This statistic depicts the percentage of the U.S. population who had bipolar disorder from 1990 to 2019, by gender. According to the data, the rate of bipolar disorder has remained relatively stable in the U.S. with approximately *** to *** percent of males and females suffering from bipolar disorder yearly.

From 1990 to 2021, the rate of bipolar disorder has remained relatively stable, with around 0.45 percent of the global population suffering each year. This statistic depicts the percentage of the world population who had bipolar disorder from 1990 to 2021.

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!

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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...

In 2021, it was estimated that some *** percent of the total population in the Americas suffered from bipolar disorder. This statistic depicts the percentage of the global population with bipolar disorder in 2021, by region.

Bipolar Disorder Market Outlook

According to our latest research, the global bipolar disorder market size is valued at USD 6.7 billion in 2024. The market is experiencing a steady expansion, driven by increasing awareness, improved diagnostics, and a growing patient population. The market is projected to grow at a CAGR of 4.3% from 2025 to 2033, reaching an estimated value of USD 9.7 billion by 2033. The primary growth factor fueling this expansion is the rising prevalence of bipolar disorder coupled with advancements in pharmacological and non-pharmacological treatment modalities, as per our comprehensive analysis.

One of the most significant growth drivers for the bipolar disorder market is the increasing recognition and diagnosis of mental health disorders globally. Over the past decade, there has been a marked shift in public perception and destigmatization of mental health issues, encouraging more individuals to seek diagnosis and treatment. This trend is further amplified by government initiatives, mental health awareness campaigns, and the integration of mental health services into primary healthcare systems. The expansion of health insurance coverage for psychiatric illnesses in various countries has also made treatments more accessible, thereby increasing the patient pool and driving up demand for both pharmacological and non-pharmacological interventions.

Another critical factor contributing to the growth of the bipolar disorder market is the ongoing innovation in drug development and therapeutic approaches. Pharmaceutical companies are investing heavily in research and development to create more effective and safer medications, including next-generation mood stabilizers and antipsychotics with improved side effect profiles. Additionally, the emergence of precision medicine and personalized treatment strategies is offering new hope to patients who have not responded to traditional therapies. The integration of digital health platforms and telepsychiatry is also enhancing patient engagement, follow-up, and compliance, further supporting market growth.

The market is also benefiting from the rising burden of comorbidities associated with bipolar disorder, such as anxiety, substance abuse, and cardiovascular diseases, which necessitate comprehensive and long-term management. The growing geriatric population, who are at higher risk for mood disorders, and the heightened focus on pediatric mental health are expanding the target demographic for bipolar disorder treatments. Moreover, the increasing adoption of non-pharmacological interventions, such as cognitive behavioral therapy and psychoeducation, in combination with pharmacotherapy, is creating a more holistic approach to care, thereby boosting market demand.

Regionally, North America continues to dominate the bipolar disorder market, accounting for the largest share in 2024 due to its advanced healthcare infrastructure, high awareness levels, and robust reimbursement frameworks. Europe follows closely, supported by strong governmental initiatives and a growing emphasis on mental health. The Asia Pacific region is anticipated to exhibit the fastest growth rate, driven by increasing healthcare investments, rising mental health awareness, and expanding access to treatment. Latin America and the Middle East & Africa are gradually catching up, albeit at a slower pace, due to improving healthcare systems and growing recognition of psychiatric disorders.

In addition to bipolar disorder, the treatment landscape for schizoaffective disorder is also evolving, offering new insights and therapeutic options. Schizoaffective disorder treatment often involves a combination of antipsychotics, mood stabilizers, and antidepressants, tailored to address both the mood and psychotic symptoms of the condition. Recent advancements in pharmacotherapy are focusing on developing medications with better efficacy and tolerability, minimizing side effects that often deter adherence. The integration of psychosocial interventions, such as cognitive behavioral therapy and family-focused therapy, is enhancing treatment outcomes by addressing the broader psychosocial challenges faced by patients. As research continues to uncover the underlying pathophysiology of schizoaffective disorder, personalized treatment strategies are becoming more prevalent, offering hope for improved quality of lif

