD) combine DSM-IV dependence and abuse criteria (without legal problems) and new withdrawal and craving criteria. Information on dimensionality, internal reliability, and differential functioning of the DSM-5 CUD criteria is lacking. Additionally, dimensionality of the DSM-5 withdrawal items is unknown. This study examined the psychometric properties of the DSM-5 CUD criteria among adults who used cannabis in the past 7 days (N = 5,119). Adults with frequent cannabis use were recruited from the US general population through social media and filled in a web-based survey about demographics and cannabis use behaviors. Factor analysis was used to assess dimensionality, and item response theory analysis models were used to explore relationships between the criteria and the underlying latent trait (CUD), and whether each criterion and the criteria set functioned differently by demographic and clinical characteristics: sex, age, state-level cannabis laws, reasons for cannabis use, and frequency of use. The DSM-5 CUD criteria showed unidimensionality and provided information about the CUD latent trait across the severity spectrum. The cannabis withdrawal items indicated one underlying latent factor. While some CUD criteria functioned differently in specific subgroups, the criteria set as a whole functioned similarly across subgroups. In this online sample of adults with frequent cannabis use, evidence supports the reliability, validity, and utility of the DSM-5 CUD diagnostic criteria set, which can be used for determining a major risk of cannabis use, i.e., CUD, to inform cannabis policies and public health messaging, and for developing intervention strategies.

Adult use of highly-potent Δ9-THC cannabis concentrate products by U.S. state cannabis legalization status, 2021.

BACKGROUND: Compared to plant/flower cannabis products, cannabis concentrates have higher average potency of delta-9-tetrahydrocannabinol (Δ9-THC), which may be associated with greater likelihood of cannabis-related harms. Information on factors associated with use of cannabis concentrates is needed. METHODS: Respondents were 4,328 adult past-7-day cannabis users from all 50 U.S. states and Washington DC (DC) who participated in an online 2021 survey. Using logistic regression to generate adjusted odds ratios (aOR), we investigated whether participants in states that enacted recreational cannabis laws (RCL, 12 states plus DC [treated as a state], n = 1,236) or medical cannabis laws (MCL-only, 23 states, n = 2,030) by December 31, 2020 were more likely than those in states without cannabis laws (no-CL, 15 states, n = 1,062) to use cannabis concentrate products in the prior 7 days. RESULTS: Most participants (92.4%) used plant material in the prior 7 days; 57.0% used cannabis concentrates. In RCL, MCL and no-CL states, concentrate use was reported by 61.5%, 56.6%, and 52.5%, respectively. Compared to participants in no-CL states, odds of using cannabis concentrate products were greater among those in RCL states (aOR = 1.47; CI = 1.17-1.84) and MCL-only states (aOR = 1.29; CI = 1.08-1.55). Whether states had legally-authorized dispensaries had little effect on results. CONCLUSION: Results suggest that individuals in MCL-only and RCL states are more likely to use cannabis concentrate products. Determining mechanisms underlying these results, e.g., commercialization, could provide important information for prevention. Clinicians should be alert to patient use of concentrates, especially in MCL-only and RCL states. Continued monitoring is warranted as additional states legalize cannabis use.

Estimating THC Consumption from Smoked and Vaped Cannabis Products in an Online Survey of Adults Who Use Cannabis.

