Approximately one in five people living in Australia had a 12-month mental health disorder between 2020 and 2022. Anxiety disorders were the most prevalent, specifically social phobia. Post-traumatic stress disorder affected over five percent of the population.

Background: While there is discussion of increasing rates of mental disorders, epidemiological research finds little evidence of change over time. This research generally compares cross-sectional surveys conducted at different times. Declining response rates to representative surveys may mask increases in mental disorders and psychological distress.Methods: Analysis of data from two large nationally representative surveys: repeated cross-sectional data from the Australian National Health Survey (NHS) series (2001–2017), and longitudinal data (2007–2017) from the Household, Income and Labor Dynamics in Australia (HILDA) Survey. Data from each source was used to generate weighted national estimates of the prevalence of very high psychological distress using the Kessler Psychological Distress scale (K10).Results: Estimates of the prevalence of very high psychological distress from the NHS were stable between 2001 and 2014, with a modest increase in 2017. In contrast, the HILDA Survey data demonstrated an increasing trend over time, with the prevalence of very high distress rising from 4.8% in 2007 to 7.4% in 2017. This increase was present for both men and women, and was evident for younger and middle aged adults but not those aged 65 years or older. Sensitivity analyses showed that this increase was notable in the upper end of the K10 distribution.Conclusions: Using household panel data breaks the nexus between declining survey participation rates and time, and suggests the prevalence of very high psychological distress is increasing. The study identifies potential challenges in estimating trends in population mental health using repeated cross-sectional survey data.

In Australia, ** percent of farmers surveyed said that they experienced anxiety in 2023, according to survey data. In addition, ** percent of respondents said that they have attempted self-harm or suicide.

Time series state level datasets showing important indicators regarding mental health. Includes data on mental health readmissions within 28 days, Mental health Community Care with within seven days of discharge and mental health average length of stay (days).

According to a survey conducted in Australia, around **** women and around **** men experienced a mental health issue such as stress or anxiety while working from home due to the COVID pandemic in 2020. The second leading cause of mental health issues by working from home was working in isolation.

Nearly one in two females aged 16-24 living in Australia had a 12-month mental health disorder between 2020 and 2022. Almost one third of young males aged 16-24 suffered a mental health disorder in the same period. Across all age groups, females were more likely than males to have a 12-month mental health disorder.

Comprehensive Mental Health Insights: A Diverse Dataset of 1000 Individuals Across Professions, Countries, and Lifestyles

This dataset provides a rich collection of anonymized mental health data for 1000 individuals, representing a wide range of ages, genders, occupations, and countries. It aims to shed light on the various factors affecting mental health, offering valuable insights into stress levels, sleep patterns, work-life balance, and physical activity.

Key Features: Demographics: The dataset includes individuals from various countries such as the USA, India, the UK, Canada, and Australia. Each entry captures key demographic information such as age, gender, and occupation (e.g., IT, Healthcare, Education, Engineering).

Mental Health Conditions: The dataset contains data on whether the individuals have reported any mental health issues (Yes/No), along with the severity of these conditions categorized into Low, Medium, or High.

Consultation History: For individuals with mental health conditions, the dataset notes whether they have consulted a mental health professional.

Stress Levels: Each individual’s stress level is classified as Low, Medium, or High, providing insights into how different factors such as work hours or sleep may correlate with mental well-being.

Lifestyle Factors: The dataset includes information on sleep duration, work hours per week, and weekly physical activity hours, offering a detailed picture of how lifestyle factors contribute to mental health.

This dataset can be used for research, analysis, or machine learning models to predict mental health trends, uncover correlations between work-life balance and mental well-being, and explore the impact of stress and physical activity on mental health.

Comprehensive dataset containing 31 verified Mental health businesses in Australia with complete contact information, ratings, reviews, and location data.

Forecast: Total Number of Scientific Publications in Psychiatric Mental Health in Australia 2024 - 2028 Discover more data with ReportLinker!

