INTRODUCTION:The prevalence of medical cannabis use, consumption methods, other key cannabis behaviors, and attitudes toward use is understudied, and associations with any cannabis use among U.S. middle-age and older adults is of particular interest because they are especially vulnerable to the adverse effects of cannabis. METHODS:Health and Retirement Study data (N=1,324) were analyzed, calculating weighted prevalence for cannabis measures, including past-year use, consumption methods, medical use, health conditions for which cannabis was used, healthcare provider recommendations, attitudes toward acceptability, risks, and legalization, by primary age groups (50-64 and ≥65 years) and specified older age groups (65-74 and ≥75 years) and sex. Associations with any cannabis use were evaluated using multivariable logistic regression, adjusting for sex, race/ethnicity, household income, and employment. RESULTS:Past-year cannabis use in the U.S. was reported by 18.5% and 5.9% of middle-age and older adults, respectively. Smoking was the primary consumption method in both groups. Approximately 25% of middle-aged adults and 20% of older adults who used cannabis consumed it for medical purposes, with ∼20% of those receiving a prescription or recommendation. Over 75% of individuals in both age groups viewed medical use as acceptable, and older adults were more likely to view cannabis as a gateway drug and to support restrictions of cannabis laws. CONCLUSIONS:Cannabis use among both middle-aged and older U.S. adults is higher than previously reported in state- and national-level studies, with many engaging in cannabis behaviors associated with increased harm. Greater public health and clinical efforts are needed for tailored prevention and intervention strategies.

ObjectiveWe assessed the contributions of B cell and T cell subsets to the disparate clinical outcomes in NZM.Baff−/− and NZM.Br3−/− mice.MethodsWe assessed in NZM wild‐type, NZM.Baff−/−, and NZM.Br3−/− mice numbers and percentages of B cells and subsets, T cells and subsets, and in vivo proliferation and survival of forkhead box P3 (Foxp3)+ cells by fluorescence‐activated cell sorting. Relationships between percentages of Foxp3+ cells and numbers of CD19+ and CD4+ cells were assessed by linear regressions.ResultsIn each age and sex cohort, percentages and numbers of CD19+ cells were similar in NZM.Baff−/− and NZM.Br3−/− mice. Percentages of CD3+ and CD4+ cells were greater in NZM.Br3−/− than in NZM.Baff−/− mice, with the CD4 to CD3 cell ratios being greater in NZM.Br3−/− than in NZM.Baff−/− mice and percentages of Foxp3+ cells in NZM.Br3−/− mice being lower than in NZM.Baff−/− mice. Percentages of Foxp3+ cells correlated positively with CD19+ cells in NZM.Baff−/− mice but negatively in NZM.Br3−/− mice. In vivo proliferation and survival of Foxp3+ cells were lower in NZM.Baff−/− mice than in NZM.Br3−/− mice.ConclusionDifferences between NZM.Baff−/− and NZM.Br3−/− mice in Foxp3+ cells and their relationships with CD19+ cells may have more to do with their divergent clinical outcomes than do differences in numbers of B cells. These unexpected findings suggest that B cell activating factor (BAFF)–B cell maturation antigen (BCMA) or BAFF–Transmembrane activator and calcium‐modulator and cyclophilin ligand interactor (TACI) interactions may help drive development of clinical systemic lupus erythematosus (SLE) even under conditions of considerable B cell depletion. Insufficient blocking of BAFF–BCMA and BAFF–TACI interactions may lie at the heart of incomplete clinical response to BAFF‐targeting agents in human SLE.