Introduction: Quantification of consumption patterns of the primary psychoactive compounds in cannabis, which cause euphoria or intoxication, is sorely needed to identify potential risks and benefits of use and to provide meaningful safety information to the public. The diversity of products available, multiple methods of administration, and lack of labeling of products have made such quantification challenging. Our group is developing a survey instrument for estimating the quantity of delta 9-tetrahydrocannabinol (THC) consumed in population samples, which is flexible and incorporates individualized reports of patterns of consumption. This study provides an illustration of a procedure for translating self-reported consumption into milligrams of THC (mgTHC), which may serve as a working model for future quantification efforts. Methods: Social media advertising was leveraged to enroll 5627 adults who use cannabis into an online, anonymous survey study. Only those who used cannabis in the past 7 days, used flower or concentrate products, and who chose to report their quantity of use in hits per day or grams per week (n=3211) were included in this report. Formulas were used to estimate mgTHC used per day, in hits per day or grams per week; potency (%THC); constants for estimating the amount of material consumed for each hit; and a method of administration efficiency constant to account for THC loss due to the administration method. Results: The estimate for mgTHC used per day was M=92.8 mg/day (SD=97.2 mg; 1st-3rd quartile range=25-132 mg). The estimated quantity of use was much lower for those reporting in hits (M=43.7 mg, SD=43.8) than for those reporting in grams (M=115.1 mg, SD=107.0). The estimated rate of binge use in the past week, arbitrarily defined as more than 50 mgTHC within any one daily time quadrant, was 6.8%, which increased to 29.3% if 25 mgTHC was used. Conclusions: The approach illustrated in this study goes beyond existing cannabis measures by asking participants to provide highly detailed estimates of their past 7-day use patterns and then applying a logical formula to translate this information into mgTHC. This initial procedure has limitations and lacks generalization; however, we hope this demonstration stimulates testing of similar approaches and relevant laboratory experiments that will enhance the validity of cannabis consumption estimation procedures.

Typical Hits, Grams, or Joints: Evaluating Cannabis Survey Measurement Strategies for Quantifying Consumption.

Aim: Standardized survey measures that capture diverse cannabis consumption patterns are needed to inform public health and policy. Our team is developing a flexible, personalized, low-burden survey item inventory to measure cannabis use patterns and estimate milligrams of THC (mgTHC) consumption in large samples. This study aimed to identify measurement gaps and analysis implications associated with an initial pool of candidate items that assessed use of cannabis flower and concentrate products (smoked and/or vaporized). Methods: Adult cannabis consumers (n=4247) completed an online survey assessing cannabis use frequency, quantity, product types, product potencies (%THC), and methods of administration. Participants chose to report their consumption quantities using one of three units: "hits per day," "grams per week," or "joints per week." Respondents also indicated whether their past 7-day consumption pattern represented their typical pattern. Results: Eighty-one percent had used cannabis daily in the past week. Thirty-two percent, 53%, and 15% chose to report flower and concentrate consumption quantity in hits, grams, and joints, respectively. Approximately 80-90% of responses for the number of hits, grams, and joints consumed were less than the maximum response option-suggesting that response options captured the full range of potential cannabis consumption behaviors. Those who chose grams or joints units were generally more likely to endorse higher risk cannabis use (e.g., morning use, high %THC products) in the past week than those who chose the hits unit (adjusted Odds Ratio range: 1.2-3.9). Among those who reported that the past week represented their typical behavior (83%), past 30-day and past 7-day frequencies were highly correlated (Spearman's Rho=0.77)-supporting the feasibility of using lower burden "typical week" items to extrapolate patterns beyond a 1-week time frame. Conclusion: Results from this online convenience sample of frequent cannabis consumers suggest that the current items yield coherent and expected response patterns. Although additional testing is required, a standardized, flexible survey instrument for large-scale assessment of cannabis patterns and calculation of mgTHC seems within reach.

Delta-8 THC use in US adults: Sociodemographic characteristics and correlates.

