The current Guidelines aim to provide evidence-based management recommendations for treatment of people living with schizophrenia in Australia and Aotearoa New Zealand. The Australian and New Zealand Journal of Psychiatry (ANZJP) commissioned a panel of experts to establish these Guidelines. The existing literature was reviewed to address key health questions. The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach, and the strength of the recommendation was determined by the panel. The ANZJP GRADE Guidelines examined the current evidence base for a range of areas relevant to treatment for people with schizophrenia including: initial physical health assessment; pharmacological treatment; psychological and psychosocial interventions; family, whānau and carers; psychiatric comorbidities; physical health and lifestyle interventions; and special populations. It is hoped that the current Guidelines provide useful recommendations in important aspects of care for people living with schizophrenia and their family, whānau and carers in Australia and Aotearoa New Zealand, both at the individual and systemic levels.
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.
Psychiatry currently faces the following four intersecting challenges: technological disruption through artificial intelligence (AI); the loss of exclusive prescribing authority; escalating systemic constraints within public psychiatry, and market-driven models in private practice. Together, these forces challenge the specialty's traditional identity, narrowing its scope towards containment rather than recovery and meaning-making, and risk diminishing the specialty's relevance if left unaddressed. To respond, we propose a structured approach based on three concentric domains of action, the circles of control, influence, and concern, to differentiate what psychiatry can act on directly, shape through collaboration, or advocate for systemically. Within the circle of control, the AIMS framework (Assessment, Intervention, Monitoring, Step-Up/Step-Down) offers a practical structure to refocus care on relational depth, ethical decision-making, and contextual continuity. The circle of influence is addressed through reform in training and interdisciplinary culture, equipping psychiatrists to lead reflectively and integrate technology wisely. Reclaiming psychiatry's biopsychosocial identity lies at the centre of this renewal, combining biological sophistication, psychological fluency, and social awareness to restore the discipline's integrative purpose. Rather than competing with AI, psychiatry must redefine its value through those capacities that cannot be automated: empathy, interpretation, and ethical discernment. The specialty's future will be secured not by speed or compliance, but by its ability to hold complexity, foster recovery, and sustain human connection in an increasingly algorithmic world.
Lifestyle-based interventions are increasingly popular for treating depression, yet a comprehensive evaluation of who benefits or may be harmed is limited. This study examined predictors of benefits and safety events, and the types of these events experienced by participants in the CALM trial, which compared lifestyle therapy with psychotherapy for depression. 'Benefit' was defined as a ⩾ 50% reduction in Patient Health Questionnaire-9 scores, along with self-reported or staff-observed safety events. Generalised estimating equations identified predictors of benefit and safety events, reporting risk ratios and beta coefficients. Exploratory subgroup analyses were conducted by treatment arm (lifestyle vs psychotherapy). Of 132 completers, 38% met criteria for benefit and 78% reported at least one safety event. Older age (RR = 1.14, 95% CI [1.01, 1.30]) and being born overseas (RR = 1.59, 95% CI [1.06, 2.38]) predicted benefit. Older age (β = 0.16, 95% CI [0.05, 0.26]) and higher baseline glucose (β = 0.16, 95% CI [0.10, 0.23]) were associated with more safety events. Subgroup analyses indicated that age predicted benefit in the psychotherapy arm, while place of birth predicted benefit in the lifestyle arm. Safety events were more common in the lifestyle arm among participants who were older or had elevated glucose. In the CALM trial, older age and being born overseas predicted benefit, while older age and higher glucose levels were associated with greater safety events. These findings provide clinicians and consumers with a clearer risk-benefit profile of behavioural therapies and support personalised treatment based on consumer characteristics. Australian and New Zealand Clinical Trials Registry (https://www.anzctr.org.au/; ACTRN12621000387820).
Artificial intelligence is emerging as a powerful tool for improving mental health research and care, offering opportunities for early intervention, personalised treatment, ongoing monitoring and enhanced capacity for the mental health workforce. In Australia, however, the integration of artificial intelligence into mental health systems is hindered by substantial knowledge, policy and regulatory gaps. This paper outlines two urgent priorities for the safe and effective use of artificial intelligence in mental health: (1) closing knowledge gaps and (2) developing robust policy and regulatory frameworks. We outline emerging opportunities, including artificial intelligence-driven technologies that could improve affordability, accessibility and treatment outcomes, as well as tools to strengthen the mental health workforce, alongside key risks such as inadequate regulation, insufficient monitoring or reporting of adverse events, perpetuation of bias in research, data privacy and security concerns, and lack of human oversight. We provide 10 recommendations to guide the safer adoption of artificial intelligence for mental health in Australia. These include the creation of a National AI in Mental Health Expert Advisory Group, evidence-based national guidelines, expanded data collection on artificial intelligence use in mental health, Australian-led research that considers priority populations, development of Australian databases for training artificial intelligence models, targeted investment in artificial intelligence technologies that can support an under-resourced mental health workforce, creation of artificial intelligence mental health literacy resources for the Australian public, and regulations that hold developers and providers accountable for the safety of their technologies.
