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AIMS: Likelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD. DESIGN: A prediction model was developed for DSM-IV AD onset by age 25 years using an ensemble machine-learning algorithm known as 'Super Learner'. Shapley additive explanations (SHAP) assessed variable importance. SETTING AND PARTICIPANTS: Respondents reporting early onset of regular alcohol use (i.e. by 17 years of age) who were aged 25 years or older at interview from 14 representative community surveys conducted in 13 countries as part of WHO's World Mental Health Surveys. MEASUREMENTS: The primary outcome to be predicted was onset of life-time DSM-IV AD by age 25 as measured using the Composite International Diagnostic Interview, a fully structured diagnostic interview. FINDINGS: AD prevalence by age 25 was 5.1% among the 10 687 individuals who reported drinking alcohol regularly by age 17. The prediction model achieved an external area under the curve [0.78; 95% confidence interval (CI) = 0.74-0.81] higher than any individual candidate risk model (0.73-0.77) and an area under the precision-recall curve of 0.22. Overall calibration was good [integrated calibration index (ICI) = 1.05%]; however, miscalibration was observed at the extreme ends of the distribution of predicted probabilities. Interventions provided to the 20% of people with highest risk would identify 49% of AD cases and require treating four people without AD to reach one with AD. Important predictors of increased risk included younger onset of alcohol use, males, higher cohort alcohol use and more mental disorders. CONCLUSIONS: A risk algorithm can be created using data collected at the onset of regular alcohol use to target youth at highest risk of alcohol dependence by early adulthood. Important considerations remain for advancing the development and practical implementation of such models. ispartof: Addiction vol:118 issue:5 pages:954-966 ispartof: location:England status: published

BackgroundCross-national studies have found, unexpectedly, that mental disorder prevalence is higher in high-income relative to low-income countries, but few rigorous studies have been conducted in very low-income countries. This study assessed mental disorders in Nepal, employing unique methodological features designed to maximize disorder detection and reporting.MethodsIn 2016–2018, 10714 respondents aged 15–59 were interviewed as part of an ongoing panel study, with a response rate of 93%. The World Mental Health version of the Composite International Diagnostic Interview (WMH-CIDI 3.0) measured lifetime and 12-month prevalence of selected anxiety, mood, alcohol use, and impulse control disorders. Lifetime recall was enhanced using a life history calendar.ResultsLifetime prevalence ranged from 0.3% (95% CI 0.2–0.4) for bipolar disorder to 15.1% (95% CI 14.4–15.7) for major depressive disorder. The 12-month prevalences were low, ranging from 0.2% for panic disorder (95% CI 0.1–0.3) and bipolar disorder (95% CI 0.1–0.2) to 2.7% for depression (95% CI 2.4–3.0). Lifetime disorders were higher among those with less education and in the low-caste ethnic group. Gender differences were pronounced.ConclusionsAlthough cultural effects on reporting cannot be ruled out, these low 12-month prevalences are consistent with reduced prevalence of mental disorders in other low-income countries. Identification of sociocultural factors that mediate the lower prevalence of mental disorders in low-income, non-Westernized settings may have implications for understanding disorder etiology and for clinical or policy interventions aimed at facilitating resilience.

Background Marriage in general is associated with better mental health in high-income industrialized countries, but it is unknown to what extent this is also the case in South Asia. Methods The Chitwan Valley Family Study (CVFS) in Nepal is a 24-year family panel study with a recent representative survey to investigate the association between sociodemographic changes and mental health (N = 10,516). We investigated timing of marital transitions and timing of onset of MDD in both male and female respondents, controlling for key confounders. Results In this setting the transition to marriage is associated with increased odds of subsequent MDD first onset (median OR=2.28). For female respondents, divorce (OR=2.68), early widowed (OR=11.25), and even getting married significantly increased the odds of subsequent MDD onset (OR=3.03). For male respondents, only becoming widowed increased the odds of subsequent MDD (OR=16.32), but marriage did not reduce the odds of MDD. Limitations Limitations of the study include large-scale protocol that may have resulted in underreporting of MDD and the exclusion of sub-threshold cases that may otherwise have qualified as a case in a clinical setting. Conclusions In the Nepalese general population, marital transitions increase the odds of subsequent depression, especially among the female population. Results provide basic but essential vital health data that can guide clinicians to proactively plan sustainable healthcare both within South Asia and among many South Asians living in other places.