According to Cognitive Market Research, the global Bipolar Disorder Therapeutics Drug market size was USD 6124.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 3.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 2449.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 1.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1837.35 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 1408.64 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 306.23 million in 2024 and will grow at a compound annual growth rate (CAGR) of 2.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 122.49 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.2% from 2024 to 2031.
The mood stabilizers category is the fastest growing segment of the Bipolar Disorder Therapeutics Drug industry

Market Dynamics of Bipolar Disorder Therapeutics Drug Market

Key Drivers for Bipolar Disorder Therapeutics Drug Market

Rising Rates of Bipolar Disorder Globally to Boost Market Growth

The Bipolar Disorder Therapeutics Drug industry is growing largely because of an upsurge in the incidence of bipolar disorder. Growing numbers of instances linked to lifestyle, environmental, and genetic factors are driving up the need for efficient therapies. As mental health awareness grows, more people are seeking treatment and diagnosis, which frequently entails long-term medication. Moreover, increased diagnosis rates are a result of early detection techniques and increased acceptance of mental health conditions. In order to properly treat bipolar disorder, a variety of drugs, such as mood stabilizers, antipsychotics, and antidepressants, are in high demand due to this expanding patient base. In response to the rising prevalence, pharmaceutical companies are spending money on research to create novel medications, which will help the market grow. /p>

Increasing Understanding of Mental Health to Drive Market Growth

The bipolar disorder therapeutics drug market is being driven mostly by increased awareness of mental health issues. The prejudice linked to mental illness is being lessened by public and healthcare initiatives, which encourage more people to seek bipolar disorder diagnosis and treatment. Campaigns by governments, prominent public figures, and mental health groups have emphasized the significance of identifying symptoms and seeking professional assistance. Higher diagnosis rates are a result of these changes in societal views, and pharmaceutical therapy is frequently used as a primary treatment component. Additionally, better adherence to medicine due to greater awareness of the importance of long-term management has led to a continued demand for therapies. Because mental health issues are becoming more widely recognized, bipolar illness is now being treated more proactively by both patients and clinicians, which is driving innovation and market expansion.

Restraint Factor for the Bipolar Disorder Therapeutics Drug Market

Side Effects of Medications Such as Weight Gain, Sedation, and Metabolic Issues, Will Limit Market Growth

The market for therapeutic drugs for bipolar disorder is severely constrained by side effects, which cause patients to stop taking their prescriptions as prescribed. Weight gain, sedation, and cognitive impairment are examples of adverse effects that might lower a patient's quality of life and lead to therapy discontinuation. Relapses could occur as a result of this cessation, making disorder management more difficult. Furthermore, mistrust of treatment procedures may be stoked by the perception that drugs are useless because of adverse effects. Treatment may also take longer if frequent drug modifications are required to minimize negative effects. Additionally, medical professionals might be reluctant to recommend specific drugs with known side effects, which would further reduce the range of available treatments and hinder market expansion.

Impact of Covid-19 on the Bipolar Disorder The...

In 2019, bipolar disorder affected about ***** Italians out of 100,000, a slight increase compared to 2010. The disease was mainly prevalent among individuals aged 55 to 64 years old and was more common among women than men. In 2021, bipolar disorder was the fourth most common cause of hospitalization for patients admitted to mental health facilities, and the fifth most common cause if only male patients were considered. Definition, risk factors and therapies The National Institute of Mental Health defines bipolar disorder as a manic-depressive illness that causes shifts in mood, energy and activity levels, altering the ability to carry out daily tasks. The causes of this mental condition are momentarily not well defined, even though a combination of brain structure, genetics, and family history may impact the onset of the disease. Bipolar disorder is usually treated using mood stabilizers such as lithium, and in Italy, the public expenditure on lithium medication amounted to roughly *** million euros in 2023. Sardinia was the region with the greatest rate of adults taking lithium.   The stigma around mental illness Bipolar disorder is difficult to diagnose due to comorbidity with other mental conditions and volatility of the symptoms. Moreover, the feeling of shame that unfortunately still surrounds people dealing with mental health disorders does not make it easy to ask for a specialist’s consultation. Between 2020 and 2021, almost ** percent of individuals suffering from depression in Italy declared that they sought help.

