Prevalence of adolescent mental disorders in Kenya, Indonesia, and Viet Nam measured by the National Adolescent Mental Health Surveys (NAMHS): a multi-national cross-sectional study.

BACKGROUND: Mental disorders are the leading global cause of health burden among adolescents. However, prevalence data for mental disorders among adolescents in low-income and middle-income countries are scarce with often limited generalisability. This study aimed to generate nationally representative prevalence estimates for mental disorders in adolescents in Kenya, Indonesia, and Viet Nam. METHODS: As part of the National Adolescent Mental Health Surveys (NAMHS), a multinational cross-sectional study, nationally representative household surveys were conducted in Kenya, Indonesia, and Viet Nam between March and December, 2021. Adolescents aged 10-17 years and their primary caregiver were interviewed from households selected randomly according to sampling frames specifically designed to elicit nationally representative results. Six mental disorders (social phobia, generalised anxiety disorder, major depressive disorder, post-traumatic stress disorder, conduct disorder, and attention-deficit hyperactivity disorder) were assessed with the Diagnostic Interview Schedule for Children, Version 5. Suicidal behaviours and self-harm in the past 12 months were also assessed. Prevalence in the past 12 months and past 4 weeks was calculated for each mental disorder and collectively for any mental disorder (ie, of the six mental disorders assessed). Prevalence of suicidal behaviours (ie, ideation, planning, and attempt) and self-harm in the past 12 months was calculated, along with adjusted odds ratios (aORs) to show the association with prevalence of any mental disorder in the past 12 months. Inverse probability weighting was applied to generate national estimates with corresponding 95% CIs. FINDINGS: Final samples consisted of 5155 households (ie, adolescent and primary caregiver pairs) from Kenya, 5664 households from Indonesia, and 5996 households from Viet Nam. In Kenya, 2416 (46·9%) adolescents were male and 2739 (53·1%) were female; in Indonesia, 2803 (49·5%) adolescents were male and 2861 (50·5%) were female; and in Viet Nam, 3151 (52·5%) were male and 2845 (47·4%) were female. Prevalence of any mental disorder in the past 12 months was 12·1% (95% CI 10·9-13·5) in Kenya, 5·5% (4·3-6·9) in Indonesia, and 3·3% (2·7-4·1) in Viet Nam. Prevalence in the past 4 weeks was 9·4% (8·3-10·6) in Kenya, 4·4% (3·4-5·6) in Indonesia, and 2·7% (2·2-3·3) in Viet Nam. The prevalence of suicidal behaviours in the past 12 months was low in all three countries, with suicide ideation ranging from 1·4% in Indonesia (1·0-2·0) and Viet Nam (1·0-1·9) to 4·6% (3·9-5·3) in Kenya, suicide planning ranging from 0·4% in Indonesia (0·3-0·8) and Viet Nam (0·2-0·6) to 2·4% (1·9-2·9) in Kenya, and suicide attempts ranging from 0·2% in Indonesia (0·1-0·4) and Viet Nam (0·1-0·3) to 1·0% (0·7-1·4) in Kenya. The prevalence of self-harm in the past 12 months was also low in all three countries, ranging from 0·9% (0·6-1·3) in Indonesia to 1·2% (0·9-1·7) in Kenya. However, the prevalence of suicidal behaviours and self-harm in the past 12 months was significantly higher among those with any mental disorder in the past 12 months than those without (eg, aORs for suicidal ideation ranged from 7·1 [3·1-15·9] in Indonesia to 14·7 [7·5-28·6] in Viet Nam). INTERPRETATION: NAMHS provides the first national adolescent mental disorders prevalence estimates for Kenya, Indonesia, and Viet Nam. These data can inform mental health and broader health policies in low-income and middle-income countries. FUNDING: The University of Queensland in America (TUQIA) through support from Pivotal Ventures, a Melinda French Gates company.

Association between Mental Disorders and Subsequent Medical Conditions.

