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Background: Previous estimates from 2007 found that co-occurring mental and/or substance use disorders were a pervasive feature of Australia's mental health. Since that time there have been shifts and improvements in the conceptualisation and incorporation of co-occurring disorders in research and treatment settings. The current study provides up-to-date estimates on the prevalence of co-occurring mental and/or substance use disorders, highlights common patterns of co-occurrence, identifies significant correlates and examines any changes in the extent of co-occurring disorders since 2007., Methods: Data were from the two Australian National Surveys of Mental Health and Wellbeing conducted in 2020-2022 ( N = 15,893) and 2007 ( N = 8841). Descriptive statistics were estimated for the number of co-occurring conditions, correlations and pairwise conditional probabilities. Multinomial logistic and robust Poisson regressions were used to identify significant correlates and compare changes in co-occurring conditions across surveys., Results: Approximately 46% of people with a mental or substance use disorder in the past 12 months experienced two or more diagnosable conditions. There was little evidence to suggest that the prevalence of co-occurring disorders has changed since 2007 (Prevalence Ratio (PR) = 1.08, 95% CI = 0.98-1.18). Subgroup analysis indicated that those aged 16-24 years were significantly more likely to experience any co-occurrence in 2020-2022 compared with those aged 16-24 years in 2007 (PR = 1.44, 95% CI = 1.17-1.77)., Conclusions: Co-occurring mental and substance use disorders remain endemic in Australia. Indeed, they appear to be increasingly problematic in younger, more recent cohorts. The results suggest that continued effort is needed to develop and implement transdiagnostic interventions that target broad contextual and/or societal factors., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Objective: Mental and substance use disorders are the leading causes of disability worldwide. Contemporary estimates of prevalence, severity and impairment are essential for service planning. This study provides estimates of prevalence, severity, impairment and demographic correlates of mental and substance use disorders in 2020-22 and changes in prevalence since 2007., Methods: Data were from the two Australian National Surveys of Mental Health and Wellbeing conducted in 2020-22 ( N = 15,893) and 2007 ( N = 8841). Descriptive statistics report prevalence of lifetime and 12-month mental and substance use disorder by sex and age, proportion of people with each mental disorder by levels of severity (mild, moderate and severe) and mean days out of role by mental disorder class (mood, anxiety, substance use). Logistic regression analyses examined demographic correlates of mental disorder class and assessed changes over time., Results: The lifetime prevalence of any mental or substance use disorder in 2020-22 was 40.2%. The 12-month prevalence was 20.2% (mood disorder - 7.4%, anxiety disorder - 15.7% and substance use disorder - 3.1%). Mood disorders were associated with significant impairment. The prevalence of mental disorders has changed over time, with mood and anxiety disorders increasing and substance use disorders decreasing. These changes were most evident among young adults., Conclusion: Mental disorders are common in Australia. Impairment associated with mental disorders remains significant. Particular focus should be paid to young adults aged 16-24 years who have shown the largest increases in anxiety and mood disorder prevalence over the past 13 years., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objective: This study aimed to describe the epidemiology of suicidal ideation, suicide plans and suicide attempts, examine services received for suicide attempts, and explore the relationship between suicide attempts and self-harm without suicidal intent., Methods: We used survey data from the 2020-2022 National Study of Mental Health and Wellbeing, which involved a nationally representative sample of Australian adults aged 16-85 ( n  = 15,893). Comparisons were made with the 2007 National Study of Mental Health and Wellbeing ( n  = 8841)., Results: In 2020-2022, the proportions of adults who had experienced suicidal ideation, suicide plans and suicide attempts during their lifetime were 16.6%, 7.5% and 4.9%, respectively. The proportions who had experienced these in the past 12 months were 3.3%, 1.1% and 0.3%. The odds of experiencing suicidal ideation and making a suicide plan were significantly higher in 2020-2022 than in 2007. Groups at heightened risk of suicidal ideation, suicide plans and/or suicide attempts in the previous 12 months were males, young people, people who were gay, lesbian, or bisexual or used some other term to describe their sexual identity, people outside the labour force, people from disadvantaged areas and people with mental disorders. Two-fifths of those who attempted suicide during the previous 12 months did not use health services following their attempt, and two-thirds also self-harmed without suicidal intent., Conclusion: The implications of these findings for the forthcoming National Suicide Prevention Strategy are discussed. Suicidal thoughts and behaviours confer risk for suicide and are significant problems in their own right. Their prevention requires a strong whole-of-government response., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Objective: Physical inactivity, sugar sweetened beverage consumption, alcohol use, smoking, poor sleep and excessive recreational screen time (the 'Big 6' lifestyle risk behaviours) often co-occur and are key risk factors for psychopathology. However, the best fitting latent structure of the Big 6 is unknown and links between multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology have not been explored among adolescents. This study aimed to address these gaps in the literature., Methods: Confirmatory factor analysis, latent class analysis and factor mixture models were conducted among 6640 students ( M age  = 12.7 years) to identify the latent structure of the Big 6 lifestyle risk behaviours. Structural equation models were then used to examine associations with psychopathology., Results: A mixture model with three classes, capturing mean differences in a single latent factor indexing overall risk behaviours, emerged as the best fitting model. This included relatively low-risk (Class 1: 30%), moderate-risk (Class 2: 67%) and high-risk (Class 3: 3%) classes. Students high on externalizing demonstrated significantly greater odds of membership to the high-risk class (odds ratio = 8.75, 99% confidence interval = [3.30, 23.26]) and moderate-risk class (odds ratio = 2.93, 99% confidence interval = [1.43, 5.97]) in comparison to the low-risk class. Similarly, students high on internalizing demonstrated significantly higher odds of membership to the high-risk class (odds ratio = 1.89, 99% confidence interval = [1.06, 3.37]) and the moderate-risk class (odds ratio = 1.66, 99% confidence interval = [1.03, 2.67]) in comparison to the low-risk class. Associations between lower order factors of psychopathology and lifestyle risk behaviours were mostly accounted for by the more parsimonious higher order factors., Conclusion: Classes representing differences in probabilities of the Big 6 lifestyle risk behaviours relate to varying levels of hierarchical dimensions of psychopathology, suggesting multiple health behaviour change and transdiagnostic intervention approaches may be valuable for reducing risk of psychopathology.

