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Background: Children and adolescents with intellectual disability are at risk of developing psychiatric symptoms and disorders; yet, the estimates reported in the literature have been inconsistent, presenting a potential barrier for service planning and delivery. Sources of variability could arise from differences in measurement instruments as well as subgroup membership by severity of intellectual disability, gender and age. This systematic review aimed to address these gaps. Method: MEDLINE and PsycINFO databases were searched from inception to 2018 and selected studies were reviewed. Studies were included if they reported point prevalence estimates of mental health symptomology or diagnoses in a general population of 6- to 21-year-old individuals with intellectual disability. The Joanna Briggs Institute Prevalence Critical Appraisal Checklist was applied to eligible papers to appraise their scientific strength. Pooled prevalence for mental health symptomology was determined using a random-effects meta-analysis. Results: A total of 19 studies were included, including 6151 children and adolescents. The pooled prevalence estimate captured by the Developmental Behaviour Checklist was 38% (95% confidence interval = [31, 46]), contrasting with 49% (95% confidence interval = [46, 51]) captured by the Child Behaviour Checklist; both rates were higher than a non-intellectual disability population. Severity of intellectual disability did not significantly influence the Developmental Behaviour Checklist risks. Insufficient data were available to conduct statistical analyses on the effects of age, gender and socioeconomic status. Of diagnosed psychiatric disorders, attention deficit/hyperactivity disorder (30%), conduct disorder (3–21%) and anxiety disorders (7–34%) were the most prevalent conditions. Conclusion: This review consists of the largest sample hitherto evaluated. In the intellectual disability population, mental health comorbidities could be better detected by a symptom phenotype than a psychiatric diagnostic phenotype. Crucially, future research needs to address the effect of measurement validity in the intellectual disability population. Estimated prevalence rates were high compared to the general population, indicating the importance of systematic screening, case detection and appropriate management. [ABSTRACT FROM AUTHOR]

Background: The need to understand and respond to the unique characteristics and drivers of suicidal behaviour in rural areas has been enabled through the Australian Government's 2015 mental health reforms facilitating a move to an evidence-based, regional approach to suicide prevention. However, a key challenge has been the complex decision-making environment and lack of appropriate tools to facilitate the use of evidence, data and expert knowledge in a way that can inform contextually appropriate strategies that will deliver the greatest impact. This paper reports the co-development of an advanced decision support tool that enables regional decision makers to explore the likely impacts of their decisions before implementing them in the real world. Methods: A system dynamics model for the rural and remote population catchment of Western New South Wales was developed. The model was based on defined pathways to mental health care and suicidal behaviour and reproduced historic trends in the incidence of attempted suicide (self-harm hospitalisations) and suicide deaths in the region. A series of intervention scenarios were investigated to forecast their impact on suicidal behaviour over a 10-year period. Results: Post-suicide attempt assertive aftercare was forecast to deliver the greatest impact, reducing the numbers of self-harm hospitalisations and suicide deaths by 5.65% (95% interval, 4.87−6.42%) and 5.45% (4.68−6.22%), respectively. Reductions were also projected for community support programs (self-harm hospitalisations: 2.83%, 95% interval 2.23−3.46%; suicide deaths: 4.38%, 95% interval 3.78−5.00%). Some scenarios produced unintuitive impacts or effect sizes that were significantly lower than what has been anticipated under the traditional evidence-based approach to suicide prevention and provide an opportunity for learning. Conclusion: Systems modelling and simulation offers significant potential for regional decision makers to better understand and respond to the unique characteristics and drivers of suicidal behaviour in their catchments and more effectively allocate limited health resources. [ABSTRACT FROM AUTHOR]