Australian & New Zealand Journal of Psychiatry

To provide critical feedback to public mental health services, Australian governments developed and implemented the Your Experience of Service survey to capture consumers’ experiences of mental health care. The grey literature reports several domain structures of the survey, but these neither used data collected during routine service delivery nor have been peer-reviewed. This study sought to confirm a widely used six-domain structure of the Your Experience of Service and examine for other structures, including one informed by the CHIME five-domain framework based on the concept of personal recovery. Personal recovery is considered best mental health service practice.

Consumer-reported Your Experience of Service data for years 2019-21 were obtained from Queensland (n = 8564) and South Australia (n = 2536) Health Departments. Exploratory and confirmatory factor analyses on subsets of data were conducted to determine the best fit domain structure. Means, Cronbach’s alphas and correlations were used to examine structure and reliability of the measured factors.

The four factors, respectful environment, making a difference, providing information and support and supporting active participation of consumers, carers and family, were found to statistically best represent the data sets. The original six domains were partly supported within the four domains however the hypothesised five-factor CHIME personal recovery structure was not supported by the analyses.

The findings highlight that a four-domain structure be reported in future and illustrate opportunities to improve the Your Experience of Service survey’s ability to more accurately measure consumers’ experiences with mental health services, including items measuring personal recovery, and therefore maximise its value and utilisation in practice.

To estimate the proportions and correlates of Australian young people who consulted with health professionals or used services via digital technologies for their mental health in 2020–2022.

Data from 16- to 24-year-olds (N = 1620) in the 2020–2022 Australian National Survey of Mental Health and Wellbeing were analysed to estimate proportions, population counts and unadjusted odds ratios of past-year health professional consultations and use of services via digital technology for mental health within geographic regions. Logistic regression models explored socio-economic, psychosocial and clinically meaningful correlates of past-year consultation in the full sample, metro subgroup and regional, rural and remote subgroup.

In total, 24.2% of Australian young people consulted with a health professional for their mental health in the past year. Of those with a probable 12-month Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) mental health condition, 46.3% consulted a health professional. This proportion differed by sex (male: 34.2%, female: 55.6%) and symptom severity (mild: 20.0%, moderate: 47.8%, severe: 66.0%) but did not vary by geographic region. One-in-ten (9.9%) young people used other services via digital technologies for their mental health in the past year, doubling among those with a probable 12-month mental health condition (18.8%), and increasing with severity (mild or moderate: 14.2%, severe: 33.6%). Different factors were associated with service use in different regions.

Experiences of young people accessing mental health care in Australia differ by geographic region of residence, neighbourhood disadvantage, sex and disorder class. Australia’s mental health care system must facilitate diverse pathways to care that are responsive to young people’s needs and preferences.

Suicide and self-harm are significant issues globally. Accurate, efficient and comprehensive data are required to identify people who present to Emergency Departments due to self-harm to receive current accepted interventions and to develop effective health policies and responses. Current methods for identifying people presenting with these behaviors can be time- and labor-intensive or can underestimate the true figure.

This study investigated the use of a novel machine learning-based Natural Language Processing program developed to quantify the number of Emergency Department presentations which were related to suicidal or self-harm ideation or behavior. The program identifies these presentations based on Emergency Department triage notes. We compared the Natural Language Processing program with alternative methods for identifying suicide or self-harm related presentations, including International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification coding and keyword searching.

Using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification codes included with the dataset, 10,399 Emergency Department presentations related to suicide or self-harm were identified for the period July 2015 to June 2022, while the Natural Language Processing program found 27,298 presentations over the same period with a precision of 0.89 and a recall of 0.94. All methods were evaluated by comparing their identifications with a set of manually identified presentations. Natural Language Processing identification was the most appropriate for providing an accurate, comprehensive and efficient quantification.

This study revealed that less than 40% of Emergency Department presentations related to suicide or self-harm are identified using existing methods in the Australian Capital Territory. By providing an improved identification method, this study enables more accurate analysis and understanding of the issues of suicide and self-harm.

The Neuropsychiatry Unit Cognitive Assessment is a valid and reliable screening tool used in detecting cognitive deficits in a range of neurological and psychiatric conditions. We aimed to develop abbreviated versions of the Neuropsychiatry Unit Cognitive Assessment tool using retrospective data, and to assess their psychometric performance in distinguishing between healthy cognition and dementia.

Healthy controls (n = 132, 41%) and those with dementia (n = 191, 59%) were randomised into a ‘training’ cohort (n = 226, 70%) for the development and a ‘testing’ cohort (n = 97, 30%) for validation of the short-form versions. Receiver-operating characteristic curves were first computed for each of the 24 original Neuropsychiatry Unit Cognitive Assessment items. Items were ranked according to area under the curve values to create five-, 10- and 15-item short-form versions, which were subsequently validated.

The psychometric properties of the Neuropsychiatry Unit Cognitive Assessment short-form versions were comparable with the original, with all maintaining high convergent validity and reliability. Of the three versions, the 10-item version strikes the ideal balance of breadth and brevity. With a cut-off score of 42/54, the 10-item version generated similar sensitivity, specificity and predictive values for dementia as the original Neuropsychiatry Unit Cognitive Assessment, with a sensitivity of 0.98, specificity of 0.95, and positive and negative predictive values of 0.97.

The 10-item Neuropsychiatry Unit Cognitive Assessment has strengths in its shorter administration time, of approximately 10 minutes, high reliability and validity, and retention of items from each cognitive domain from the original Neuropsychiatry Unit Cognitive Assessment. Future research may involve testing these short forms in non-tertiary settings, across dementia subtypes and in non-dementia groups.

