ABSTRACT Objective: Identify the prevalence of anxious and depressive symptoms and their correlations with sociodemographic and occupational characteristics in university students. Method: This is census, cross-sectional and analytical study, developed with nursing students of a federal public university in the Northeast of Brazil in the months of September and October 2016. 205 university students of all the periods of the course attended the study. Beck’s inventories for anxiety and depression were applied. Results: Most of the participants were female, single, native of the state capital and living with his parents. The prevalence of depression was 30.2% and of anxiety, 62.9%. Association between the level of depressive symptoms, work, sex and leisure was identified. Conclusion: The prevalence of symptoms of anxiety and depression was quite expressive, lacking, thus, more attention to the promotion of mental health of nursing students.

Overall, it is estimated that one in ten children and young people have a diagnosable mental disorder – the equivalent of three pupils in every classroom across the country. For well over a decade the important role played by schools and colleges in promoting good mental health and wellbeing among children and young people has been a prominent theme of national UK policy.

The Supporting Mental Health in Schools and Colleges, 2016-2017 survey was commissioned by the Department for Education (DfE) in order to understand what schools, colleges and other educational institutions in England currently do to support the mental health and well-being of their pupils, and to explore their experiences of putting this provision into place. The DfE intends for this evidence to provide a basis for future work, including research into effective practice and gaps in provision.

This survey was carried out in the final term of the academic year 2015-16, and in the first two terms of the academic year 2016-17. The survey forms part of a wider, mixed methods project exploring mental health and character education provision in schools and colleges across England.

Further information and publications from the survey can be found at GOV.UK's https://www.gov.uk/government/publications/supporting-mental-health-in-schools-and-colleges" title ="Supporting mental health in schools and colleges">Supporting mental health in schools and colleges webpage.

This data package contains the research survey, deidentified data set, associated SPSS syntax file, and variable naming information for the following research article: Rubin, M., Evans, O., & Wilkinson, R. B. (2016). A longitudinal study of the relations between university students’ subjective social status, social contact with university friends, and mental health and well-being. Journal of Social and Clinical Psychology.If you are interested in analysing the data from this data set, then please contact Mark.Rubin@newcastle.edu.au to discuss the ethical issues.

This database is comprised of 951 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 509 males (54%) and 442 females (46%). Their ages ranged from 12 to 16 years (M = 13.69, SD = 0.72). Seven participants did not report their age. The majority were born in Australia (N = 849, 89%). The next most common countries of birth were China (N = 24, 2.5%), the UK (N = 23, 2.4%), and the USA (N = 9, 0.9%). Data were drawn from students at five Australian independent secondary schools. The data contains item responses for the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. The Social media question asked about frequency of use with the question “How often do you use social media?”. The response options ranged from constantly to once a week or less. Items measuring Fear of Missing Out were included and incorporated the following five questions based on the APS Stress and Wellbeing in Australia Survey (APS, 2015). These were “When I have a good time it is important for me to share the details online; I am afraid that I will miss out on something if I don’t stay connected to my online social networks; I feel worried and uncomfortable when I can’t access my social media accounts; I find it difficult to relax or sleep after spending time on social networking sites; I feel my brain burnout with the constant connectivity of social media. Internal consistency for this measure was α = .81. Self compassion was measured using the 12-item short-form of the Self-Compassion Scale (SCS-SF; Raes et al., 2011). The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels. References: Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4 Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. https://doi.org/10.1002/cpp.702 Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. https://doi.org/10.1016/S0005-7967(98)00034-5