BACKGROUND: Use of novel cannabis products whose primary active compound is Delta-8 tetrahydrocannabinol (Delta-8 THC), an isomer of Delta-9 THC has recently surged. While Delta-8 THC has psychoactive effects and is potentially harmful, little is known about its use. We examined sociodemographic characteristics, motivations, and consumption patterns of Delta-8 THC in US adult cannabis users. METHODS: Cannabis-using adult online survey participants (N = 4,348) provided information on Delta-8 use, and other characteristics. We assessed frequencies of sociodemographics, patterns, and correlates of Delta-8 THC use. Regression models estimated adjusted odds ratios (aOR) and 95% confidence intervals (CI) of associations between past 30-day Delta-8 THC use, sociodemographic and other characteristics. FINDINGS: Among past 30-day cannabis users, 16.7% reported Delta-8 THC use. The most common consumption method was vaping concentrated formulations of Delta-8 THC (41.2%). Primary motivations for use were its legal status and perceived therapeutic benefits. Males were more likely than females to report Delta-8 THC use (aOR = 1.4, 95% CI 1.2, 1.7). Respondents residing in states with restrictions on sales of Delta-8 THC products had lower odds of Delta-8 THC use (aOR = 0.7, 95% CI 0.57, 0.86). CONCLUSIONS: Findings provide initial insight into the current state of Delta-8 THC use in the US. Given the limited knowledge on use of Delta-8 THC, and considering emergence of reports indicating its harmful effects, there is urgent need for nationally representative data to investigate correlates of Delta-8 THC use (e.g., effectiveness of state-specific restrictions on its products). Such information can guide public-health policy around Delta-8 THC use.

Diagnosing Prescription Opioid Use Disorder in Patients Using Prescribed Opioids for Chronic Pain.

OBJECTIVE: The diagnostic criteria for opioid use disorder, originally developed for heroin, did not anticipate the surge in prescription opioid use and the resulting complexities in diagnosing prescription opioid use disorder (POUD), including differentiation of pain relief (therapeutic intent) from more common drug use motives, such as to get high or to cope with negative affect. The authors examined the validity of the Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 opioid version, an instrument designed to make this differentiation. METHODS: Patients (N=606) from pain clinics and inpatient substance treatment who ever received a ≥30-day opioid prescription for chronic pain were evaluated for DSM-5 POUD (i.e., withdrawal and tolerance were not considered positive if patients used opioids only as prescribed, per DSM-5 guidelines) and pain-adjusted POUD (behavioral/subjective criteria were not considered positive if pain relief [therapeutic intent] was the sole motive). Bivariate correlated-outcome regression models indicated associations of 10 validators with DSM-5 and pain-adjusted POUD measures, using mean ratios for dimensional measures and odds ratios for binary measures. RESULTS: The prevalences of DSM-5 and pain-adjusted POUD, respectively, were 44.4% and 30.4% at the ≥2-criteria threshold and 29.5% and 25.3% at the ≥4-criteria threshold. Pain adjustment had little effect on prevalence among substance treatment patients but resulted in substantially lower prevalence among pain treatment patients. All validators had significantly stronger associations with pain-adjusted than with DSM-5 dimensional POUD measures (ratios of mean ratios, 1.22-2.31). For most validators, pain-adjusted binary POUD had larger odds ratios than DSM-5 measures. CONCLUSIONS: Adapting POUD measures for pain relief (therapeutic intent) improved validity. Studies should investigate the clinical utility of differentiating between therapeutic and nontherapeutic intent in evaluating POUD diagnostic criteria.

Validity of the DSM-5 tobacco use disorder diagnostics in adults with problematic substance use.

BACKGROUND: DSM-5 tobacco use disorder (TUD) nosology differs from DSM-IV nicotine dependence (ND) by including craving and DSM-IV abuse criteria, a lower threshold (≥ 2 criteria), and severity levels (mild; moderate; severe). We assessed concurrent and prospective validity of the DSM-5 TUD diagnosis and severity and compared validity with DSM-IV ND diagnosis. METHODS: The sample included U.S. adults with current problematic substance use and past year cigarette smoking (N = 396). Baseline assessment collected information on DSM-IV ND and DSM-5 TUD criteria, smoking-related variables, and psychopathology. Over the following 90 days, electronic daily assessments queried smoking and cigarette craving. Variables expected to be related to TUD were validators: cigarette consumption, cigarette craving scale, Fagerström Test for Nicotine Dependence, and psychiatric disorders. Regression models estimated the association of each validator with DSM-5 TUD and severity levels, and differential association between DSM-5 TUD and DSM-IV ND diagnoses. RESULTS: DSM-5 TUD and DSM-IV ND were associated with most baseline validators (p-values < 0.05), with significantly stronger associations with DSM-5 TUD for number of days smoked (p = 0.023) and cigarette craving scale (p = 0.007). Baseline DSM-5 TUD and DSM-IV ND predicted smoking and craving on any given day during follow-up, with stronger associations for DSM-5 TUD (association difference [95% CI%]: any smoking, 0.53 [0.27, 0.77]; number of cigarettes smoked, 1.36 [0.89, 1.78]; craving scale, 0.19 [0.09, 0.28]). Validators were associated with TUD severity in a dose-dependent manner. CONCLUSION: DSM-5 TUD diagnostic measures as operationalized here demonstrated concurrent and prospective validity. Inclusion of new criteria, particularly craving, improved validity and clinical relevance.