BACKGROUND: Persons with mental disorders are at a higher risk than the general population for the subsequent development of certain medical conditions. METHODS: We used a population-based cohort from Danish national registries that included data on more than 5.9 million persons born in Denmark from 1900 through 2015 and followed them from 2000 through 2016, for a total of 83.9 million person-years. We assessed 10 broad types of mental disorders and 9 broad categories of medical conditions (which encompassed 31 specific conditions). We used Cox regression models to calculate overall hazard ratios and time-dependent hazard ratios for pairs of mental disorders and medical conditions, after adjustment for age, sex, calendar time, and previous mental disorders. Absolute risks were estimated with the use of competing-risks survival analyses. RESULTS: A total of 698,874 of 5,940,299 persons (11.8%) were identified as having a mental disorder. The median age of the total population was 32.1 years at entry into the cohort and 48.7 years at the time of the last follow-up. Persons with a mental disorder had a higher risk than those without such disorders with respect to 76 of 90 pairs of mental disorders and medical conditions. The median hazard ratio for an association between a mental disorder and a medical condition was 1.37. The lowest hazard ratio was 0.82 for organic mental disorders and the broad category of cancer (95% confidence interval [CI], 0.80 to 0.84), and the highest was 3.62 for eating disorders and urogenital conditions (95% CI, 3.11 to 4.22). Several specific pairs showed a reduced risk (e.g., schizophrenia and musculoskeletal conditions). Risks varied according to the time since the diagnosis of a mental disorder. The absolute risk of a medical condition within 15 years after a mental disorder was diagnosed varied from 0.6% for a urogenital condition among persons with a developmental disorder to 54.1% for a circulatory disorder among those with an organic mental disorder. CONCLUSIONS: Most mental disorders were associated with an increased risk of a subsequent medical condition; hazard ratios ranged from 0.82 to 3.62 and varied according to the time since the diagnosis of the mental disorder. (Funded by the Danish National Research Foundation and others; COMO-GMC ClinicalTrials.gov number, NCT03847753.).

Diagnostic accuracy of the Composite International Diagnostic Interview (CIDI 3.0) in an urban Indigenous Australian sample.

OBJECTIVE: The Composite International Diagnostic Interview 3.0 is a standardised diagnostic interview commonly used in population-based mental health surveys, but has not been used in community-residing Indigenous Australians. This paper seeks to determine whether the Composite International Diagnostic Interview 3.0 can produce valid diagnostic information when compared with a diagnostic interview in an urban Indigenous Australian sample. METHOD: This research was conducted over 10 weeks with adult Indigenous clients of two participating Aboriginal Medical Services in South-East Queensland. Using a cross-sectional, repeated-measures design, participants were administered the Composite International Diagnostic Interview 3.0 by an Indigenous interviewer and within 2 weeks attended a second appointment with an Indigenous clinical psychologist, who produced a diagnostic summary. The Composite International Diagnostic Interview 3.0 diagnoses were compared with the diagnostic summaries and clinical concordance between the two measures was calculated. RESULTS: The diagnostic accuracy of the Composite International Diagnostic Interview 3.0 differed by module. The Post-traumatic Stress Disorder and Major Depression modules had good utility in diagnosing post-traumatic stress disorder and major depressive episodes, respectively; however, the Mania module that provides diagnoses of bipolar disorder was found to be unsuitable for this population. Although there were no identified contraindications for the use of the Generalised Anxiety and Alcohol Use Disorder modules, further research on the diagnostic accuracy of these modules is warranted. CONCLUSIONS: The Composite International Diagnostic Interview 3.0 can accurately diagnose some common mental disorders in an Indigenous Australian population, but was found to be unsuitable for others. Given these findings, care should be taken when using the Composite International Diagnostic Interview 3.0 in epidemiological prevalence studies with Indigenous Australian populations.

Quantifying the size of the informal care sector for Australian adults with mental illness: caring hours and replacement cost.

