In the 2021 financial year, depressive episodes were the most common affective disorders to be experienced by males and females living in Australia. Overall, females were more likely to suffer an affective disorder than males.

Abstract Background Research suggests that rates of mental illness are similar in rural and urban Australia, although there are significant workforce shortages in rural regions along with higher rates of chronic disease and obesity and lower levels of socioeconomic status. However, there are variations across rural Australia and limited local data on mental health prevalence, risk, service use and protective factors. This study describes the prevalence of self-reported mental health problems of psychological distress and depression, in a rural region in Australia and aims to identify the factors associated with these problems. Methods The Crossroads II study was a large-scale cross-sectional study undertaken in the Goulburn Valley region of Victoria, Australia in 2016–18. Data were collected from randomly selected households across four rural and regional towns and then screening clinics from individuals from these households. The main outcome measures were self-reported mental health problems of psychological distress assessed by the Kessler 10 and depression assessed by Patient Health Questionnaire-9. Unadjusted odd ratios and 95% confidence intervals of factors associated with the two mental health problems were calculated using simple logistic regression with multiple logistic regression using hierarchical modelling to adjust for the potential confounders. Results Of the 741 adult participants (55.6% females), 67.4% were aged ≥ 55 years. Based on the questionnaires, 16.2% and 13.6% had threshold-level psychological distress and depression, respectively. Of those with threshold-level K-10 scores, 19.0% and 10.5% had seen a psychologist or a psychiatrist respectively while 24.2% and 9.5% of those experiencing depression had seen a psychologist or a psychiatrist, respectively in the past year. Factors such as being unmarried, current smoker, obesity, were significantly associated with a higher prevalence of mental health problems whereas physical activity, and community participation reduced the risk of mental health problems. Compared to rural towns, the regional town had higher risk of depression which was non-significant after adjusting for community participation and health conditions. Conclusions The high prevalence of psychological distress and depression in this rural population was consistent with other rural studies. Personal and lifestyle factors were more relevant to mental health problems than degree of rurality in Victoria. Targeted lifestyle interventions could assist in reducing mental illness risk and preventing further distress.

Between 2020 and 2022, depressive episodes were the most common affective disorders to be experienced by males and females living in Australia. Nearly six percent of women suffered from depressive episodes in this time period, and just over four percent of males.

In 2022, the most common long-term health condition reported by Australians were mental and behavioral conditions, representing 26.1 percent of the population. By comparison, diabetes and heart diseases affected around five percent of the population each. Mental health in Australia Around 27.6 percent of the Australian population suffered from depression or symptoms of depression in 2020 amidst the COVID pandemic. Despite so many Australians being affected by mental illness, many do not initially seek help or know where to look to find help. For those that do seek help, not for profit organizations like Beyond Blue, the Black Dog Institute, and Sane are available for Australians to receive information and support. For young people, Headspace is a government funded national youth support service. However, in a 2022 survey on where young people go for help, around 80 percent of young people indicated that they feel most comfortable speaking with their friends about important issues such as mental health.  Chronic illness as an underlying cause of death Diabetes was a considerable underlying cause of death in the Australian population in 2020. The rate has not changed significantly over the past 20 years compared to other prevalent causes of death, like cancer. Arthritis, hypertension, and asthma are among the most common chronic illnesses in Australia, but these illnesses alone are not usually significant contributors to a cause of death.

Age distribution of individuals enrolling in the This Way Up Clinic iCBT courses and of those diagnosed with psychiatric disorders in the general population according to the 2007 Australian National Survey of Mental Health and Well-Being (NSMHWB).

This statistic displays the share of the population experiencing mental and behavioral conditions in Australia in financial year 2018. That year, about 10.4 percent of Australians suffered from depression or feeling depressed.

In early 2020, characterized by the outbreak of COVID-19, across select OECD countries there was an increase in the prevalence of depression or symptoms of depression. In the United States, for example, around 23.5 percent of repondents reported suffering from depression or had symptoms of depression in 2020, while only 6.6 percent reported depression or depression symptoms in the year prior. The graph shows the results of different national surveys measuring the prevalence of depression or symptoms of depression in early 2020 and in the year before.

According to a survey conducted in Australia between 2020 and 2022, 16 percent of the population aged between 16 and 85 years had experienced an affective disorder at some point in their lifetime. Nearly 12 percent of people had a depressive episode in this time period.