IntroductionDigital mental health is a promising solution to support people with severe mental health problems (SMI) in China. However, little is known about the ownership rate of digital technologies and attitudes towards utilising digital health technologies (DHTs) among people with SMI in the Chinese context. The aims of this study were to understand: (i) digital technology ownership and usage rate of people with SMI in China; (ii) attitudes toward DHTs in mental health services; and (iii) how the COVID-19 pandemic has influenced views on digital mental health.MethodsA cross-sectional survey was given to outpatients with SMI using the REDCap platform. To capture a diverse sample of people with SMI, the survey was distributed across psychiatric hospitals, general hospitals with a psychiatric unit, secondary hospitals, and community healthcare centres.ResultsIn total, 447 survey respondents completed the survey. Relative high ownership rates of digital technologies were found, with smartphone ownership (95.5%) and access to the internet (82.1%) being the highest technologies reported. However, less than half of respondents reported frequent health-related usage of digital technologies, which may be related to the lack of knowledge in using DHTs. Most respondents found DHTs being useful for access to mental health services during the pandemic and were willing to use DHTs after the pandemic.DiscussionOur data suggest that, despite the high ownership rate of digital technologies, training programmes to improve digital health literacy for people with SMI in China are necessary to realise the full potential of digital mental health.

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

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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 ...

Bipolar Disorder Therapeutics Market Outlook

According to our latest research, the global Bipolar Disorder Therapeutics market size reached USD 6.3 billion in 2024, reflecting consistent demand for effective treatments and growing awareness of mental health disorders worldwide. The market is projected to expand at a CAGR of 4.7% from 2025 to 2033, reaching a forecasted value of approximately USD 9.3 billion by 2033. The upward growth trajectory is fueled by increased diagnosis rates, expanding access to healthcare, and ongoing advances in pharmacological and non-pharmacological interventions for bipolar disorder. As per our latest research, the market’s robust growth is further propelled by rising investments in mental health, the development of novel therapeutics, and a growing emphasis on patient-centric care models.

A key growth factor in the Bipolar Disorder Therapeutics market is the significant rise in mental health awareness globally. Governments, healthcare organizations, and advocacy groups have initiated numerous campaigns to reduce stigma and encourage early diagnosis and treatment of bipolar disorder. This has resulted in a higher rate of patients seeking medical help, which in turn is driving demand for both pharmacological and non-pharmacological therapies. Additionally, the integration of mental health services into primary healthcare systems, especially in high-income countries, has improved accessibility and continuity of care for individuals suffering from bipolar disorder. These efforts are expected to further boost market growth as more patients are diagnosed and treated effectively.

Another critical driver is the ongoing innovation in drug development and therapeutic modalities. Pharmaceutical companies are investing heavily in R&D to develop new drug classes and improve existing formulations, targeting both efficacy and safety. The introduction of next-generation antipsychotics, mood stabilizers, and combination therapies has expanded the treatment landscape, offering patients more choices and better outcomes. Furthermore, advancements in personalized medicine, such as the use of pharmacogenomics to tailor treatments to individual patient profiles, are enhancing the effectiveness of bipolar disorder therapeutics. These innovations are not only addressing unmet needs but are also creating opportunities for premium pricing and market expansion.

The increasing prevalence of bipolar disorder, coupled with rising comorbidities such as anxiety and substance abuse, is also contributing to market growth. Epidemiological studies indicate a steady increase in the global incidence and prevalence rates of bipolar disorder, particularly in urban areas where lifestyle changes, stress, and environmental factors play a significant role. Moreover, the growing geriatric population, which is more susceptible to mood disorders, is further expanding the patient pool. As healthcare systems evolve to manage chronic mental health conditions more effectively, the demand for comprehensive and long-term therapeutic solutions is expected to rise, bolstering the market’s growth prospects.

Regionally, North America continues to dominate the Bipolar Disorder Therapeutics market due to its advanced healthcare infrastructure, high awareness levels, and substantial investments in mental health research. Europe follows closely, benefiting from strong government support and expanding reimbursement policies. The Asia Pacific region is emerging as a high-growth market, driven by increasing healthcare expenditure, large patient populations, and growing acceptance of mental health treatments. Latin America and the Middle East & Africa are also witnessing gradual improvements, supported by international collaborations and the expansion of healthcare services. Each region presents unique opportunities and challenges, shaping the overall dynamics of the global market.

