Patterns of Melatonin Use in a Diverse National Pediatric Sample.

This cohort study examines patterns of melatonin use among participants in the Adolescent Brain Cognitive Development (ABCD) Study and characterizes factors associated with use.

The association of sexual minority status and bullying victimization is modified by sex and grade: findings from a nationally representative sample.

BACKGROUND: Sexual minority status is associated with face-to-face bullying and cyberbullying victimization. However, limited studies have investigated whether such a relationship differs by sex or grade in a nationally representative sample. METHODS: We concatenated the national high school data from the Youth Risk Behavior Surveillance System (YRBSS) chronologically from 2015 to 2019, resulting in a sample of 32,542 high school students. We constructed models with the interaction term between sexual minority status and biological sex assigned at birth to test the effect modification by sex on both the multiplicative and additive scales. A similar method was used to test the effect modification by grade. RESULTS: Among heterosexual students, females had a higher odds of being bullied than males, while among sexual minority students, males had a higher odds of being bullied. The effect modification by sex was significant on both the multiplicative and additive scales. We also found a decreasing trend of bullying victimization as the grade increased among both heterosexual and sexual minority students. The effect modification by the grade was significant on both the multiplicative and the additive scale. CONCLUSIONS: Teachers and public health workers should consider the difference in sex and grade when designing prevention programs to help sexual minority students.

Childhood adversities and mental disorders in first-year college students: results from the World Mental Health International College Student Initiative.

BACKGROUND: This study investigates associations of several dimensions of childhood adversities (CAs) with lifetime mental disorders, 12-month disorder persistence, and impairment among incoming college students. METHODS: Data come from the World Mental Health International College Student Initiative (WMH-ICS). Web-based surveys conducted in nine countries (n = 20 427) assessed lifetime and 12-month mental disorders, 12-month role impairment, and seven types of CAs occurring before the age of 18: parental psychopathology, emotional, physical, and sexual abuse, neglect, bullying victimization, and dating violence. Poisson regressions estimated associations using three dimensions of CA exposure: type, number, and frequency. RESULTS: Overall, 75.8% of students reported exposure to at least one CA. In multivariate regression models, lifetime onset and 12-month mood, anxiety, and substance use disorders were all associated with either the type, number, or frequency of CAs. In contrast, none of these associations was significant when predicting disorder persistence. Of the three CA dimensions examined, only frequency was associated with severe role impairment among students with 12-month disorders. Population-attributable risk simulations suggest that 18.7-57.5% of 12-month disorders and 16.3% of severe role impairment among those with disorders were associated with these CAs. CONCLUSION: CAs are associated with an elevated risk of onset and impairment among 12-month cases of diverse mental disorders but are not involved in disorder persistence. Future research on the associations of CAs with psychopathology should include fine-grained assessments of CA exposure and attempt to trace out modifiable intervention targets linked to mechanisms of associations with lifetime psychopathology and burden of 12-month mental disorders.

Optimized short-forms of the Cognitive Distortions Questionnaire.

INTRODUCTION: The Cognitive Distortions Questionnaire (CD-Quest) is a self-report questionnaire that assesses common cognitive distortions. Although the CD-Quest has excellent psychometric properties, its length may limit its use. METHODS: We attempted to develop short-forms of the CD-Quest using RiskSLIM - a machine learning method to build short-form scales that can be scored by hand. Each short-form was fit to maximize concordance with the total CD-Quest score for a specified number of items based on an objective function, in this case R2, by selecting an optimal subset of items and an optimal set of small integer weights. The models were trained in a sample of US undergraduate students (N = 906). We then validated each short-form on five independent samples: two samples of undergraduate students in Brazil (Ns = 182, 183); patients with depression in Brazil (N = 62); patients with social anxiety disorder in the US (N = 198); and psychiatric outpatients in Turkey (N = 269). RESULTS: A 9-item short-form with integer scoring was created that reproduced the total 15-item CD-Quest score in all validation samples with excellent accuracy (R2 = 90.4-93.6%). A 5-item ultra-short-form had good accuracy (R2 = 78.2-85.5%). DISCUSSION: A 9-item short-form and a 5-item ultra-short-form of the CD-Quest both reproduced full CD-Quest scores with excellent to good accuracy. These shorter versions of the full CD-Quest could facilitate measurement of cognitive distortions for users with limited time and resources.

