The bi-directional associations between psychotic experiences and DSM-IV mental disorders

OBJECTIVE: While it is now recognized that psychotic experiences are associated with an increased risk of later mental disorders, we lack a detailed understanding of the reciprocal time-lagged relationships between first onsets of psychotic experiences and mental disorders. Using data from World Health Organization World Mental Health (WMH) Surveys, the authors assessed the bidirectional temporal associations between psychotic experiences and mental disorders. METHOD: The WMH Surveys assessed lifetime prevalence and age at onset of psychotic experiences and 21 common DSM-IV mental disorders among 31,261 adult respondents from 18 countries. Discrete-time survival models were used to examine bivariate and multivariate associations between psychotic experiences and mental disorders. RESULTS: Temporally primary psychotic experiences were significantly associated with subsequent first onset of eight of the 21 mental disorders (major depressive disorder, bipolar disorder, generalized anxiety disorder, social phobia, posttraumatic stress disorder, adult separation anxiety disorder, bulimia nervosa, and alcohol abuse), with odds ratios ranging from 1.3 (95% CI=1.2-1.5) for major depressive disorder to 2.0 (95% CI=1.5-2.6) for bipolar disorder. In contrast, 18 of 21 primary mental disorders were significantly associated with subsequent first onset of psychotic experiences, with odds ratios ranging from 1.5 (95% CI=1.0-2.1) for childhood separation anxiety disorder to 2.8 (95% CI=1.0-7.8) for anorexia nervosa. CONCLUSIONS: While temporally primary psychotic experiences are associated with an elevated risk of several subsequent mental disorders, these data show that most mental disorders are associated with an elevated risk of subsequent psychotic experiences. Further investigation of the underlying factors accounting for these time-order relationships may shed light on the etiology of psychotic experiences