Drug Class Analysis

The Drug Class segment is pivotal in the Bipolar Disorder Therapeutics market, encompassing mood stabilizers, antipsychotic drugs, antidepressant drugs, anticonvulsants, and other medications. Mood stabilizers remain the cornerstone of bipolar disorder management, with lithium and valproate being widely prescribed due to their proven efficacy in controlling manic and depressive episodes. Despite concerns about side effects and the need for regular monitoring, mood stabilizers continue to hold a significant market share, especially in long-term maintenance ther

Korea Bipolar Disorder Therapeutics Market size was valued at USD 132.80 Million in 2023 and is projected to reach USD 211.68 Million by 2030, growing at a CAGR of 6.15% from 2024 to 2030.Korea Bipolar Disorder Therapeutics Market OverviewFormerly known as manic depression, bipolar disorder is characterized by alternate periods of depression and abnormally elevated mood. Bipolar disorder is characterized by diverse symptoms including manic, hypomanic, depressive, mixed and psychotic features, and by chronically debilitating patterns that create challenges for treatment. Bipolar disorder treatment in South Korea has seen a sharp rise in number of patients. According to the data from the National Health Insurance Service, an average annual growth rate of 4.9 percent over the five-year period before COVID situation.In the FY 2019, According to the data based on treatments covered by the state health insurance system, the on-year increase was the highest among patients in their 70s or older at ~12 -14 percent followed by twenty-somethings with ~8-10 percent and those in their 60s with ~7-9 percent. In FY 2017, The number of female patients grew at an average annual rate of 4.6 percent, with that of male patients increasing 5.2 percent. The prevalence of bipolar disorder was estimated to be between 2 and 3 percent, or less than 0.2 percent, of the population in South Korea, despite a notable increase in the number of people receiving treatment for the mental illness.

A study estimated that more than ************* Chinese people were suffering from bipolar disorder in 2019, representing a considerable hike of around ** percent since 1990. Similar to depression patients, patients with bipolar disorder are more likely to commit suicide or self-harm, making the condition a burden to the patients' families and the wider Chinese society.

The global market for bipolar disorder medications is experiencing robust growth, driven by increasing prevalence of the disorder, rising awareness, and advancements in treatment options. The market, valued at approximately $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 6% from 2025 to 2033. This growth is fueled by several factors. Increased research and development efforts are leading to the development of more effective and targeted therapies with improved tolerability profiles. Furthermore, a growing understanding of bipolar disorder among healthcare professionals and patients is leading to improved diagnosis and treatment rates. The expansion of healthcare infrastructure, particularly in emerging economies, is also contributing to market expansion. However, high treatment costs, potential side effects of some medications, and the need for long-term treatment pose challenges to market growth. The market is segmented by drug type (mood stabilizers, anticonvulsants, antipsychotics, antidepressants, and anti-anxiety drugs) and application (hospital and clinic settings). Mood stabilizers currently hold the largest segment share due to their efficacy and widespread use. Geographically, North America and Europe currently dominate the market, reflecting higher healthcare expenditure and greater awareness. However, Asia-Pacific is anticipated to exhibit significant growth potential in the coming years, driven by rising disposable incomes and increased healthcare investment. The competitive landscape is characterized by the presence of several major pharmaceutical companies, including AbbVie, GlaxoSmithKline, Eli Lilly, Janssen, Johnson & Johnson, and Pfizer. These companies are engaged in strategic initiatives such as new product development, partnerships, and mergers and acquisitions to strengthen their market position. The introduction of novel therapies with improved efficacy and safety profiles will likely shape the market dynamics in the coming years. The market is expected to witness increased competition, particularly in the development and commercialization of newer and more effective treatments for bipolar disorder. This will likely lead to innovation and price competition, benefiting patients and impacting market share dynamics.

ABSTRACT

The issue of diagnosing psychotic diseases, including schizophrenia and bipolar disorder, in particular, the objectification of symptom severity assessment, is still a problem requiring the attention of researchers. Two measures that can be helpful in patient diagnosis are heart rate variability calculated based on electrocardiographic signal and accelerometer mobility data. The following dataset contains data from 30 psychiatric ward patients having schizophrenia or bipolar disorder and 30 healthy persons. The duration of the measurements for individuals was usually between 1.5 and 2 hours. R-R intervals necessary for heart rate variability calculation were collected simultaneously with accelerometer data using a wearable Polar H10 device. The Positive and Negative Syndrome Scale (PANSS) test was performed for each patient participating in the experiment, and its results were attached to the dataset. Furthermore, the code for loading and preprocessing data, as well as for statistical analysis, was included on the corresponding GitHub repository.