Objective: This study examined the secondary mental health outcomes of two contrasting alcohol prevention approaches, whereby one intervention targets common underlying personality risk for alcohol use and mental health problems ( Preventure ) and the other targets alcohol- and drug-related behaviours and cognitions ( Climate Schools )., Methods: A 2 × 2 cluster randomised controlled factorial design trial was conducted in 26 Australian schools randomised to the following 4 conditions: Climate Schools ( n  = 6), Preventure ( n  = 7), combined Climate Schools and Preventure (CAP; n  = 6) or treatment as usual (TAU; n  = 7). Participants completed questionnaires at baseline, 6, 12, 24 and 36 months post-baseline including the Brief Symptom Inventory anxiety and depression scales and hyperactivity and conduct scales of the Strengths and Difficulties Questionnaire. Analyses focused on students who were at high-risk based on personality traits ( n  = 947; M age  = 13.3). The effectiveness of each approach in reducing symptoms of internalising and externalising problems was assessed using multi-level mixed effects analysis., Results: Main effects for each intervention relative to not receiving that intervention revealed significant main effects of Preventure in reducing anxiety symptoms ( d  = -0.27, 95% confidence interval [CI] = [-0.53, -0.01], p  < 0.05) and a marginal effect in reducing depressive symptoms ( d  = -0.24, 95% CI = [-0.49, 0.01], p  = 0.06) over 3 years. Interaction effects revealed that when delivered alone, Preventure significantly reduced conduct problems ( d  = -0.45, 95% CI = [-0.78, -0.11], p  < 0.05) and hyperactivity symptoms ( d  = -0.38, 95% CI = [-0.70,-0.07], p  < 0.05) compared to TAU., Conclusion: This study is the first to report the effectiveness of personality-targeted alcohol prevention in reducing internalising and externalising symptoms relative to an active control, providing evidence in favour of its specificity in preventing concurrent substance use and mental health problems among high-risk youth.