PURPOSE: To quantify and value the total informal support provided by family and friends to Australian adults with mental illness in 2018. METHODS: The number of mental health carers was drawn from the 2015 Survey of Disability, Ageing and Carers (SDAC), adjusted to the 2018 population. Annual caring hours by type of assistance were estimated using the SDAC, 2007 National Survey of Mental Health and Wellbeing and an online carer survey. Caring hours for each task were assigned an hourly replacement cost from the National Disability Insurance Scheme. Informal caring was valued as the sum of these costs minus expenditure on carer income support payments, estimating how much it would hypothetically cost governments to replace this care with formal support services. RESULTS: An estimated 354,000 (95% uncertainty interval (UI): 327,000-383,000) Australian mental health carers provided 186 million (95% UI: 159-215) hours of support in 2018. The estimated replacement cost was AU$8.4 billion (95% UI: 7.0-10.0), excluding AU$1.3 billion in income support. Univariate sensitivity analyses demonstrated that results were robust to variation in model inputs, with total caring hours the most influential parameter. Using an alternative estimate of mean caring hours, the replacement cost could be as high as AU$13.2 billion (95% UI: 11.2-15.4). CONCLUSION: Informal carers provide substantial support to people with mental illness, highlighting their important contribution to the mental health system and reinforcing the need for carer support services. Future valuation studies would benefit from refinement of available data collections, particularly on hours and types of care provided.

A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study.

BACKGROUND: Systematic reviews have consistently shown that individuals with mental disorders have an increased risk of premature mortality. Traditionally, this evidence has been based on relative risks or crude estimates of reduced life expectancy. The aim of this study was to compile a comprehensive analysis of mortality-related health metrics associated with mental disorders, including sex-specific and age-specific mortality rate ratios (MRRs) and life-years lost (LYLs), a measure that takes into account age of onset of the disorder. METHODS: In this population-based cohort study, we included all people younger than 95 years of age who lived in Denmark at some point between Jan 1, 1995, and Dec 31, 2015. Information on mental disorders was obtained from the Danish Psychiatric Central Research Register and the date and cause of death was obtained from the Danish Register of Causes of Death. We classified mental disorders into ten groups and causes of death into 11 groups, which were further categorised into natural causes (deaths from diseases and medical conditions) and external causes (suicide, homicide, and accidents). For each specific mental disorder, we estimated MRRs using Poisson regression models, adjusting for sex, age, and calendar time, and excess LYLs (ie, difference in LYLs between people with a mental disorder and the general population) for all-cause mortality and for each specific cause of death. FINDINGS: 7 369 926 people were included in our analysis. We found that mortality rates were higher for people with a diagnosis of a mental disorder than for the general Danish population (28·70 deaths [95% CI 28·57-28·82] vs 12·95 deaths [12·93-12·98] per 1000 person-years). Additionally, all types of disorders were associated with higher mortality rates, with MRRs ranging from 1·92 (95% CI 1·91-1·94) for mood disorders to 3·91 (3·87-3·94) for substance use disorders. All types of mental disorders were associated with shorter life expectancies, with excess LYLs ranging from 5·42 years (95% CI 5·36-5·48) for organic disorders in females to 14·84 years (14·70-14·99) for substance use disorders in males. When we examined specific causes of death, we found that males with any type of mental disorder lost fewer years due to neoplasm-related deaths compared with the general population, although their cancer mortality rates were higher. INTERPRETATION: Mental disorders are associated with premature mortality. We provide a comprehensive analysis of mortality by different types of disorders, presenting both MRRs and premature mortality based on LYLs, displayed by age, sex, and cause of death. By providing accurate estimates of premature mortality, we reveal previously underappreciated features related to competing risks and specific causes of death. FUNDING: Danish National Research Foundation.

The prevalence and burden of mental and substance use disorders in Australia: Findings from the Global Burden of Disease Study 2015.

OBJECTIVES: Timely and accurate assessments of disease burden are essential for developing effective national health policies. We used the Global Burden of Disease Study 2015 to examine burden due to mental and substance use disorders in Australia. METHODS: For each of the 20 mental and substance use disorders included in Global Burden of Disease Study 2015, systematic reviews of epidemiological data were conducted, and data modelled using a Bayesian meta-regression tool to produce prevalence estimates by age, sex, geography and year. Prevalence for each disorder was then combined with a disorder-specific disability weight to give years lived with disability, as a measure of non-fatal burden. Fatal burden was measured as years of life lost due to premature mortality which were calculated by combining the number of deaths due to a disorder with the life expectancy remaining at the time of death. Disability-adjusted life years were calculated by summing years lived with disability and years of life lost to give a measure of total burden. Uncertainty was calculated around all burden estimates. RESULTS: Mental and substance use disorders were the leading cause of non-fatal burden in Australia in 2015, explaining 24.3% of total years lived with disability, and were the second leading cause of total burden, accounting for 14.6% of total disability-adjusted life years. There was no significant change in the age-standardised disability-adjusted life year rates for mental and substance use disorders from 1990 to 2015. CONCLUSION: Global Burden of Disease Study 2015 found that mental and substance use disorders were leading contributors to disease burden in Australia. Despite several decades of national reform, the burden of mental and substance use disorders remained largely unchanged between 1990 and 2015. To reduce this burden, effective population-level preventions strategies are required in addition to effective interventions of sufficient duration and coverage.