BACKGROUND

Heart rate variability (HRV), calculated based on electrocardiographic (ECG) recordings of R-R intervals stemming from the heart's electrical activity, may be used as a biomarker of mental illnesses, including schizophrenia and bipolar disorder (BD) [Benjamin et al]. The variations of R-R interval values correspond to the heart's autonomic regulation changes [Berntson et al, Stogios et al]. Moreover, the HRV measure reflects the activity of the sympathetic and parasympathetic parts of the autonomous nervous system (ANS) [Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology, Matusik et al]. Patients with psychotic mental disorders show a tendency for a change in the centrally regulated ANS balance in the direction of less dynamic changes in the ANS activity in response to different environmental conditions [Stogios et al]. Larger sympathetic activity relative to the parasympathetic one leads to lower HRV, while, on the other hand, higher parasympathetic activity translates to higher HRV. This loss of dynamic response may be an indicator of mental health. Additional benefits may come from measuring the daily activity of patients using accelerometry. This may be used to register periods of physical activity and inactivity or withdrawal for further correlation with HRV values recorded at the same time.

EXPERIMENTS

In our experiment, the participants were 30 psychiatric ward patients with schizophrenia or BD and 30 healthy people. All measurements were performed using a Polar H10 wearable device. The sensor collects ECG recordings and accelerometer data and, additionally, prepares a detection of R wave peaks. Participants of the experiment had to wear the sensor for a given time. Basically, it was between 1.5 and 2 hours, but the shortest recording was 70 minutes. During this time, evaluated persons could perform any activity a few minutes after starting the measurement. Participants were encouraged to undertake physical activity and, more specifically, to take a walk. Due to patients being in the medical ward, they received instruction to take a walk in the corridors at the beginning of the experiment. They were to repeat the walk 30 minutes and 1 hour after the first walk. The subsequent walks were to be slightly longer (about 3, 5 and 7 minutes, respectively). We did not remind or supervise the command during the experiment, both in the treatment and the control group. Seven persons from the control group did not receive this order and their measurements correspond to freely selected activities with rest periods but at least three of them performed physical activities during this time. Nevertheless, at the start of the experiment, all participants were requested to rest in a sitting position for 5 minutes. Moreover, for each patient, the disease severity was assessed using the PANSS test and its scores are attached to the dataset.

The data from sensors were collected using Polar Sensor Logger application [Happonen]. Such extracted measurements were then preprocessed and analyzed using the code prepared by the authors of the experiment. It is publicly available on the GitHub repository [Książek et al].

Firstly, we performed a manual artifact detection to remove abnormal heartbeats due to non-sinus beats and technical issues of the device (e.g. temporary disconnections and inappropriate electrode readings). We also performed anomaly detection using Daubechies wavelet transform. Nevertheless, the dataset includes raw data, while a full code necessary to reproduce our anomaly detection approach is available in the repository. Optionally, it is also possible to perform cubic spline data interpolation. After that step, rolling windows of a particular size and time intervals between them are created. Then, a statistical analysis is prepared, e.g. mean HRV calculation using the RMSSD (Root Mean Square of Successive Differences) approach, measuring a relationship between mean HRV and PANSS scores, mobility coefficient calculation based on accelerometer data and verification of dependencies between HRV and mobility scores.

DATA DESCRIPTION

The structure of the dataset is as follows. One folder, called HRV_anonymized_data contains values of R-R intervals together with timestamps for each experiment participant. The data was properly anonymized, i.e. the day of the measurement was removed to prevent person identification. Files concerned with patients have the name treatment_X.csv, where X is the number of the person, while files related to the healthy controls are named control_Y.csv, where Y is the identification number of the person. Furthermore, for visualization purposes, an image of the raw RR intervals for each participant is presented. Its name is raw_RR_{control,treatment}_N.png, where N is the number of the person from the control/treatment group. The collected data are raw, i.e. before the anomaly removal. The code enabling reproducing the anomaly detection stage and removing suspicious heartbeats is publicly available in the repository [Książek et al]. The structure of consecutive files collecting R-R intervals is following:

Phone timestamp	RR-interval [ms]
12:43:26.538000	651
12:43:27.189000	632
12:43:27.821000	618
12:43:28.439000	621
12:43:29.060000	661
...	...