Objective: The current study examined whether trauma characteristics such as the type and number of traumatic events were associated with three suicidal behaviours (i.e. ideation, plan and attempt) after adjusting for sociodemographic factors, post-traumatic symptoms and history of psychiatric disorders., Method: Data came from the 2007 Australian National Survey of Mental Health and Wellbeing ( N = 8841). Respondents were asked about exposure to 28 traumatic events that occurred during their lifetime. Suicidal behaviours were measured using three statements about whether the person ever seriously thought about or planned or attempted suicide., Results: Sexual violence and exposure to multiple traumatic events were particularly associated with suicidal behaviours. The presence of the emotional numbing symptom cluster and co-occurrence of three psychiatric disorders (major depressive disorder, alcohol use disorder and substance use disorder) also increased the odds of suicidal behaviours. Analysis of age of onset revealed that the mean age of traumatic exposure was earlier than the age at which suicidal behaviours emerged., Conclusions: The current study is the first to demonstrate that sexual violence and exposure to multiple traumatic events are associated with suicidal behaviours in a representative sample of Australian adults. The results underline the potential benefits of thorough assessment of trauma history, post-traumatic symptoms and history of psychiatric disorders and their additive contribution in suicide risk among trauma victims. These findings can be used by clinicians and researchers for early intervention programmes.

Objective: Replication is an important step in evaluating evidence-based preventive interventions and is crucial for establishing the generalizability and wider impact of a program. Despite this, few replications have occurred in the prevention science field. This study aims to fill this gap by conducting a cross-validation trial of the Climate Schools: Alcohol and Cannabis course, an Internet-based prevention program, among a new cohort of Australian students., Method: A cluster randomized controlled trial was conducted among 1103 students (Mage: 13.25 years) from 13 schools in Australia in 2012. Six schools received the Climate Schools course and 7 schools were randomized to a control group (health education as usual). All students completed a self-report survey at baseline and immediately post-intervention. Mixed-effects regressions were conducted for all outcome variables. Outcomes assessed included alcohol and cannabis use, knowledge and intentions to use these substances., Results: Compared to the control group, immediately post-intervention the intervention group reported significantly greater alcohol (d = 0.67) and cannabis knowledge (d = 0.72), were less likely to have consumed any alcohol (even a sip or taste) in the past 6 months (odds ratio = 0.69) and were less likely to intend on using alcohol in the future (odds ratio = 0.62). However, there were no effects for binge drinking, cannabis use or intentions to use cannabis., Conclusion: These preliminary results provide some support for the Internet-based Climate Schools: Alcohol and Cannabis course as a feasible way of delivering alcohol and cannabis prevention. Intervention effects for alcohol and cannabis knowledge were consistent with results from the original trial; however, analyses of longer-term follow-up data are needed to provide a clearer indication of the efficacy of the intervention, particularly in relation to behavioral changes., (© The Royal Australian and New Zealand College of Psychiatrists 2015.)

Objective: Current and accurate estimates of prevalence, correlates, comorbid concerns and treatment-seeking behaviours associated with disorders are essential for informing policy, clinical practice and research. The most recent snapshot of social anxiety disorder in Australia was published more than a decade ago, with significant changes to the accessibility of mental health treatment services and diagnostic measures occurring during this period. This paper aims to (i) update the understanding of social anxiety disorder, its associations and patterns of treatment-seeking behaviours in the Australian population, and (ii) explore the impact of revised diagnostic criteria detailed in the Fifth Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) on prevalence estimates., Methods: The National Survey of Mental Health and Wellbeing (NSMHWB) was conducted by the Australian Bureau of Statistics in 2007, collecting information from a nationally representative random sample of 8841 Australians aged 16-85 years. The presence of social anxiety disorder diagnostic criteria and related disorders were assessed over 12 months and lifetime periods using the World Mental Health Composite International Diagnostic Interview., Results: Profiles of social anxiety disorder were consistent with previous estimates, with higher prevalence in females and younger age groups. Of the 8.4% of Australians meeting criteria for social anxiety disorder at some point in their lifetime (12-month prevalence 4.2%), a majority also experienced comorbid mental health concerns (70%). The revised performance-only specifier included in the DSM-5 was applicable to only 0.3% of lifetime cases. Just over 20% of people reporting social anxiety disorder as their primary concern sought treatment, most commonly through general practitioners., Conclusions: Social anxiety disorder continues to be prevalent in the Australian population and highly related to other disorders, yet few people experiencing social anxiety disorder seek treatment., (© The Royal Australian and New Zealand College of Psychiatrists 2014.)