The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States.

Introduction: Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective: To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting: A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures: Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results: Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance: There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.

Identifying characteristics and practices of multidisciplinary team reviews for patients with severe mental illness: a systematic review.

OBJECTIVES: Multidisciplinary teams in mental health receive limited guidance, leading to inconsistent practices. We undertook a systematic review of the characteristics and practices of multidisciplinary team reviews for patients with severe mental illness or in relevant mental health service settings. METHODS: Sources published since 2000 were located via academic database and web searches. Results were synthesised narratively. RESULTS: A total of 14 sources were analysed. Important characteristics and practices identified included routine monitoring and evaluation, good communication, equality between team members, and clear documentation practices. Success factors included defined leadership and clear team goals. Four sources described considerations for patients with complex clinical needs, including allocating sufficient time for discussion, maintaining connections with community providers, and ensuring culturally sensitive practices. CONCLUSIONS: No single best practice model was found, due to variations in team caseload, casemix, and resourcing levels. However, key ingredients for success were proposed. Sources were mostly descriptive; there remains a lack of evidence-based guidance regarding multidisciplinary team review characteristics and practices.

The burden of mental, neurological, and substance use disorders in China and India: a systematic analysis of community representative epidemiological studies.

BACKGROUND: China and India jointly account for 38% of the world population, so understanding the burden attributed to mental, neurological, and substance use disorders within these two countries is essential. As part of the Lancet/Lancet Psychiatry China-India Mental Health Alliance Series, we aim to provide estimates of the burden of mental, neurological, and substance use disorders for China and India from the Global Burden of Disease Study 2013 (GBD 2013). METHODS: In this systematic analysis for community representative epidemiological studies, we conducted systematic reviews in line with PRISMA guidelines for community representative epidemiological studies. We extracted estimates of prevalence, incidence, remission and duration, and mortality along with associated uncertainty intervals from GBD 2013. Using these data as primary inputs, DisMod-MR 2.0, a Bayesian meta-regression instrument, used a log rate and incidence-prevalence-mortality mathematical model to develop internally consistent epidemiological models. Disability-adjusted life-year (DALY) changes between 1990 and 2013 were decomposed to quantify change attributable to population growth and ageing. We projected DALYs from 2013 to 2025 for mental, neurological, and substance use disorders using United Nations population data. FINDINGS: Around a third of global DALYs attributable to mental, neurological, and substance use disorders were found in China and India (66 million DALYs), a number greater than all developed countries combined (50 million DALYs). Disease burden profiles differed; India showed similarities with other developing countries (around 50% of DALYs attributable to non-communicable disease), whereas China more closely resembled developed countries (around 80% of DALYs attributable to non-communicable disease). The overall population growth in India explains a greater proportion of the increase in mental, neurological, and substance use disorder burden from 1990 to 2013 (44%) than in China (20%). The burden of mental, neurological, and substance use disorders is estimated to increase by 10% in China and 23% in India between 2013 and 2025. INTERPRETATION: The current and projected burden of mental, neurological, and substance use disorders in China and India warrants the urgent prioritisation of programmes focused on targeted prevention, early identification, and effective treatment. FUNDING: China Medical Board, Bill & Melinda Gates Foundation.

An analysis of policy success and failure in formal evaluations of Australia's national mental health strategy (1992-2012).