The first column contains the timestamp for which the distance between two consecutive R peaks was registered. The corresponding R-R interval is presented in the second column of the file and is expressed in milliseconds.
The second folder, called accelerometer_anonymized_data contains values of accelerometer data collected at the same time as R-R intervals. The naming convention is similar to that of the R-R interval data: treatment_X.csv and control_X.csv represent the data coming from the persons from the treatment and control group, respectively, while X is the identification number of the selected participant. The numbers are exactly the same as for R-R intervals. The structure of the files with accelerometer recordings is as follows:

Phone timestamp	X [mg]	Y [mg]	Z [mg]
13:00:17.196000	-961	-23	182
13:00:17.205000	-965	-21	181
13:00:17.215000	-966	-22	187
13:00:17.225000	-967	-26	193
13:00:17.235000	-965	-27	191
...	...	...	...

The first column contains a timestamp, while the next three columns correspond to the currently registered acceleration in three axes: X, Y and Z, in milli-g unit.

We also attached a file with the PANSS test scores (PANSS.csv) for all patients participating in the measurement. The structure of this file is as follows:

no_of_person	PANSS_P	PANSS_N	PANSS_G	PANSS_total
1	8	13	22	43
2	11	7	18	36
3	14	30	44	88
4	18	13	27	58
...	...	...	...	..

The first column contains the identification number of the patient, while the three following columns refer to the PANSS scores related to positive, negative and general symptoms, respectively.

USAGE NOTES

All the files necessary to run the HRV and/or accelerometer data analysis are available on the GitHub repository [Książek et al]. HRV data loading, preprocessing (i.e. anomaly detection and removal), as well as the

BackgroundBipolar disorder (BD) is a severe mental illness characterized by alternating episodes of mania and depression. Among women of reproductive age (15–49 years), the risk of onset is higher and clinical manifestations are more complex due to the combined influence of hormonal fluctuations, reproductive pressures, and conflicts in social roles. Mental health problems in this population not only significantly impair quality of life but also place a sustained burden on family stability and public health systems. Although awareness of BD has been increasing, studies specifically focusing on the disease burden among women of reproductive age remain limited, particularly lacking systematic analyses based on the latest Global Burden of Disease (GBD) data.MethodsThis study was based on data from the GBD 2021 and systematically analyzed the incidence, prevalence, and disability-adjusted life years (DALYs) of BD among women aged 15–49 at the global, regional, and national levels from 1990 to 2021. We calculated age-standardized incidence rate (ASIR), prevalence rate (ASPR), and DALYs rate (ASDR), along with the estimated annual percentage change (EAPC) for each metric. In addition, cross-national health inequality was assessed using the slope index of inequality (SII) and the concentration index (CII). Future trends in the disease burden were projected to 2041 using a Bayesian age–period–cohort (BAPC) model.ResultsFrom 1990 to 2021, the overall burden of BD among women aged 15–49 years has continued to rise globally. In 2021, the numbers of new cases, prevalent cases, and DALYs were all significantly higher than in 1990. Although the ASIR showed a slight decline (EAPC = −0.07; 95% CI: −0.08 to −0.05), the ASPR and ASDR continued to increase, with EAPC of 0.06 (95% CI: 0.04–0.07) and 0.05 (95% CI: 0.04–0.07), respectively. High-SDI regions ranked highest across all three metrics, while middle-high SDI regions had the lowest ASIR and ASPR, and middle-low SDI regions had the lowest ASDR. Regionally, South Asia bore the heaviest absolute burden in terms of incident cases, prevalence, and DALYs, whereas Oceania had the lightest burden. In terms of standardized rates, Tropical Latin America had the highest ASIR, while Australasia recorded the highest ASPR and ASDR; East Asia had the lowest values across all three indicators. At the national level in 2021, New Zealand reported the highest ASIR, ASPR, and ASDR globally; China had the lowest ASIR, and the Democratic People’s Republic of Korea had the lowest ASPR and ASDR. The burden of BD was positively correlated with the level of socio-demographic development, showing a mild positive correlation between ASIR and SDI, and a stronger correlation for ASPR and ASDR. Age-wise, all age groups saw increases in incident cases, prevalence, and DALYs compared to 1990, with the 35–39 age group showing the greatest rise in incidence, and the 45–49 group the largest increase in prevalence and DALYs. In 2021, the ASIR peaked in the 15–19 age group, while ASPR and ASDR were highest in the 25–29 age group. Health inequality analysis indicated persistent disparities in BD burden between high- and low-SDI countries, with little improvement over the past three decades. Projections using the BAPC model suggest that ASIR, ASPR, and ASDR may slightly decline by 2041, but the overall disease burden is expected to remain high.ConclusionFrom 1990 to 2021, the disease burden of BD among women of reproductive age has continued to rise globally, exhibiting significant regional, national, and socioeconomic disparities. This highlights the uneven development of mental health systems across different settings. Countries should develop more targeted mental health intervention strategies based on their stage of development. It is recommended to strengthen early screening, standardized diagnosis, and long-term comprehensive management for women of reproductive age, in order to effectively reduce the disease burden and improve overall mental health in this population.