Objective: To describe and compare individuals with any DSM-IV mental disorder from three different birth cohorts - young (16-34 years), middle age (35-59 years) and older age (60-85 years) - on a range of clinically relevant factors., Method: Data were derived from the 2007 Australian National Survey of Mental Health and Wellbeing. Individuals from three birth cohorts with a range of mental health and substance use disorders were identified using DSM-IV criteria and compared using regression analysis. The specific factors that were compared include: (1) type of disorder/disorders present; (2) suicidality; (3) number of co-occurring disorders; (4) levels of distress and impairment; (5) self-assessed physical and mental health; (6) presence of physical conditions; (7) size and quality of social support/network; and (8) treatment-seeking behaviour., Results: The birth cohorts differed dramatically in terms of the specific disorders that were present. The older cohort were significantly more likely to experience internalising disorders and significantly less likely to experience externalising disorders in comparison to the young cohort. The older cohort were significantly more likely to experience co-morbid physical conditions as well as lower life satisfaction, poorer self-rated physical health, increased functional impairment, and more days out of role. The younger cohort had a significantly larger peer group that they could confide in and rely on in comparison to the older cohort., Conclusions: Clinicians and researchers need to be cognisant that mental disorders manifest as highly heterogeneous constructs. The presentation of a disorder in a younger individual could be vastly different from the presentation of the same disorder in an older individual. The additional burden associated with these factors and how they apply to different birth cohorts must be taken into consideration when planning mental health services and effective treatment for the general population.

Objective: To report nationally representative findings on the prevalence, correlates, psychiatric comorbidity and treatment of DSM-IV Cannabis Use and Cannabis Use Disorders in Australia., Method: The 2007 National Survey of Mental Health and Wellbeing was a nationally representative household survey of 8841 Australians (16-85 years) that assessed symptoms of the most prevalent DSM-IV mental disorders., Results: Prevalence of lifetime and 12-month cannabis use was 18% and 6%; prevalence of lifetime and 12-month cannabis use disorder was 6% and 1%. The conditional prevalence (proportion of ever users who met criteria for a disorder) of lifetime and 12-month cannabis use disorder was 32.2% and 14.3%. Current cannabis use disorders were more common in males (OR 2.0) and younger users (OR 4.6). Strong associations were observed between current cannabis use disorders and alcohol use disorders (OR 3.6) and current affective disorders (OR 3.0). Only 36.2% of those with current cannabis use disorders sought any treatment., Conclusions: The prevalence of cannabis use disorders in the Australian population is comparable with that in the USA. Current cannabis use disorders are highly concentrated in young Australians who have high levels of comorbidity. The low rates of treatment seeking warrant attention in treatment and prevention strategies.

Objective: The aims of this study were to (a) describe patterns of tobacco smoking among Australians living with a psychotic illness and (b) explore the association between smoking and measures of psychopathology, psychiatric history, psychosocial functioning, physical health, substance use and demographic characteristics., Methods: Data were from 1812 participants in the 2010 Australian Survey of High Impact Psychosis. Participants were aged 18-64 years and resided in seven mental health catchment sites across five states of Australia. Bivariate statistics were used to compare smokers with non-smokers on the measures of interest, and to compare ICD-10 diagnostic categories on measures of smoking prevalence, nicotine addiction and quitting history. Multivariate logistic regression was used to test whether (a) demographics and psychiatric history were associated with having ever smoked and (b) whether symptoms and psychosocial functioning were independently associated with current smoking, after controlling for demographics, psychiatric history and substance use., Results: The prevalence of current tobacco smoking was 66.6% (72% of men and 59% of women); lifetime prevalence was 81%. In univariate analyses, individuals with a diagnosis of schizophrenia or schizoaffective disorder were most likely to be smoking tobacco (70%) and were more nicotine dependent. Smokers reported worse perceived physical health, lower body mass index and waist circumference, and more lifetime medical conditions. A younger age of illness onset, male gender and low education were associated with having ever smoked. Associations with current smoking included low education, male gender, no formal employment, worse negative symptoms, higher daily caffeine consumption, and alcohol dependence and substance abuse/dependence., Conclusions: The prevalence of tobacco smoking is high amongst people with a psychotic disorder, and is associated with adverse mental health symptoms as well as high rates of other substance use, poorer subjective physical health, and a higher risk of the many known health consequences of smoking.