The Adult Psychiatric Morbidity Survey (APMS) series provides data on the prevalence of both treated and untreated psychiatric disorder in the English adult population (aged 16 and over). This survey is the fourth in a series and was conducted by NatCen Social Research, in collaboration with the University of Leicester, for NHS Digital. The previous surveys were conducted in 1993 (16-64 year olds) and 2000 (16-74 year olds) by the Office for National Statistics, which covered England, Scotland and Wales. The 2007 Survey included people aged over 16 and covered England only. The survey used a robust stratified, multi-stage probability sample of households and assesses psychiatric disorder to actual diagnostic criteria for several disorders. The report features chapters on: common mental disorders, mental health treatment and service use, post-traumatic stress disorder, psychotic disorder, autism, personality disorder, attention-deficit/hyperactivity disorder, bipolar disorder, alcohol, drugs, suicidal thoughts, suicide attempts and self-harm, and comorbidity. All the APMS surveys have used largely consistent methods. They have been designed so that the survey samples can be combined. This is particularly useful for examination of low prevalence population groups and disorders. For example, in the APMS 2014 survey report, analyses of psychotic disorder (Chapter 5) and autism (Chapter 6) have been run using the 2007 and 2014 samples combined. Due to the larger sample size, we consider estimates based on the combined sample to be the more robust. Further notes on the Autism chapter can be found with that chapter and in the 'Additional notes on autism' document below. NHS Digital carried out a consultation exercise to obtain feedback from users on the APMS publication and statistics. The consultation will inform the design, content and reporting of any future survey. The consultation closed 30 December 2016, findings will be made available by April 2017. You can access the results of consultation when available in the Related Links below. A correction has been made to this publication in September 2017. This correction applies to all statistics relating to people receiving medication for a mental health condition and more widely to people accessing mental health treatment. This correction increases the proportion of adults (aged 16-74) with a common mental disorder accessing mental health treatment in 2014 from 37 per cent to 39 per cent. Overall the proportion of all people receiving mental health treatment in 2014 increases from 12 per cent to 13 per cent. Logistic regression models used in chapter 3 have not been corrected due to the change not being large enough to change the findings of this analysis. A further correction has been made to this publication in February 2018. This correction applies to statistics for Asian/Asian British men and all adults in Table 10.5 - Harmful and dependent drinking in the past year (observed and age-standardised), by ethnic group and sex. Statistics for the number of respondents with an AUDIT score of 16 or over previously incorrectly included only those with an AUDIT score between 16 and 19. This has now been corrected to include respondents with an AUDIT score of 20 or more. NHS Digital apologies for any inconvenience caused.

Demographic and clinical data on patient encounters with mental health encounters in Duke University Health System between January 1, 2016 and March 31, 2021.

The data has been generated by ethnographic observations, interviews and interactions with migrant workers in two sites in Shanghai in 2017/2018: Songjiang District on the south-western outskirts, and the inner-city Huangpu District, in proximity to some of the city’s most famous tourist attractions, such as the Bund or Nanjing Road. Ethnography, with its focus on everyday experience, can yield significant insights into understanding migrant mental health in contexts where signs of severe mental distress remain largely imperceptible, and more generally, into how stresses and strains are lived through the spaces, times and affective atmospheres of the city. Migrant ethnography can help us reconsider the oft-made connection between everyday stress and mental ill health. In this research, drawing on field evidence in central and peripheral Shanghai, we highlight the importance of attending to the forms of spatial and temporal agency through which migrants actively manage the ways in which the city affects their subjectivity. These everyday subjective practices serve to problematize the very concept of ‘mental health’, enabling us to engage in a critical dialogue with sociological and epidemiological research that assesses migrant mental health states through the lens of the vulnerability or resilience of this social group, often reducing citiness to a series of environmental ‘stressors’.