BACKGROUND: Heightened fiscal constraints, increases in the chronic disease burden and in consumer expectations are among several factors contributing to the global interest in evidence-informed health policy. The present article builds on previous work that explored how the Australian Federal Government applied five instruments of policy, or policy levers, to implement a series of reforms under the Australian National Mental Health Strategy (NMHS). The present article draws on theoretical insights from political science to analyse the relative successes and failures of these levers, as portrayed in formal government evaluations of the NMHS. METHODS: Documentary analysis of six evaluation documents corresponding to three National Mental Health Plans was undertaken. Both the content and approach of these government-funded, independently conducted evaluations were appraised. RESULTS: An overall improvement was apparent in the development and application of policy levers over time. However, this finding should be interpreted with caution due to variations in evaluation approach according to Plan and policy lever. Tabulated summaries of the success and failure of each policy initiative, ordered by lever type, are provided to establish a resource that could be consulted for future policy-making. CONCLUSIONS: This analysis highlights the complexities of health service reform and underscores the limitations of narrowly focused empirical approaches. A theoretical framework is provided that could inform the evaluation and targeted selection of appropriate policy levers in mental health.

How do we define the policy impact of public health research? A systematic review.

BACKGROUND: In order to understand and measure the policy impact of research we need a definition of research impact that is suited to the task. This article systematically reviewed both peer-reviewed and grey literature for definitions of research impact to develop a definition of research impact that can be used to investigate how public health research influences policy. METHOD: Keyword searches of the electronic databases Web of Science, ProQuest, PubMed, EMBASE, CINAHL, Informit, PsycINFO, The Cochrane Database of Systematic Reviews and Google Scholar were conducted between August 2015 and April 2016. Keywords included 'definition' and 'policy' and 'research impact' or 'research evidence'. The search terms 'health', public health' or 'mental health' and 'knowledge transfer' or 'research translation' were used to focus the search on relevant health discipline approaches. Studies included in the review described processes, theories or frameworks associated with public health, health services or mental health policy. RESULTS: We identified 108 definitions in 83 publications. The key findings were that literature on research impact is growing, but only 23% of peer-reviewed publications on the topic explicitly defined the term and that the majority (76%) of definitions were derived from research organisations and funding institutions. We identified four main types of definition, namely (1) definitions that conceptualise research impacts in terms of positive changes or effects that evidence can bring about when transferred into policies (example Research Excellence Framework definition), (2) definitions that interpret research impacts as measurable outcomes (Research Councils UK), and (3) bibliometric and (4) use-based definitions. We identified four constructs underpinning these definitions that related to concepts of contribution, change, avenues and levels of impact. CONCLUSION: The dominance of bureaucratic definitions, the tendency to discuss but not define the concept of research impact, and the heterogeneity of definitions confirm the need for conceptual clarity in this area. We propose a working definition of research impact that can be used in a range of health policy contexts.

The prevalence and burden of bipolar disorder: findings from the Global Burden of Disease Study 2013.

OBJECTIVES: We present the global burden of bipolar disorder based on findings from the Global Burden of Disease Study 2013 (GBD 2013). METHODS: Data on the epidemiology of bipolar disorder were obtained from a systematic literature review and assembled using Bayesian meta-regression modelling to produce prevalence by country, age, sex and year. Years lived with disability (YLDs) were estimated by multiplying prevalence by disability weights quantifying the severity of the health loss associated with bipolar disorder. As there were no years of life lost (YLLs) attributed to bipolar disorder, YLDs equated to disability-adjusted life years (DALYs) as a measure of total burden. RESULTS: There were 32.7 million cases of bipolar disorder globally in 1990 and 48.8 million in 2013; equivalent to a 49.1% increase in prevalent cases, all accounted for by population increase and ageing. Bipolar disorder accounted for 9.9 million DALYs in 2013, explaining 0.4% of total DALYs and 1.3% of total YLDs. There were 5.5 million DALYs recorded for female individuals and 4.4 million for male individuals. DALYs were evident from age 10 years, peaked in the 20s, and decreased thereafter. DALYs were relatively constant geographically. CONCLUSIONS: Despite being relatively rare, bipolar disorder is a disabling illness due to its early onset, severity and chronicity. Population growth and aging are leading to an increase in the burden of bipolar disorder over time. It is important that resources be directed towards improving the coverage of evidence-based intervention strategies for bipolar disorder and establishing strategies to prevent new cases of the disorder.

