In the United States, the prevalence of mental illness in the past year is more common among females than males and more common among the young than the old. As of 2024, some 26.7 percent of females reported some type of mental illness in the past year, compared to 20 percent of males. Common forms of mental illness include depression, anxiety disorders, and mood disorders. Depression Depression is one of the most common mental illnesses in the United States. Depression is defined by prolonged feelings of sadness, hopelessness, and despair leading to a loss of interest in activities once enjoyed, a loss of energy, trouble sleeping, and thoughts of death or suicide. It is estimated that around five percent of the U.S. population suffers from depression. Depression is more common among women with around six percent of women suffering from depression compared to four percent of men. Mental illness and substance abuse Data has shown that those who suffer from mental illness are more likely to suffer from substance abuse than those without mental illness. Those with mental illness are more likely to use illicit drugs such as heroin and cocaine, and to abuse prescription drugs than those without mental illness. As of 2023, around 7.9 percent of adults in the United States suffered from co-occuring mental illness and substance use disorder.

Global Mental Health Disorders

Prevalence of Common Mental Health Conditions, 2005-2017

By Amit [source]

About this dataset

This dataset contains valuable information about the prevalence of mental health disorders including schizophrenia, bipolar disorder, eating disorders, anxiety disorders, drug use disorders, depression, and alcohol use disorders from various countries across the globe. Mental health is a critical and complex issue which touches us all and this dataset allows a deeper dive into the quantitative understanding of its prevalence and geographical distribution. With this data at hand one can gain insight on questions such as: which countries have rates of mental illness that are higher or lower than average? Which regions are disproportionately dealing with certain types of mental health disruptions? Who is struggling with particular types of illnesses? This data provides answers to those inquiries as well as helping us gain a better understanding of how we can take action towards increasing global awareness, prevention efforts, and access to vital resources that help individuals become healed and empowered

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides information on the prevalence of mental health disorders globally, with data collected from various countries in a given year. It includes statistics on several types of mental health disorders, such as schizophrenia, bipolar disorder, eating disorders, anxiety disorders, drug use disorders and depression.

Using this dataset can provide useful insights into the prevalence of mental health conditions worldwide. This could be used to better understand how different countries are affected by mental health issues and to identify areas that may need more help or attention. The data is broken down by country or region and year to allow for a better understanding of trends over time.

To use this dataset effectively for research or data analysis purposes it is important to first familiarize yourself with the columns available in the dataset: Entity (country/region), Code (country code), Year (year in which the data was collected), Schizophrenia (%) , Bipolar Disorder (%) , Eating Disorders (%) , Anxiety Disorders (%) , Drug Use Disorders (%) , Depression (%) and Alcohol Use Disorders (%). Each column represents a specific type of mental health disorder and provides information on its prevalence rate in each country/region during that calendar year.

Once you have an understanding of these columns you can begin analyzing the data to gain further insights into global trends related to these mental health conditions. You might perform descriptive analyses such as finding average percentages across different groups (e.g., genders) or time periods, as well as performing inferential analyses like assessing relationships between different variables within your data set (e.g., correlation). Additionally you could create visualizations such as charts, maps or other graphics that help make sense out of large amounts of statistical information easily accessible to a wider audience

Research Ideas

• Creating age-group specific visualizations and infographics that compare the prevalence of mental health disorders in different countries or regions to better understand how the issue of depression or anxiety intersects with factors such as gender, culture, or socioeconomic status.
• Creating a global map visualization that shows the prevalence of different mental health disorders in different countries/regions to demonstrate disparities between places and provide a way for policy makers to better target areas most affected by these issues.
• Developing data visualizations exploring relationships between demographic variables (e.g., gender, age) and prevalence of mental health disorder types such as depression or anxiety disorders in order to gain insight into possible correlations between them

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: Mental health Depression disorder Data.csv | Column name | Description | |:------------------------------|:--------------------------------------------------------------------------------------| | Entity | The name of the country or region. (String) | | Code ...

Mental Illness Prevalence Across the US

Substate Level Estimates

By Substance Abuse and Mental Health Services Organization [source]

About this dataset

This dataset contains estimates of serious mental illness in the US by state and substate region from 2012-2014. This data helps to understand better the mental health disparities that exist between states and different regions within states. By looking at this data, researchers can identify the parts of the country with particularly high or low rates of serious mental illness, which can help prioritize resources for affected areas.

