Changes in Rates of Special Considerations in Higher Education Applications Pre- and During the COVID-19 Pandemic in Victoria, Australia.

BACKGROUND AND AIMS: Since the onset of the COVID-19 pandemic, a significant rise in mental ill health has been observed globally in young people, particularly those in their final years of secondary school. Students' negative experiences coincide with a critical transitional period which can disrupt milestones in social and educational development. This study aimed to use innovative population-level data to map the impact of the pandemic on students entering higher education. METHODS: Pre-pandemic (2019/2020) and pandemic (2020/2021) tertiary education application data were obtained from the Victorian Tertiary Admissions Centre. Prevalence of applications for special consideration related to mental ill health were compared between cohorts across various geographical areas and applicant demographic subgroups. Relative risk regression models were used to understand the role of different risk factors. RESULTS: Rates of mental health-related special consideration applications increased by 38% among all applications (pre-pandemic: 7.8%, n = 56 916; pandemic: 10.8%, n = 58 260). Highest increases were observed among students in areas with both extended and close-quarter lockdown experiences, and areas impacted by 2019/2020 black summer bushfires. The increases were higher among Year 12 students and students with other special consideration needs (e.g., physical condition, learning disability). Slightly higher increases were observed in areas with higher socio-economic status, which may potentially be related to inequality in mental health service access. CONCLUSION: As consequences of mental health difficulties and academic disruption in youth can be long lasting, it is critical to establish a mental health support framework both in and outside of higher education to facilitate young people's recovery from the pandemic.

Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods.

BACKGROUND: In randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual's risk of experiencing an outcome, then measuring treatment effect by subgroup. Given the limited availability of externally validated outcome risk prediction models, internal models (created using the same dataset in which heterogeneity of treatment analyses also will be performed) are commonly developed for subgroup identification. We aim to compare different methods for generating internally developed outcome risk prediction models for subject partitioning in HTE analysis. METHODS: Three approaches were selected for generating subgroups for the 2,441 participants from the United States enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial. An extant proportional hazards-based outcomes predictive risk model developed on the overall ASPREE cohort of 19,114 participants was identified and was used to partition United States' participants by risk of experiencing a composite outcome of death, dementia, or persistent physical disability. Next, two supervised non-parametric machine learning outcome classifiers, decision trees and random forests, were used to develop multivariable risk prediction models and partition participants into subgroups with varied risks of experiencing the composite outcome. Then, we assessed how the partitioning from the proportional hazard model compared to those generated by the machine learning models in an HTE analysis of the 5-year absolute risk reduction (ARR) and hazard ratio for aspirin vs. placebo in each subgroup. Cochran's Q test was used to detect if ARR varied significantly by subgroup. RESULTS: The proportional hazard model was used to generate 5 subgroups using the quintiles of the estimated risk scores; the decision tree model was used to generate 6 subgroups (6 automatically determined tree leaves); and the random forest model was used to generate 5 subgroups using the quintiles of the prediction probability as risk scores. Using the semi-parametric proportional hazards model, the ARR at 5 years was 15.1% (95% CI 4.0-26.3%) for participants with the highest 20% of predicted risk. Using the random forest model, the ARR at 5 years was 13.7% (95% CI 3.1-24.4%) for participants with the highest 20% of predicted risk. The highest outcome risk group in the decision tree model also exhibited a risk reduction, but the confidence interval was wider (5-year ARR = 17.0%, 95% CI= -5.4-39.4%). Cochran's Q test indicated ARR varied significantly only by subgroups created using the proportional hazards model. The hazard ratio for aspirin vs. placebo therapy did not significantly vary by subgroup in any of the models. The highest risk groups for the proportional hazards model and random forest model contained 230 participants each, while the highest risk group in the decision tree model contained 41 participants. CONCLUSIONS: The choice of technique for internally developed models for outcome risk subgroups influences HTE analyses. The rationale for the use of a particular subgroup determination model in HTE analyses needs to be explicitly defined based on desired levels of explainability (with features importance), uncertainty of prediction, chances of overfitting, and assumptions regarding the underlying data structure. Replication of these analyses using data from other mid-size clinical trials may help to establish guidance for selecting an outcomes risk prediction modelling technique for HTE analyses.

Long-term effects of a coalmine fire on hospital and ambulance use: An interrupted time series study.