Although the Young Schema Questionnaire and its current variants have been widely used, its continued use would be strengthened practically if a briefer version was available for clinical assessment and research. This study aimed to provide an assessment of the psychometric properties of the original YSQ-S3 and to create a brief version (YSQ-Brief) with equal or superior psychometric properties to the YSQ-S3. A non-clinical sample of university students (N = 800) completed an online test battery of questionnaires. Diagnostic groups were created based off current self-report of a mental health diagnosis (e.g. generalised anxiety disorder and major depressive disorder), and an eating disorder symptomatic subgroup created based on Eating Disorder Examination Questionnaire scores. Psychometric evaluations were conducted, including confirmatory factor analyses, internal consistency and validity analyses (criterion and construct). Further, group differences and relationships between mental health symptomatology and early maladaptive schemas (EMS) were examined. Both the YSQ-S3 and the revised YSQ-Brief displayed good model fit. Further, using both measures, all 18 EMS dimensions displayed acceptable internal consistency, good construct validity, ability to discriminate between diagnostic groups, and relationships with depression, anxiety, stress, and eating disorder symptomatology. The results of this study suggest that both the YSQ-S3 and the revised YSQ-Brief are valid, reliable and clinically useful measures. However, the YSQ-Brief provides greater efficiency and reduced burden, as well as equal psychometric soundness as compared to the original measure. What is already known about this topic:The Young Schema Questionnaire is widely used but has significant clinician and respondent burden.A psychometric evaluation of the YSQ-S3 is yet to be conducted in a young adult Australian sample.The relationship between anxiety and schema dimensions has not been studied in this population nor the relationship between disordered eating symptomatology “approval seeking”, “negativity/pessimism”, and “punitiveness”. The Young Schema Questionnaire is widely used but has significant clinician and respondent burden. A psychometric evaluation of the YSQ-S3 is yet to be conducted in a young adult Australian sample. The relationship between anxiety and schema dimensions has not been studied in this population nor the relationship between disordered eating symptomatology “approval seeking”, “negativity/pessimism”, and “punitiveness”. What this topic adds: The YSQ-S3 displayed good validity and reliability in young adult Australian population.The newly revised YSQ-Brief displayed equal psychometric soundness, but with greater efficiency and reduced burden.The YSQ-Brief can discriminate young adults with various self-reported mental health diagnoses and displayed relationships with depression, anxiety, stress, and eating disorder symptomatology. The YSQ-S3 displayed good validity and reliability in young adult Australian population. The newly revised YSQ-Brief displayed equal psychometric soundness, but with greater efficiency and reduced burden. The YSQ-Brief can discriminate young adults with various self-reported mental health diagnoses and displayed relationships with depression, anxiety, stress, and eating disorder symptomatology.

Figure S1 and Tables S1–S4. Figure S1. A) DRD3 gene structure, B) genotyped SNPs, C) D' in the HapMap CEPH data (NCBI Build 36), D) r2 in the HapMap CEPH data, E) D' in the study sample (non-related individuals; one per family), F) r2 in the study sample. Table S1. Correlations between the included phenotypes. Correlations were computed by polychoric (tetrachoric and point biserial) and spearman correlation. Number of individuals varies from 1326 to 1428 depending on presence of missing values. Table S2. Marker quality controls. Table S3. Association analysis results (p-values) for all dopamine receptor genes. The study-specific P-value threshold for significant and suggestive association is 0.00042 and 0.0014, respectively. Table S4. a. The association of rs2399496, rs3732790 and rs2134655 with nicotine dependence (ND) and Major Depressive Disorder (MDD) in the Australian NAG-OZALC sample. Age, sex, and principal components (for population stratification) were used as covariates. All results are based on recessive models. b. The associations of rs2399496, rs3732790 and rs2134655 with nicotine dependence (ND) and Major Depressive Disorder (MDD) in the NTR-NESDA sample. Age, sex, and principal components (for population stratification) were used as covariates. All results are based on recessive models. c. The associations of rs2399496, rs3732790 and rs2134655 with nicotine dependence (ND) and Major Depressive Disorder (MDD) in the FT12 sample. Age and sex were used as covariates. All results are based on recessive models. d. The associations of rs2399496, rs3732790 and rs2134655 with nicotine dependence (ND1) and Major Depressive Disorder (MDD) in the T2000 sample. Age and sex were used as covariates. All results are based on recessive models. (DOCX)

BackgroundThe mental health of children conceived using Assisted Reproductive Technologies (ARTs) such as In-Vitro-Fertilization (IVF) is a subject of significant controversy. Existing studies suggest children conceived through ART meet physical and cognitive developmental milestones at similar rates to their spontaneously conceived peers, however, a significant number of studies have connected ART conception with mental health conditions, particularly depression and attention-deficit hyperactivity disorder (ADHD) in adolescence. This study, therefore, aimed to determine whether maternal use of ARTs to achieve pregnancy is associated with an increased risk of mental disorders in these children, and whether these effects are sex-dependent or confounded by known covariates in the ART population.MethodsSecondary data analysis was performed using Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) data; a nationally representative population-based cross-sequential cohort study. Multivariate logistic regression models examined the impact of ART (including IVF and other fertility drugs, from LSAC wave-1 and wave-2 conducted in 2004 and 2006, respectively) on mental health outcomes (i.e., autism, ADHD, anxiety and/or depression, from LSAC waves 8 conducted in 2018) in Australian adolescents aged 18–19 years in 2018 (n = 1735). Known sociological and obstetric covariates including maternal age, birth weight, smoking and drinking alcohol during pregnancy, maternal gestational diabetes, postnatal depression, hypertension, and socioeconomic status were considered to generate an adjusted logistic model. Variables with a p-value of