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.
To test the relative importance of key social determinants (as specified in the Australian National Suicide Prevention Strategy 2025-2035) associated with suicidal ideation and non-suicidal self-injury in Australian youth. Representative data from the cross-sectional National Study of Mental Health and Wellbeing 2020-2022 were analysed for Australian youth aged 16-24 years. We used population-weighted multivariable logistic regression analyses to predict 12-month suicidal ideation and non-suicidal self-injury from several social determinants: household income, receipt of government pension/allowance payments, study/work engagement, experience of homelessness, household financial stress, urban residence and social connectedness. Social connectedness was a statistically significant predictor in both models, such that a one-unit increase reduced the odds of 12-month suicidal ideation by 52% and non-suicidal self-injury by 55%. Other significant predictors were having ever experienced homelessness, which increased the odds of suicidal ideation by 116%, while each household financial stressor (e.g. not being able to pay bills on time) increased the odds of non-suicidal self-injury by 34%. No other social determinant was statistically significant in the multivariable models. Social connectedness was the only social determinant associated with lower odds of both suicidal ideation and non-suicidal self-injury in youth. Although further longitudinal studies are needed to confirm these benefits, our cross-sectional findings provide initial support for the National Suicide Prevention Strategy's emphasis on strengthening social inclusion and economic security as key prevention strategies. Our findings highlight the importance of implementing and evaluating connectedness interventions for youth as a priority next step in suicide and NSSI prevention efforts.
This study examined the effectiveness of the Better Access initiative using outcome data from real-world practice settings. We used anonymised data from four datasets to assess outcomes for consumers over 86,121 episodes of care. The datasets contained routinely captured episode-level data from the practices of psychologists and other eligible Better Access providers. Across the datasets, outcomes were assessed on 11 different measures (mostly consumer-rated measures of depression and anxiety symptoms, psychological distress, functioning and wellbeing). We conducted purpose-designed analyses with three of the datasets (83,346 episodes), examining score changes on given measures between the first and last assessment occasion within an episode. We used preexisting outputs for the fourth dataset (2775 episodes), again considering change from the beginning to the end of the episode. In the purpose-designed analyses, consumers' mental health improved in around 50-60% of episodes. However, consumers showed no change or experienced deterioration in their mental health in 20-30% and 10-20% of episodes, respectively. Those with more severe baseline scores had a greater probability of showing improvement. The preexisting outputs also identified significant improvements, particularly in episodes where treatment was complete. Better Access is achieving reductions in symptoms and improvements in functioning and wellbeing for the majority of consumers. A minority of consumers do not have these sorts of positive outcomes, however, and further work is required to understand why. Routine measurement of outcomes - particularly consumer-rated outcomes - would enable ongoing monitoring of the extent to which Better Access is achieving its goals.
To describe characteristics, service use and clinical changes among people who received treatment through Australia's Better Access programme. We re-analysed data from the usual care arms of two randomised controlled trials of tailored care approaches for depression and anxiety in primary care (Target-D, 2016-2019; Link-me, 2017-2019). Participants completed measures of depression and anxiety symptoms, quality of life and days out of role due to psychological distress over 12 months. They reported the use of mental health services from different providers/settings; from this, we classified a subset as likely Better Access treatment users. Of 394 Target-D and 547 Link-me participants, one-third were classified as having used Better Access treatment sessions over 12 months. They used five to seven Better Access sessions on average; half to two-thirds paid out-of-pocket costs (median $78-$89 per session). The number of Better Access sessions and other mental health services they used increased with severity of mental health problems. At baseline, Better Access treatment users reported more severe symptoms and more days out of role than those who used other or no mental health services, and poorer quality of life than those who used no services. Approximately half (43-55%) of Better Access treatment users showed improvements in mental health over 12 months. Among those with severe problems, improvements in depression and anxiety symptoms were associated with using 5+ Better Access sessions. Better Access treatment is used by people with different levels of mental health need. Many experience improvements in their mental health and functioning.