BACKGROUND: In 2014, the Hazelwood coalmine fire in regional Victoria, Australia shrouded nearby communities in smoke for six weeks. Prior investigations identified substantial adverse effects, including increases in the use of health services. In this study, we examined the effects on hospital and ambulance use in the eight years following the fire. METHODS: Using Victorian hospital (Jan 2009-Jun 2022) and ambulance (Jan 2013-Dec 2021) data, we conducted an interrupted time series of changes to the rate of hospital admissions, emergency presentations, and ambulance attendances. A categorical exposure model compared two locations, most-exposed Morwell and less-exposed Latrobe Valley, to the rest of regional Victoria. A continuous exposure model used spatial estimates of fire-related PM2.5. Analyses were stratified by sex, age group (<65/65+ years), and condition (cardiovascular, respiratory, mental health, injury). RESULTS: There were small but significant increases in overall hospital admissions and emergency presentations across all analyses, but little evidence of change in overall ambulance attendances. Effects varied considerably by condition, with the biggest relative increases observed among hospital admissions for mental health conditions and injuries. While cardiovascular-related hospital admissions and emergency presentations increased post-fire, ambulance attendances decreased. CONCLUSIONS: Our findings suggest the Hazelwood coalmine fire likely increased hospital usage. However, it is unclear whether this was due to the direct effects of smoke exposure on health, or the disruptive socioeconomic and behavioural impacts of an environmental disaster that affected how communities engaged with various health services.

Vocational functioning in young people accessing services for first-episode psychosis and ultra-high risk of psychosis: A longitudinal naturalistic cohort study.

AIMS: Young people with first-episode psychosis (FEP) or at ultra-high risk (UHR) of psychosis often have lower vocational engagement than their peers. This study examines the effect of treatment in early intervention for psychosis services in Australia on engagement in education and employment. METHODS: This is a naturalistic sample of young people aged 12-25 with FEP (n = 1574) and UHR (n = 1515), accessing treatment in the headspace Early Psychosis (hEP) programme. Engagement in education and employment was assessed at baseline and every 90 days in treatment. Mixed effects logistic regression were used to analyse changes over time. RESULTS: On entering the hEP programme, approximately 49% of the young people with FEP and 28% of the young people at UHR status identified as Not in Education, Employment or Training (NEET). The odds of being NEET were reduced by 27% (95% confidence interval = [14, 39]) for every 6 months treatment for the FEP group, but no change in NEET status was observed in the UHR group. In both groups, absence from daily activities was significantly reduced during time in treatment. CONCLUSION: While there are methodological challenges analysing real-world non-control group cohort data, the findings indicate positive effects of the hEP programme on vocational and daily activity engagement for young people with FEP and at UHR status. A large proportion of the young people still identified as NEET after receiving treatment services, suggesting further refinement to ensure targeted and consistent vocational support throughout care.

Association between PM2.5 from a coal mine fire and FeNO concentration 7.5 years later.

BACKGROUND AND AIM: There are few long-term studies of respiratory health effects of landscape fires, despite increasing frequency and intensity due to climate change. We investigated the association between exposure to coal mine fire PM2.5 and fractional exhaled nitric oxide (FeNO) concentration 7.5 years later. METHODS: Adult residents of Morwell, who were exposed to the 2014 Hazelwood mine fire over 6 weeks, and unexposed residents of Sale, participated in the Hazelwood Health Study Respiratory Stream in 2021, including measurements of FeNO concentration, a marker of eosinophilic airway inflammation. Individual exposure to coal mine fire PM2.5 was modelled and mapped to time-location diaries. The effect of exposure to PM2.5 on log-transformed FeNO in exhaled breath was investigated using multivariate linear regression models in the entire sample and stratified by potentially vulnerable subgroups. RESULTS: A total of 326 adults (mean age: 57 years) had FeNO measured. The median FeNO level (interquartile range [IQR]) was 17.5 [15.0] ppb, and individual daily exposure to coal mine fire PM2.5 was 7.2 [13.8] µg/m3. We did not identify evidence of association between coal mine fire PM2.5 exposure and FeNO in the general adult sample, nor in various potentially vulnerable subgroups. The point estimates were consistently close to zero in the total sample and subgroups. CONCLUSION: Despite previous short-term impacts on FeNO and respiratory health outcomes in the medium term, we found no evidence that PM2.5 from the Hazelwood coal mine fire was associated with any long-term impact on eosinophilic airway inflammation measured by FeNO levels.