findings from the World Health Organization World Mental Health surveys

Funding Information: The World Health Organization World Mental Health (WMH) Survey Initiative is supported by the United States National Institute of Mental Health (NIMH; R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the United States Public Health Service (R13-MH066849, R01-MH069864 and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical Inc., GlaxoSmithKline and Bristol-Myers Squibb. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork and consultation on data analysis. The Argentina survey—Estudio Argentino de Epidemiología en Salud Mental (EASM)— was supported by a grant from the Argentinian Ministry of Health (Ministerio de Salud de la Nación). The São Paulo Megacity Mental Health Survey is supported by the State of São Paulo Research Foundation (FAPESP) Thematic Project Grant 03/00204–3. The Colombian National Study of Mental Health (NSMH) is supported by the Ministry of Social Protection. The ESEMeD surveys were funded by the European Commission (contracts QLG5–1999-01042; SANCO 2004123 and EAHC 20081308), the Piedmont Region, Italy, Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spain (FIS 00/0028), Ministerio de Ciencia y Tecnología, Spain (SAF 2000– 158-CE), Departament de Salut, Generalitat de Catalunya, Spain, Instituto de Salud Carlos III (CIBER CB06/02/0046, RETICS RD06/0011 REM-TAP) and other local agencies and by an unrestricted educational grant from GlaxoSmithKline. Implementation of the Iraq Mental Health Survey (IMHS) and data entry were carried out by the staff of the Iraqi MOH and MOP with direct support from the Iraqi IMHS team with funding from both the Japanese and European Funds through the United Nations Development Group Iraq Trust Fund (UNDG ITF). The Lebanese Evaluation of the Burden of Ailments and Needs of the Nation (L.E.B.A.N.O.N.) is supported by the Lebanese Ministry of Public Health, the WHO (Lebanon), National Institute of Health/Fogarty International Center (R03 TW006481–01), anonymous private donations to IDRAAC, Lebanon and unrestricted grants from, Algorithm, AstraZeneca, Benta, Bella Pharma, Eli Lilly, Glaxo Smith Kline, Lundbeck, Novartis, OmniPharma, Pfizer, Phenicia, Servier, UPO. The Mexican National Comorbidity Survey (MNCS) is supported by The National Institute of Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science and Technology (CONACyT-G30544-H), with supplemental support from the PanAmerican Health Organization (PAHO). Te Rau Hinengaro: the New Zealand Mental Health Survey (NZMHS) is supported by the New Zealand Ministry of Health, Alcohol Advisory Council and the Health Research Council. The Nigerian Survey of Mental Health and Wellbeing (NSMHW) is supported by the WHO (Geneva), the WHO (Nigeria) and the Federal Ministry of Health, Abuja, Nigeria. The Peruvian World Mental Health Study was funded by the National Institute of Health of the Ministry of Health of Peru. The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health. The Romania WMH study projects ‘Policies in Mental Health Area’ and ‘National Study regarding Mental Health and Services Use’ were carried out by the National School of Public Health and Health Services Management (former National Institute for Research and Development in Health, present National School of Public Health Management and Professional Development, Bucharest), with technical support of Metro Media Transilvania, the National Institute of Statistics—National Centre for Training in Statistics, SC. Cheyenne Services SRL, Statistics Netherlands and were funded by the Ministry of Public Health (former Ministry of Health) with supplemental support of Eli Lilly Romania SRL. The US National Comorbidity Survey Replication (NCS-R) is supported by the National Institute of Mental Health (NIMH; U01-MH60220) with supplemental support from the National Institute of Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; grant 044708) and the John W. Alden Trust. None of the funders had any role in the design, analysis, interpretation of results or preparation of this paper. The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of the World Health Organization, other sponsoring organizations, agencies or governments. J.J.M. received the John Cade Fellowship APP1056929 from the National Health and Medical Research Council and the Niels Bohr Professorship from the Danish National Research Foundation. A complete list of all within-country and cross-national WMH publications can be found at http://www.hcp.med. harvard.edu/wmh/. Publisher Copyright: © 2017 Society for the Study of AddictionBackground and aims: Prior research has found bidirectional associations between psychotic experiences (PEs) and selected substance use disorders. We aimed to extend this research by examining the bidirectional association between PEs and various types of substance use (SU) and substance use disorders (SUDs), and the influence of antecedent mental disorders on these associations. Design, setting, participants and measurements: We used data from the World Health Organization World Mental Health surveys. A total of 30 902 adult respondents across 18 countries were assessed for (a) six types of life-time PEs, (b) a range of types of SU and DSM-IV SUDs and (c) mental disorders using the Composite International Diagnostic Interview. Discrete-time survival analyses based on retrospective age-at-onset reports examined the bidirectional associations between PEs and SU/SUDs controlling for antecedent mental disorders. Findings: After adjusting for demographics, comorbid SU/SUDs and antecedent mental disorders, those with prior alcohol use disorders [odds ratio (OR) = 1.6, 95% confidence interval (CI) = 1.2–2.0], extra-medical prescription drug use (OR = 1.5, 95% CI = 1.1–1.9), alcohol use (OR = 1.4, 95% CI = 1.1–1.7) and tobacco use (OR = 1.3, 95% CI = 1.0–1.8) had increased odds of subsequent first onset of PEs. In contrast, those with temporally prior PEs had increased odds of subsequent onset of tobacco use (OR = 1.5, 95% CI = 1.2–1.9), alcohol use (OR = 1.3, 95% CI = 1.1–1.6) or cannabis use (OR = 1.3, 95% CI = 1.0–1.5) as well as of all substance use disorders (ORs ranged between 1.4 and 1.5). There was a dose response relationship between both count and frequency of PEs and increased subsequent odds of selected SU/SUDs. Conclusions: Associations between psychotic experiences (PEs) and substance use/substance use disorders (SU/SUDs) are often bidirectional, but not all types of SU/SUDs are associated with PEs. These findings suggest that it is important to be aware of the presence of PEs within those with SUDs or at risk of SUDs, given the plausibility that they may each impact upon the other.publishersversionpublishe

Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use

The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123 and EAHC 20081308). The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health.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.publishersversionepub_ahead_of_prin

Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use

The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123 and EAHC 20081308). The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health.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.publishersversionepub_ahead_of_prin

Proof-of-concept of a data-driven approach to estimate the associations of comorbid mental and physical disorders with global health-related disability

Objective: The standard method of generating disorder-specific disability scores has lay raters make rankings between pairs of disorders based on brief disorder vignettes. This method introduces bias due to differential rater knowledge of disorders and inability to disentangle the disability due to disorders from the disability due to comorbidities. Methods: We propose an alternative, data-driven, method of generating disorder-specific disability scores that assesses disorders in a sample of individuals either from population medical registry data or population survey self-reports and uses Generalized Random Forests(GRF) to predict global (rather than disorder-specific) disability assessed by clinician ratings or by survey respondent self-reports. This method also provides a principled basis for studying patterns and predictors of heterogeneity in disorder-specific disability. We illustrate this method by analyzing data for 16 disorders assessed in the World Mental Health Surveys(n=53,645).Results: Adjustments for comorbidity decreased estimates of disorder-specific disability substantially. Estimates were generally somewhat higher with GRF than conventional multivariable regression models. Heterogeneity was nonsignificant. Conclusions: The results show clearly that the proposed approach is practical, and that adjustment is needed for comorbidities to obtain accurate estimates of disorder-specific disability. Expansion to a wider range of disorders would likely find more evidence for heterogeneity