To synthesise the primary literature reporting the incidence of suicide in general hospitals. Peer-reviewed papers reporting suicides among the medically and surgically admitted patients of general hospitals were located by searches of MEDLINE, PsycINFO and EMBASE between 1946 and 2025. Random effects meta-analyses were used to estimate the number of suicides per 1,000,000 admissions, the rate of suicide per 100,000 patient years and the proportion of suicides by common suicide methods. Temporal trends were examined with mixed-effects meta-regression. The pooled number of suicides per 1,000,000 admissions was 16.3 (95% confidence interval = [9.8, 27.0]). The pooled rate of suicide per 100,000 patient-years was 82.7 suicides (95% confidence interval = [49.6, 115.7]). Jumping accounted for 52.1% (95% confidence interval = [39.4, 64.4]) of suicides, and 20.6% (95% confidence interval = [13.1, 30.8]) were by hanging. The number of suicides per admission declined over time (point estimate of slope = -0.039, standard error = 0.01, p < 0.0004) to 4.7 suicides per 1,000,000 admissions (95% confidence interval = [1.7, 12.9], I2 = 97) in nine studies published after 2010. The rate of suicide per patient year was unchanged over 60 years of primary research (slope ⩽ -0.0001, standard error = 0.0001, p = 0.97). The rate of suicide in general hospital inpatients is an order of magnitude higher than the global suicide rate. While general hospital suicide is a critical patient safety concern, the stability in suicide rates over time highlights the persistent difficulty of suicide prevention in this setting.
This study was conducted as part of an evaluation of the Better Access initiative. It examined (1) pathways into Better Access treatment; (2) the proportion of Better Access treatment users who are 'new'; (3) patterns of use and non-use of Better Access treatment services in relation to need; and (4) socioeconomic differences in Better Access treatment service use. We used linked administrative and survey data available through the Person-Level Integrated Data Asset (PLIDA). More specifically, we used Medicare Benefits Schedule (MBS) data, Pharmaceutical Benefits Scheme (PBS) data, 2016 Census data, and data from the 2017/18 National Health Survey. About two-thirds of individuals who have had a mental health treatment plan prepared for them receive Better Access treatment services (albeit often after a considerable wait), but one-third do not. Although Better Access is reaching those with high levels of need, access is not equitable. It is harder for new users to access the programme than it was previously, as the number of continuing users and the number of treatment sessions provided to them have increased. People on low incomes are less likely to receive psychological treatment through Better Access (and more likely to be prescribed antidepressant or anxiolytic medication), and if they do receive Better Access services, they typically wait longer than their high-income counterparts to see a provider. Better Access appears to be responsive to need, but there are equity issues regarding its accessibility. These equity issues should be addressed as Better Access continues.
This study aimed to provide a picture of who uses Better Access treatment services, how they do so and what the benefits are. We conducted an observational prospective study involving independent cohorts from the Australian Longitudinal Study on Male Health (Ten to Men [TTM]) and the Australian Longitudinal Study of Women's Health (ALSWH). We used data from two pairs of baseline (T0) and follow-up (T1) waves for those aged ⩾ 18 in TTM and those in the 1989-1995, 1973-1978 and 1946-1951 cohorts in ALSWH. Using survey data and linked Medicare Benefits Schedule (MBS) claims data, we identified participants with 'mental health need' at T0 who had and had not used Better Access treatment services between T0 and T1. Proportions of Better Access users varied across study cohorts and analyses, with 45% being the highest. Those who used Better Access treatment services typically accessed 5-6 sessions, usually from clinical psychologists and/or psychologists. Between half and three-quarters paid out-of-pocket costs (usually $80-$100/session). Typically, around half of those who used Better Access had better mental health at T1 than T0. Severity of mental health problems at baseline was strongly predictive of both Better Access use and improvements in mental health. Australian adults with mental health need make varying use of Better Access treatment services, but the programme appears to serve those with high levels of need relatively well.