Frequency and quality of mental health treatment for affective and anxiety disorders among Australian adults.

OBJECTIVES: To describe the frequency, type and quality of mental health treatment among Australian adults with past-year affective and/or anxiety disorders. DESIGN, SETTING AND PARTICIPANTS: Retrospective analysis of data for 8831 adults aged 16-85 years interviewed for the 2007 National Survey of Mental Health and Wellbeing, of whom 17% (n = 1517) met International Classification of Diseases, 10th revision (ICD-10) criteria for a past-year affective and/or anxiety disorder. MAIN OUTCOME MEASURES: Three levels of mental health treatment received in the past year: (1) any consultation with a health professional for mental health; (2) any evidence-based intervention (antidepressant medication, mood stabiliser medication, cognitive behaviour therapy and/or psychotherapy); and (3) minimally adequate treatment (a "dose" of an evidence-based intervention above a minimum threshold, consistent with treatment guidelines). RESULTS: Of participants with past-year affective and/or anxiety disorders, 39% sought professional help for mental health, 26% received an evidence-based treatment, and 16% received minimally adequate treatment. After controlling for clinical factors including type and severity of disorder, the odds of all levels of treatment were lower among younger adults (16-29 years) compared with middle-aged adults, and the odds of receiving an evidence-based treatment or minimally adequate treatment were lower among people who consulted a general practitioner only compared with a mental health professional. CONCLUSIONS: Closing the gap in treatment quality requires strategies to increase the use of evidence-based interventions, and to ensure these are delivered in sufficient doses. Research to elucidate why some patients are at increased risk of inadequate treatment, and the aspects of treatment that contribute to inadequate care, is indicated.

Males' mental health disadvantage: An estimation of gender-specific changes in service utilisation for mental and substance use disorders in Australia.

BACKGROUND: Concerns about low levels of service utilisation for mental and substance use disorders in Australia - especially among males - have prompted targeted help-seeking and stigma-reduction initiatives. Resulting changes in service utilisation according to gender are unknown. We modelled the percentage of Australian males with a mental or substance use disorder who used services each year between 2006-2007 and 2011-2012, and the types of services they used, relative to females. METHODS: Twelve-month prevalence of mental and substance use disorders, stratified by gender, was synthesised from existing estimates. The percentage of males and females with these disorders who used mental health services in each year from 2006-2007 to 2011-2012 was modelled from published programme activity data, supplemented by analyses of epidemiological survey data. Uncertainty analysis quantified the effects of sampling error and assumptions on the estimates. RESULTS: Modelling showed a significant increase in the percentage of people with mental or substance use disorders who used services for their mental health - from 32.0% in 2006-2007 to 40.0% in 2011-2012 in males and from 45.1% in 2006-2007 to 54.6% in 2011-2012 in females. Growth was driven largely by uptake of private specialised services - males' use of these services grew by 92.7% and females' by 115.4%. There appeared to be a non-significant decrease in use of general practitioner-only mental health care for males (-17.9%), and a significant decrease in the same for females (-35.1%); however, some assumptions made in the modelling of general practitioner-only care require validation. In 2006-2007, the percentage of females treated was 40.9% higher than for males; in 2011-2012, it was 36.6% greater. CONCLUSIONS: Recently implemented initiatives have improved males' likelihood of service utilisation, particularly their use of specialised mental health services. Although the gender gap may have narrowed, improving males' access to services should remain a policy priority.

Stimulant use disorders in people with psychosis: a meta-analysis of rate and factors affecting variation.

