The National Database for Clinical Trials Related to Mental Illness (NDCT) is an extensible informatics platform for relevant data at all levels of biological and behavioral organization (molecules, genes, neural tissue, behavioral, social and environmental interactions) and for all data types (text, numeric, image, time series, etc.) related to clinical trials funded by the National Institute of Mental Health. Sharing data, associated tools, methodologies and results, rather than just summaries or interpretations, accelerates research progress. Community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches for the sharing of de-identified human subject research data. Built on the National Database for Autism Research (NDAR) informatics platform, NDCT provides a comprehensive data sharing platform for NIMH grantees supporting clinical trials.

An online resource for locating mental health treatment facilities and programs supported by the Substance Abuse and Mental Health Services Administration (SAMHSA). The Mental Health Treatment Locator section of the Behavioral Health Treatment Services Locator lists facilities providing mental health services to persons with mental illness. It includes: Public mental health facilities that are funded by their State mental health agency (SMHA) or other State agency or department Mental health treatment facilities administered by the Department of Veterans Affairs, Private for-profit and non-profit mental health facilities that are licensed by the State or accredited by a national accreditation organization. NOTE: The Mental Health Treatment Locator does not include facilities whose primary or only focus is the provision of services to persons with Mental Retardation (MR), Developmental Disability (DD), and Traumatic Brain Injuries (TBI). Facilities that provide treatment exclusively to persons with mental illness who are incarcerated. Mental health professionals in private practice (individual) or in a small group practice not licensed or certified as a mental health clinic or (community) mental health center. SAMHSA endeavors to keep the Locator current. All information in the Locator is updated annually based on facility responses to SAMHSA's National Mental Health Services Survey (N-MHSS). The most recent complete update includes data collected as of April 30, 2010 in the N-MHSS. New facilities are added monthly. Updates to facility names, addresses, telephone numbers and services are made weekly, if facilities inform SAMHSA of changes. For additional advice, you may call the Referral Helpline operated by SAMHSA's Center for Substance Abuse Treatment: 1-800-662-HELP (English & Español) 1-800-487-4889 (TTY)

This dataset contains all data and analysis scripts pertaining to the research conducted for the CyberPsychology23 conference paper: “EHealth4MDD: a database of e-health systems for the prevention and treatment of depressive disorders.” In the scope of the research conducted and described in this paper, we have developed a relational database to systematically describe e-mental health systems for the prevention and treatment of Major Depressive Disorder (MDD). For the purpose of creating this database, literature had to be retrieved from PubMed, Scopus, and Web of Knowledge and filtered for inclusion and exclusion based on title, abstract, and full-paper. Samples of records at each stage were double coded. Once the final body of literature was identified, information from the papers had to be extracted (coded) and entered into the database. Four of the database attributes were selected to be double coded again on samples. Furthermore, a set of scales was developed of which we assessed concurrent validity. We here deliver the version of the database used for the analyses as well as all files and documents required for potential replication.

Database of the nation''s substance abuse and mental health research data providing public use data files, file documentation, and access to restricted-use data files to support a better understanding of this critical area of public health. The goal is to increase the use of the data to most accurately understand and assess substance abuse and mental health problems and the impact of related treatment systems. The data include the U.S. general and special populations, annual series, and designs that produce nationally representative estimates. Some of the data acquired and archived have never before been publicly distributed. Each collection includes survey instruments (when provided), a bibliography of related literature, and related Web site links. All data may be downloaded free of charge in SPSS, SAS, STATA, and ASCII formats and most studies are available for use with the online data analysis system. This system allows users to conduct analyses ranging from cross-tabulation to regression without downloading data or relying on other software. Another feature, Quick Tables, provides the ability to select variables from drop down menus to produce cross-tabulations and graphs that may be customized and cut and pasted into documents. Documentation files, such as codebooks and questionnaires, can be downloaded and viewed online.

An Excel spreadsheet which includes every peer reviewed publication written by occupational therapists in mental health since 2000. It is updated each January to include the previous years publications. Information recorded includes author number, author designation, bibliographic details (i.e. title, journal), categorisation according to doing/being/becoming/belonging, levels of evidence and days between submission and acceptance, and acceptance and publication.

Statistical reports from all medical institutions in Latvia according to their medical activity (ambulatory and inpatient work, medical staff, radiology, dentistry, abortions, medical tourism, emergency medical assistance, etc.)