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

BAFF, a vital B cell survival and differentiation factor, has three receptors: B-cell maturation antigen (BCMA), transmembrane activator and CAML interactor (TACI) and BR3. Although B cells are greatly reduced in B6.Baff-/- (which harbour no BAFF) and B6.Br3-/- mice (which harbour supra-normal levels of BAFF), the distributions of B cell subsets and relationships between Foxp3+ and CD4+ cells in these mice differ. Using a large panel of B6 congenic knockout and/or transgenic mice, we demonstrate that (1) supra-normal levels of BAFF per se do not explain the phenotypic differences between B6.Baff-/- and B6.Br3-/- mice; (2) B cells are expanded in B6.Taci-/- mice, with preferential expansion of follicular (FO) B cells at the expense of CD19+CD21-/loCD23-/lo B cells but without the preferential expansion of Foxp3+ cells observed in B6 mice bearing a Baff transgene; (3) despite no expansion in total B cells, percentages of FO B cells and marginal zone B cells are higher and percentages of CD19+CD21-/loCD23-/lo B cells are lower in young B6.Bcma-/- mice, consistent with the inability of B6.Br3-/-.Taci-/- mice to recapitulate the B cell profile of B6.Baff-/- mice; and (4) percentages of Foxp3+ cells in B6.Br3-/-.Taci-/- mice are intermediate between those in B6.Br3-/- and B6.Taci-/- mice despite the B cell profile of B6.Br3-/-.Taci-/- mice strongly resembling that of B6.Br3-/- mice. Collectively, our findings point to a non-redundant role for each of the BAFF receptors in determining the ultimate lymphocyte profile of the host. This may have clinically relevant ramifications in that the degree that a candidate therapeutic agent blocks engagement of any given individual BAFF receptor may affect its clinical utility.

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.

This corrigendum concerns the need to correct an oversight in the authors list. We regret not including Ms. Stephanie Roncone in the list of authors for this paper. It was due to an oversight on our part and needs to be corrected. We would like to apologise for any inconvenience caused. Deborah S. Hasin: Conceptualization; Funding acquisition; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Visualization; Roles/Writing - original draft; Writing - review & editing. Efrat Aharonovich: Conceptualization; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Visualization; Roles/Writing - original draft; Writing - review & editing. Barry S. Zingman: Conceptualization; Project administration; Supervision; Writing - review & editing. Malka Stohl: Data curation; Formal analysis; Validation; Writing - review & editing. Claire Walsh: Data curation; Writing - review & editing. Jennifer C. Elliott: Roles/Writing - original draft; Writing - review & editing. David Fink: Writing - review & editing. Justin Knox: Writing - review & editing. Stephanie Roncone: data collection, investigation, writing – review and editing. Sean Durant: Investigation; Methodology; Writing - review & editing. Raquel Menchaca: Investigation; Methodology; Writing - review & editing. Deborah S. Hasina,b,c,⁎, Efrat Aharonovicha,b, Barry S. Zingmand, Malka Stohlb, Claire Walshb, Jennifer C. Elliotta,b, David S. Finkb, Justin Knoxb, Stephanie Ronconeb, Sean Durantd, Raquel Menchacad, Anjali Sharmad Stephanie Roncone's affiliation when the work was done has been added: bNew York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032, USA. HealthCall: A randomized trial assessing a smartphone enhancement of brief interventions to reduce heavy drinking in HIV careJournal of Substance Abuse TreatmentVol. 138PreviewHeavy 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. Full-Text PDF

The DSM-5 definition of cannabis use disorder (CUD) differs from DSM-IV by combining abuse and dependence criteria (without the legal criterion) and including withdrawal and craving criteria. Information on construct validity of the DSM-5 CUD diagnosis and severity levels is lacking. This study examines the associations between DSM-5 CUD and severity classification and a set of concurrent validators. Adults with problematic substance use were recruited from two settings: a research setting in an urban medical center and a suburban inpatient addiction treatment program. Participants who reported past-year cannabis use (n = 392) were included in this study and completed a semi-structured, clinician-administered diagnostic interview. Regression models estimated the associations between binary DSM-5 CUD and severity levels with a set of validators, including cannabis use variables, psychopathology, and functional impairment. DSM-5 CUD and all severity levels were associated with cannabis use validators, including number of days used, self-reporting that cannabis use was a major problem, and greater cannabis craving. DSM-5 CUD and severe CUD were associated with other psychiatric disorders and social impairment. Findings add information about the validity of DSM-5 CUD diagnosis and severity levels, with severe CUD receiving the strongest support from its association with validators across all domains, as distinct from the mild and moderate CUD measures that were associated with cannabis-specific validators alone. Severe CUD is likely to require more intensive treatment to bolster physical, psychiatric, and social functioning, whereas the mild and moderate severity thresholds provide useful information for identifying less severe disorders for prevention and brief intervention.