Optimal individualized decision rules using instrumental variable methods.

There is an extensive literature on the estimation and evaluation of optimal individualized treatment rules in settings where all confounders of the effect of treatment on outcome are observed. We study the development of individualized decision rules in settings where some of these confounders may not have been measured but a valid binary instrument is available for a binary treatment. We first consider individualized treatment rules, which will naturally be most interesting in settings where it is feasible to intervene directly on treatment. We then consider a setting where intervening on treatment is infeasible, but intervening to encourage treatment is feasible. In both of these settings, we also handle the case that the treatment is a limited resource so that optimal interventions focus the available resources on those individuals who will benefit most from treatment. Given a reference rule, we evaluate an optimal individualized rule by its average causal effect relative to a prespecified reference rule. We develop methods to estimate optimal individualized rules and construct asymptotically efficient plug-in estimators of the corresponding average causal effect relative to a prespecified reference rule.

An individualized treatment rule to optimize probability of remission by continuation, switching, or combining antidepressant medications after failing a first-line antidepressant in a two-stage randomized trial.

BACKGROUND: There is growing interest in using composite individualized treatment rules (ITRs) to guide depression treatment selection, but best approaches for doing this are not widely known. We develop an ITR for depression remission based on secondary analysis of a recently published trial for second-line antidepression medication selection using a cutting-edge ensemble machine learning method. METHODS: Data come from the SUN(^_^)D trial, an open-label, assessor blinded pragmatic trial of previously-untreated patients with major depressive disorder from 48 clinics in Japan. Initial clinic-level randomization assigned patients to 50 or 100 mg/day sertraline. We focus on the 1549 patients who failed to remit within 3 weeks and were then rerandomized at the individual-level to continuation with sertraline, switching to mirtazapine, or combining mirtazapine with sertraline. The outcome was remission 9 weeks post-baseline. Predictors included socio-demographics, clinical characteristics, baseline symptoms, changes in symptoms between baseline and week 3, and week 3 side effects. RESULTS: Optimized treatment was associated with significantly increased cross-validated week 9 remission rates in both samples [5.3% (2.4%), p = 0.016 50 mg/day sample; 5.1% (2.7%), p = 0.031 100 mg/day sample] compared to randomization (30.1-30.8%). Optimization was also associated with significantly increased remission in both samples compared to continuation [24.7% in both: 11.2% (3.8%), p = 0.002 50 mg/day sample; 11.7% (3.9%), p = 0.001 100 mg/day sample]. Non-significant gains were found for optimization compared to switching or combining. CONCLUSIONS: An ITR can be developed to improve second-line antidepressant selection, but replication in a larger study with more comprehensive baseline predictors might produce stronger and more stable results.

Correction to: "Optimal Individualized Decision Rules Using Instrumental Variable Methods".

[This corrects the article PMC7959164.].

Barriers to Mental Health Service Use and Predictors of Treatment Drop Out: Racial/Ethnic Variation in a Population-Based Study.

This study examines racial/ethnic differences in perceived need for mental health treatment, barriers to treatment receipt, and reasons for dropout. Data are from the Collaborative Psychiatric Epidemiology Studies, a pooled dataset from three U.S. nationally-representative adult samples. Among respondents with a 12-month psychiatric disorder who received no treatment (N = 1417), Asians and Latinos reported lower perceived need than Blacks and Whites, and Latinos reported the fewest attitudinal barriers. Among those with a 12-month disorder who dropped out of treatment, Asians and Latinos gave more reasons for dropping out. Significant interactions of race/ethnicity with other characteristics identified subpopulations with high unmet need.

Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia.

Importance: Little guidance exists to date on how to select antipsychotic medications for patients with first-episode schizophrenia. Objective: To develop a preliminary individualized treatment rule (ITR) for patients with first-episode schizophrenia. Design, Setting, and Participants: This prognostic study obtained data from Taiwan's National Health Insurance Research Database on patients with prescribed antipsychotic medications, ambulatory claims, or discharge diagnoses of a schizophrenic disorder between January 1, 2005, and December 31, 2011. An ITR was developed by applying a targeted minimum loss-based ensemble machine learning method to predict treatment success from baseline clinical and demographic data in a 70% training sample. The model was validated in the remaining 30% of the sample. The probability of treatment success was estimated for each medication for each patient under the model. The analysis was conducted between July 16, 2018, and July 15, 2019. Exposures: Fifteen different antipsychotic medications. Main Outcomes and Measures: Treatment success was defined as not switching medication and not being hospitalized for 12 months. Results: Among the 32 277 patients in the analysis, the mean (SD) age was 36.7 (14.3) years, and 15 752 (48.8%) were male. In the validation sample, the treatment success rate (SE) was 51.7% (1.0%) under the ITR and was 44.5% (0.5%) in the observed population (Z = 7.1; P < .001). The estimated treatment success if all patients were given a prescription for 1 medication was significantly lower for each of the 13 medications than under the ITR (Z = 4.2-16.8; all P < .001). Aripiprazole (3088 [31.9%]) and amisulpride (2920 [30.2%]) were the medications most often recommended by the ITR. Only 1054 patients (10.9%) received ITR-recommended medications. Observed treatment success, although lower than the success under the ITR, was nonetheless significantly higher than if medications had been randomized (44.5% [SE, 0.55%] vs 41.3% [SE, 0.4%]; Z = 6.9; P < .001), although only marginally higher than if medications had been randomized in their observed population proportions (44.5% [SE, 0.5%] vs 43.5% [SE, 0.4%]; Z = 2.2; P = .03]). Conclusions and Relevance: These results suggest that an ITR may be associatded with an increase in the treatment success rate among patients with first-episode schizophrenia, but experimental evaluation is needed to confirm this possibility. If confirmed, model refinement that investigates biomarkers, clinical observations, and patient reports as additional predictors in iterative pragmatic trials would be needed before clinical implementation.

The importance of physical and mental health in explaining health-related academic role impairment among college students.

Research consistently documents high rates of mental health problems among college students and strong associations of these problems with academic role impairment. Less is known, though, about prevalence and effects of physical health problems in relation to mental health problems. The current report investigates this by examining associations of summary physical and mental health scores from the widely-used Short-Form 12 (SF-12) Health Survey with self-reported academic role functioning in a self-report survey of 3,855 first-year students from five universities in the northeastern United States (US; mean age 18.5; 53.0% female). The mean SF-12 physical component summary (PCS) score (55.1) was half a standard deviation above the benchmark US adult population mean. The mean SF-12 mental component summary (MCS) score (38.2) was more than a full standard deviation below the US adult population mean. Two-thirds of students (67.1%) reported at least mild and 10.5% severe health-related academic role impairment on a modified version of the Sheehan Disability Scale. Both PCS and MCS scores were significantly and inversely related to these impairment scores, but with nonlinearities and interactions and much stronger associations involving MCS than PCS. Simulation suggests that an intervention that improved the mental health of all students with scores below the MCS median to be at the median would result in a 61.3% reduction in the proportion of students who experienced severe health-related academic role impairment. Although low-cost scalable interventions exist to address student mental health problems, pragmatic trials are needed to evaluate the effectiveness of these interventions in reducing academic role impairment.

A Preliminary Precision Treatment Rule for Remission of Suicide Ideation.