BackgroundRetrospective reports of lifetime experience with mental disorders greatly underestimate the actual experiences of disorder because recall error biases reporting of earlier life symptoms downward. This fundamental obstacle to accurate reporting has many adverse consequences for the study and treatment of mental disorders. Better tools for accurate retrospective reporting of mental disorder symptoms have the potential for broad scientific benefits.MethodsWe designed a life history calendar (LHC) to support this task, and randomized more than 1000 individuals to each arm of a retrospective diagnostic interview with and without the LHC. We also conducted a careful validation with the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition.ResultsResults demonstrate that—just as with frequent measurement longitudinal studies—use of an LHC in retrospective measurement can more than double reports of lifetime experience of some mental disorders.ConclusionsThe LHC significantly improves retrospective reporting of mental disorders. This tool is practical for application in both large cross-sectional surveys of the general population and clinical intake of new patients.

Objectives Recall error biases reporting of earlier life experiences, even potentially traumatic experiences (PTEs). Better tools for accurate retrospective reporting of PTEs and other health risk factors have the potential for broad scientific and health intervention benefits. Methods We designed a life history calendar (LHC) to support this task and randomized more than 1000 individuals to each arm of a retrospective diagnostic interview, including detailed measures of PTEs, with and without the LHC. This is one of the largest experiments ever done to assess the benefit of an LHC approach and the only large‐scale experiment done in a poor, agrarian, non‐Western setting (rural Nepal). Results Results demonstrate use of an LHC in retrospective measurement can significantly increase lifetime reports of PTEs, especially reports of two or more PTEs. The LHC increases PTE reporting more for men and those with less education. Conclusions The LHC approach is practical for many uses ranging from large surveys of the general population to clinical intake of new patients. It significantly increases reporting of health risk factors.

Background: Efforts to develop and validate fully-structured diagnostic interviews of mental disorders in non-Western countries have been largely unsuccessful. However, the principled methods of translation, harmonization, and calibration that have been developed by cross-national survey methodologists have never before been used to guide such development efforts. The current report presents the results of a rigorous program of research using these methods designed to modify and validate the Composite International Diagnostic Interview (CIDI) for an epidemiological survey in Nepal. Methods: A five-step process of translation, harmonization, and calibration was used to modify the instrument. A blinded clinical reappraisal design was used to validate the instrument. Results: Preliminary interviews with local mental health expert led to a focus on major depressive episode, mania/hypomania, panic disorder, post-traumatic stress disorder, generalized anxiety disorder, and intermittent explosive disorder. After an iterative process of multiple translations-revisions guided by the principles developed by cross-national survey methodologists, lifetime DSM-IV diagnoses based on the final Nepali CIDI had excellent concordance with diagnoses based on blinded Structured Clinical Interview for DSM-IV (SCID) clinical reappraisal interviews. Conclusions: Valid assessment of mental disorders can be achieved with fully-structured diagnostic interviews even in low-income non-Western settings with rigorous implementation of replicable developmental strategies. Copyright © 2013 John Wiley & Sons, Ltd.

Our understanding of the demography of mental health has been revolutionized by the WHO’s World Mental Health (WMH) survey data collection. This is because WMH surveys take a general population approach, aiming to measure prevalence and subgroup differences among the entire population. To describe the demography of mental health we draw upon these general population measures, rather than clinical or other special sub-population measures. We consider the demography of mental health at the global scale, describing what is known about comparisons across countries and comparisons across categories of age, gender, marital status, race/ethnicity, and economic status.

This paper provides an overview of the development and implementation of the Collaborative Psychiatric Epidemiology Surveys (CPES): the National Comorbidity Survey Replication (NCS‐R), the National Survey of American Life (NSAL), and the National Latino and Asian American Study (NLAAS). It describes the instrument development and testing phases, the development of training and other project materials, interviewer recruitment and training activities, and data collection procedures and outcomes. The last section offers recommendations for other researchers who undertake similar studies and who might benefit from the experiences learned in the development and operation of NCS‐R, NSAL and NLAAS. Copyright © 2004 Whurr Publishers Ltd.