A Prototype Software Framework for Transferable Computational Health Economic Models and Its Early Application in Youth Mental Health.

We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework.

Somatic symptoms, psychological distress and trauma after disasters: lessons from the 2014 Hazelwood mine fire and 2019-20 Black Summer bushfires.

BACKGROUND: Wildfires cause significant physical and mental ill-health. How physical and mental symptoms interact following wildfire smoke exposure is unclear, particularly in the context of repeated exposures. In this cross-sectional study we investigated how posttraumatic stress and general psychological distress associated with somatic symptoms in a community exposed to multiple smoke events. METHODS: A random weighted sample of 709 adults exposed to smoke during the 2014 Hazelwood coal mine fire in south-eastern Australia completed a survey in 2020. The survey coincided with the Black Summer wildfires that caused a similar period of smoke haze in the region. Participants self-reported somatic symptoms (PHQ-15) and mine fire-related posttraumatic stress (IES-R) experienced over the previous week, general psychological distress (K10) experienced over the previous four weeks, lifetime health diagnoses and demographic information. Associations between posttraumatic stress, general psychological distress, and each PHQ-15 somatic symptom were analysed using ordinal logistic regression models. RESULTS: Overall, 36.2% of participants reported moderate- or high-level somatic symptomology. The most frequent somatic symptoms were fatigue, limb pain, trouble sleeping, back pain, headaches, and shortness of breath. After controlling for confounding factors, general psychological distress and posttraumatic stress were independently associated with all somatic symptoms (except menstrual problems in females for posttraumatic stress). CONCLUSIONS: Results highlight the high prevalence of somatic symptoms and their association with general psychological distress and posttraumatic stress within a community in the midst of a second large-scale smoke event. It is essential that healthcare providers and public health authorities consider the interconnections of these conditions when supporting communities affected by climate-related disasters.

An overview of clustering methods with guidelines for application in mental health research.

Cluster analyzes have been widely used in mental health research to decompose inter-individual heterogeneity by identifying more homogeneous subgroups of individuals. However, despite advances in new algorithms and increasing popularity, there is little guidance on model choice, analytical framework and reporting requirements. In this paper, we aimed to address this gap by introducing the philosophy, design, advantages/disadvantages and implementation of major algorithms that are particularly relevant in mental health research. Extensions of basic models, such as kernel methods, deep learning, semi-supervised clustering, and clustering ensembles are subsequently introduced. How to choose algorithms to address common issues as well as methods for pre-clustering data processing, clustering evaluation and validation are then discussed. Importantly, we also provide general guidance on clustering workflow and reporting requirements. To facilitate the implementation of different algorithms, we provide information on R functions and libraries.

Accelerating youth mental health services research.

OBJECTIVE: We describe a research program to advance youth mental health service research in Australia, addressing two core knowledge gaps: the lack of available routine outcome measures and lack of understanding of how to assess and monitor complexity and heterogeneity in illness presentation and trajectory. CONCLUSIONS: Our research identifies better routine outcome measures (ROM) that are: designed specifically for the developmental nuances of the 12-25-year age range; multidimensional; and meaningful to young people, their carers, and service providers. Alongside much-needed new measures of complexity and heterogeneity, these tools will inform service providers to better meet the needs of young people presenting with mental health problems.

Understanding the complexity, patterns, and correlates of alcohol and other substance use among young people seeking help for mental ill-health.

PURPOSE: Use of alcohol and other substances is a multifaceted issue impacting young people across multiple life domains. This paper aims to elucidate patterns of substance use and associated demographic and clinical factors among young people seeking treatment for their mental health. METHODS: Young people (12-25 years old) were recruited from five youth-specific primary mental health ("headspace") services in Australia. Self-reported substance use and harms in the past 3 months were measured using WHO-ASSIST. Network analyses were conducted to evaluate interrelationships between use and harms associated with different substances. Subgroups were then identified based on whether participants reported using high centrality substances, and associated demographic and clinical factors were assessed with multinomial logistic regression. RESULTS: 1107 youth participated. 70% reported use of at least one substance in the past 3 months, with around 30% of those reporting related health, social, legal or financial problems. Network analysis highlighted substantial interconnections between use and harm indicators for all substances, with amphetamine-type stimulants (ATS) and cannabis being high central substances. Higher levels of substance use and harms were reported in subgroups with ATS or cannabis use and different risk factors were associated with these subgroups. CONCLUSIONS: Findings highlight the importance of screening for substance use in youth primary mental healthcare settings, offering a key opportunity for early intervention. Clinicians should be aware of the inner connections of use and harms of different drugs and the role of cannabis and amphetamine use as a marker for more substance use profiles.