OBJECTIVE: There is growing interest in the development of composite precision treatment rules (PTRs) to guide the selection of the treatments most likely to be helpful for individual patients. We present here the results of an effort to develop a preliminary PTR for Collaborative Assessment and Management of Suicidality (CAMS) relative to enhanced-care as usual based on secondary analysis of the Operation Worth Living (OWL) randomized controlled trial. The outcome of interest is eliminating suicide ideation (SI) within 3 months of initiating treatment. METHOD: A state-of-the-art ensemble machine learning method was used to develop the PTR among the n = 148 U.S. Soldiers (predominately male and White, age range 18-48) OWL patients. RESULTS: We estimated that CAMS was the better treatment for 77.8% of patients and that treatment assignment according to the PTR would result in a 13.6% (95% CI: 0.9%-26.3%) increase in 3-month SI remission compared to random treatment assignment. CONCLUSIONS: Although promising, results are limited by the small sample size, restrictive baseline assessment, and inability to evaluate effects on suicidal behaviors or disaggregate based on history of suicidal behaviors. Replication is needed in larger samples with comprehensive baseline assessments, longer-term follow-ups, and more extensive outcomes.

Increased cancer rates in patients with chronic hepatitis C.

AIMS: As previous reports show an association of chronic hepatitis C (HCV) with hepatocellular carcinoma (HCC) and non-liver cancers, we examine the association of HCV with liver cancer and non-liver cancers. METHODS: Retrospective cross-sectional study at Kaiser Permanente Southern California (KPSC) evaluating HCV and non-HCV patients from 1 January 2008 to 12 December 2012. Cancer diagnoses were obtained from the KPSC-SEER-affiliated registry. Logistic regression analyses were used for rate ratios and time-to-event analyses were performed using Cox proportional hazards models, adjusted for age, gender, race, smoking and cirrhosis. Cancer rate ratios were stratified by tobacco, alcohol abuse, diabetes and body mass index (BMI). RESULTS: The initial population and final population of multivariable analysis were N = 5 332 903 and N = 2 080 335 respectively. Cancer burden (all sites) was significantly higher in HCV than in non-HCV patients and HCV patients had a high rate of liver cancer. When liver cancer was excluded, cancer rates remained significantly increased in HCV. Unadjusted cancer rates were significantly higher in HCV compared to non-HCV for oesophageal, stomach, colorectal, pancreas, myeloma, non-Hodgkin's lymphoma, head/neck, lung, renal and prostate cancer. After stratification for alcohol abuse, tobacco, diabetes and BMI, increased cancer rates remained significant for all cancer sites, liver cancer and non-Hodgkin's lymphoma. Multivariable analyses demonstrated a strong correlation between cirrhosis and cancer. Tobacco use and diabetes were also associated with cancer. In the absence of cirrhosis, HCV, tobacco use and diabetes significantly increased the cancer risk. Mediation analyses showed that cirrhosis was responsible for a large proportion on the effect of HCV on cancer risk. CONCLUSION: This study supports the concept of HCV as a systemic illness and treating HCV regardless of disease severity and prior to progression to cirrhosis.

Racial and ethnic differences in individual-level and area-based socioeconomic status and 12-month DSM-IV mental disorders.

The purpose of this study was to: (1) examine the associations of individual-level objective socioeconomic status (OSS), subjective socioeconomic status (SSS), and area-based indicators of socioeconomic status, with 12-month DSM-IV mood, anxiety, alcohol use, and drug use disorders; and, (2) determine the extent of racial/ethnic differences in these associations across non-Latino White, non-Latino Black, Latino, and Asian participants. Data are from the Collaborative Psychiatric Epidemiology Studies dataset, a collection of three population-based surveys of mental disorders among U.S. residents aged 18 and older (n = 13,775). Among all indicators of socioeconomic status, SSS was most consistently associated with 12-month mental disorders. Income was negatively associated with mood and anxiety disorders; education was negatively associated with alcohol use and drug use disorders. Significant interactions with race/ethnicity were found for the associations of socioeconomic indicators with anxiety, alcohol use, and drug use disorders but not with mood disorders. SSS was not associated with any of the 12-month mental disorders among Blacks. Education had stronger associations with 12-month anxiety and alcohol use disorders among Whites than among other racial/ethnic groups. Among Asians, low income compared to high income was associated with a lower risk of anxiety disorders and less than high school completion compared to college or more was associated with a lower risk of alcohol use disorders. Finally, tract-level income inequality was associated with a greater risk of drug use disorders only among Blacks. The patterns and magnitudes of the associations of individual-level and area-based socioeconomic indicators differed by type of disorder and race/ethnicity.