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.

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.

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.

Abstract Objective The Department of Veterans Affairs’ (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not. Methods We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen’s d of group differences in absolute risk by past-year VA healthcare use. Results Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40). Conclusions Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

Background: In DSM-5, definitions of substance use disorders (SUD) were changed considerably from DSM-IV, yet little is known about how well DSM-IV and DSM-5 SUD diagnoses agree among substance users. Because data from many studies are based on DSM-IV diagnostic criteria, understanding the agreement between DSM-5 and DSM-IV SUD diagnoses and reasons for discordance between these diagnoses is crucial for comparing results across studies. Measurements: Prevalences and chance-corrected agreement of DSM-5 SUD and DSM-IV substance dependence were evaluated in 588 substance users in a suburban inpatient addiction program and an urban medical center, using a semi-structured interview (PRISM-5). Alcohol, tobacco, cannabis, cocaine, heroin, opioid, sedative, and stimulant use disorders were examined. Cohen's kappa was used to assess agreement between DSM-5 and DSMIV SUD (abuse or dependence), DSM-5 SUD and DSM-IV dependence, and DSM-5 moderate/severe SUD and DSM-IV dependence. Results: Agreement between DSM-5 and DSM-IV SUD was excellent for all substances (Kappa = 0.84-0.99), except for cannabis and tobacco (Kappa = 0.75; 0.80, respectively). The most common reason for diagnostic discrepancies was a positive DSM-5 SUD diagnosis but no DSM-IV diagnosis, due to the lowered DSM-5 SUD threshold. Agreement between DSM-5 SUD and DSM-IV dependence was excellent for all substances (Kappa = 0.88-0.94), except for alcohol, tobacco, and cannabis (Kappa = 0.63-0.75). Agreement between moderate/severe DSM-5 SUD and DSM-IV dependence was excellent across all substances. Conclusion: While care should be used in interpreting results of studies using different methods, studies relying on DSM-IV or DSM-5 SUD diagnostic criteria offer similar information and thus can be compared when accumulating a body of evidence.

Background: Although the problems associated with alcohol use disorder (AUD) are well known, little is known about the psychosocial problems associated with cannabis use disorder (CUD), and the harmfulness of CUD relative to AUD. We compared the odds of psychosocial and health-related problems between individuals with DSM-5 AUD-only, CUD-only and co-occurring AUD+CUD. Methods: The 2012-2013 NESARC-III, a nationally representative cross-sectional survey of non-institutionalized US adults (n = 36,309), assessed participants for DSM-5 AUD, CUD, and psychosocial (interpersonal, financial, legal) and health-related problems. Based on their responses, participants were categorized into mutually exclusive groups: no AUD/CUD, AUD-only, CUD-only, and AUD+CUD. Multivariable logistic regression models examined the associations between psychosocial problems and the four AUD/CUD groups, adjusting for sociodemographic characteristics. Results: People with AUD-only, CUD-only, and AUD+CUD had higher odds of most interpersonal problems (adjusted odds ratio [aORs] 1.07-4.01), financial problems (aORs 1.53-4.28), legal problems (aORs 3.34-7.71), and health-related problems (aORs 1.29-1.92). The odds of psychosocial and health-related problems were similar for CUD-only and AUD-only in direct comparisons. Compared to those with AUD-only, those with AUD+CUD had higher odds of most problems examined (aORs 1.42-2.31). In contrast, there were few differences when comparing AUD+CUD with CUD-only. Conclusions: AUD and CUD were similarly associated with interpersonal, financial, and legal problems, emergency treatment and suicide attempt. People with AUD+CUD had higher odds of certain problems than individuals with either AUD-only or CUD-only. Although most people who use cannabis do not experience harms, our results indicate that CUD does not appear to be less harmful than AUD.