Objective: To provide the most up-to-date prevalence estimates of alcohol and illicit drug use among individuals with psychosis in Australia, and explore correlates associated with a lifetime diagnosis of both alcohol abuse/dependence and cannabis abuse/dependence., Method: This paper uses data from the Survey of High Impact Psychosis (SHIP), conducted as a follow-up to the first Australian National Low Prevalence (Psychotic) Disorders Study (1997-1998). The SHIP was a national study, carried out across five states, in which a sample of 1825 individuals was recruited through a two-phase sampling framework., Results: Alcohol and illicit drug use was highly prevalent for the entire sample. There were few significant differences in the prevalence or frequency of use across the diagnostic categories examined. Substantial increases in substance abuse/dependence were noted since the 1997-1998 survey (51% diagnosed with alcohol abuse/dependence, 51% with cannabis abuse/dependence and 32% with other illicit drug abuse/dependence, compared to 28%, 23% and 12% respectively, in the 1997-1998 survey by Kavanagh et al., 2004). Factors significantly associated with both lifetime alcohol and cannabis dependence included male gender, younger age, single marital status, lower educational attainment, shorter duration of illness, lifetime presence of hallucinations, higher negative syndrome score and lower body mass index (BMI). A number of other factors were found to be differentially associated with either lifetime alcohol or cannabis dependence., Conclusions: The use of alcohol and illicit substances is common among people with a psychotic illness, with a concerning upward trend in rates of substance abuse/dependence since the 1997-1998 survey. Clinicians should be aware of the potential impact of concurrent substance use and provide integrated treatment for individuals presenting with psychotic illnesses. More research and investment in new intervention programs is required.

Objective: The aim of this study was to report nationally representative data on the prevalence and patterns of 12 month comorbidity of chronic physical conditions (diabetes, asthma, coronary heart disease, stroke, cancer, arthritis) and DSM-IV affective and anxiety disorders in Australian adults., Method: The 2007 National Survey of Mental Health and Wellbeing (NSMHWB) was a nationally representative household survey of 8841 Australian adults (16-85 years) assessing symptoms of ICD-10 mental disorders and the presence of chronic physical conditions., Results: Prevalence of at least one National Health Priority Area chronic physical condition was 32.2% (95%CI = 30.9%-33.5%). Among those with chronic physical conditions 21.9% had an affective or anxiety disorder. Affective and anxiety disorders were more common among people with physical conditions than among people without chronic physical conditions (affective OR 1.5; anxiety OR 1.8). Of those with a 12 month affective or anxiety disorder, 45.6% had a chronic physical condition. Physical disorders were more common in those with an affective or anxiety disorder than among people without an affective or anxiety disorder (affective OR 1.6; anxiety OR 2.0). Disability was high in those with an anxiety disorder, an affective disorder and a physical condition and 43.4% were classified as high service users., Conclusions: Comorbidity between chronic physical conditions and affective and anxiety disorders is widespread and is associated with high levels of disability and service use.

Objective: The aims of this study were to report 12-month and lifetime prevalence for anxiety disorders in the Australian general population, identify sociodemographic and clinical correlates of anxiety disorders, and report the rates of comorbidity among anxiety, affective, and substance use disorders across the lifespan., Method: The 2007 National Survey of Mental Health and Wellbeing was a nationally representative, face-to-face household survey of 8841 (60% response rate) community residents aged between 16 and 85 years. Diagnoses for anxiety, affective and substance use disorders were made according to the DSM-IV using the World Mental Health Survey Initiative version of the Composite International Diagnostic Interview., Results: 12-month and lifetime prevalence of anxiety disorders were 11.8% and 20.0%, respectively. Anxiety disorders had a similar median age of onset (19 years) compared to substance use disorders (20 years), but earlier than affective disorders (34 years). Social phobia was the earliest onset anxiety disorder (median 13 years), with generalized anxiety disorder the latest (median 33 years). Significant correlates of the presence of anxiety disorders included being female, single, not in the labour force, in the middle age groups, not having post-graduate qualifications, having a comorbid physical condition, and having a family history of mental disorders. Being in the oldest age ranges and being born in another non-English speaking country were associated with lower odds of having an anxiety disorder. Body mass index was not associated with the presence of an anxiety disorder. Anxiety disorders were highly comorbid, particularly with major depression, dysthymia, and alcohol dependence. Comorbidity with substance use disorders reduced with age. Comorbidity with affective disorders was high across the lifespan., Conclusions: Anxiety disorders are common, can have an early onset, and are highly comorbid. Prevention, early detection, and treatment of anxiety disorders should be a priority.