This dataset includes number of Hospital admissions by mental health diagnosis; Community mental health service contacts by Statistical Local Area e.g. incl. Health Region, Metro Adelaide & Country SA. Dataset to be attributed to Public Health Information Unit (PHIDU) located at Torrens University Adelaide. http://phidu.torrens.edu.au/social-health-atlases

This dataset presents the footprint of the number of emergency department presentations in public hospitals by patient demographics and location. Mental health-related emergency department (ED) presentations are defined as presentations to public hospital EDs that have a principal diagnosis of mental and behavioural disorders. However, the definition does not fully capture all potential mental health-related presentations to EDs such as intentional self-harm, as intent can be difficult to identify in an ED environment and can also be difficult to code. The data spans the financial years of 2014-2018 and is aggregated to Statistical Area Level 3 (SA3) geographic areas from the 2016 Australian Statistical Geography Standard (ASGS).

State and territory health authorities collect a core set of nationally comparable information on most public hospital ED presentations in their jurisdiction, which is compiled annually into the National Non-Admitted Patient Emergency Department Care Database (NNAPEDCD). The data reported for 2014–15 to 2017–18 is sourced from the NNAPEDCD. Information about mental health-related services provided in EDs prior to 2014–15 was supplied directly to the Australian Institute of Health and Welfare (AIHW) by states and territories.

Mental health services in Australia (MHSA) provides a picture of the national response of the health and welfare service system to the mental health care needs of Australians. MHSA is updated progressively throughout each year as data becomes available. The data accompanies the Mental Health Services - In Brief 2018 Web Report.

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Mental health services in Australia Data Tables.

Please note:

• AURIN has spatially enabled the original data.

• Caution is required when conducting time-series analyses. The data source changed in 2014–15 from data provided by state and territory health authorities (2004–05 to 2013–14) to the NNAPEDCD. Additionally, due to the methodology applied for mapping the data over time, years prior to 2017–18 may be an undercount or data may not be displayed where SA3s have changed over time.

• Mental health-related emergency department presentations included in this report are those that had a principal diagnosis that fell within the Mental and behavioural disorders chapter (Chapter 5) of ICD-10-AM (codes F00–F99) or the equivalent ICD-9-CM or SNOMED codes. It does not include codes for self-harm or poisoning.

• From 2014–15 onwards, diagnosis information was not reported using a uniform classification. The mapping of SNOMED codes (used by NSW) to ICD-10AM may lead to an under-estimation of mental health-related presentations.

• Changes in the volume of patients over time for NSW may be attributed, in part, to the increased number of hospitals included in the data for this jurisdiction.

This dataset includes data from the Young and Well Towns (YAWT) Collaborative Research Centre (CRC) project. An uncontrolled trial was conducted that investigated the use and effect of mobile apps for mental health and wellbeing in young people. The study targeted adolescents and young adults (age 16 - 25) from Australia. Participants were asked to complete a profiling survey that assessed demographic characteristics, mental health, personality, and app use. Furthermore, they were asked to use and link a range of freely and commercially available health, fitness, or wellbeing apps. A range of app-specific metrics were assessed throughout the study period. Individuals were asked to use the mobile apps for a period of at least two weeks. Participants were continuously monitored over the study period with regard to subjective mood, sleep, rest and energy, through regular web-based self-report assessments.Date coverage: 2016-06-01 - 2017-01-31

This dataset presents the footprint of the number and rate of overnight admitted mental health-related separations and bed days, with and without specialised psychiatric care by patient location. Overnight admitted patient separations refers to those separations when a patient undergoes a hospital’s formal admission process, completes an episode of care, is in hospital for more than one day and ‘separates’ from the hospital. The data spans the financial year of 2015-2016 and is aggregated to 2017 Department of Health Primary Health Network (PHN) areas, based on the 2016 Australian Statistical Geography Standard (ASGS). The data is sourced from the National Hospital Morbidity Database (NHMD) which is a compilation of episode-level records from admitted patient morbidity data collections in Australian hospitals. It includes demographic, administrative and length of stay data for each hospital separation. Clinical information such as diagnoses, procedures undergone and external causes of injury and poisoning are also recorded. Mental health services in Australia (MHSA) provides a picture of the national response of the health and welfare service system to the mental health care needs of Australians. MHSA is updated progressively throughout each year as data becomes available. The data accompanies the Mental Health Services - In Brief 2018 Web Report. For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Mental health services in Australia Data Tables. Please note: AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

According to a survey conducted between 2020 and 2022, approximately 13 percent of people living in Australia had consulted a general practitioner regarding their mental health in the 12 months preceding the survey. Nearly 22 percent of females in Australia had had at least one consultation with a health professional for mental health.