The dataset includes estimates along with 95% confidence intervals based on a survey-weighted hierarchical Bayes estimation approach and are generated by Markov Chain Monte Carlo techniques. Columns labeled Map Group can be used to distinguish substate regions included in corresponding maps as well as numerical order for sorting original sort order. For definitions in Substate Region, refer to the National Survey on Drug Use and Health's Substate Region Definitions found here: https://www.samhsa.gov/data/sites/default/files/NSDUHsubstateRegionDefs2014/NSDUHsubstateRegionDefs2014.pdf

This reliable information is provided by SAMHSA, Center for Behavioral Health Statistics and Quality through their National Survey on Drug Use and Health from 2012-2014; helping us gain insights into America’s overall mental health picture – revealing more about where help is needed most urgently so that we can take steps towards a healthier future for all Americans!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

Welcome to this dataset! This dataset contains estimates of Serious Mental Illnesses in the United States by state and substate region from 2012 to 2014. It is designed for researchers, analysts, and data scientists looking for information about the prevalence of Serious Mental Illnesses across the US.

Research Ideas

• Performing a trend analysis to identify changes in the estimates of serious mental illnesses over time and across different geographic regions.
• Exploring disparities in serious mental illnesses among certain minority groups or deprived socio-economic subgroups by comparing estimates at the substate level.
• Developing targeted public health strategies and interventions for states with higher than average rates of serious mental illness prevalence

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: 2012-2014_Substate_SAE_Table_24.csv | Column name | Description | |:--------------------|:----------------------------------------------------------------------------------------------------------------------------------------------| | Order | A numerical order that can be used to sort the data back to its original order. (Numeric) | | State | The US state associated with the data. (String) | | Substate Region | The substate region associated with the data. (String) | | 95% CI (Lower) | The lower bound of the 95 percent confidence interval for the estimated number of people with serious mental illness in the region. (Numeric) | | 95% CI (Upper) | The upper bound of the 95 percent confidence interval for the estimated number of people with serious mental illness in the region. (Numeric) | | Map Group | A numerical value which can distinguish between different substate regions included in the maps. (Numeric) |

...

In 2021, it was estimated that over **** percent of the total global population suffered from an anxiety disorder. This statistic depicts the percentage of the global population with select mental health disorders in 2021.

In 2014, 29% of Black women had experienced a common mental disorder in the week before being surveyed, a higher rate than for White women.

A survey of 15 countries worldwide, fielded in May 2022, found that those in Australia and China were most likely to report currently experiencing mental health conditions such as depression and anxiety. This statistic shows the percentage of adults in select countries worldwide currently experiencing mental health conditions (e.g. depression, anxiety).

Global Trends in Mental Health Disorder

From Schizophrenia to Depression

By Amit [source]

About this dataset

This dataset contains informative data from countries across the globe about the prevalence of mental health disorders including schizophrenia, bipolar disorder, eating disorders, anxiety disorders, drug use disorders, depression and alcohol use disorders. By providing this data in an easy to visualise format you can gain an insight into how these issues are impacting lives; allowing for a deeper understanding of these conditions and the implications. Through this reflection you may be able to answer some important questions: - What are the types of mental health disorder that people around the world suffer? - How many people in each country suffer mental health problems? - Are men or women more likely to have depression? - Is depression linked with suicide and what is the percentage rate? - In which age groups is depression more common?
From exploring patterns between prevalence rates through in-depth data visualisation you’ll be able to further understand these complex issues. The knowledge gained from this dataset can help bring valuable decision making skills such as research grants, policy making or preventative intervention plans across various countries. So if you wish to create meaningful data viz then start with this global prevalence of mental health disorder’s together with accompanying videos for extra context - Deepen your understanding about Mental Health Disorders today!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

Using this dataset is quite straightforward. Each row of the table contains information about a certain country or region for a certain year. The following columns are provided: Entity (the country or region name), Code (the code for the country or region), Year (the year the data was collected) Schizophrenia (% - percentage of people with schizophrenia), Bipolar Disorder (%) - percentage of people with bipolar disorder) Eating Disorders (%) - Percentage of individuals with disordered eating patterns Anxiety Disorders (%) - Percentage of individuals with anxiety Drug Use Disorders (%) - Percentage figures for those struggling with substance abuse Depression (%) – Percentages relating to those struggling with depressive illness Alcohol Use Disorders (%) – Percentages relating to those battling alcoholism

Using this dataset requires no special skills; however it is best suited for those comfortable navigating spreadsheets and tables as well as analyzing numerical information quickly and accurately. Many software suites like excel are useful here but simple internet searches will reveal free alternatives if your preference is web-based solutions!