Objective: The aim of this study was to present scoring rules for predicting DSM-IV mental illness in the previous 12 months using the Kessler Psychological Distress Scale in the Australian population., Method: The method described in Kessler et al. was closely followed using data from the 2007 Australian Survey of Mental Health and Wellbeing. A series of 93 nested logistic regression models were generated and compared to estimate the predicted probabilities of mental illness for each survey respondent using scores on the Kessler Psychological Distress Scale. The best model was selected using information theoretic criteria. Concordance between the predicted probabilities of mental illness generated by the best models with DSM-IV defined mental illness, assessed using the Composite International Diagnostic Interview, was determined using receiver operating characteristic analysis., Results: The best fitting models were found to contain the quadratic form of the Kessler Psychological Distress Scale (both 6 item and 10 item versions). Age was found to be significant in the model predicting mood, anxiety, and substance use with serious impairment using the 6 item version whilst age and gender was found to be significant in the model for the 10 item version. The concordance between the predicted probabilities of mood, anxiety, and substance use with serious impairment generated from the best models and DSM-IV mood, anxiety, and substance use with serious impairment was within an acceptable level for both versions. Results were similar when predicting DSM-IV mood, anxiety, and substance use without seriousness indicators and DSM-IV anxiety and depression. The performance of predicted probabilities was then examined in various sub-populations of the Australian population., Conclusions: Using a logistic regression model, the Kessler Psychological Distress Scale can be used to generate predicted probabilities of mental illness with an acceptable level of agreement in Australian-based population studies where it is not feasible to conduct a comprehensive assessment.

Objective: Estimates of the prevalence of exposure to potentially traumatic events (PTEs) in population surveys have increased over time. There is limited empirical evidence on the impact of changes in measurement practices on these estimates. The present study examined the effect of increasing the number of events assessed on the prevalence of exposure longitudinally., Methods: Data were ultilized from the 1997 and 2007 Australian National Surveys of Mental Health and Wellbeing. The 1997 survey assessed exposure using 11 items from the Composite International Diagnostic Interview (CIDI), version 2.1. The 2007 survey utilized 29 items from the World Mental Health CIDI. Prevalence rates of exposure to matched events among age-matched samples from both surveys were compared to determine whether differences in the estimates obtained were due to respondents having been asked about an increased number of event types in the latter survey., Results: The effect of increasing the number of event types in the CIDI from 11 to 29 was to increase the overall population prevalence of exposure to PTEs by 18%. The difference between estimates was more pronounced in women than in men. The cross-cohort analyses revealed that these differences were not indicative of an increase in trauma exposure over time; but rather the endorsement of new events that were not listed in the earlier survey., Conclusions: The findings underscore the importance of using comprehensive assessments in the measurement of exposure to PTEs. Previous epidemiological surveys may have underestimated the prevalence of traumatic and other stressful life events, particularly among women.

Objective: To present Australian normative data on the ten-item Kessler Psychological Distress Scale (K10)., Method: Analysis of cross-sectional data from the 2007 Australian National Survey of Mental Health and Wellbeing, a nationally representative household survey of 8841 adults. Mean K10 scores and K10 scores at selected percentiles of the K10 score distribution are presented by sex, age, the presence of mental disorders and the presence of physical conditions. Stratum-specific likelihood ratios were computed to help clinicians and researchers calculate predicted probabilities of mental disorder given scores on the K10., Results: Scores on the K10 were generally higher in women compared to men, in people with a mental disorder compared to without a mental disorder and in people with affective disorders compared to people with substance use disorders. The SSLRs were informative in ruling in a diagnosis of mental disorder, particularly at the high or very high end of the psychological distress spectrum., Conclusions: These data may be helpful for clinicians and researchers alike in understanding the likelihood of mental disorder in a given individual or sample.