Prevalence and Correlates of Tobacco Use in Young People Presenting to Australian Primary Mental Health Services.

INTRODUCTION: In Australian youth primary mental health settings it is unclear as to the rates and correlates of tobacco use at service entry. AIMS AND METHODS: We aimed to delineate the prevalence and correlates of recent tobacco use (eg, cigarettes, chewing tobacco, cigars, etc) in the past 3 months in young people at their first presentation to primary mental health services as a function of age. Cross-sectional self-report measures were collected using a tablet device from young people presenting to one of five Australian primary mental health (headspace) services. Logistic regression assessed correlates of past 3-month tobacco use in adolescents (12-17 years) and young adults (18-25 years). RESULTS: Regular (at least monthly) tobacco use in the past 3 months was found in 23.4% (n = 247, N = 1055) of the sample. Increasing age (odds ratio [OR] =1.47 per year; 95% confidence interval [CI]: 1.15 to 1.89), male sex (OR = 1.98; 95% CI: 1.02 to 3.83), being in a relationship (OR = 1.96; 95% CI: 1.01 to 3.82), and poorer functioning (OR = 0.95 per unit Social and Occupational Functioning Assessment Scale increase; 95% CI: 0.91 to 0.99) predicted regular tobacco use in adolescents, but not in young adults. Living in a regional location (OR = 2.10; 95% CI: 1.40 to 3.13) and not studying (OR = 0.47; 95% CI: 0.31 to 0.73) predicted tobacco use in young adults. Having a diagnosed mental illness other than depression and/or anxiety predicted tobacco use in both groups (adolescents OR = 2.49; 95% CI: 1.26 to 4.94; young adults OR = 1.80; 95% CI: 1.13 to 2.89). CONCLUSIONS: Nearly a quarter of young people with mental illness are using tobacco, supporting the need for early intervention approaches. Adapting treatment targets by age could improve the impact of interventions in adolescents versus young adults. Poor functioning and lack of engagement in education were associated with tobacco use in both age groups, respectively; however, more research is needed to determine the direction of these relationships. IMPLICATIONS: Young people with mental illness have a high prevalence of recent tobacco use and this is evident when they first present to youth primary mental health services. Youth-oriented mental health settings may provide a unique window for tobacco use prevention and early intervention to reduce smoking in people with mental illness, a priority population. Age-specific targeted approaches might be needed in adolescents and young adults.

Inequalities in Access to Mental Health Treatment by Australian Youths During the COVID-19 Pandemic.

OBJECTIVE: The authors aimed to evaluate changes in use of government-subsidized primary mental health services, through the Medicare Benefits Schedule (MBS), by young people during the first year of the COVID-19 pandemic in Australia and whether changes were associated with age, sex, socioeconomic status, and residence in particular geographical areas. METHODS: Interrupted time-series analyses were conducted by using quarterly mental health MBS service data (all young people ages 12-25 years, 2015-2020) for individual Statistical Area Level 3 areas across Australia. The data captured >22.4 million service records. Meta-analysis and meta-regression models estimated the pandemic interruption effect at the national level and delineated factors influencing these estimates. RESULTS: Compared with expected prepandemic trends, a 6.2% (95% CI=5.3%-7.2%) increase was noted for all young people in use of MBS mental health services in 2020. Substantial differences were found between age and sex subgroups, with a higher increase among females and young people ages 18-25. A decreasing trend was observed for males ages 18-25 (3.5% reduction, 95% CI=2.5%-4.5%). The interruption effect was strongly associated with socioeconomic status. Service uptake increased in areas of high socioeconomic status, with smaller or limited uptake in areas of low socioeconomic status. CONCLUSIONS: During 2020, young people's use of primary mental health services increased overall. However, increases were inequitably distributed and relatively low, compared with increases in population-level mental health burden. Policy makers should address barriers to primary care access for young people, particularly for young males and those from socioeconomically disadvantaged backgrounds.