By piecing together these different columns’ values we can get an idea if prevalence rates across different types of mental illnesses increase or decrease over time. For example we could compare depression levels between 2015 and 2018 by creating two separate sets containing information filtered just within our parameters respectively only reading records from 2015 then 2018). From here we can see whether numbers changed very much or stayed stagnant supefying any sort of patterns that could exist

Research Ideas

• Visualizing the prevalence of mental health disorders - Create a data visualization that compares and contrasts the prevalence of depression, anxiety, bipolar disorder, schizophrenia, eating disorders, alcohol use disorder and drug use disorder across different countries. This could provide insight into global differences in mental health and potential causes of those differences.

• Mapping depression rates - Create an interactive map that shows both regional and national variations in depression rates within a specific country or region. This would allow people to easily identify areas with higher or lower than average prevalence of depression which could help inform decision-makers when it comes to policy-making related to mental healthcare services provisioning.

• Developing predictive models for mental health - Use the data from this dataset as part of a larger machine learning project to build predictive models for mental health across countries or regions based on various factors such as demographics, economic indicators etc., This can be helpful for researchers working on understanding populations’ susceptibility towards developing certain disorders so as to craft appropriate preventive strategies accordingly

Acknowledgements

If you use this dataset in your research, please credit the original aut...

This report presents findings from the third (wave 3) in a series of follow up reports to the 2017 Mental Health of Children and Young People (MHCYP) survey, conducted in 2022. The sample includes 2,866 of the children and young people who took part in the MHCYP 2017 survey. The mental health of children and young people aged 7 to 24 years living in England in 2022 is examined, as well as their household circumstances, and their experiences of education, employment and services and of life in their families and communities. Comparisons are made with 2017, 2020 (wave 1) and 2021 (wave 2), where possible, to monitor changes over time.

These are the detailed tables pertaining to adult mental health from the 2010 National Survey on Drug Use and Health (NSDUH). These detailed tables present totals and prevalence estimates of past year any mental illness (AMI), serious mental illness (SMI), suicidal thoughts and behavior, major depressive episode (MDE), treatment for depression (among adults with MDE), mental health service utilization, and measuers related to the co-occurrence of mental disorders with substance use or with substance use disorders. Results are provided for age group, gender, race/ethnicity, education level, employment status, poverty level, geographic area, insurance status. Comparisons are made between 2011 and 2002 to 2010.

These detailed tables present totals and prevalence estimates of mental health related issues among adults aged 18 or older from the 2012 National Survey on Drug Use and Health (NSDUH). Tables with data on adults include measures on any mental illness (AMI), serious mental illness (SMI), moderate mental illness, low (mild) mental illness, mental health service utilization (i.e., mental health treatment or counseling), suicidal thoughts and behaviors, major depressive episode (MDE), treatment for depression (among adults with MDE), and serious psychological distress (SPD), and co-occurrence of mental disorders with substance use or with substance use disorders. Results are provided by age group, gender, race/ethnicity, education level, employment status, county type, poverty level, insurance status, overal health, and geographic area. Comparisons are made between 2012 and 2011.

This publication contains the official statistics about uses of the Mental Health Act(1) ('the Act') in England during 2018-19. Under the Act, people with a mental disorder may be formally detained in hospital (or 'sectioned') in the interests of their own health or safety, or for the protection of other people. They can also be treated in the community but subject to recall to hospital for assessment and/or treatment under a Community Treatment Order (CTO). In 2016-17, the way we source and produce these statistics changed. Previously these statistics were produced from the KP90 aggregate data collection. They are now primarily produced from the Mental Health Services Data Set (MHSDS). The MHSDS provides a much richer data source for these statistics, allowing for new insights into uses of the Act. However, some providers that make use of the Act are not yet submitting data to the MHSDS, or submitting incomplete data. Improvements in data quality have been made over the past year. NHS Digital is working with partners to ensure that all providers are submitting complete data and this publication includes guidance on interpreting these statistics. Footnotes (1) The Mental Health Act 1983 as amended by the Mental Health Act 2007 and other legislation.