We have known, since at least the early twentieth century, that there is an association between living in a city and being diagnosed with a mental illness. But questions around the specificity of relationship between urban life and have continued well into the twenty-first century. We still don't know, for example, exactly why mental illness clusters in cities; we don't know how it relates to experiences of urban poverty, deprivation, overcrowding, social exclusion, and racism; and we don't know the precise biological and sociological mechanisms that turn difficult urban lives into diagnosable mental health conditions. What we do know is that migrants into cities bear a disproportionately large share of the burden of urban mental illness; we know that dense living conditions seem to exacerbate the problem; and we know that the general stress, tumult and precarity of urban living can, sometimes, create the basis for the development of clinical problems. If there are unanswered questions around the relationship between mental health and the city, these questions are particularly acute in contemporary China: China has urbanised at an unprecedented rate in the last decade, and has now become a majority urban society. But whereas in nineteenth-century Europe urbanization came from a growth in population, in twenty-first century China the situation is different: most of the growth is from rural migrants coming into the cities. In China, then, the link between urban transformation and mental illness is a critical issue: (1) Development in China is related to migration from the countryside into the cities; (2) Unrecognized and untreated mental disorder is a key factor in casting individuals and families into poverty and social exclusion; (3) Effective development of urban mental health policu requires far greater understanding of the related problems of urban stress, precarious living conditions and mental disorder. This project is an attempt to understand the relationship between migration and mental health in one Chinese mega-city: Shanghai. Given what we know about the relationship between urban mental health and particular patterns of social life (poverty, migration, dense housing, and so on), it starts from the position that this question requires new input from the social sciences. At the heart of the project is an attempt to mix what we know about mental health in contemporary Shanghai with a new kind of close-up, street-level data on what the daily experience of being a migrant on Shanghai is actually life - especially with regard to stress, housing, and access to services. We will then connect these two forms of knowledge to produce a new kind of survey for getting a new sociological deep surveying instrument for mapping migrant mental health in Shanghai. The project, which is split between researchers in the UK and China, asks: (1) How is mental disorder actually patterned in Shanghai, and how is that pattern affected by recent migration? (2) How are immigrants absorbed in Shanghai, and what is daily life actually like in Shanghai's migrant communities? (3) What policies, services, or laws might alleviate mental health among migrants in Shanghai? (4) What can be learned in Shanghai for similar problems in other developing mega-cities (such as Sao Paolo or Lagos). This project should also us to also produce new data on two of the major research-areas that are prioritised under this join UK-China research-scheme: 'Migration and public services,' where we will look at the relationship between the welfare system and migration, and analyse the services that currently help to alleviate this problem, as well as migrants' access to those services; (2) 'Inequalities and everyday life,' where we will develop a close-up, street-level analysis of the lived inequalities of everyday migrant life in Shanghai, and try to understand how urban inequality might contribute to the development of mental health problems?

Objectives: Mental health problems are among the leading causes of health-related disability among children and adolescents worldwide. However, there is still a global challenge in terms of gathering consistent epidemiological information about the issue. The present study was designed to describe various mental health issues and factors associated with negative feelings among adolescents in Greater London.Methods: This is a cross sectional study, using a self-administered questionnaire (Cronbach's alpha = 0.742). A convenience sampling strategy was used to recruit participants who were school/college-attending adolescents, aged 11–19. A minimum sample size of 199 was required (95% confidence interval, 5% margin of error, and 15.3% population proportion). The study was conducted between February and April 2016 in Greater London. Descriptive statistics and inferential statistics including chi square, Spearman correlation, and binary logistic regression were used to identify the key findings. Data analysis was performed using SPSS v21.Results: A total of 526 out of 1,920 surveys were collected across 18 secondary schools and two colleges, giving a response rate of 27.4%. More than half of the adolescents reported to be either neutral (41.4%), sad (7.8%), or very sad (2.8%), whereas 48% reported to be either happy (35%) or very happy (13%). Difficulties in relationships and hectic schedules were among the most stressful situations affecting adolescents' mental health. Discrimination was identified as the main predicting factor with five-fold increase in odds of having negative mental health symptomatology. Other significant risk factors identified were age, gender, smoking, and health comorbidities.Conclusion: Discrimination was identified as the most predictive factor influencing negative symptomatology among the study cohort. The study had several limitations, most notably the use of a non-validated surrogate measure for mental health, in addition to the exclusion of adolescents aged 10–11 years, school/college dropouts and non-school-going adolescents. A similar study on a national scale is highly recommended to determine the real magnitude of the problem, which would be the starting point toward proper tackling of mental health issues and associated complexities among the adolescent population across England.