HealthCall: A randomized trial assessing a smartphone enhancement of brief interventions to reduce heavy drinking in HIV care.

INTRODUCTION: Heavy drinking among people living with HIV (PLWH) worsens their health outcomes and disrupts their HIV care. Although brief interventions to reduce heavy drinking in primary care are effective, more extensive intervention may be needed in PLWH with moderate-to-severe alcohol use disorder. Lengthy interventions are not feasible in most HIV primary care settings, and patients seldom follow referrals to outside treatment. Utilizing visual and video features of smartphone technology, we developed the "HealthCall" app to provide continued engagement after brief intervention, reduce drinking, and improve other aspects of HIV care with minimal demands on providers. We conducted a randomized trial of its efficacy. METHODS: The study recruited alcohol-dependent PLWH (n = 114) from a large urban HIV clinic. Using a 1:1:1 randomized design, the study assigned patients to: Motivational Interviewing (MI) plus HealthCall (n = 39); NIAAA Clinician's Guide (CG) plus HealthCall (n = 38); or CG-only (n = 37). Baseline MI and CG interventions took ~25 min, with brief (10-15 min) 30- and 60-day booster sessions. HealthCall involved daily use of the smartphone app (3-5 min/day) to report drinking and health in the prior 24 h. Outcomes assessed at 30 and 60 days and at 3, 6 and 12 months included drinks per drinking day (DpDD; primary outcome) and number of drinking days, analyzed with generalized linear mixed models and pre-planned contrasts. RESULTS: Study retention was excellent (85%-94% across timepoints). At 30 days, DpDD among patients in MI + HealthCall, CG + HealthCall, and CG-only was 3.80, 5.28, and 5.67, respectively; patients in MI + HealthCall drank less than CG-only and CG + HealthCall (IRRs = 0.62, 95% CI = 0.46, 0.84, and 0.64, 95% CI = 0.48, 0.87, respectively). At 6 months (end-of-treatment), DpDD was lower in CG + HealthCall (DpDD = 4.88) than MI + HealthCall (DpDD = 5.88) or CG-only (DpDD = 6.91), although these differences were not significant. At 12 months, DpDD was 5.73, 5.31, and 6.79 in MI + HealthCall, CG + HealthCall, and CG-only, respectively; DpDD was significantly lower in CG + HealthCall than CG-only (IRR = 0.71, 95% CI = 0.51, 0.98). CONCLUSIONS: During treatment, patients in MI + HealthCall had lower DpDD than patients in other conditions; however, at 12 months, drinking was lowest among patients in CG + HealthCall. Given the importance of drinking reduction and the low costs/time required for HealthCall, pairing HealthCall with brief interventions merits widespread consideration.

Pain, cannabis use, and physical and mental health indicators among veterans and nonveterans: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III.