Objective: To explore the rates and correlates of antidepressant (AD) and anxiolytic, hypnotic or sedative (AHS) medication use in Australia, and describe possible reasons for their use., Method: Analysis of data from the 2007 National Survey of Mental Health and Wellbeing, a nationally representative household survey of 8841 Australians aged 16 to 85 years. Two primary outcome variables: (i) use of any AD medication; and (ii) use of any AHS medication, in the past 2 weeks., Results: Rates of AD and AHS medication use were 6.8% and 4.7% respectively. AD and AHS medication use were each associated with 12-month affective or anxiety disorder, age, chronic physical illness, sleep difficulties, and impaired role functioning. Psychological distress and lifetime affective or anxiety disorder or 12-month symptoms were associated with AD use; being previously married was associated with AHS use. Potential reasons for use are complex. Almost one third (30.6%) of AD users and half (49.2%) of AHS users did not report symptoms consistent with a 12-month or lifetime affective or anxiety disorder. Chronic physical illness was reported by 68.8% of AD users and 73.5% of AHS users, around half of whom had a 12-month mental disorder. People with mental-physical comorbidity had especially high rates of AD and AHS use. People with musculoskeletal and other conditions that may involve chronic pain had elevated rates of AD and AHS use, even in the absence of a mental disorder., Conclusions: Low rates of medication use in younger adults and high rates of AHS use in older people warrant further investigation. Many AD and AHS users were not assessed as having an affective or anxiety disorder, suggesting that these medications are frequently used for other indications. Findings call for further research to explore the relationship between mental disorders, physical conditions and medication use.

Objective: Social phobia is a common mental disorder associated with significant impairment. Current research and treatment models of social phobia rely on categorical diagnostic conceptualizations lacking empirical support. This study aims to further research exploring whether social phobia is best conceptualized as a dimension or a discrete categorical disorder., Methods: This study used three distinct taxometric techniques (mean above minus below a cut, maximum Eigen value and latent mode) to explore the latent structure of social phobia in two large epidemiological samples, using indicators derived from diagnostic criteria and associated avoidant personality traits., Results: Overall, outcomes from multiple taxometric analyses supported dimensional structure. This is consistent with conceptualizations of social phobia as lying on a continuum with avoidant personality traits., Conclusions: Support for the dimensionality of social phobia has important implications for future research, assessment, treatment, and public policy.

Objective: To profile the Australian adults who are caring for a relative with a mental disorder., Method: Data came from the 2007 National Survey of Mental Health and Wellbeing 2007 (NSMHWB), a nationally representative household survey of 8841 individuals aged between 16 and 85 years., Results: Many people act as carers: 15% of the Australian adult population, or nearly 2.4 million individuals. The strongest predictors of being a carer are being female and being in a relatively older age bracket. Carers provide a range of emotional and practical supports to close relatives with a range of mental disorders, most notably high prevalence disorders. Their relatives' health problems cause them considerable worry, anxiety and depression, and their caring role can be associated with high financial costs., Conclusions: Carers are significant stakeholders in the mental health system. Providing support for carers is crucial, particularly because their own mental health and well-being may be affected by their care-giving role. The nature of this support should take into account their large numbers, their profile and the role they perform.

Objective: The aim of the present study was to report the prevalence and patterns of 12 month comorbidity in the 2007 National Survey of Mental Health and Wellbeing (2007 NSMHWB). In this paper the comorbidity between common mental disorders (affective, substance use and anxiety) and between physical and mental disorders is examined., Method: The 2007 NSMHWB was a nationally representative household survey of 8841 Australian adults (16-85 years) that assessed participants for symptoms of the most prevalent ICD-10 mental disorders., Results: The common mental disorder classes (affective, anxiety and substance use disorders) often occur together and 25.4% of persons with an anxiety, affective or substance use disorder had at least one other class of mental disorder. A small proportion (3.5%, 95% confidence interval (CI) = 2.3-4.7%) had all three classes of disorder. Mental disorder and physical disorder comorbidity was also common, with 28% (95%CI = 25.1-30.9%) of those with a chronic physical disorder also having a mental disorder. Comorbidity was associated with greater severity and greater health service use., Conclusions: Comorbidity is widespread and remains a significant challenge for the delivery of effective health-care services and treatment.