In 2022, almost 282,000 people were treated for bipolar disorders in France. That year, with roughly 96,400 patients, the highest prevalence for such disorders was found within the age group of 35 to 54 years.

Interventions delivered via smartphone apps may support individuals with bipolar disorder (BD) to learn about and implement evidence-based self-management strategies in the context of their daily lives. However, app usage rates are often suboptimal. The subjective experience of users may provide insights into factors influencing engagement (and disengagement) with an mHealth intervention. The present study describes a qualitative investigation of the experiences of people with BD who participated in the evaluation of a novel app-based intervention for BD self-management, the PolarUs app. Twenty-five individuals with BD were provided with access to an app-based self-management intervention over a three-month study period, and were later interviewed about personal experiences of engagement with the intervention, including attempts to enact self-management strategies. Thematic analysis was used to identify important aspects of the experience of engaging with a self-management app. Three themes describing drivers of engagement with the PolarUs app and associated features were generated: 1) Motivations, 2) Salience, and 3) Perceived effort. Drivers of engagement were shaped by contextual influences, summarised in four themes: 1) The smartphone ecosystem, 2) Daily life, 3) Mood symptoms, and 4) Involvement in a research study. The findings of this research generate insights into how individuals with BD engage with app-based interventions. Lived experience perspectives can inform the design of engaging app-based interventions for BD. Further, these findings emphasise the importance of considering the context in which people use self-management apps for BD for both research studies and implementation.

Mental Disorder App Market Outlook

The global market size for mental disorder apps was valued at approximately $3.2 billion in 2023 and is projected to grow at a Compound Annual Growth Rate (CAGR) of 18.5% to reach around $10.8 billion by 2032. The increasing incidence of mental health issues globally, coupled with advancements in mobile health technology, are pivotal growth factors fueling the expansion of this market.

One of the primary growth drivers for the mental disorder app market is the rising prevalence of mental disorders worldwide. With anxiety, depression, and other mental health issues becoming more common, there is an increasing demand for accessible and effective mental health solutions. Mental disorder apps provide a convenient way for individuals to manage their mental health, offering features such as mood tracking, cognitive behavioral therapy exercises, and instant access to mental health professionals. These applications are becoming increasingly popular due to their affordability and privacy compared to traditional therapy sessions.

Another significant factor propelling market growth is the continual technological advancements in mobile health apps. Modern smartphones are equipped with advanced sensors and capabilities that enable the development of sophisticated mental health applications. Innovations such as artificial intelligence (AI) and machine learning (ML) are being integrated into mental disorder apps to provide personalized treatment plans and real-time mental health monitoring. These technological advancements not only enhance the effectiveness of these apps but also make them more user-friendly and engaging, thereby attracting a larger user base.