OBJECTIVE: Stimulant abuse and dependence often complicate the care of people with psychotic disorders. This study systematically reviews the prevalence estimates reported for stimulant abuse and dependence in people with psychotic disorders, and examines personal, clinical, regional and methodological factors which explain variation in these rates. METHODS: PsychINFO, EMBASE and MEDLINE (1946-2013) were searched systematically for studies reporting on stimulant drug use disorders in representative samples of people with psychotic disorders. Random effects models estimated the pooled rate of a stimulant use disorder, defined to include stimulant abuse and stimulant dependence. Study characteristics associated with heterogeneity in rates of stimulant use disorder were examined by subgroup analyses for categorical variables, by meta-regression for continuous independent variables and by multiple meta-regression. RESULTS: Sixty-four studies provided 68 estimates of lifetime or recent stimulant use disorders in 22,500 people with psychosis. The pooled rate of stimulant use disorder was 8.9% (95% CI 7.4%, 10.5%). Higher rates of stimulant use disorders were reported in studies of affective psychosis, studies from inpatient settings, studies from the USA and Australia, and studies with higher rates of cannabis disorder; in multiple meta-regression analysis these factors explained 68% of between-study variance. Rates of stimulant use disorder were stable over time, and unrelated to age, sex, stage of psychosis, type of stimulant drug or study methodology factors. CONCLUSIONS: Reported rates of stimulant use disorder in people with psychosis are much higher than in the general population but vary widely and are associated with regional, service setting and clinical differences between studies. It is likely that stimulants contribute to the overall burden of psychosis, and that social and environmental factors combine with drug and illness-related factors to influence stimulant use in psychosis.

An analysis of policy levers used to implement mental health reform in Australia 1992-2012.

BACKGROUND: Over the past two decades, mental health reform in Australia has received unprecedented government attention. This study explored how five policy levers (organisation, regulation, community education, finance and payment) were used by the Australian Federal Government to implement mental health reforms. METHODS: Australian Government publications, including the four mental health plans (published in 1992, 1998, 2003 and 2008) were analysed according to policy levers used to drive reform across five priority areas: [1] human rights and community attitudes; [2] responding to community need; [3] service structures; [4] service quality and effectiveness; and [5] resources and service access. RESULTS: Policy levers were applied in varying ways; with two or three levers often concurrently used to implement a single initiative or strategy. For example, changes to service structures were achieved using various combinations of all five levers. Attempts to improve service quality and effectiveness were instead made through a single lever-regulation. The use of some levers changed over time, including a move away from prescriptive, legislative use of regulation, towards a greater focus on monitoring service standards and consumer outcomes. CONCLUSIONS: Patterns in the application of policy levers across the National Mental Health Strategy, as identified in this analysis, represent a novel way of conceptualising the history of mental health reform in Australia. An improved understanding of the strategic targeting and appropriate utilisation of policy levers may assist in the delivery and evaluation of evidence-based mental health reform in the future.

Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010.

BACKGROUND: We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) to estimate the burden of disease attributable to mental and substance use disorders in terms of disability-adjusted life years (DALYs), years of life lost to premature mortality (YLLs), and years lived with disability (YLDs). METHODS: For each of the 20 mental and substance use disorders included in GBD 2010, we systematically reviewed epidemiological data and used a Bayesian meta-regression tool, DisMod-MR, to model prevalence by age, sex, country, region, and year. We obtained disability weights from representative community surveys and an internet-based survey to calculate YLDs. We calculated premature mortality as YLLs from cause of death estimates for 1980-2010 for 20 age groups, both sexes, and 187 countries. We derived DALYs from the sum of YLDs and YLLs. We adjusted burden estimates for comorbidity and present them with 95% uncertainty intervals. FINDINGS: In 2010, mental and substance use disorders accounted for 183·9 million DALYs (95% UI 153·5 million-216·7 million), or 7·4% (6·2-8·6) of all DALYs worldwide. Such disorders accounted for 8·6 million YLLs (6·5 million-12·1 million; 0·5% [0·4-0·7] of all YLLs) and 175·3 million YLDs (144·5 million-207·8 million; 22·9% [18·6-27·2] of all YLDs). Mental and substance use disorders were the leading cause of YLDs worldwide. Depressive disorders accounted for 40·5% (31·7-49·2) of DALYs caused by mental and substance use disorders, with anxiety disorders accounting for 14·6% (11·2-18·4), illicit drug use disorders for 10·9% (8·9-13·2), alcohol use disorders for 9·6% (7·7-11·8), schizophrenia for 7·4% (5·0-9·8), bipolar disorder for 7·0% (4·4-10·3), pervasive developmental disorders for 4·2% (3·2-5·3), childhood behavioural disorders for 3·4% (2·2-4·7), and eating disorders for 1·2% (0·9-1·5). DALYs varied by age and sex, with the highest proportion of total DALYs occurring in people aged 10-29 years. The burden of mental and substance use disorders increased by 37·6% between 1990 and 2010, which for most disorders was driven by population growth and ageing. INTERPRETATION: Despite the apparently small contribution of YLLs--with deaths in people with mental disorders coded to the physical cause of death and suicide coded to the category of injuries under self-harm--our findings show the striking and growing challenge that these disorders pose for health systems in developed and developing regions. In view of the magnitude of their contribution, improvement in population health is only possible if countries make the prevention and treatment of mental and substance use disorders a public health priority. FUNDING: Queensland Department of Health, National Health and Medical Research Council of Australia, National Drug and Alcohol Research Centre-University of New South Wales, Bill & Melinda Gates Foundation, University of Toronto, Technische Universität, Ontario Ministry of Health and Long Term Care, and the US National Institute of Alcohol Abuse and Alcoholism.