Heterogeneity of quality of life in young people attending primary mental health services.

AIMS: The utility of quality of life (QoL) as an outcome measure in youth-specific primary mental health care settings has yet to be determined. We aimed to determine: (i) whether heterogeneity on individual items of a QoL measure could be used to identify distinct groups of help-seeking young people; and (ii) the validity of these groups based on having clinically meaningful differences in demographic and clinical characteristics. METHODS: Young people, at their first presentation to one of five primary mental health services, completed a range of questionnaires, including the Assessment of Quality of Life-6 dimensions adolescent version (AQoL-6D). Latent class analysis (LCA) and multivariate multinomial logistic regression were used to define classes based on AQoL-6D and determine demographic and clinical characteristics associated with class membership. RESULTS: 1107 young people (12-25 years) participated. Four groups were identified: (i) no-to-mild impairment in QoL; (ii) moderate impairment across dimensions but especially mental health and coping; (iii) moderate impairment across dimensions but especially on the pain dimension; and (iv) poor QoL across all dimensions along with a greater likelihood of complex and severe clinical presentations. Differences between groups were observed with respect to demographic and clinical features. CONCLUSIONS: Adding multi-attribute utility instruments such as the AQoL-6D to routine data collection in mental health services might generate insights into the care needs of young people beyond reducing psychological distress and promoting symptom recovery. In young people with impairments across all QoL dimensions, the need for a holistic and personalised approach to treatment and recovery is heightened.

Psychometric properties of a brief, self-report measure of social inclusion: the F-SIM16.

AIMS: A disproportionate number of people with mental ill-health experience social exclusion. Appropriate measurement tools are required to progress opportunities to improve social inclusion. We have developed a novel measure, the Filia Social Inclusion Measure (F-SIM). Here we aimed to present a more concise, easy-to-use form, while retaining its measurement integrity by (i) refining the F-SIM using traditional and contemporary item-reduction techniques; and (ii) testing the psychometric properties of the reduced measure. METHODS: Five hundred and six participants completed the F-SIM, younger and older groups of people with serious mental illness (including psychosis, mood, anxiety disorders) and same-aged community counterparts. The F-SIM was completed at baseline and 2-week follow-up, alongside other measures (including social inclusion, loneliness). The F-SIM was refined using multidimensional scaling network analysis, confirmatory factor analysis and item response theory. The psychometric evaluation included assessment of dimensionality, internal consistency, test-retest reliability, discriminant ability and construct validity. RESULTS: The F-SIM was reduced from 135-items to 16; with 4-items in each domain of housing and neighbourhood, finances, employment and education and social participation and relationships. Psychometric properties were sound, including strong internal consistency within domains (all α > 0.85) and excellent overall (α = 0.92). Test-retest reliability was also high (γ = 0.90). Differences between groups were observed; clinical subgroups consistently reported lower levels of social inclusion compared to community counterparts. CONCLUSIONS: The F-SIM16 is a sound, reliable, brief self-report measure of social inclusion suitable for use in clinical and research settings. It has the potential to evaluate the effectiveness of interventions, and aid in fostering targeted and personalised needs-based care.

The Neuropsychological Symptoms Self-Report: psychometric properties in an adolescent and young adult mental health cohort.