ABSTRACT The health of the population deprived of liberty has unusual aspects, due to the high prevalence of sexually transmitted diseases, dermatological injuries, and mental disorders aggravated by the overcrowding and precarious conditions in the penitentiary units. The health care offered is of poor quality, based on resolving specific complaints, but with difficulty accessing other health services. Integration between teaching and service is one of the guidelines for medical courses, which have the role of training critical and reflective physicians who are aware of the social needs. It was out of this approach of the university to the prison system that the discipline of Confinement Medicine emerged, in 2011, at the Ribeirão Preto Medical School of the University of São Paulo. The present report describes the process of conception and formation of the discipline and its theoretical-practical structure, and offers a reflection on the learning and its particular characteristics in confinement. This optional discipline has 30 hours and is offered twice a year, with places for forty students per year. Up until 2016, 188 medical students took this discipline. Besides the academic program, the discipline also includes practical activities, carried out in penitentiaries in the region of Ribeirão Preto. The different realities experienced by the undergraduate students in the university and penitentiary scenarios enables them to reflect on the importance of integrating these two worlds that, when in contact, contribute both to the qualification of the medical care provided and to students’ sense of responsibility as citizens, and their role as professionals. The discipline helps strengthen ties between society and marginalized populations, promoting the resocialization of people deprived of liberty. It also prompts reflections about the dimensions of illness, and their influence on the life context of these patients, enabling us to reflect on how the construction of a proper project based on these social realities can guarantee the principles of universality, equity and integrally of care.

Background:Intellectual disability confers increased risk of mental illness; however, a robust prevalence study of the occurrence of mental illness in adults with intellectual disability (ID) has not been conducted in the United States. Present prevalence estimates, based on previous research in the United Kingdom (Cooper et al., 2007; Strømme & Diseth, 2000), Australia (Morgan et al., 2008), and some U.S. studies (Fletcher et al., 2016; Reiss, 1994; Rojahn & Tassé, 1996; Smiley, 2005;), have suggested that mental illness occurs in 30% to 50% of adults with intellectual disability. This rate of comorbidity of psychiatric disorders in persons with ID might be as much as twofold higher than what has been reported in the general population (SAMHSA, 2023; Steel et al., 2014). Co-occurring mental illness is associated with an increased intensity and complexity of support needs compared to adults with ID without comorbid psychiatric disorders (Rojahn et al., 2004; Tassé & Wehmeyer, 2010). A systematic national study to determine more precise prevalence rates of mental disorders among adults with ID is needed to guide federal policy and programs. Study Purpose:The purpose of this research was to estimate prevalence rates of mental disorders among adults with intellectual disability in the US.Sample:We recruited a sample of approximately 500 adults (18+ years old) with intellectual disability (ID) and their caregivers/study partners (approximately 500 dyad pairs or approximately 1000 individuals in total) from across the United States (US). To estimate prevalence of mental illness, we leveraged the National Core Indicators (NCI) project (https://www.nationalcoreindicators.org/) sampling pool from 6 states (Michigan, North Carolina, Ohio, Oregon, Rhode Island, Virginia) that also have a University Center for Excellence in Developmental Disabilities (UCEDD) involved in coordinating the NCI project data collection in their state. We recruited adults with ID and their caregivers/study partners through the NCI sample in these states through convenience sampling. In general, the research sample mean age, sex, race, ethnicity, and ID level proportions were representative of the population of adults with ID surveyed by NCI data (P>.10). Research sample data aligned with US Census data though our percentage of Hispanic/Latino individuals in the study sample was lower than the percentage in the general population. Methods:Primary measures (surveys) were administered via in-person structured research interviews with adults with ID and their caregivers/study partners before 2020. After 2020 primary measures were administered via virtual structured research interviews with adults with ID and their caregivers/study partners. The caregivers/study partners completed select secondary measures online before the research interview. The interview process was broken into multiple steps including an eligibility interview to determine if the AID was qualified to participate in the research based on study criteria. For this purpose, the WASI-2 and ABAS-3 measures were administered to determine AID eligibility. Primary Measures:Ohio State University researchers adapted these two measures for adults with ID in Study 1 of the Can You Hear Me Now? project. (a) The Diagnostic Interview for Adolescents and Adults with Intellectual Disability (DIAAID): Adult with intellectual Disability (AID) and Study Partner (SP) Versions(b) My Health and Wellbeing Survey (MHWBS) (AID)For more details about these measures, please see Related Publications.Secondary Measures:Key:() = The Ohio State University researchers did not produce this measure. They do not claim ownership of this measure. This measure was developed by other researchers and is protected by copyright. We purchased publisher copies and/or the rights to use this measure unless the measure was in the public domain. AID=Measure was administered to adult with intellectual disabilitySP=Measure was administered to caregiver/study partnerAdaptive Behavior Assessment System (Third Edition) (ABAS-3) (SP)The Behavior Problems Inventory for Individuals with ID (BPI-S)* (SP)Adapted Children’s Alexithymia Measure (CAM)* (SP)DIAAID Demographic Survey (SP) DIAAID Timeline of Reference Points (Visual Support for AID) DIAAID