Controller therapy in Asians and whites with persistent Asthma.

BACKGROUND: Little is known concerning the relative effectiveness of LTRAs compared to ICSs as monotherapy or LABA as add-on therapy in the Asian population. OBJECTIVES: In this retrospective cohort study, we examined the comparative effectiveness of montelukast to ICS as a first-line monotherapy and as an add-on in comparison with LABA on asthma exacerbations among Asian and non -Hispanic white persistent asthma patients in a large managed care organization. METHODS: The three add-on comparisons were montelukast plus low-dose ICS versus LABA plus low-dose ICS, montelukast plus low-dose ICS versus medium-dose ICS, and montelukast plus medium-dose ICS versus LABA plus medium-dose ICS. Patients were identified based on ICD-9 diagnosis codes and administrative pharmacy dispensing. Exacerbations were defined as asthma emergency department visit or hospitalization, or asthma outpatient visits requiring systemic corticosteroid dispensing. Patient demographic and clinical characteristics were balanced by using inverse probability treatment weighting. Multivariable robust Poisson and Cox-proportional hazards regression models were applied to estimate rate ratios and hazard ratios. RESULTS: Compared with low-dose ICS monotherapy, montelukast monotherapy evidenced a lower incidence rate (RR 0.89, CI 0.79-0.99, p = 0.03) but similar hazard rate (HR 0.96, CI 0.86-1.06, p = 0.43) of asthma exacerbation in white patients 12 years of age or older. No difference was observed in Asian patients or in white children 4-11 years of age. All other comparisons did not reveal a statistically significant difference in incidence or hazard rate. CONCLUSION: In a real-world comparative effectiveness study, asthma exacerbation rates were similar among guideline alternative controller regimens in Asians and whites.

Racial/ethnic variation in trauma-related psychopathology in the United States: a population-based study.

BACKGROUND: The prevalence of mental disorders among Black, Latino, and Asian adults is lower than among Whites. Factors that explain these differences are largely unknown. We examined whether racial/ethnic differences in exposure to traumatic events (TEs) or vulnerability to trauma-related psychopathology explained the lower rates of psychopathology among racial/ethnic minorities. METHODS: We estimated the prevalence of TE exposure and associations with onset of DSM-IV depression, anxiety and substance disorders and with lifetime post-traumatic stress disorder (PTSD) in the Collaborative Psychiatric Epidemiology Surveys, a national sample (N = 13 775) with substantial proportions of Black (35.9%), Latino (18.9%), and Asian Americans (14.9%). RESULTS: TE exposure varied across racial/ethnic groups. Asians were most likely to experience organized violence - particularly being a refugee - but had the lowest exposure to all other TEs. Blacks had the greatest exposure to participation in organized violence, sexual violence, and other TEs, Latinos had the highest exposure to physical violence, and Whites were most likely to experience accidents/injuries. Racial/ethnic minorities had lower odds ratios of depression, anxiety, and substance disorder onset relative to Whites. Neither variation in TE exposure nor vulnerability to psychopathology following TEs across racial/ethnic groups explained these differences. Vulnerability to PTSD did vary across groups, however, such that Asians were less likely and Blacks more likely to develop PTSD following TEs than Whites. CONCLUSIONS: Lower prevalence of mental disorders among racial/ethnic minorities does not appear to reflect reduced vulnerability to TEs, with the exception of PTSD among Asians. This highlights the importance of investigating other potential mechanisms underlying racial/ethnic differences in psychopathology.