Increased vascular stiffness in children exposed in utero but not children exposed postnatally to emissions from a coal mine fire.

Background: Chronic, low-intensity air pollution exposure has been consistently associated with increased atherosclerosis in adults. However, there was limited research regarding the implications of acute, high-intensity air pollution exposure during childhood. We aimed to determine whether there were any associations between early-life exposure to such an episode and early-life vascular function changes. Methods: We conducted a prospective cohort study of children (<9 years old) who lived in the vicinity of the Hazelwood coal mine fire (n = 206). Vascular function was measured using noninvasive diagnostic methods including carotid intima-media thickness and pulse wave velocity (PWV). Exposure estimates were calculated from prognostic models and location diaries during the exposure period completed by each participant's parent. Linear mixed-effects models were used to determine whether there were any associations between exposure and changes in vascular outcomes at the 3- and 7-year follow-ups and over time. Results: At the 7-year follow-up, each 10 µg/m3 increase in daily PM2.5 in utero was associated with increased PWV (ß = 0.13 m/s; 95% confidence interval [CI] = 0.02, 0.24; P = 0.02). The association between in utero exposure to daily PM2.5 was not altered by adjustment for covariates, body mass index, and maternal fire stress. Each 1 µg/m3 increase in background PM2.5 was associated with increased PWV (ß = 0.68 m/s; 95% CI = 0.10, 1.26; P = 0.025), in children from the in utero exposure group. There was a trend toward smaller PWV (ß = -0.17 m/s; 95% CI = -0.366, 0.02) from the 3- to 7-year follow-up clinic suggesting that the deficits observed previously in children exposed postnatally did not persist. Conclusion: There was a moderate improvement in vascular stiffness of children exposed to PM2.5 from a local coal mine fire in infancy. There was a mild increase in vascular stiffness in children exposed to PM2.5 from a local coal mine fire while their mothers were pregnant.

Does diet quality moderate the long-term effects of discrete but extreme PM2.5 exposure on respiratory symptoms? A study of the Hazelwood coalmine fire.

In 2014, a fire at an open cut coalmine in regional Victoria, Australia burned for 6 weeks. Residents of the nearby town of Morwell were exposed to smoke, which included high levels of fine particulate matter (PM2.5). We investigated whether the long-term effects of PM2.5 on respiratory health were moderated by diet quality. A cross-sectional analysis was conducted of data collected 8.5 years after the mine fire from 282 residents of Morwell and 166 residents from the nearby unexposed town of Sale. Primary outcomes were respiratory symptoms. Exposure was coalmine fire-related PM2.5 and diet quality was assessed as Australian Recommended Food Score (ARFS) derived using the Australian Eating Survey (AES). The moderating effect of diet quality on respiratory outcomes associated with PM2.5 was assessed using logistic regression models, adjusting for potential confounders. Diet quality was poor in this sample, with 60% in the lowest category of overall diet quality. Overall diet quality and fruit and vegetable quality significantly attenuated the association between PM2.5 and prevalence of chronic cough and phlegm. Sauce/condiment intake was associated with a greater effect of PM2.5 on COPD prevalence. No other moderating effects were significant. The moderating effects of overall diet quality and vegetable and fruit intake aligned with a priori hypotheses, suggesting potential protective benefits. While more evidence is needed to confirm these findings, improving diets, especially fruit and vegetable intake, may provide some protection against the effects of smoke exposure from fire events.

Impact of climate zones and seasons on indoor airborne microbial communities: Insights from a comprehensive analysis.

Bacteria and fungi are ubiquitous throughout built environments and are suspended in the air, potentially affecting human health. However, the impacts of climate zones on the diversity, structure, and stochastic assembly of indoor airborne microbes remain unknown. This study comprehensively analyzed indoor airborne microbes across five climate zones in China during the summer and winter using high-throughput sequencing. The diversity and structure of indoor airborne communities vary across climatic zones. A random forest model was used to identify biomarkers in different climate zones. The results showed no relationship between the biomarkers and their rankings in mean relative abundance. The Sloan neutral model fitting results indicated that the impact of climate zones on the stochastic process in the assembly of indoor airborne microbes was considerably more important than that of seasons. Additionally, the influence of seasons on the diversity, structure, and stochastic assembly process of indoor airborne microbes differed among different climate zones. The diversity, structure, and stochastic assembly processes of bacteria present distinctive outcomes in climate zones and seasons compared with those of fungi. Overall, these findings indicate that customized strategies are necessary to manage indoor airborne microbial communities in each climate zone, season, and for specific microbial species.