The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Secure Access datasetsSecure Access versions of BCS70 have more restrictive access conditions than versions available under the standard End User Licence (EUL). SN 8547 - 1970 British Cohort Study: Age 46, Sweep 10, 2016-2018: The aim of the 46-year follow-up was to collect key details of the cohort members’ lives including their socio-economic circumstances (e.g. household composition, cohabiting relationships, housing, economic activity, and income) and their health (physical health, mental health, medication, and health behaviours). This survey had a significant biomedical focus, with objective health measurements and assessments being conducted for the first time in the cohort members’ adulthood.The 'bcs_age46_child_died' and 'bcs_age46_unsuccessful_pregnancies' datasetsThis note is to inform researchers that the 'bcs_age46_child_died' and 'bcs_age46_unsuccessful_pregnancies' datasets, which were previously available as safeguarded data under EUL, have been classified as controlled data by CLS and can only be accessed via the UKDS SecureLab, subject to the UKDS Secure Access licence. The aim of this note is to provide practical information and guidance to researchers who have downloaded the BCS70 Age 46 datasets 'bcs_age46_child_died' and 'bcs_age46_unsuccessful_pregnancies' from the UK Data Archive. CLS requires that all EUL holders delete their versions of these datasets. Should they require them, users can apply for access through the new Secure Access study SN 9115. However, where a user has downloaded these dataset and is using them in a current project, they may continue to use the data and any outputs derived from their use until the project is completed. On completion of the project, users are then required to delete the original datasets. Future projects should use the new versions of the data. Any users having concerns about this should contact CLS. Further guidelines on destroying data are provided in the UKDS guidelines.Latest edition informationFor the second edition (July 2023), a new data file including newly derived nutritional intake variables based on the food composition table from the UK Nutrient Databank (UKNDB) has been added to the study. In addition, four data files have been updated (main, employment, relationships and dietary questionnaire) and a new version of the user guide is available. Sensitive survey data for Sweep 10 is now available under restrictive access conditions under SN 9115. The 45-minute core interview covered: relationships, children, parents, place of residence, economic activity, income, qualifications and training, physical and mental health, smoking, drinking, exercise. Additional data collected included:

Cognitive assessments – immediate and delayed word recall, letter cancellation and animal-naming tasksPaper self-completion questionnaire – topics covered include physical health, mental health and well-being, physical activity, and leisure activitiesAnthropometric measurements (height, weight, body-fat, waist/hip circumference)Blood pressure measurementGrip strength assessmentBalance assessmentBlood sample collectionActivity monitorOnline dietary diary

Abstract copyright UK Data Service and data collection copyright owner.

The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.

Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.

BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Polygenic Indices
Polygenic indices are available under Special Licence SN 9439. Derived summary scores have been created that combine the estimated effects of many different genes on a specific trait or characteristic, such as a person's risk of Alzheimer's disease, asthma, substance abuse, or mental health disorders, for example. These polygenic scores can be combined with existing survey data to offer a more nuanced understanding of how cohort members' outcomes may be shaped.

Secure Access datasets
Secure Access versions of BCS70 have more restrictive access conditions than versions available under the standard Safeguarded Licence.

The BCS70 linked Scottish Medical Records (SMR) datasets include data files from the Information Services Division (ISD) part of the NHS National Services Scotland database for those cohort members who provided consent to health data linkage in the Age 42 sweep.

The SMR database contains information about all hospital admissions in Scotland. The following linked HES datasets are available:

• SN 8768: 1970 British Cohort Study: Linked Administrative Data, Prescribing Information System, Scottish Medical Records 2009-2015: Secure Access (PIS)
• SN 8769: 1970 British Cohort Study: Linked Administrative Data, Maternity Attendance, Scottish Medical Records 1984-2016: Secure Access (SMR02)
• SN 8770: 1970 British Cohort Study: Linked Administrative Data, Inpatient Attendance, Scottish Medical Records 1981-2016: Secure Access (SMR01)
• SN 8771 (this study): 1970 British Cohort Study: Linked Administrative Data, Outpatient Attendance, Scottish Medical Records, 1981-2016: Secure Access (SMR00)

Researchers who require access to more than one dataset need to apply for them individually.

Further information about the SMR database can be found on the Information Services Division Scotland SMR Datasets webpage.

Health; operations; medical records; outpatients

The Collaborative Psychiatric Epidemiology Surveys (CPES) were initiated in recognition of the need for contemporary, comprehensive epidemiological data regarding the distributions, correlates and risk factors of mental disorders among the general population with special emphasis on minority groups. The primary objective of the CPES was to collect data about the prevalence of mental disorders, impairments associated with these disorders, and their treatment patterns from representative samples of majority and minority adult populations in the United States. Secondary goals were to obtain information about language use and ethnic disparities, support systems, discrimination and assimilation, in order to examine whether and how closely various mental health disorders are linked to social and cultural issues. To this end, CPES joins together three nationally representative surveys: the NATIONAL COMORBIDITY SURVEY REPLICATION (NCS-R), the NATIONAL SURVEY OF AMERICAN LIFE (NSAL), and the NATIONAL LATINO AND ASIAN AMERICAN STUDY (NLAAS). These surveys collectively provide the first national data with sufficient power to investigate cultural and ethnic influences on mental disorders. In this manner, CPES permits analysts to approach analysis of the combined dataset as though it were a single, nationally representative survey. Each of the CPES surveys has been documented in a comprehensive and flexible manner that promotes cross-survey linking of key data and scientific constructs.

This dataset presents the footprint of the number and rate of emergency department presentations in public hospitals by patient location. Mental health-related emergency department (ED) presentations are defined as presentations to public hospital EDs that have a principal diagnosis of mental and behavioural disorders. However, the definition does not fully capture all potential mental health-related presentations to EDs such as intentional self-harm, as intent can be difficult to identify in an ED environment and can also be difficult to code. The data spans the financial years of 2014-2018 and is aggregated to Statistical Area Level 3 (SA3) geographic areas from the 2016 Australian Statistical Geography Standard (ASGS). State and territory health authorities collect a core set of nationally comparable information on most public hospital ED presentations in their jurisdiction, which is compiled annually into the National Non-Admitted Patient Emergency Department Care Database (NNAPEDCD). The data reported for 2014–15 to 2017–18 is sourced from the NNAPEDCD. Information about mental health-related services provided in EDs prior to 2014–15 was supplied directly to the Australian Institute of Health and Welfare (AIHW) by states and territories. Mental health services in Australia (MHSA) provides a picture of the national response of the health and welfare service system to the mental health care needs of Australians. MHSA is updated progressively throughout each year as data becomes available. The data accompanies the Mental Health Services - In Brief 2018 Web Report. For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Mental health services in Australia Data Tables. Please note: AURIN has spatially enabled the original data.