Clinicians rely on clinical practice guidelines to inform evidence-based management of conditions. However, the quality and availability of clinical practice guidelines for mental health conditions in children and adolescents vary. This systematic review aimed to assess the quality of existing clinical practice guidelines and identify gaps to inform future guideline development in child and adolescent mental health. A systematic literature search was conducted to identify clinical practice guidelines for mental health conditions in children and adolescents published between April 2019 and April 2025. Using the Appraisal of Guidelines for Research and Evaluation II tool, identified clinical practice guidelines were assessed for rigour of development (n = 85) using a 70% cut-off. Gaps in the literature were identified by categorising guidelines based on the Diagnostic and Statistical Manual of Mental Disorders (5th ed., text rev.), ensuring comprehensive coverage while considering feasibility in guideline development. Nine of the 22 Diagnostic and Statistical Manual of Mental Disorders (5th ed., text rev.) categories were represented among the 20 clinical practice guidelines extracted. Literature gaps were identified for bipolar and related disorders, trauma and stressor-related disorders, sleep-wake disorders and neurocognitive disorders. In addition, gaps persisted in 13 categories where high-quality guidance was not identified. While methodological quality varied (M = 5.6/7 ± 0.7), guidelines that met threshold were identified for depressive disorders, attention deficit/hyperactivity disorder, autism spectrum disorder, anxiety disorders, feeding and eating disorders, and suicidal behaviours and non-suicidal self-injury. There is a high degree of variability in the quality of available clinical practice guidelines for child and adolescent mental health conditions, emphasising the need for more rigorous development and implementation standards. While some disorders have sufficient guidance, there are major gaps, necessitating the development of high-quality resources to enhance clinical impact.
Diversionary approaches seek to address criminal legal system involvement among people with psychosis and other mental illness. There is limited evidence examining health characteristics of people with psychosis in Australian criminal legal systems and how these vary with court outcomes, including diversion. We conducted a data-linkage study of 21,229 adults hospitalised with psychosis in New South Wales (June 2001 to December 2019) with a subsequent offence finalised in the New South Wales Local Court. We described psychosis types, co-occurring conditions and prior health service use and examined their associations with court outcome (diversion vs conviction) using logistic regression, adjusting for sociodemographic and legal factors. A total of 70.8% of participants had a schizophrenia spectrum disorder (substance-induced psychosis 22.6%; affective psychosis 6.6%). Co-occurring conditions were common (lifetime substance-related harm 84.8%; personality disorder 41.3%; neurodevelopmental disorder 17.5%; physical condition 25.6%), and 76.3% used mental health services in the year before the index offence. Affective and substance-induced psychoses were negatively associated with diversion vs schizophrenia spectrum disorders (adjusted odds ratios = 0.64 [95% confidence interval = 0.54-0.74] and 0.29 [95% confidence interval = 0.26-0.33], respectively). Duration of psychosis admissions and past-year mental health service use were positively associated with diversion, while in those with schizophrenia spectrum disorders, lifetime substance-related harm was negatively associated. Court defendants with psychosis have a complex health profile. Although people with schizophrenia spectrum disorders are more likely to be diverted than those with other psychosis types, substance use may inhibit diversion. Health and criminal legal system collaboration is needed to facilitate diversion and treatment for this group.
Suicide is one of the leading causes of death in children aged 14 years and under in Australia, and child maltreatment is consistently identified as an antecedent. Despite this, not enough is known about the pathways from child maltreatment to suicidal behaviour, hampering prevention efforts. In this perspective, we examine the association between (1) various types of childhood maltreatment, and (2) the presence of mental disorders, and subsequent suicidal behaviours in children aged 14 years and under. We present a conceptual model of childhood suicidal behaviours which incorporates both direct and indirect mechanisms by which maltreatment (and other risk factors) exert an influence. Bodily intrusive maltreatment, especially sexual and physical abuse, significantly increases the risk of suicidal behaviours in childhood. Other forms of maltreatment, such as neglect and emotional abuse, may also contribute. While the presence of a mental disorder is another prominent risk factor for suicidal behaviours in adolescents and adults, there is less evidence of this association in childhood. Efforts to prevent child maltreatment can support suicide prevention efforts in children and other age groups. In addition, screening for suicidal behaviours and targeted interventions should be prioritised for populations at increased risk, particularly children with a history of maltreatment and their families.
The Early Psychosis Prevention and Intervention Centre model has significantly shaped early intervention strategies for psychotic disorders, setting a benchmark for effective care and influencing practices globally. The model's effectiveness has been demonstrated through various trials and systematic reviews, highlighting its benefits in symptomatic relief, functional improvement and reduced hospitalisation. This paper explores and proposes advancements to the current model of care for early psychosis, incorporating recent developments and emerging evidence in the field. We highlight several areas to further enhance the Early Psychosis Prevention and Intervention Centre model. This includes highlighting the importance of interventions to reduce duration of untreated psychosis, maximising pharmacological and cognitive interventions, incorporating digital technologies for real-time feedback and personalised care, and access to physical health interventions to prevent unwanted long-term physical outcomes. In addition, the growing role of trauma-informed care, and more recently, peer support, as well as approaches and interventions for culturally diverse and high-risk populations, underscores the need for more inclusive and tailored interventions. Future directions also need to concentrate especially on the long-term outcome, which are less favourable and equity of access to high-quality services. The development of national and international collaborative research platforms, including Australia's new clinical quality registry and clinical trials network, also represents a significant step forward in generating robust evidence and refining care models. We suggest that to further progress the early psychosis field a personalised, data-informed approach is needed and that we find ways to harness technological innovations and collaborative networks to enhance care and subsequent treatment outcomes.