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research.

Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.

Long-term effects of extreme smoke exposure on COVID-19: A cohort study.

BACKGROUND: In 2014, the Hazelwood coalmine fire shrouded the regional Australian town of Morwell in smoke and ash for 6 weeks. One of the fire's by-products, PM2.5 , is associated with an increased risk of COVID-19 and severe disease. However, it is unclear whether the effect persisted for years after exposure. In this study, we surveyed a cohort established prior to the pandemic to determine whether PM2.5 from the coalmine fire increased long-term vulnerability to COVID-19 and severe disease. METHODS: From August to December 2022, 612 members of the Hazelwood Health Study's adult cohort, established in 2016/17, participated in a follow-up survey that included standardized items to capture COVID-19 cases, as well as questions about hospitalization and vaccinations. Associations were evaluated in crude and adjusted logistic regression models. RESULTS: A total of 268 (44%) participants self-reported or met symptom criteria for having had COVID-19 at least once. All models found a positive association, with odds of COVID-19 increasing by between 4% and 30% for a 10 µg/m3 increase in coalmine fire-related PM2.5 exposure. However, the association was significant in only 2 of the 18 models. There were insufficient hospitalizations to examine severity (n = 7; 1%). CONCLUSION: The findings are inconclusive on the effect of coalmine fire-related PM2.5 exposure on long-term vulnerability to COVID-19. Given the positive association that was robust to modelling variations as well as evidence for a causal mechanism, it would be prudent to treat PM2.5 from fire events as a long-term risk factor until more evidence accumulates.

Risk evaluation of venue types and human behaviors of COVID-19 outbreaks in public indoor environments: A systematic review and meta-analysis.

Despite increasing vaccination rates, the incidence of breakthrough infections with COVID-19 has increased due to the continued emergence of new variants of the SARS-CoV-2 coronavirus. Therefore, Non-pharmaceutical interventions remain the most effective measures for coping with the ever-changing pandemic. The lifting of compulsory interventions has made individuals primary responsibility for their own health, which highlights the importance of increasing awareness of the infection risk from the environment in which they live and their individual behaviors. We systematically searched PubMed, Web of Science, ScienceDirect, and Scopus on April 17, 2023, for all studies reporting COVID-19 outbreaks in public indoor venues. The study outcome was the attack rate. A total of 42 studies, which included cross-sectional studies, cohort studies, and case studies, reporting data on 1951 confirmed cases in 64 COVID-19 outbreaks satisfied the meta-analysis and were included in the review. A random-effect model was used in the meta-analysis, and subgroup analyses were conducted to investigate factors affecting attack rates. We found a strong level of evidence (p < 0.01) supporting a higher pooled attack rate in recreation-related venues (0.44, 95% CI: 0.30 to 0.60) than in work-related venues (0.21, 95% CI: 0.16 to 0.27). Compared to those outbreaks without that, outbreaks with high-intensity exercise, vocalization, contact behavior, or close body proximity had a higher attack rate of 0.51, 0.55, 0.33, and 0.39, respectively. Further studies suggest that different attack rates across different types of settings may be the result of heterogeneity in exposed people's behaviors. There were significant heterogeneities that may limit the interpretation of connections between influencing factors and outbreak outcomes. The identification of key behaviors that may contribute to transmission risk, and their correlation with venue type, has important implications for the development of future public health interventions and individual prevention strategies for respiratory infectious diseases such as COVID-19.

Exposure to air pollution concentrations of various intensities in early life and allergic sensitisation later in childhood.