Objective: To provide a description of the methods and key findings of the 2007 Australian National Survey of Mental Health and Wellbeing., Method: A national face-to-face household survey of 8841 (60% response rate) community residents aged between 16 and 85 years was carried out using the World Mental Health Survey Initiative version of the Composite International Diagnostic Interview. Diagnoses were made according to ICD-10. Key findings include the prevalence of mental disorder, sex and age distributions of mental disorders, severity of mental disorders, comorbidity among mental disorders, and the extent of disability and health service use associated with mental disorders., Results: The prevalence of any lifetime mental disorder was 45.5%. The prevalence of any 12 month mental disorder was 20.0%, with anxiety disorders (14.4%) the most common class of mental disorder followed by affective disorders (6.2%) and substance use disorders (5.1%). Mental disorders, particularly affective disorders, were disabling. One in four people (25.4%) with 12 month mental disorders had more than one class of mental disorder. One-third (34.9%) of people with a mental disorder used health services for mental health problems in the 12 months prior to the interview., Conclusions: Mental disorders are common in Australia. Many people have more than one class of mental disorder. Mental disorders are associated with substantial disability, yet many people with mental disorders do not seek help for their mental health problems.

Objectives: It has been previously argued that the methodology used by the Composite International Diagnostic Interview version 2.1 to assess the substance-induced and general medical condition exclusion criteria are inadequate. As a result prevalence estimates generated from epidemiological studies using this interview may be underestimated. The purpose of the current study was to examine the substance-induced and general medical condition exclusion criteria in the Australian National Survey for Mental Health and Well-being and determine the impact that they have on prevalence estimates of the common mental disorders., Method: Data from the 1997 Australian National Survey of Mental Health and Well-being were analysed. Frequencies were generated as an indication of how many respondents believed that their psychiatric symptoms were always due to a substance or general medical condition. New DSM-IV prevalence estimates were calculated ignoring the application of the substance-induced and general medical condition exclusion criteria and compared to standard DSM-IV prevalence estimates., Results: The effect of the substance-induced and general medical condition exclusion criteria on final prevalence rates were minimal, with approximately a 0.1% increase when the exclusions were ignored. This equates to a relative difference ranging from no difference for generalized anxiety disorder to an increase of 12% of the base prevalence estimate for agoraphobia., Conclusions: In surveys that use the Composite International Diagnostic Interview version 2.1 the substance-induced and general medical condition exclusion criteria have a minor impact on determining final case definition in the majority of mental disorders.

Objective: Past taxometric studies of depression have yielded equivocal results. Diversity of sample type may provide one explanation for this. The aim of the present study was to examine the latent structure of depression across clinical and community samples using exactly the same taxometric procedures involving exactly the same indicators of depression., Method: Two taxometric procedures, MAXEIG (maximum eigenvalue) and MAMBAC (mean above minus mean below a cut), were carried out on a clinical sample of 960 outpatients with mood and anxiety disorders. Simulated categorical and dimensional data sets as well as other consistency tests aided in the interpretation of the research data. Results were compared to a prior taxometric analysis in a community sample., Results: The results of the current taxometric analyses were consistent with a dimensional latent structure and were compatible with the findings from identical analyses in a community sample., Conclusions: The findings of the current study highlight the importance of identifying factors that may contribute to, and explain, differences in the identified latent structure of depression.

Objective: The aim of the current study was to examine two major assumptions behind the DSM-IV diagnosis of major depressive episode (MDE): that depression represents a distinct category defined by a valid symptom threshold, and that each depressive symptom contributes equally to the diagnosis., Methods: Data were from the Australian National Survey of Mental Health and Wellbeing. Participants consisted of a random population-based sample of 10 641 community volunteers, representing a response rate of 78%. DSM-IV diagnoses of MDE and other mental disorders were obtained using the Composite International Diagnostic Interview, version 2.0. Analyses were carried out on the subsample of respondents who endorsed either depressed mood or loss of interest (n =2137). Multivariate linear regression analyses examined the relationship between the number and type of symptoms and four independent measures of impairment., Results: The relationship between the number of depressive symptoms and the four measures of impairment was purely linear. Three individual symptoms (sleep problems, energy loss, and psychomotor disturbance) were all independent predictors of three of the four measures of impairment., Conclusions: Counting symptoms alone is limited in guiding a clear diagnostic threshold. The differential impact of individual symptoms on impairment suggests that impairment levels may be more accurately estimated by weighting the particular symptoms endorsed.