ABSTRACT: Chronic pain is associated with mental and physical health difficulties and is prevalent among veterans. Cannabis has been put forth as a treatment for chronic pain, and changes in laws, attitudes, and use patterns have occurred over the past 2 decades. Differences in prevalence of nonmedical cannabis use and cannabis use disorder (CUD) were examined across 2 groups: veterans or nonveterans and those reporting or not reporting recent pain. Data from the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013; n = 36,309) were analyzed using logistic regression. Prevalence differences (PDs) for 3 cannabis outcomes (1) past-year nonmedical cannabis use, (2) frequent (≥3 times a week) nonmedical use, and (3) DSM-5 CUD were estimated for those reporting recent moderate to severe pain (veterans or nonveterans) and veterans reporting or not reporting recent pain. Difference in differences was calculated to investigate PDs on outcomes associated with residence in a state with medical cannabis laws (MCLs). Associations between physical and mental health and cannabis variables were tested. The results indicated that the prevalence of recent pain was greater among veterans (PD = 7.25%, 95% confidence interval (CI) [4.90-9.60]). Among veterans, the prevalence of frequent cannabis use was greater among those with pain (PD = 1.92%, 98% CI [0.21-3.63]), and among veterans residing in a state with MCLs, the prevalence of CUD was greater among those reporting recent pain (PD = 3.88%, 98% CI [0.36-7.39]). Findings failed to support the hypothesis that cannabis use improves mental or physical health for veterans with pain. Providers treating veterans with pain in MCL states should monitor such patients closely for CUD.

Cannabis Practices Among a Gender-Diverse Sample of Young Adults.

Background: Gender is an important factor in understanding cannabis patterns, yet few studies have explored cannabis patterns among gender minority (GM) individuals - particularly among high-risk age groups including young adults. The evolving cannabis market is reshaping typical patterns of cannabis use in the U.S. The combination of these factors warrants increased efforts to examine cannabis practices in gender-diverse samples. Methods: Online survey participants between 18-34 years (N=2377) from the U.S. provided information on cannabis practices from May - July 2021. Gender differences across several cannabis outcomes (onset, methods of consumption, product potency, frequency, and quantity) were assessed. Bivariate tests and multiple regression models examined associations between gender (cisgender men: n=1020; cisgender women: n=1178; and GM: n=179) and cannabis outcomes adjusting for sociodemographic characteristics. Results: In regression models adjusted for sociodemographic characteristics, GM identity was associated with later age of onset and lower likelihood of daily use compared to cisgender men and women. Identifying as GM or cisgender woman was associated with fewer lifetime methods of consumption and lower plant and concentrate potency usage. Conclusions: Findings provide initial insights into potential gender differences in cannabis practices from a sample of heavy cannabis users. GM young adults report use patterns indicative of lower risk compared to cisgender men and women in our sample. Future investigations of gender differences in cannabis use that explore specific gender minority categories and that include alternative sampling strategies are needed to better understand differential risks associated with gender.

Use of highly-potent cannabis concentrate products: More common in U.S. states with recreational or medical cannabis laws.

BACKGROUND: Highly-potent cannabis products, e.g., concentrates, entail greater risks of cannabis-related harms than lower-potency products such as plant or flower material. However, little information is available on whether individuals in U.S. states with recreational cannabis laws (RCL) or medical cannabis laws (MCL) are more likely than individuals in U.S. states without cannabis legalization (no-CL) to use highly-potent forms of cannabis. METHODS: Cannabis-using adults in a 2017 online survey (N = 4064) provided information on state of residence and past-month cannabis use, including types of products used, categorized as low-potency (smoked or vaped plant cannabis) or high-potency (vaping or dabbing concentrates). Multivariable logistic regression models generated adjusted odds ratios (aOR) and 95% confidence intervals (CI) for use of high-potency cannabis products by state cannabis legalization status (RCL, MCL, no-CL). RESULTS: Compared to participants in no-CL states, participants in RCL states had greater odds of using high-potency concentrate products (aOR=2.61;CI=1.77-3.86), as did participants in MCL-only states (aOR=1.55;CI=1.21-1.97). When participants in RCL states and MCL states were directly compared, those in RCL states had greater odds of using high-potency concentrate products (aOR=1.69;CI=1.27-2.42). DISCUSSION: Although the sample was not nationally representative and the cross-sectional data precluded determining the direction of effect, results suggest that use of high-potency cannabis concentrates is more likely among those in RCL states. Clinicians in RCL states should screen cannabis users for harmful patterns of use. Policymakers in states that do not yet have RCL should consider these findings when drafting new cannabis laws, including the specific products permitted and how best to regulate them.