BACKGROUND: Evidence on the relationship between air pollution and allergic sensitisation in childhood is inconsistent, and this relationship has not been investigated in the context of smoke events that are predicted to increase with climate change. Thus, we aimed to evaluate associations between exposure in two early life periods to severe levels of particulate matter with an aerodynamic diameter < 2.5 µm (PM2.5) from a mine fire, background PM2.5, and allergic sensitisation later in childhood. METHODS: We measured specific immunoglobulin E (IgE) levels for seven common aeroallergens as well as total IgE levels in a cohort of children who had been exposed to the Hazelwood coal mine fire, either in utero or during their first two years of life, in a regional area of Australia where ambient levels of PM2.5 are generally low. We estimated personal exposure to fire-specific emissions of PM2.5 based on a high-resolution meteorological and pollutant dispersion model and detailed reported movements of pregnant mothers and young children during the fire. We also estimated the usual background exposure to PM2.5 at the residential address at birth using a national satellite-based land-use regression model. Associations between both sources of PM2.5 and sensitisation to dust, cat, fungi, and grass seven years after the fire were estimated with logistic regression, while associations with total IgE levels were estimated with linear regression. RESULTS: No association was found between the levels of exposure at either developmental stage to fire-related PM2.5 and allergic sensitisation seven years after the event. However, levels of background exposure were positively associated with sensitisation to dust (OR = 1.90, 95%CI = 1.12,3.21 per 1 µg/m3). CONCLUSIONS: Chronic but low exposure to PM2.5 in early life could be more strongly associated with allergic sensitisation in childhood than time-limited high exposure levels, such as the ones experienced during landscape fires.

Contrasting Health Outcomes following a Severe Smoke Episode and Ambient Air Pollution in Early Life: Findings from an Australian Data Linkage Cohort Study of Hospital Utilization.

BACKGROUND: Episodic spikes in air pollution due to landscape fires are increasing, and their potential for longer term health impacts is uncertain. OBJECTIVE: Our objective is to evaluate associations between exposure in utero and in infancy to severe pollution from a mine fire, background ambient air pollution, and subsequent hospital care. METHODS: We linked health records of births, emergency department (ED) visits, and hospitalizations of children born in the Latrobe Valley, Australia, 2012-2015, which included a severe pollution episode from a mine fire (9 February 2014 to 25 March 2014). We assigned modeled exposure estimates for fire-related and ambient particulate matter with an aerodynamic diameter of 2.5µm (PM2.5) to residential address. We used logistic regression to estimate associations with hospital visits for any cause and groupings of infectious, allergic, and respiratory conditions. Outcomes were assessed for the first year of life in the in utero cohort and the year following the fire in the infant cohort. We estimated exposure-response for both fire-related and ambient PM2.5 and also employed inverse probability weighting using the propensity score to compare exposed and not/minimally exposed children. RESULTS: Prenatal exposure to fire-related PM2.5 was associated with ED presentations for allergies/skin rash [odds ratio (OR)=1.34, 95% confidence interval (CI): 1.01, 1.76 per 240 µg/m3 increase]. Exposure in utero to ambient PM2.5 was associated with overall presentations (OR=1.18, 95% CI: 1.05, 1.33 per 1.4 µg/m3) and visits for infections (ED: OR=1.13, 95% CI: 0.98, 1.29; hospitalizations: OR=1.23, 95% CI: 1.00, 1.52). Exposure in infancy to fire-related PM2.5 compared to no/minimal exposure, was associated with ED presentations for respiratory (OR=1.37, 95% CI: 1.05, 1.80) and infectious conditions (any: OR=1.21, 95% CI: 0.98, 1.49; respiratory-related: OR=1.39, 95% CI: 1.05, 1.83). Early life exposure to ambient PM2.5 was associated with overall ED visits (OR=1.17, 95% CI: 1.05, 1.30 per 1.4 µg/m3 increase). DISCUSSION: Higher episodic and lower ambient concentrations of PM2.5 in early life were associated with visits for allergic, respiratory, and infectious conditions. Our findings also indicated differences in associations at the two developmental stages. https://doi.org/10.1289/EHP12238.

Social disadvantage in early psychosis and its effect on clinical presentation and service access, engagement and use.

Incidence of psychosis varies geographically due to factors such as social disadvantage. Whether this influences the clinical presentation and/or engagement of those experiencing psychosis remains relatively understudied. This study analysed data from young people across Australia accessing ultra-high risk (UHR) or first episode psychosis (FEP) services delivered through the headspace Early Psychosis (hEP) program between June 2017 and March 2021. The cohort was categorised into low, middle, and high tertiles of social disadvantage using the Index of Relative Socioeconomic Disadvantage (IRSD). Data from 3089 participants aged 15-25 were included (1515 UHR, 1574 FEP). The low and middle tertiles for both cohorts had greater percentages of those not in education or employment (NEET), with First Nations or culturally and linguistically diverse backgrounds. Clinical presentations to services were similar across all tertiles in both cohorts, however, functioning at presentation varied significantly within the FEP cohort. Significantly lower numbers of direct services were provided in the low tertile of both cohorts, with significantly poorer engagement in the initial three-months also occurring for these young people. This variation in early psychosis service patterns associated with geographical variation in social deprivation demonstrates the need for further research and fine tuning of national early psychosis services.