Though risk factors of Alcohol Use Disorder (AUD) have been well-studied, information is lacking on whether clinical characteristics differentiate between the three levels of severity (mild, moderate, severe) that were established for the first time in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). Therefore, in this study, we examined the association between alcohol consumption, mental and physical health, and functional impairment with the three DSM-5 AUD severity levels among adults age 18+ (N=588) pre-screened for problems with at least one substance. Participants recruited between 2016-2019 completed measures of AUD, harmful alcohol use, psychiatric conditions, and mental, physical, and social functional impairment. For each predictor, a multinomial logistic regression model was used to evaluate the association with a four-level AUD outcome (mild, moderate, severe, vs none), controlling for sociodemographic characteristics and other substance use. Twelve-month prevalence of none, mild, moderate, and severe DSM-5 AUD was 34.0%, 12.2%, 13.4%, and 40.3%, respectively. Participants reported a mean of 11.3 (SD=9.90) days of alcohol use in the past month, nearly half (48.0%) perceived to have a major problem with alcohol, and 61.4% met the threshold for harmful drinking. Multinomial logistic regression demonstrated that compared to the reference group (no AUD), all three AUD severity levels were associated with drinking frequency, problematic, and harmful alcohol use. However, only severe AUD was associated with personality disorders: (AOR=1.91, 95% CI=1.28, 2.86), MDD (AOR= 2.44, 95% CI= 1.62, 3.66) or PTSD (AOR= 1.65, 95% CI= 1.00, 2.71),. Similarly, only severe AUD was associated with impaired physical (AOR= 1.63, 95% CI= 1.01, 2.61), mental (AOR= 1.80, 95% CI= 1.16, 2.79), and social functioning (AOR= 1.87, 95% CI= 1.39, 2.51). This study adds to existing literature on clinical correlates of AUD by further elucidating the risk factors of the different AUD severity groups, while also highlighting an important, differential observation wherein measures of psychiatric disorders and functional impairment were only associated with severe AUD. The study suggests that the DSM-5 category of severe AUD most closely corresponds to AUD cases often found in secondary or tertiary treatment settings, and that cases of mild or moderate AUD may warrant less intensive treatment approaches. Future investigations should seek to examine the validity of the DSM-5 AUD three-level severity distinction by using longitudinal designs to evaluate change in mental health and functioning over time, along with their association with AUD severity classification.

Aim: In DSM-5, the definitions of substance use disorders (SUD) were changed considerably, yet little is known about the reliability of DSM-5 SUD and its new features. Methods: The test-retest reliability of DSM-5 SUD and DSM-IV substance dependence (SD) was evaluated in 565 adult substance users, each interviewed twice by different clinician interviewers using the semi-structured Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 version (PRISM-5). DSM-5 SUD and DSM-IV SD criteria were assessed for past year and lifetime, yielding diagnoses and severity levels for alcohol, tobacco, cannabis, cocaine, heroin, opioids, sedatives, hallucinogen, and stimulant use disorders. Cohen's and intraclass correlation coefficients (ICC) assessed reliability for categorical and graded outcomes, respectively. Factors potentially influencing reliability were explored, including inpatient vs. community participant, days between interviews gender, age, race/ethnicity, and SUD severity. Results: DSM-5 SUD diagnoses had substantial to excellent reliability for most substances (kappa = 0.63-0.94), and moderate for others (hallucinogens, stimulants, sedatives; kappa = 0.50-0.59). For graded outcomes (DSM-5 SUD mild, moderate, severe; criteria count 0-11), reliability was substantial to excellent (ICC = 0.74-0.99). Comparisons of DSM-5 SUD and DSM-IV SD reliability showed few significant differences. Reliability of the DSM-5 craving criterion was excellent for heroin (kappa = 0.84-0.95) and moderate to substantial for other substances (kappa = 0.49-0.76). The only factor influencing reliability of SUD was severity, with milder disorders significantly more likely to be discordant between the interviews. Conclusion: Reproducibility is crucial to good measurement. In a large sample using rigorous methodology, diagnoses and dimensional measures from clinician-administered interviews for DSM-5 SUD were generally highly reliable.