BACKGROUND: Subjective cognitive symptoms are common in young people receiving mental health treatment and are associated with poorer outcomes. The aim of this study was to determine the psychometric properties of the Neuropsychological Symptoms Self-Report (NSSR), an eight-item measure recently developed to provide a snapshot of young people's perceived change in cognitive functioning in relation to mental health treatment. METHOD: The sample included 633 youth aged 12-25 years (Mage = 18.2, 66.5% female, 88.6% Australian-born) who had sought mental health treatment in primary headspace services. At three-month follow-up, participants completed the NSSR and self-report measures of depression and anxiety. RESULTS: Excellent internal consistency was found: Cronbach's alpha = 0.93. The NSSR had negative correlations with self-reported anxiety (r = -.33, p < .001) and depression (r = -.48, p < .001) symptoms, suggesting a link with affective symptoms, but still independence of constructs. Exploratory and confirmatory factor analyses supported a single-factor model. Item response theory (IRT) analysis suggested good model fit (homogeneity, data integrity, scalability, local independence and monotonicity) for all items. There was some evidence of measurement noninvariance (for item thresholds) by sex and age, but not diagnosis. IRT models also supported briefer six- and three-item versions of the NSSR. CONCLUSION: In busy clinical practice, clinicians need a rapid and reliable method for determining whether cognitive symptoms are of concern and in need of further assessment and treatment. Study findings support the NSSR as a brief, psychometrically sound measure for assessing subjective cognitive functioning in adolescents and young adults receiving mental health treatment.

Validation of a brief tool to assess and monitor suicidal ideation: The Youth Suicide Ideation Screen (YSIS-3).

BACKGROUND: . Suicidal ideation is common in young people. Assessment and monitoring can help to understand its dynamic nature and inform treatment planning. AIMS: . The aims were to evaluate psychometric properties of a brief screening tool - the Youth Suicide Ideation Screen-3 item (YSIS-3) and determine its correlation with the Suicidal Ideation Question-Junior (SIQ-JR) and measures of depressive and anxiety symptoms a. METHOD: . Cronbach's alpha (α) was used to evaluate internal consistency of the YSIS-3 in 1107 young people. Convergent validity was evaluated using network analysis based on individual item polychoric correlations. Structural equation modelling was used to understand latent constructs; pearson product moment correlations to validate the integrity of the underlying construct. and two-way mixed Intraclass Correlation Coefficient to examine longitudinal stability and Cohen's d to assess sensitivity to change. RESULTS: . The YSIS-3 was found to have internal consistency, convergent validity and criteria validity almost identical to the 15-item SIQ-JR. There was a high correlation (0.91) between the latent factor underpinning YSIS-3 and SIQ-JR. The YSIS-3 was more sensitive to change among those presenting with suicidal ideation at baseline. CONCLUSIONS: . The YSIS-3 is a valid measure for the assessment and monitoring of suicidal ideation, and is sensitive to change. This brief measure can contribute to regular monitoring of the presence and nature of suicidal ideation, which when included in comprehensive assessment, will inform the clinical management of those at risk of suicide.

Subjective cognitive functioning in relation to changes in levels of depression and anxiety in youth over 3 months of treatment.

BACKGROUND: Subjective cognitive difficulties are common in mental illness and have a negative impact on role functioning. Little is understood about subjective cognition and the longitudinal relationship with depression and anxiety symptoms in young people. AIMS: To examine the relationship between changes in levels of depression and anxiety and changes in subjective cognitive functioning over 3 months in help-seeking youth. METHOD: This was a cohort study of 656 youth aged 12-25 years attending Australian headspace primary mental health services. Subjective changes in cognitive functioning (rated as better, same, worse) reported after 3 months of treatment was assessed using the Neuropsychological Symptom Self-Report. Multivariate multinomial logistic regression analysis was conducted to evaluate the impact of baseline levels of and changes in depression (nine-item Patient Health Questionnaire; PHQ9) and anxiety symptoms (seven-item Generalised Anxiety Disorder scale; GAD7) on changes in subjective cognitive function at follow-up while controlling for covariates. RESULTS: With a one-point reduction in PHQ9 at follow-up, there was an estimated 11-18% increase in ratings of better subjective cognitive functioning at follow-up, relative to stable cognitive functioning. A one-point increase in PHQ9 from baseline to follow-up was associated with 7-14% increase in ratings of worse subjective cognitive functioning over 3 months, relative to stable cognitive functioning. A similar attenuated pattern of findings was observed for the GAD7. CONCLUSIONS: A clear association exists between subjective cognitive functioning outcomes and changes in self-reported severity of affective symptoms in young people over the first 3 months of treatment. Understanding the timing and mechanisms of these associations is needed to tailor treatment.