The Mental Health Depression Disorder dataset provides comprehensive information on the prevalence of various mental health disorders across different countries over multiple years. This dataset includes data on schizophrenia, bipolar disorder, eating disorders, anxiety disorders, drug use disorders, depression, and alcohol use disorders. It is a valuable resource for analyzing trends in mental health disorders and understanding the global burden of mental illness.

**Usage: **

This dataset can be used for analyzing trends in mental health disorders, comparing the prevalence of different disorders across countries and years, and conducting epidemiological research. It is valuable for researchers, public health officials, and mental health professionals aiming to understand and address the global burden of mental illness.

**Acknowledgements: **

We acknowledge the contributions of international health organizations and research institutions that made this data publicly available for research and analysis.

Introduction

Mental Health Statistics: Mental health is vital to well-being, influencing how people think, feel, and act. In recent years, there has been increasing recognition of its significance as societies become more aware of the far-reaching effects mental health disorders have on individuals, families, and communities.

Mental health statistics provide crucial insights into these conditions' prevalence, causes, and consequences, enabling policymakers, healthcare providers, and researchers to understand emerging trends better. This data supports effective resource allocation and the development of targeted interventions to tackle mental health issues.

We can pinpoint high-risk groups and regions that require additional support by examining these trends. Additionally, these insights help inform public health initiatives focused on reducing stigma and promoting mental health awareness. Accurate statistics are essential for shaping evidence-based policies emphasizing prevention, early intervention, and improving access to mental health services. As mental health continues to gain attention, continuous data collection and research will be key to addressing the global mental health crisis effectively.

This dataset was originally collected for a data science and machine learning project that aimed at investigating the potential correlation between the amount of time an individual spends on social media and the impact it has on their mental health.

The project involves conducting a survey to collect data, organizing the data, and using machine learning techniques to create a predictive model that can determine whether a person should seek professional help based on their answers to the survey questions.

This project was completed as part of a Statistics course at a university, and the team is currently in the process of writing a report and completing a paper that summarizes and discusses the findings in relation to other research on the topic.

The following is the Google Colab link to the project, done on Jupyter Notebook -

https://colab.research.google.com/drive/1p7P6lL1QUw1TtyUD1odNR4M6TVJK7IYN

The following is the GitHub Repository of the project -

https://github.com/daerkns/social-media-and-mental-health

Libraries used for the Project -

Pandas
Numpy
Matplotlib
Seaborn
Sci-kit Learn

These detailed tables present totals and prevalence estimates of mental health related issues among adolescents aged 12 to 17 from the 2012 National Survey on Drug Use and Health (NSDUH). Tables with data on ayouths include measures on mental health service utilization, MDE, treatment for depression (among youths with MDE), and co-occurrence of mental disorders with substance use or with substance use disorders. Results are provided by age group, gender, race/ethnicity, education level, county type, poverty level, insurance status, overal health, and geographic area. Comparisons are made between 2012 and 2011.

The measure shows the percentage of adults receiving secondary mental health services living independently at the time of their most recent assessment, formal review or other multidisciplinary care planning meeting. Adults 'in contact with secondary mental health services' is defined as those aged 18 to 69 who are receiving secondary mental health services and who are on the Care Programme Approach (CPA). 'Living independently, with or without support' refers to accommodation arrangements where the occupier has security of tenure or appropriate stability of residence in their usual accommodation in the medium-to-long-term, or is part of a household whose head holds such security of tenure/residence. These accommodation arrangements are recorded as settled accommodation in the Mental Health Minimum Data Set. The calculation of the measure was changed in 2013-14. Previously, outcome scores were calculated from annual totals from the MHMDS, whereas now the outcome is calculated each month and the ASCOF measure for the year is derived as an average of these monthly scores. In 2017-18 The Mental Health Services Dataset (MHSDS) methodology has also been updated so that only whole numbers are published. Only covers people receiving partly or wholly supported care from their Local Authority and not wholly private, self-funded care. Data Source: Mental Health Minimum Data Set'. Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Any Mental Illness

Any Mental Illness in the Past Year among Adults Aged, by State and Region

By Substance Abuse and Mental Health Services Organization [source]