There is a well-established trend of increasing prevalence of mental health disorders among children and young people. Understanding patterns across diagnostic categories and predicting future changes is crucial for effective interventions and service planning.

We employed advanced time series analysis techniques, autoregressive integrated moving average-based time series modelling and forecasting, to analyse two decades of routinely collected data from the Western Australian Child and Adolescent Mental Health Services system. The large-scale dataset, with consistent sampling intervals, enabled robust time series analyses to account for secular, seasonal and random fluctuations. Models estimated both historical and forecasted future trends in mental health presentations at Western Australian Child and Adolescent Mental Health Services.

Modelling of historical data from 2004 to 2024 shows significant increases for anxiety disorders, mood disorders, personality disorders, sleep disorders, attention deficit hyperactivity disorder (ADHD) and autism and eating disorders. Forecasting to 2044 suggests that while anxiety disorders will decrease, ADHD, autism, eating disorders and sleep disorders will continue to increase.

We have established autoregressive integrated moving average modelling and forecasting as a robust, sophisticated and useful statistical approach to characterising historical and future trends in youth mental health. The ability to forecast into the future with confidence means we can identify what services are most needed and where gaps exist in current service provision or fund distribution permitting strategic allocation of finite resources and supporting complex funding decisions. Importantly, our findings encourage other health care services, locally and internationally, to use autoregressive integrated moving average modelling and forecasting to capitalize on routine health data to support proactive service planning initiatives.

People with mental health problems often report that they are avoided and discriminated against. However, less is known about the occurrence of supportive actions. This study aimed to investigate the prevalence in Australian adults of actions recommended by expert consensus mental health first aid guidelines, as well as actions not recommended.

A national survey was carried out with 6045 Australians aged 18+ who were members of the Life in Australia probability-based online panel. Participants were asked about actions they intended to take to support a person with a mental health problem or in a mental health crisis. Those who had actually provided support to someone in the past 12 months were asked about what supportive actions they took, while those who had personally had a mental health problem were asked what support they had received.

Respondents more frequently reported providing actions that were recommended in mental health first aid guidelines than those not recommended (medians across actions of 88.2% vs 37.8%). However, people who had a mental health problem in the past 12 months reported actually receiving recommended actions less frequently (median across actions of 65.5%). Actions to support a person at suicide risk were particularly in need of improvement, with only 41.8% of suicidal persons being asked about suicidal thoughts.

The findings show a need to further upskill Australian adults on how best to support people with mental health problems or in a mental health crisis, particularly those at suicide risk.

The aim of the present study was to undertake a retrospective analysis of national data on psychostimulant prescription for attention-deficit hyperactivity disorder for youths aged 5 to 17 years in Australia for the period 2003 to 2022.

An area-based national data set (including number of individuals and total dispensing) was used to analyse: (1) total prescription patterns over the period; (2) geographical variation in prescription by state/territory; and (3) socioeconomic variation of prescriptions by postcode.

Four major findings were observed over the period: (1) prescriptions per thousand rose sixfold; (2) variance of standardised prescription levels by state and territory are narrowing around the national average; (3) standardised prescription levels vary by socioeconomics of postcode but variance is narrowing around the national average; and (4) the highest socioeconomic decile has lifted from the lowest standardised prescription ratio to the highest between census years 2006 to 2021.

Standardised prescription levels in Australia are narrowing around the national average. Findings for both individual prescriptions and total dispensing are similar, providing little evidence for large quantum of drug use. Youth from lower socioeconomic regions are slightly more likely to be prescribed medication. Youth from the highest socioeconomic decile are now much more likely to be prescribed medication. The was an increase in prescription levels across the first 2 years of COVID-19. The drivers behind these changes are worthy of further research.

Clozapine is the most effective therapy for treatment-resistant schizophrenia, yet adverse drug reactions (ADRs) limit its use. The concurrent ADR burden in outpatients and its relation to psychotropic polypharmacy, tobacco smoking and measured clozapine exposure has not been well characterised.

We conducted a retrospective, cross-sectional review of medical records for 360 adults receiving maintenance clozapine at a dedicated outpatient clinic. Adverse drug reactions (ADRs) were ascertained using a standardised patient checklist alongside clinical measures. We used multivariate logistic regression to estimate the association between antipsychotic polypharmacy and the presence of ADRs, and negative binomial regression to quantify its association with ADR burden. We conducted a log-linear model to evaluate dose-concentration compensation in tobacco smokers.

At the clinic visit, 89.6% had ⩾1 symptomatic ADR. The most prevalent were metabolic syndrome (71.8%), hypersalivation (64.7%) and tachycardia (61.2%). Antipsychotic augmentation (51.4%) was independently associated with ADRs (adjusted odds ratios [aOR] = 3.38, 95% confidence interval [CI] = 1.41–8.06) and a 28% higher ADR count per person (incidence-rate ratio [IRR] = 1.28, 95% CI = 1.11–1.48). Smokers received higher doses yet had lower plasma concentrations, suggesting incomplete dose compensation for CYP1A2 induction and had higher odds of antipsychotic augmentation (odds ratio [OR] = 2.50, 95% CI = 1.53–4.10).

In maintenance clozapine care, persistent ADRs were common and were more frequent in patients receiving antipsychotic augmentation. Smokers were under-exposed to clozapine and were more likely to receive antipsychotic augmentation. Services should implement structured ADR surveillance and prioritise therapeutic drug monitoring-guided dose optimisation, particularly in smokers, before considering antipsychotic augmentation.