ObjectivesThe focus of this review was to systematically review and meta-analyse the prevalence of ACEs among university students in the UK.MethodThe systematic searching of six electronic databases (conducted February 2024) identified ten relevant articles (peer-reviewed articles of a quantitative nature that included ACE prevalence). PROSPERO reference: CRD42022364799.ResultsPooled prevalence for number of ACEs endured was 55.4% (95% CI: 32.4% - 78.4%; I2 > 99.5%) for one or more, and 31.6% (7.5% - 55.6%; I2 > 99.5%) for three or more. Pooled prevalence was: 15.9% (7.0% - 24.7%; I2 > 94.5%) for physical abuse; 27.0% (18.1% - 35.9%; I2 > 94.5%) for emotional abuse; 12.1% (5.2% - 19.0%; I2 > 94.5%) for sexual abuse; 8.4% (1.7% - 15.1%; I2 > 95.4%) for physical neglect, and 30.0% (21.5% - 38.5%; I2 > 95.4%) for emotional neglect. Pooled prevalence for household dysfunction categories were: 34.4% (22.8% - 46.0%) for parental separation; 18.4% (10.1% - 26.8%) for domestic violence; 35.2% (23.6% - 46.8%) for mental health difficulties; 21.4% (12.9% - 29.9%) for substance use; and 5.7% (2.3% - 9.1%) for incarceration (I2 > 88.8% for all household dysfunction items). Significant heterogeneity was observed between studies for most categories of adversity, and it was not possible to explain/reduce this variance by removing small numbers of influential/discrepant studies. Further analyses suggested potential influences of measurement tool used, country of data collection, and age and sex of participants.ConclusionResults demonstrate considerable, largely unaccounted-for, heterogeneity in estimates of the prevalence of ACEs, impeding confidence in any summary statistics. Conclusions must be tentative due to analyses being underpowered given small numbers of papers, as well as potential confounds, meaning results may not be truly representative. However, results do suggest high prevalence rates which warrant further investigation, with appropriate support offered to students.

In this project, we aimed to increase what is known about the negative effects of maternal depression and anxiety disorders (MDAD) on the mental health outcomes of children. Mental health is a topical area of research that is receiving increasing attention in the media and is one of five ESRC strategic priorities for investment. The main aim of the project was to help develop an understanding of how mental depression and anxiety disorders are transmitted from one generation to the next and ultimately help to design interventions better able to reduce the consequences of maternal mental health for children. We have used data from QResearch, a large consolidated database derived from anonymized health records from general practices in England matched with hospital administrative data, the Hospital Episode Statistics (HES). Further information is available under Related Resources.

Problems relating to Maternal Depression and Anxiety Disorders (MDAD) are common and are known to affect child health and development. In the UK, the cost of perinatal mental health problems has been estimated at £8.1 billion for each birth cohort of children, and 72 percent of this cost is related to the direct impact on the children.

The overarching aim of our proposed research is to examine the effect of MDAD on child health outcomes, with a special focus on the role that MDAD plays in the development of child depression and anxiety disorders (CDAD) in adolescence. In particular, this research will provide robust empirical evidence to understand how depression and anxiety disorders are transmitted from one generation to the next and to help design interventions aimed at reducing the negative consequences of poor maternal mental health for children.

To achieve this aim, we will address the following research questions:

1) Are the negative effects of MDAD on children exclusively explained by genetic transmission and family background characteristics? Or are these negative effects also explained by changes in the child's home environment? If the transmission of mental and anxiety disorders is explained exclusively by genetic traits and family background characteristics, then interventions targeted at reducing the negative effect of MDAD on maternal behaviour, e.g. through cognitive behavioural therapy, would be ineffective. On the contrary, evidence on significant effects of MDAD after controlling for genetic and family background characteristics would suggest that MDAD can lead to changes in the child home environment, e.g. changes in maternal behaviour, harsher parenting style and lower time investments in the child, with negative consequences on children.

2) Do school policies and health practices have a role in attenuating the negative effect of maternal depression on children? We will answer this research question by focusing on whether starting school earlier harms or protects children who are exposed to MDAD, and on whether an early diagnosis of maternal depression can attenuate the negative effects suffered by children.

We will develop and use state-of-the-art estimation methods in combination with a novel administrative dataset covering general practices and hospitals created by merging two population-based health databases from England - namely QResearch and Hospital Episode Statistics. Using this merged database, we will create a longitudinal household dataset that will allow us to study the mental health of mothers and their children at different stages of the children's lives up to adolescence.

We are a multi-disciplinary team from the Universities of Oxford and York, consisting of experts in applied econometric methods, child and maternal mental health, psychology, general practice, and on the data that we plan to utilise.

We will translate our research findings into advice for policy-makers to help them design new interventions aimed at achieving better outcomes for patients suffering from maternal mental health issues and their children. Our research will also have an impact on health practitioners, psychologists, academics and charities working with mothers and children. We will produce papers aimed at academics as well as non-technical outputs to engage with policy-makers and a non-academic audience. Furthermore, by sharing and explaining our data and estimation methods to academics, we will build capacity for further research based on large health datasets.