Age of onset and cumulative risk of mental disorders:a cross-national analysis of population surveys from 29 countries

Background: Information on the frequency and timing of mental disorder onsets across the lifespan is of fundamental importance for public health planning. Broad, cross-national estimates of this information from coordinated general population surveys were last updated in 2007. We aimed to provide updated and improved estimates of age-of-onset distributions, lifetime prevalence, and morbid risk. Methods: In this cross-national analysis, we analysed data from respondents aged 18 years or older to the World Mental Health surveys, a coordinated series of cross-sectional, face-to-face community epidemiological surveys administered between 2001 and 2022. In the surveys, the WHO Composite International Diagnostic Interview, a fully structured psychiatric diagnostic interview, was used to assess age of onset, lifetime prevalence, and morbid risk of 13 DSM-IV mental disorders until age 75 years across surveys by sex. We did not assess ethnicity. The surveys were geographically clustered and weighted to adjust for selection probability, and standard errors of incidence rates and cumulative incidence curves were calculated using the jackknife repeated replications simulation method, taking weighting and geographical clustering of data into account. Findings: We included 156 331 respondents from 32 surveys in 29 countries, including 12 low-income and middle-income countries and 17 high-income countries, and including 85 308 (54·5%) female respondents and 71 023 (45·4%) male respondents. The lifetime prevalence of any mental disorder was 28·6% (95% CI 27·9–29·2) for male respondents and 29·8% (29·2–30·3) for female respondents. Morbid risk of any mental disorder by age 75 years was 46·4% (44·9–47·8) for male respondents and 53·1% (51·9–54·3) for female respondents. Conditional probabilities of first onset peaked at approximately age 15 years, with a median age of onset of 19 years (IQR 14–32) for male respondents and 20 years (12–36) for female respondents. The two most prevalent disorders were alcohol use disorder and major depressive disorder for male respondents and major depressive disorder and specific phobia for female respondents. Interpretation: By age 75 years, approximately half the population can expect to develop one or more of the 13 mental disorders considered in this Article. These disorders typically first emerge in childhood, adolescence, or young adulthood. Services should have the capacity to detect and treat common mental disorders promptly and to optimise care that suits people at these crucial parts of the life course. Funding: None.</p

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

Patterns and correlates of patient-reported helpfulness of treatment for common mental and substance use disorders in the WHO World Mental Health Surveys

Patient-reported helpfulness of treatment is an important indicator of quality in patient-centered care. We examined its pathways and predictors among respondents to household surveys who reported ever receiving treatment for major depression, generalized anxiety disorder, social phobia, specific phobia, post-traumatic stress disorder, bipolar disorder, or alcohol use disorder. Data came from 30 community epidemiological surveys - 17 in high-income countries (HICs) and 13 in low- and middle-income countries (LMICs) - carried out as part of the World Health Organization (WHO)'s World Mental Health (WMH) Surveys. Respondents were asked whether treatment of each disorder was ever helpful and, if so, the number of professionals seen before receiving helpful treatment. Across all surveys and diagnostic categories, 26.1% of patients (N=10,035) reported being helped by the very first professional they saw. Persisting to a second professional after a first unhelpful treatment brought the cumulative probability of receiving helpful treatment to 51.2%. If patients persisted with up through eight professionals, the cumulative probability rose to 90.6%. However, only an estimated 22.8% of patients would have persisted in seeing these many professionals after repeatedly receiving treatments they considered not helpful. Although the proportion of individuals with disorders who sought treatment was higher and they were more persistent in HICs than LMICs, proportional helpfulness among treated cases was no different between HICs and LMICs. A wide range of predictors of perceived treatment helpfulness were found, some of them consistent across diagnostic categories and others unique to specific disorders. These results provide novel information about patient evaluations of treatment across diagnoses and countries varying in income level, and suggest that a critical issue in improving the quality of care for mental disorders should be fostering persistence in professional help-seeking if earlier treatments are not helpful