About this dataset

This dataset provides a comprehensive overview of mental illness in the United States between 2012 and 2014, broken down by state and substate region. The estimates come from a survey-weighted hierarchical Bayes estimation approach, generated using Markov Chain Monte Carlo techniques. For the Total U.S. row, design-based (direct) estimates and corresponding 95 percent confidence intervals are provided as well. Along with this, there is an Order column that can be used to sort the data into its original order and a Map Group column which serves to distinguish different substate regions included in the maps from one another. By analyzing this extensive collection of information gathered from SAMHSA's National Survey on Drug Use and Health for the years 2012 - 2014, researchers can gain valuable insights into better understanding mental illness on both macro-level (across states) and micro-level scales (such as individual counties or cities)

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides estimates of mental illness in the United States from 2012-2014, broken down by state and substate region, along with 95% confidence intervals. In order to use this dataset effectively, it is important to first understand the columns included in this dataset.

The “Order” column lists a numerical order of the data which can be used to sort the data in its original sort order. The “Map Group” column is a numerical group that can be used to distinguish substate regions included in the maps from other substate regions. A “1” represents the national estimate, a “2” represents census region estimates, a “3” represents state-level estimates while a “4” and “5” respectively represent substate/aggregate region-level estimates included and not included in the maps.

The remaining columns—State, Substate Region, 95% CI (Lower),and 95% CI (Upper)—are self explanatory; listing each state followed by its corresponding estimated mental illness percentage for 2012-2014 accompanied by its lower and upper bounds for 95 % confidence interval percentiles respectively.

By using these variables together within this dataset as well as combining them with outside research/knowledge on US states or areas of interest within different US states can provide valuable understanding on mental health trends throughout different areas of different U.S states during 2012 - 2014 period of time when gathered information was collected.

Research Ideas

• Analyzing regional mental health trends over time by examining the data across multiple years in order to compare and contrast the differences of mental illness prevalence among states and substate regions.
• Creating visualizations such as maps or charts to illustrate the variation in mental illness prevalence between states and within each state by substate region, utilizing both higher-level (state-wide) and lower-level (substate/aggregate region) estimates.
• Examining relationships between areas with higher rates of mental illness to indicators such as poverty, education level, access to medical care, etc., which may help identify potential underlying causes of differences in prevalence

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: 2012-2014_Substate_SAE_Table_25.csv | Column name | Description | |:--------------------|:-------------------------------------------------------------------------------------------------------------------| | Order | A numerical value used to sort the data into its original order...

A 2023 survey conducted in the United States found that approximately 87 percent of young individuals had suffered from some mental health problem on a regular basis. The leading mental health challenge experienced by most youth respondents was anxiety, with 58 percent. This statistic illustrates the percentage of U.S. youth who experienced mental health challenges regularly as of 2023, by type.

This publication contains the official statistics about uses of the Mental Health Act ('the Act') in England during 2023-24. Under the Act, people with a mental disorder may be formally detained in hospital (or 'sectioned') in the interests of their own health or safety, or for the protection of other people. They can also be treated in the community but subject to recall to hospital for assessment and/or treatment under a Community Treatment Order (CTO). In 2016-17, the way we source and produce these statistics changed. Previously these statistics were produced from the KP90 aggregate data collection. They are now primarily produced from the Mental Health Services Data Set (MHSDS). The MHSDS provides a much richer data source for these statistics, allowing for new insights into uses of the Act. People may be detained in secure psychiatric hospitals, other NHS Trusts or at Independent Service Providers (ISPs). All organisations that detain people under the Act must be registered with the Care Quality Commission (CQC). In recent years, the number of detentions under the Act have been rising. An independent review has examined how the Act is used and has made recommendations for improving the Mental Health Act legislation. In responding to the review, the government said it would introduce a new Mental Health Bill to reform practice. This publication does not cover: 1. People in hospital voluntarily for mental health treatment, as they have not been detained under the Act (see the Mental Health Bulletin). 2. Uses of section 136 where the place of safety was a police station; these are published by the Home Office.

These are the detailed tables pertaining to adult mental health from the 2011 National Survey on Drug Use and Health (NSDUH). These detailed tables present totals and prevalence estimates for youths include major depressive episode (MDE), treatment for depression (among youths with MDE), mental health service utilization, and measures related to the co-occurrence of mental disorders with substance use or with substance use disorders. Results are provided for age group, gender, race/ethnicity, education level, government assistance status, poverty level, geographic area, insurance status. Comparisons are made between 2011 and 2002 to 2010.