The final central element of the project will be to build the capacity of early career researchers to undertake and lead large interdisciplinary projects.

The Estonian Drug Treatment Database is a state register which is kept on the people who have started drug treatment. The Drug Treatment Database started its work on January 1, 2008.

Collection and processing of data on these people is necessary for getting an overview on occurrence of mental and behavioural disorders related to drug use, as well as for organising of relevant health services and planning of drug abuse preventive actions. Health care institutions holding a psychiatry authorization in Estonia present data to the database if they are turned to by a patient who is diagnosed with a mental and behavioural disorder due to drug use.

On the basis of the database's data, an annual overview is compiled, giving information about drug addicts who have turned to drug treatment in the previous calendar year, about the health service provided, the patients' socio-economic background, drug use and the related risk behaviour.

The data on the Drug Treatment Database are also submitted to the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) and United Nations Office on Drugs and Crime (UNODC).

The scores of those health problems belonging to each factor are highlighted in bold.NL: The Netherlands; SP: Spain.*KMO: 0.69.*Percentage of cumulative variance: 19.02%.

The data includes information on procedures, diagnosis (coded according to ICD-10), length of stay, department and selected sociodemographic characteristics such as age, gender and place of residence.

The aim of the Database Minimal Psychiatric Data (MPG) is to support the health policy to be pursued with regard to: (1) determining the needs for psychiatric facilities; (2) the definition of the qualitative and quantitative accreditation standards for these facilities; (3) organizing the financing of these facilities and monitoring the proper use of public funds; (4) developing policies based on epidemiological data.

NL: The Netherlands; SP: Spain; EDC: Expanded Diagnostic Cluster.

The baseline NCS, fielded from the fall of 1990 to the spring of 1992, was the first nationally representative mental health survey in the U.S. to use a fully structured research diagnostic interview to assess the prevalences and correlates of DSM-III-R disorders. The baseline NCS respondents were re-interviewed in 2001-02 (NCS-2) to study patterns and predictors of the course of mental and substance use disorders and to evaluate the effects of primary mental disorders in predicting the onset and course of secondary substance disorders. In conjunction with this, an NCS Replication survey (NCS-R) was carried out in a new national sample of 10,000 respondents. The goals of the NCS-R are to study trends in a wide range of variables assessed in the baseline NCS and to obtain more information about a number of topics either not covered in the baseline NCS or covered in less depth than we currently desire. A survey of 10,000 adolescents (NCS-A) was carried out in parallel with the NCS-R and NCS-2 surveys. The goal of NCS-A is to produce nationally representative data on the prevalences and correlates of mental disorders among youth. The NCS-R and NCS-A, finally, are being replicated in a number of countries around the world. Centralized cross-national analysis of these surveys is being carried out by the NCS data analysis team under the auspices of the World Health Organization (WHO) World Mental Health Survey Initiative. In order to provide an easily accessible database which can be updated and checked on a regular basis, we have created a public use file system containing all the documents from the NCS and NCS-R programs. These file systems can be accessed through the Internet and either downloaded onto a disk or printed. We will update the system on a regular basis to add newly completed paper abstracts and other documents. In addition, the NCS and NCS-R data can be accessed through ICPSR (Inter-university Consortium for Political and Social Research). Any updates to the data to correct coding or classification errors will be made available along with written documentation of the changes in ICPSR''s quarterly newsletter.

Publicly funded child and youth mental health services across the province including:

• child and youth mental health agencies
• child and youth mental health services offered through community agencies, including:
  • individual counselling
  • family counselling
  • group counselling
  • grief and loss counselling
  • anger management programs
  • suicide counselling
  • in person crisis intervention programs

The following information is provided for each service:

• name
• location
• hours of operation
• contact information
• description of program
• service area
• eligibility
• application process
• accessibility
• languages offered
• fee structure if applicable
• documents required

Location of mental health counseling in Los Angeles CountyThis dataset is maintained through the County of Los Angeles Location Management System. The Location Management System is used by the County of Los Angeles GIS Program to maintain a single, comprehensive geographic database of locations countywide. For more information on the Location Management System, visithttp://egis3.lacounty.gov/lms/.