***************************************************************************************** April 29, 2025: STARRS - Longitudinal Study Wave 4 (LSW4) data released ***************************************************************************************** The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) is an extensive study of mental health risk and resilience among military personnel. Army STARRS consists of eight separate but integrated epidemiologic and neurobiologic studies. Survey data for three of the Army STARRS study components are available via Secure Dissemination or via the ICPSR Virtual Data Enclave: New Soldier Study (NSS); All Army Study (AAS) and Pre-Post Deployment Study (PPDS). Also available are data for the STARRS-Longitudinal Study (STARRS-LS), which are follow-up surveys conducted with Army STARRS participants from AAS, NSS and PPDS studies. Lastly, baseline administrative data from the Army/Department of Defense (DoD) and blood sample flags for Soldiers who had blood drawn as a part of their participation in NSS or PPDS are available. The AAS component of Army STARRS assesses soldiers' psychological and physical health, events encountered during training, combat, and non-combat operations, and life and work experiences across all phases of Army service. The AAS data includes data on soldiers' psychological resilience, mental health, and risk for self-harm. The NSS data are drawn from new soldiers who have just entered the Army. The data contain information on soldier health, personal characteristics, and prior experiences. Results from a series of neurocognitive tests are also included in the NSS data. The PPDS data are drawn from active duty soldiers who were interviewed at four points in time: 3-4 months prior to deployment to Afghanistan; within 1-2 weeks after return from deployment; 1-3 months after return from deployment; and 9-12 months after return from deployment. The PPDS data contain information on soldiers' psychological resilience, mental health, deployment experiences, and risk for self-harm. The STARRS-LS data are from multiple follow-up interviews with individuals who previously participated in the AAS, NSS and PPDS study components of Army STARRS. STARRS-LS data contain follow-up information on soldiers' and veterans' physical and mental health, resilience and risk for self-harm, military and employment status, deployment experience, and personal characteristics as they move through their Army careers and after they leave the Army.

The data was gathered from adult primary care patients in Yogyakarta, Indonesia, between June 2016 and July 2017. The data captures two studies as part of a clinical trial: the pilot study and a substantive study. Data was gathered through self-completed questionnaires as well as in-depth psychiatric interview and clinical ratings.

The National Survey of American Life Adolescent Supplement (NSAL-A), 2001-2004, was designed to estimate the lifetime-to-date and current prevalence, age-of-onset distributions, course, and comorbidity of DSM-IV disorders among African American and Caribbean adolescents in the United States; to identify risk and protective factors for the onset and persistence of these disorders; to describe patterns and correlates of service use for these disorders; and to lay the groundwork for subsequent follow-up studies that can be used to identify early expressions of adult mental disorders. In addition and similar to the NSAL adult dataset (Collaborative Psychiatric Epidemiology Surveys (CPES), 2001-2003 United States), the adolescent dataset contains detailed measures of health; social conditions; stressors; distress; racial identity; subjective, neighborhood conditions; activities and school; media; and social and psychological protective and risk factors. Numerous variables from the adult dataset have been merged into the adolescent dataset, as the NSAL adult and adolescent respondents reside in the same households. Some of these variables apply to the entire household (i.e. region, urbanicity, and family income), while others apply specifically to the NSAL adult respondent living in the adolescent's household (i.e. adult years of education, adult marital status, and adult nativity [foreign-born vs. US born]). The immigration measures were asked of Caribbean black adult respondents only. No comparable measures assess the immigration and generational status of the Caribbean black adolescent respondents. The adult dataset measures are merged into the adolescent dataset to assist in approximating these measures for adolescent respondents. The NSAL adolescent dataset also includes variables for other non-core and experimental disorders. These include tobacco use/nicotine dependence, premenstrual syndrome, minor depression, recurrent brief depression, hypomania, and hypomania sub-threshold. Demographic variables include age, race and ethnicity, ancestry or national origins, height, weight, marital status, income, and education level.