Australia’s headspace initiative is world-leading in nation-wide youth mental healthcare reform for young people aged 12 to 25 years, now with 16 years of implementation. This paper examines changes in the key outcomes of psychological distress, psychosocial functioning, and quality of life for young people accessing headspace centres across Australia for mental health problems. Routinely collected data from headspace clients commencing an episode of care within the data collection period, 1 April 2019 to 30 March 2020, and at 90-day follow-up were analysed. Participants came from the 108 fully-established headspace centres across Australia, and comprised 58,233 young people aged 12–25 years first accessing headspace centres for mental health problems during the data collection period. Main outcome measures were self-reported psychological distress and quality of life, and clinician-reported social and occupational functioning. Most headspace mental health clients presented with depression and anxiety issues (75.21%). There were 35.27% with a diagnosis: overall, 21.74% diagnosed with anxiety, 18.51% with depression, and 8.60% were sub-syndromal. Younger males were more likely to present for anger issues. Cognitive behavioural therapy was the most common treatment. There were significant improvements in all outcome scores over time (P<0.001). From presentation to last service rating, over one-third had significant improvements in psychological distress and a similar proportion in psychosocial functioning; just under half improved in self-reported quality of life. Significant improvement on any of the three outcomes was shown for 70.96% of headspace mental health clients. After 16 years of headspace implementation, positive outcomes are being achieved, particularly when multi-dimensional outcomes are considered. A suite of outcomes that capture meaningful change for young people’s quality of life, distress and functioning, is critical for early intervention, primary care settings with diverse client presentations, such as the headspace youth mental healthcare initiative.

Comprehensive dataset containing 6,843 verified Mental health service businesses in Australia with complete contact information, ratings, reviews, and location data.

Using a rich individual level dataset from six countries, we examine the association between job loss and mental wellbeing loss during the first phase of the COVID-19 pandemic. We consider four indicators of mental health status based on their severity, viz. anxiety, insomnia, boredom, and loneliness. We draw our conclusions based on two groups of countries that differ by the timing of their peak infections count. Using a logit model and controlling for endogeneity, we find that the people who lost their jobs due to the pandemic are more likely to suffer from mental wellbeing loss, especially insomnia and loneliness. Additionally, people with financial liabilities, such as housing mortgages, are among the mentally vulnerable groups to anxiety. Women, urban residences, youth, low-income groups, and tobacco users are more prone to mental wellbeing loss. The findings from this research have significant policy implications on infectious disease control measures and mental health status due to lockdowns and social distancing.

The objective of the Young Minds Matter survey was to estimate the prevalence, severity, and impact of mental disorders in children and adolescents in Australia. Seven mental disorders were assessed using the parent or carer completed version of the Diagnostic Interview Schedule for Children Version IV (DISC-IV), and major depressive disorder was also assessed using the youth self-report version of the DISC-IV. Severity and impact were assessed using an extended version of the DISC-IV impact on functioning questions, and days absent from school due to symptoms of mental disorders. Data were collected in a national face-to-face survey of 6,310 parents or carers of children and adolescents aged 4-17 years, accompanied by self-report surveys of 2,969 young people aged 11-17 years. The 12-month prevalence of mental disorders was 13.9%. The most common class of disorders was ADHD followed by anxiety disorders. Mental disorders were more common in step-, blended- or one parent families, in families living in rented accommodation and families where one or both carers were not in employment. Some 2.1% of children and adolescents had severe disorders, 3.5% had moderate disorders and 8.3% had mild disorders. Mental disorders were associated with a substantial number of days absent from school, particularly in adolescents.

The MH-NOCC was established in 2002 by the Australian Mental Health Outcomes and Classification Network (AMHOCN) to collect data on the mental health-related treatment and outcomes of consumers of Australia's public specialised mental health services. The MH-NOCC includes all people in Australia who receive clinical care in public specialised mental health services, including psychiatric inpatient, residential, and ambulatory settings. Data is collected at admission to, review, and departure from a mental health care service.

This data comes from an online survey of 527 Australian tertiary education students completing questionnaires on faith in God and depression, anxiety and stress via meaning of life, hope and resilience.

This is the dataset for Shereen Metry's Master of Philosophy, entitled Faith in God as a Protective Factor Against Mental Illness Among University Students Within Australia. The dataset contains raw data underpinning the manuscript.