Moreover, the growing awareness and acceptance of mental health issues are also driving the market. Governments and organizations worldwide are increasingly recognizing the importance of mental health and are investing in awareness campaigns and mental health services. This has led to a reduction in the stigma associated with mental health issues, encouraging more individuals to seek help. Mental disorder apps offer an anonymous and stigma-free way for individuals to seek help and manage their mental health, which further boosts their adoption.

Regionally, North America holds the largest share of the mental disorder app market, driven by high smartphone penetration, advanced healthcare infrastructure, and increasing awareness of mental health issues. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to the rapidly growing smartphone user base, increasing internet penetration, and rising awareness about mental health. Europe also represents a significant market due to favorable government initiatives and high healthcare expenditure.

In recent years, the integration of Meditation Devices And Apps into mental health management has gained significant traction. These tools offer users the ability to engage in mindfulness practices, which are known to reduce stress and improve mental well-being. Meditation apps, in particular, provide guided sessions, breathing exercises, and relaxation techniques that can be accessed anytime, making them a convenient option for individuals seeking to enhance their mental health. The use of meditation devices, such as wearable sensors, further complements these apps by providing real-time feedback on physiological responses, helping users to better understand and manage their stress levels. As awareness of the benefits of meditation grows, these devices and apps are becoming an integral part of comprehensive mental health strategies.

Disorder Type Analysis

The mental disorder app market can be segmented by disorder type into anxiety, depression, bipolar disorder, schizophrenia, PTSD, and others. Anxiety apps are among the most popular, addressing a prevalent issue affecting millions globally. These apps provide tools such as breathing exercises, meditation guides, and cognitive behavioral therapy techniques to help users manage their anxiety. The increasing prevalence of anxiety disorders, particularly among younger populations, is driving the demand for these specialized applications.

Depression apps similarly hold a significant market share. These applications offer features like mood tracking, journaling, and virtual therapy sessions to help individuals manage depression. The rising number of people suffering from depression, coupled

IntroductionMonitoring biometric data using smartwatches (digital phenotypes) provides a novel approach for quantifying behavior in patients with psychiatric disorders. We tested whether such digital phenotypes predict changes in psychopathology of patients with psychotic disorders.MethodsWe continuously monitored digital phenotypes from 35 patients (20 with schizophrenia and 15 with bipolar spectrum disorders) using a commercial smartwatch for a period of up to 14 months. These included 5-min measures of total motor activity from an accelerometer (TMA), average Heart Rate (HRA) and heart rate variability (HRV) from a plethysmography-based sensor, walking activity (WA) measured as number of total steps per day and sleep/wake ratio (SWR). A self-reporting questionnaire (IPAQ) assessed weekly physical activity. After pooling phenotype data, their monthly mean and variance was correlated within each patient with psychopathology scores (PANSS) assessed monthly.ResultsOur results indicate that increased HRA during wakefulness and sleep correlated with increases in positive psychopathology. Besides, decreased HRV and increase in its monthly variance correlated with increases in negative psychopathology. Self-reported physical activity did not correlate with changes in psychopathology. These effects were independent from demographic and clinical variables as well as changes in antipsychotic medication dose.DiscussionOur findings suggest that distinct digital phenotypes derived passively from a smartwatch can predict variations in positive and negative dimensions of psychopathology of patients with psychotic disorders, over time, providing ground evidence for their potential clinical use.

Light Therapy DevicesMedications for SAD (SSRIs, SNRIs, MAOIs, and Tricyclic Antidepressants)Vitamin D Supplements Recent developments include: February 2022: Granules, the United States Food and Drug Administration has granted India permission to market Bupropion Hydrochloride extended-release tablets in the United States to treat major depressive Disorder and seasonal affective Disorder., June 2021: Alkermes plc received approval from the US Food and Drug Administration for a novel medicine for schizophrenia and bipolar Disorder. Lybalvi is a medicine that combines the active ingredient of Eli Lilly's Zyprexa with a newer chemical compound called samidorphan.. Key drivers for this market are: Growing awareness of mental health disorders, including Seasonal Affective Disorder, is driving the demand for effective treatments and solutions.. Potential restraints include: The cost of specialized treatments, such as light therapy devices and medications, may be prohibitive for some individuals, especially in low-income regions.. Notable trends are: Light therapy is becoming the preferred treatment for SAD, with advancements in light therapy devices making them more accessible and effective.