Global burden of disease attributable to illicit drug use and dependence: findings from the Global Burden of Disease Study 2010.

BACKGROUND: No systematic attempts have been made to estimate the global and regional prevalence of amphetamine, cannabis, cocaine, and opioid dependence, and quantify their burden. We aimed to assess the prevalence and burden of drug dependence, as measured in years of life lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life years (DALYs). METHODS: We conducted systematic reviews of the epidemiology of drug dependence, and analysed results with Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) Bayesian meta-regression technique (DisMod-MR) to estimate population-level prevalence of dependence and use. GBD 2010 calculated new disability weights by use of representative community surveys and an internet-based survey. We combined estimates of dependence with disability weights to calculate prevalent YLDs, YLLs, and DALYs, and estimated YLDs, YLLs, and DALYs attributable to drug use as a risk factor for other health outcomes. FINDINGS: Illicit drug dependence directly accounted for 20·0 million DALYs (95% UI 15·3-25·4 million) in 2010, accounting for 0·8% (0·6-1·0) of global all-cause DALYs. Worldwide, more people were dependent on opioids and amphetamines than other drugs. Opioid dependence was the largest contributor to the direct burden of DALYs (9·2 million, 95% UI 7·1-11·4). The proportion of all-cause DALYs attributed to drug dependence was 20 times higher in some regions than others, with an increased proportion of burden in countries with the highest incomes. Injecting drug use as a risk factor for HIV accounted for 2·1 million DALYs (95% UI 1·1-3·6 million) and as a risk factor for hepatitis C accounted for 502,000 DALYs (286,000-891,000). Suicide as a risk of amphetamine dependence accounted for 854,000 DALYs (291,000-1,791,000), as a risk of opioid dependence for 671,000 DALYs (329,000-1,730,000), and as a risk of cocaine dependence for 324,000 DALYs (109,000-682,000). Countries with the highest rate of burden (>650 DALYs per 100,000 population) included the USA, UK, Russia, and Australia. INTERPRETATION: Illicit drug use is an important contributor to the global burden of disease. Efficient strategies to reduce disease burden of opioid dependence and injecting drug use, such as delivery of opioid substitution treatment and needle and syringe programmes, are needed to reduce this burden at a population scale. FUNDING: Australian National Health and Medical Research Council, Australian Government Department of Health and Ageing, Bill & Melinda Gates Foundation.

Cannabis and stimulant disorders and readmission 2 years after first-episode psychosis.

BACKGROUND: Few studies have examined the impact of stimulant use on outcome in early psychosis. Ceasing substance use may lead to positive outcomes in psychosis. AIMS: To examine whether baseline cannabis or stimulant disorders and ongoing drug use predict readmission within 2 years of a first psychosis admission. METHOD: Predictors of readmission were examined with Cox regression in 7269 people aged 15-29 years with a first psychosis admission. RESULTS: Baseline cannabis and stimulant disorders did not predict readmission. A stimulant disorder diagnosis prior to index psychosis admission predicted readmission, but a prior cannabis disorder diagnosis did not. Ongoing problem drug use predicted readmission. The lowest rate of readmission occurred in people whose baseline drug problems were discontinued. CONCLUSIONS: Prior admissions with stimulant disorder may be a negative prognostic sign in first-episode psychosis. Drug use diagnoses at baseline may be a good prognostic sign if they are identified and controlled.