Racial/ethnic differences in 12-month prevalence and persistence of mood, anxiety, and substance use disorders: Variation by nativity and socioeconomic status.

BACKGROUND: Despite equivalent or lower lifetime and past-year prevalence of mental disorder among racial/ethnic minorities compared to non-Latino Whites in the United States, evidence suggests that mental disorders are more persistent among minorities than non-Latino Whites. But, it is unclear how nativity and socioeconomic status contribute to observed racial/ethnic differences in prevalence and persistence of mood, anxiety, and substance disorders. METHOD: Data were examined from a coordinated series of four national surveys that together assessed 21,024 Asian, non-Latino Black, Latino, and non-Latino White adults between 2001 and 2003. Common DSM-IV mood, anxiety, and substance disorders were assessed using the Composite International Diagnostic Interview. Logistic regression analyses examined how several predictors (e.g., race/ethnicity, nativity, education, income) and the interactions between those predictors were associated with both 12-month disorder prevalence and 12-month prevalence among lifetime cases. For the second series of analyses, age of onset and time since onset were used as additional control variables to indirectly estimate disorder persistence. RESULTS: Non-Latino Whites demonstrated the highest unadjusted 12-month prevalence of all disorder types (p < 0.001), though differences were also observed across minority groups. In contrast, Asian, Latino, and Black adults demonstrated higher 12-month prevalence of mood disorders among lifetime cases than Whites (p < 0.001) prior to adjustments Once we introduced nativity and other relevant controls (e.g., age, sex, urbanicity), US-born Whites with at least one US-born parent demonstrated higher 12-month mood disorder prevalence than foreign-born Whites or US-born Whites with two foreign parents (OR = 0.51, 95% CI = [0.36, 0.73]); this group also demonstrated higher odds of past-year mood disorder than Asian (OR = 0.59, 95% CI = [0.42, 0.82]) and Black (OR = 0.70, 95% CI = [0.58, 0.83]) adults, but not Latino adults (OR = 0.89, 95% CI = [0.74, 1.06]). Racial/ethnic differences in 12-month mood and substance disorder prevalence were moderated by educational attainment, especially among adults without a college education. Additionally, racial/ethnic minority groups with no more than a high school education demonstrated more persistent mood and substance disorders than non-Latino Whites; these relationships reversed or disappeared at higher education levels. CONCLUSION: Nativity may be a particularly relevant consideration for diagnosing mood disorder among non-Latino Whites; additionally, lower education appears to be associated with increased relative risk of persistent mood and substance use disorders among racial/ethnic minorities compared to non-Latino Whites.

Race/ethnicity, nativity, and lifetime risk of mental disorders in US adults.

PURPOSE: There has been no comprehensive examination of how race/ethnicity and nativity intersect in explaining differences in lifetime prevalence of mental disorders among Asian, Black, Latino, and White adults. This study aims to estimate racial/ethnic differences in lifetime risk of mental disorders and examine how group differences vary by nativity. METHODS: Survival models were used to estimate racial/ethnic and nativity differences in lifetime risk of DSM-IV anxiety, mood, and substance use disorders in a nationally representative sample of over 20,000 respondents to four US surveys. RESULTS: Asians had the lowest lifetime prevalence of mental disorders (23.5%), followed by Blacks (37.0%), Latinos (38.8%), and Whites (45.6%). Asians and Blacks had lower lifetime risk than Whites for all disorders even after adjusting for nativity; Latinos and Whites had similar risk after adjusting for nativity. Risk of disorder onset was lowest for foreign-born respondents in years before migration. There were significant race/ethnicity and nativity interactions for mood and substance use disorders. Odds of mood disorder onset were higher for Whites with at least one US-born parent. Odds of substance use disorder onset among Asians were higher for US-born respondents; for Latinos, they were higher for those with at least one US-born parent. CONCLUSIONS: Parental foreign-born nativity is associated with a low risk of mental disorders, but not uniformly across racial/ethnic groups or disorders. Exposure to the US context may be associated with greater mental disorder risk for Latinos and Whites particularly. Investigations of cultural processes, including among Whites, are needed to understand group differences.