Cognitive impairments are associated with poor outcomes when treating cocaine dependent patients, but behavioral interventions to mitigate this impact have not been developed. In this Stage 1A/1B treatment development study, several compensatory strategies (e.g., content repetition, daily logs, diaries, visual presentation) were combined to create a modified cognitive behavioral therapy (M-CBT) for treating cocaine dependence. Initially, a select group of therapists, neuropsychology experts, and patients were asked to provide input on early drafts of the treatment manual and companion patient workbook. After an uncontrolled small trial (N = 15) and two rounds of manual development (Stage 1A), a pilot randomized clinical trial (N = 102) of cocaine dependent outpatients with and without cognitive impairments was conducted (Stage 1B). Participants were randomized to M-CBT (N = 52) or CBT (N = 50). Both treatments were individually delivered over 12 weeks with assessments conducted at baseline, end-of-treatment, and 3-month follow-up. The primary outcome was frequency of cocaine use, measured by number of days used in the prior 7 days. Participants in the two treatment groups did not differ significantly on drug use reduction or retention in treatment. However, among participants who completed at least 9 weeks of treatment, those in M-CBT showed a trend toward greater reduction in cocaine use compared to those in the CBT group. M-CBT is feasible for impaired and nonimpaired cocaine dependent participants. However, M-CBT treatment did not show significant superiority over standard CBT in the present sample.

Importance No US national data are available on the prevalence and correlates of DSM-5–defined major depressive disorder (MDD) or on MDD specifiers as defined in DSM-5. Objective To present current nationally representative findings on the prevalence, correlates, psychiatric comorbidity, functioning, and treatment of DSM-5 MDD and initial information on the prevalence, severity, and treatment of DSM-5 MDD severity, anxious/distressed specifier, and mixed-features specifier, as well as cases that would have been characterized as bereavement in DSM-IV. Design, Setting, and Participants In-person interviews with a representative sample of US noninstitutionalized civilian adults (≥18 years) (n = 36 309) who participated in the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-III). Data were collected from April 2012 to June 2013 and were analyzed in 2016-2017. Main Outcomes and Measures Prevalence of DSM-5 MDD and the DSM-5 specifiers. Odds ratios (ORs), adjusted ORs (aORs), and 95% CIs indicated associations with demographic characteristics and other psychiatric disorders. Results Of the 36 309 adult participants in NESARC-III, 12-month and lifetime prevalences of MDD were 10.4% and 20.6%, respectively. Odds of 12-month MDD were significantly lower in men (OR, 0.5; 95% CI, 0.46-0.55) and in African American (OR, 0.6; 95% CI, 0.54-0.68), Asian/Pacific Islander (OR, 0.6; 95% CI, 0.45-0.67), and Hispanic (OR, 0.7; 95% CI, 0.62-0.78) adults than in white adults and were higher in younger adults (age range, 18-29 years; OR, 3.0; 95% CI, 2.48-3.55) and those with low incomes ($19 999 or less; OR, 1.7; 95% CI, 1.49-2.04). Associations of MDD with psychiatric disorders ranged from an aOR of 2.1 (95% CI, 1.84-2.35) for specific phobia to an aOR of 5.7 (95% CI, 4.98-6.50) for generalized anxiety disorder. Associations of MDD with substance use disorders ranged from an aOR of 1.8 (95% CI, 1.63-2.01) for alcohol to an aOR of 3.0 (95% CI, 2.57-3.55) for any drug. Most lifetime MDD cases were moderate (39.7%) or severe (49.5%). Almost 70% with lifetime MDD had some type of treatment. Functioning among those with severe MDD was approximately 1 SD below the national mean. Among 12.9% of those with lifetime MDD, all episodes occurred just after the death of someone close and lasted less than 2 months. The anxious/distressed specifier characterized 74.6% of MDD cases, and the mixed-features specifier characterized 15.5%. Controlling for severity, both specifiers were associated with early onset, poor course and functioning, and suicidality. Conclusions and Relevance Among US adults, DSM-5 MDD is highly prevalent, comorbid, and disabling. While most cases received some treatment, a substantial minority did not. Much remains to be learned about the DSM-5 MDD specifiers in the general population.