The dual-factor model of mental health postulates a role for positive mental health, alongside mental illness, in determining mental health care needs. Informed by this model, the present study delineated profiles of social-emotional competencies and difficulties during middle childhood in a population-based sample of girls and boys and determined their association with adolescent mental disorder diagnoses. Latent profile analyses were conducted across five indices of social-emotional competency and four indices of psychopathology that were measured by questionnaire self-report among 13,349 girls and 13,488 boys at age ~11 years. The association of the profiles with adolescent presentations to hospital or ambulatory services (ages ~12-17 years) were determined using logistic regression. Analyses yielded five profiles in each sex: complete mental health (44% girls; 42% boys), average mental health (30%; 33%), internalising symptoms with poor relationship skills (9%; 7%), externalising symptoms with poor self-management (12%; 9%) and low mental health (5%; 10%). Profiles associated differentially with adolescent presentations with any mental disorder, externalising disorders, internalising disorders and self-harm/suicidal ideation, identified in linked health records. Greater odds of any and specific mental disorder diagnoses were characteristic of all profiles relative to average mental health (adjusted odds ratios [aOR]: 1.7-3.3) except complete mental health (aOR: 0.7-0.9), with different strengths of association according to profile. Combining information on social-emotional competencies and psychopathology in middle childhood may help refine the provision of mental health promotion and early intervention to alleviate adolescent mental disorder.
Universal screening for perinatal mental illness is recommended in Australia; however, these tools do not screen for perinatal post-traumatic stress disorder (PTSD). While existing perinatal PTSD tools show validity, they vary in diagnostic agreement, and most are focused on PTSD following childbirth. Early detection of PTSD symptoms at any phase of perinatal care is critical to improve maternal/infant outcomes and engagement with effective treatment. Unfortunately, gaps remain in practice for identifying perinatal PTSD. The aim of the study was to develop a screening tool to detect current symptoms of perinatal PTSD or higher risk of developing the disorder, resulting from index perinatal event(s) or experience(s) during conception, pregnancy and the postpartum. If any perinatal trauma was endorsed, participants completed an online questionnaire and if consenting, a semi-structured clinical telephone interview during their current pregnancy. Twenty-five items were submitted for exploratory factor analysis, n = 114, and the results supported a two-factor solution. After removing items with poor loadings, a 17-item, two-factor solution explained 68.36% of the total variance. Each of the components had excellent internal consistency; component one α = .954 and component two α = .897. Following a receiver operating characteristic analysis n = 52, the optimal cutoff score of ⩾11 was identified with 90.9% sensitivity and 61% specificity. Moderate predictive validity of the tool shows promise for detecting those currently experiencing symptoms of perinatal PTSD and at higher risk of developing the disorder, supporting utility in clinical settings, pending future validation.
This systematic review and meta-analysis aimed to investigate the impacts of screen time and screen behaviours on suicidality and non-suicidal self-injury (NSSI) in children and young people. A systematic search was conducted of the following databases: CINAHL, PubMed, Embase, PsycARTICLES, PsycINFO, Scopus, and Web of Science. The search identified 61 eligible studies comprising 338,472 participants aged up to 18 years, drawn from 16 countries. A random-effects meta-analysis of odds ratios was conducted across 15 studies. A meta-analysis revealed that screen time was measured inconsistently across studies, yet frequent screen use - particularly nocturnal smartphone use - was significantly associated with increased odds of NSSI and suicidal behaviours. Internet addiction (IA) showed strong links to suicidal behaviours, often mediated by insomnia, depression, or anxiety. Internet gaming disorder (IGD) also predicted suicidality and NSSI, while mobile phone and social media addiction demonstrated weaker but significant associations. IA was positively associated with NSSI across all seven relevant studies. Structural models identified depression, loneliness, and interpersonal problems as key mediators. Some gender disparities emerged, with females reporting higher NSSI and suicidality, and males showing higher rates of digital addiction. While these findings highlight concerning associations between excessive screen time and suicidality, they are limited by methodological heterogeneity and inconsistency, raising questions about directionality, whether excessive screen time contributes to poor mental health, or pre-existing vulnerabilities drive increased screen use.
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.