Treatment gap for anxiety disorders is global: Results of the World Mental Health Surveys in 21 countries.

BACKGROUND: Anxiety disorders are a major cause of burden of disease. Treatment gaps have been described, but a worldwide evaluation is lacking. We estimated, among individuals with a 12-month DSM-IV (where DSM is Diagnostic Statistical Manual) anxiety disorder in 21 countries, the proportion who (i) perceived a need for treatment; (ii) received any treatment; and (iii) received possibly adequate treatment. METHODS: Data from 23 community surveys in 21 countries of the World Mental Health (WMH) surveys. DSM-IV mental disorders were assessed (WHO Composite International Diagnostic Interview, CIDI 3.0). DSM-IV included posttraumatic stress disorder among anxiety disorders, while it is not considered so in the DSM-5. We asked if, in the previous 12 months, respondents felt they needed professional treatment and if they obtained professional treatment (specialized/general medical, complementary alternative medical, or nonmedical professional) for "problems with emotions, nerves, mental health, or use of alcohol or drugs." Possibly adequate treatment was defined as receiving pharmacotherapy (1+ months of medication and 4+ visits to a medical doctor) or psychotherapy, complementary alternative medicine or nonmedical care (8+ visits). RESULTS: Of 51,547 respondents (response = 71.3%), 9.8% had a 12-month DSM-IV anxiety disorder, 27.6% of whom received any treatment, and only 9.8% received possibly adequate treatment. Of those with 12-month anxiety only 41.3% perceived a need for care. Lower treatment levels were found for lower income countries. CONCLUSIONS: Low levels of service use and a high proportion of those receiving services not meeting adequacy standards for anxiety disorders exist worldwide. Results suggest the need for improving recognition of anxiety disorders and the quality of treatment.

Estimating treatment coverage for people with substance use disorders: an analysis of data from the World Mental Health Surveys.

Substance use is a major cause of disability globally. This has been recognized in the recent United Nations Sustainable Development Goals (SDGs), in which treatment coverage for substance use disorders is identified as one of the indicators. There have been no estimates of this treatment coverage cross-nationally, making it difficult to know what is the baseline for that SDG target. Here we report data from the World Health Organization (WHO)'s World Mental Health Surveys (WMHS), based on representative community household surveys in 26 countries. We assessed the 12-month prevalence of substance use disorders (alcohol or drug abuse/dependence); the proportion of people with these disorders who were aware that they needed treatment and who wished to receive care; the proportion of those seeking care who received it; and the proportion of such treatment that met minimal standards for treatment quality ("minimally adequate treatment"). Among the 70,880 participants, 2.6% met 12-month criteria for substance use disorders; the prevalence was higher in upper-middle income (3.3%) than in high-income (2.6%) and low/lower-middle income (2.0%) countries. Overall, 39.1% of those with 12-month substance use disorders recognized a treatment need; this recognition was more common in high-income (43.1%) than in upper-middle (35.6%) and low/lower-middle income (31.5%) countries. Among those who recognized treatment need, 61.3% made at least one visit to a service provider, and 29.5% of the latter received minimally adequate treatment exposure (35.3% in high, 20.3% in upper-middle, and 8.6% in low/lower-middle income countries). Overall, only 7.1% of those with past-year substance use disorders received minimally adequate treatment: 10.3% in high income, 4.3% in upper-middle income and 1.0% in low/lower-middle income countries. These data suggest that only a small minority of people with substance use disorders receive even minimally adequate treatment. At least three barriers are involved: awareness/perceived treatment need, accessing treatment once a need is recognized, and compliance (on the part of both provider and client) to obtain adequate treatment. Various factors are likely to be involved in each of these three barriers, all of which need to be addressed to improve treatment coverage of substance use disorders. These data provide a baseline for the global monitoring of progress of treatment coverage for these disorders as an indicator within the SDGs.