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.

Mental health systems modelling for evidence-informed service reform in Australia.

Australia's Fifth National Mental Health Plan required governments to report, not only on the progress of changes to mental health service delivery, but to also plan for services that should be provided. Future population demand for treatment and care is challenging to predict and one solution involves modelling the uncertain demands on the system. Modelling can help decision-makers understand likely future changes in mental health service demand and more intelligently choose appropriate responses. It can also support greater scrutiny, accountability and transparency of these processes. Australia has an emerging national capacity for systems modelling in mental health which can enhance the next phase of mental health reform. This paper introduces concepts useful for understanding mental health modelling and identifies where modelling approaches can support health service planners to make evidence-informed decisions regarding planning and investment for the Australian population.

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.

Sociodemographic circumstances, health, and life experience shape posttraumatic distress trajectories among individuals exposed to smoke during a large-scale coal mine fire.

The 2014 Hazelwood coal mine fire in the Latrobe Valley, Australia, distributed toxic smoke into surrounding communities over 45 days. This study investigated risk and protective factors associated with four trajectories of posttraumatic distress (resilient, recovery, delayed-onset, chronic) among exposed adults. Participants (N = 709) completed surveys in 2016-2017 and 2019-2020 assessing mine fire-related particulate matter (PM2.5 ) exposure; sociodemographic, physical, and mental health variables; and exposure to other traumatic and recent stressful events. Mine fire-related posttraumatic distress was measured using the IES-R; trajectories were determined according to established clinical significance thresholds. Relative risk ratios (RRRs) were generated from multivariate multinomial regressions. The resilient trajectory was most common (77.0%). The chronic trajectory (8.5%) was associated with loneliness, RRR = 2.59, 95% CI [1.30, 5.16], and physical health diagnoses, RRR = 2.31, 95% CI [1.32, 4.02]. The delayed-onset trajectory (9.1%) was associated with multiple recent stressful events, RRR = 2.51, 95% CI [1.37, 4.59]; mental health diagnoses, RRR = 2.30, 95% CI [1.25, 4.24]; loneliness, RRR = 2.05, 95% CI [1.09, 3.88]; and male gender, RRR = 2.01, 95% CI [1.18, 3.44]. Socioeconomic advantage protected against chronic, RRR = 0.68, 95% CI [0.53, 0.86], and delayed-onset trajectory membership, RRR = 0.68, 95% CI [0.50, 0.94]; social support protected against chronic trajectory membership, RRR = 0.67, 95% CI [0.49, 0.92]. PM2.5 exposure did not determine trajectory. These findings enhance understanding of longer-term posttraumatic responses to large-scale smoke events and can inform mental health initiatives within at-risk communities.

Tracing the origin of large respiratory droplets by their deposition characteristics inside the respiratory tract during speech.

Origin of differently sized respiratory droplets is fundamental for clarifying their viral loads and the sequential transmission mechanism of SARS-CoV-2 in indoor environments. Transient talking activities characterized by low (0.2 L/s), medium (0.9 L/s), and high (1.6 L/s) airflow rates of monosyllabic and successive syllabic vocalizations were investigated by computational fluid dynamics (CFD) simulations based on a real human airway model. SST k-ω model was chosen to predict the airflow field, and the discrete phase model (DPM) was used to calculate the trajectories of droplets within the respiratory tract. The results showed that flow field in the respiratory tract during speech is characterized by a significant laryngeal jet, and bronchi, larynx, and pharynx-larynx junction were main deposition sites for droplets released from the lower respiratory tract or around the vocal cords, and among which, over 90% of droplets over 5 µm released from vocal cords deposited at the larynx and pharynx-larynx junction. Generally, droplets' deposition fraction increased with their size, and the maximum size of droplets that were able to escape into external environment decreased with the airflow rate. This threshold size for droplets released from the vocal folds was 10-20 µm, while that for droplets released from the bronchi was 5-20 µm under various airflow rates. Besides, successive syllables pronounced at low airflow rates promoted the escape of small droplets, but do not significantly affect the droplet threshold diameter. This study indicates that droplets larger than 20 µm may entirely originate from the oral cavity, where viral loads are lower; it provides a reference for evaluating the relative importance of large-droplet spray and airborne transmission route of COVID-19 and other respiratory infections.