Citations from Database Searches for "Mental Illness and Marketing: A 50-Year Scoping Review and Future Research Framework"

United States Employment: NF: sa: EH: Outpatient Care Centers ex Mental Health data was reported at 688.600 Person th in May 2018. This records an increase from the previous number of 686.000 Person th for Apr 2018. United States Employment: NF: sa: EH: Outpatient Care Centers ex Mental Health data is updated monthly, averaging 337.500 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 688.600 Person th in May 2018 and a record low of 190.200 Person th in Jan 1990. United States Employment: NF: sa: EH: Outpatient Care Centers ex Mental Health data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G026: Current Employment Statistics Survey: Employment: Non Farm: sa.

This dataset contains data from the Mental Health System of Gipuzkoa, which are described in the manuscript: “Garcia-Alonso, CR., Almeda, N., Salinas-Pérez, JA., Gutiérrez-Colosía, MR., Iruin-Sanz, A., & Salvador-Carulla., L. (2021). Use of a decision support system for benchmarking analysis and organizational improvement of regional mental health care: The case of Gipuzkoa (Basque Country, Spain)”. This manuscript has been submitted to Plos One journal.

This research focused on developing an analytical process for assessing the performance of the Mental health (MH) system of Gipuzkoa and identifying benchmark and target-for-improvement catchment areas. For doing so a decision support system that integrated data envelopment analysis, Monte Carlo simulation and artificial intelligence was used. The units of analysis, which are considered the decision-making units, were the 13 catchment areas defined by a reference MH centre. The following indicators were assessed: relative technical efficiency, stability and entropy to guide organizational interventions.

Main results of the analyses pointed out that the MH system of Gipuzkoa showed high efficiency scores in each main type of care (inpatient, day and outpatient), but it can be considered unstable (small changes can have relevant impacts on MH provision and performance). With regards to performance improvement, it is recommended to reduce admissions and readmissions for inpatient care, increase workforce capacity and utilization of day care services and increase the availability of outpatient care services.

Methods The Mental Health Network of Gipuzkoa manages its community and rehabilitation MH services (774,700 residents). These services include outpatient and core health day care facilities closely related to both hospital services (inpatient) and the social care network for severe cases. The Mental Health Network of Gipuzkoa is divided into 13 catchment areas, all of which have a mental health centre, considered as a reference, with a distinct orientation to outpatient care (some of them also include health day care facilities). This paper has been submitted to Plos One journal.

Each catchment area was described by 25 variables: service availability, placement capacity and workforce capacity. Most variable values were expressed in rates per 100,000 inhabitants (adults, over 18 years old). Utilization and performance variables were selected to collect information about service use, treated prevalence and incidence. Hospital discharges and readmissions were obtained from the 2015 MH utilization database (Health care Dashboard, Mental Health Network of Gipuzkoa). The structural variables (resource availability) were considered the input set, and utilization and performance variables (outcome proxies) were considered the output set.

The inputs for the inpatient acute hospital care scenario were the number of available services (rate per 100,000 inhabitants), number of beds (rate), number of psychiatrists (rate), number of psychologists and nurses (rate) and total number of professionals (rate), and the outputs were discharges (number of users), readmissions (number of users) and average length of stay (days). For the acute and non-acute core health day care scenario, the inputs were the number of available services (rate), number of psychiatrists (rate), number of psychologists and nurses (rate), total number of professionals (rate) and placement capacity (rate), and the outputs were the utilization of acute core health day care health services (number of places) and utilization of non-acute day care core health services (number of places). Finally, for the non-acute outpatient care scenario, the inputs were the number of available services (rate), number of psychiatrists (rate), number of psychologists (rate), number of nurses (rate) and total number of professionals (rate), and the outputs were the incidence (number of users), prevalence (number of users) and contacts (number of users).

This table shows the number of persons treated in specialized mental health care (GGZ), by mental disorder for which care was provided in the year under review. It only concerns care financed in the form of DBCs (Diagnosis Treatment Combinations). This concerns ambulatory care and care with a stay of up to one year, for persons aged 18 or older. The table shows persons for whom the diagnosis to be selected was the main (primary) diagnosis, as well as persons for whom this diagnosis was registered as a primary or secondary diagnosis. For example: the table counts both the number of people for whom a depressive disorder was the main diagnosis to be treated, and also people for whom a depressive disorder was an additional (secondary) diagnosis that was registered because it influenced the treatment. Data is presented by age, gender and income groups. It can also be seen whether a stay has taken place (one or more overnight stays in a mental health institution). The last few years are based on a less complete database and are therefore less reliable. Data available from: 2015 Status of the figures: The figures from 2015 to 2019 are final. 2020 and 2021 are provisional. Changes as of February 27, 2023: - 2019 has been made final. - Provisional figures for 2020 and 2021 have been added. When will new numbers come out? The DBC system in mental health care has been abolished as of 1 January 2022. The figures for 2020 and 2021 will be finalized at the end of 2023. After this, the table will be stopped.