Development and temporal validation of a clinical prediction model of transition to psychosis in individuals at ultra-high risk in the UHR 1000+ cohort.

The concept of ultra-high risk for psychosis (UHR) has been at the forefront of psychiatric research for several decades, with the ultimate goal of preventing the onset of psychotic disorder in high-risk individuals. Orygen (Melbourne, Australia) has led a range of observational and intervention studies in this clinical population. These datasets have now been integrated into the UHR 1000+ cohort, consisting of a sample of 1,245 UHR individuals with a follow-up period ranging from 1 to 16.7 years. This paper describes the cohort, presents a clinical prediction model of transition to psychosis in this cohort, and examines how predictive performance is affected by changes in UHR samples over time. We analyzed transition to psychosis using a Cox proportional hazards model. Clinical predictors for transition to psychosis were investigated in the entire cohort using multiple imputation and Rubin's rule. To assess performance drift over time, data from 1995-2016 were used for initial model fitting, and models were subsequently validated on data from 2017-2020. Over the follow-up period, 220 cases (17.7%) developed a psychotic disorder. Pooled hazard ratio (HR) estimates showed that the Comprehensive Assessment of At-Risk Mental States (CAARMS) Disorganized Speech subscale severity score (HR=1.12, 95% CI: 1.02-1.24, p=0.024), the CAARMS Unusual Thought Content subscale severity score (HR=1.13, 95% CI: 1.03-1.24, p=0.009), the Scale for the Assessment of Negative Symptoms (SANS) total score (HR=1.02, 95% CI: 1.00-1.03, p=0.022), the Social and Occupational Functioning Assessment Scale (SOFAS) score (HR=0.98, 95% CI: 0.97-1.00, p=0.036), and time between onset of symptoms and entry to UHR service (log transformed) (HR=1.10, 95% CI: 1.02-1.19, p=0.013) were predictive of transition to psychosis. UHR individuals who met the brief limited intermittent psychotic symptoms (BLIPS) criteria had a higher probability of transitioning to psychosis than those who met the attenuated psychotic symptoms (APS) criteria (HR=0.48, 95% CI: 0.32-0.73, p=0.001) and those who met the Trait risk criteria (a first-degree relative with a psychotic disorder or a schizotypal personality disorder plus a significant decrease in functioning during the previous year) (HR=0.43, 95% CI: 0.22-0.83, p=0.013). Models based on data from 1995-2016 displayed good calibration at initial model fitting, but showed a drift of 20.2-35.4% in calibration when validated on data from 2017-2020. Large-scale longitudinal data such as those from the UHR 1000+ cohort are required to develop accurate psychosis prediction models. It is critical to assess existing and future risk calculators for temporal drift, that may reduce their utility in clinical practice over time.

Markers of positive affect and brain state synchrony discriminate melancholic from non-melancholic depression using naturalistic stimuli.

Melancholia has been proposed as a qualitatively distinct depressive subtype associated with a characteristic symptom profile (psychomotor retardation, profound anhedonia) and a better response to biological therapies. Existing work has suggested that individuals with melancholia are blunted in their display of positive emotions and differ in their neural response to emotionally evocative stimuli. Here, we unify these brain and behavioural findings amongst a carefully phenotyped group of seventy depressed participants, drawn from an established Australian database (the Australian Genetics of Depression Study) and further enriched for melancholia (high ratings of psychomotor retardation and anhedonia). Melancholic (n = 30) or non-melancholic status (n = 40) was defined using a semi-structured interview (the Sydney Melancholia Prototype Index). Complex facial expressions were captured whilst participants watched a movie clip of a comedian and classified using a machine learning algorithm. Subsequently, the dynamics of sequential changes in brain activity were modelled during the viewing of an emotionally evocative movie in the MRI scanner. We found a quantitative reduction in positive facial expressivity amongst participants with melancholia, combined with differences in the synchronous expression of brain states during positive epochs of the movie. In non-melancholic depression, the display of positive affect was inversely related to the activity of cerebellar regions implicated in the processing of affect. However, this relationship was reduced in those with a melancholic phenotype. Our multimodal findings show differences in evaluative and motoric domains between melancholic and non-melancholic depression through engagement in ecologically valid tasks that evoke positive emotion. These findings provide new markers to stratify depression and an opportunity to support the development of targeted interventions.

Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology.

Mental fitness is a construct that goes beyond a simple focus on subjective emotional wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we want in our daily lives. The measurement and monitoring of multiple (often interacting) domains is crucial to gain a holistic and complete insight into an individual's mental fitness. We aimed to demonstrate the capability of a new mobile app to characterise the mental fitness of a general population of Australians and to quantify the interrelationships among different domains of mental fitness. Cross-sectional data were collected from 4901 adults from the general population of Australians engaged in work or education who used a mobile app (Innowell) between September 2021 and November 2022. Individuals completed a baseline questionnaire comprised of 26 questions across seven domains of mental fitness (i.e., physical activity, sleep and circadian rhythms, nutrition, substance use, daily activities, social connection, psychological distress). Network analysis was applied at both a domain-level (e.g., 7 nodes representing each cluster of items) and an individual item-level (i.e., 26 nodes representing all questionnaire items). Only 612 people (12%) were functioning well across all domains. One quarter (n = 1204, 25%) had only one problem domain and most (n = 3085, 63%) had multiple problem domains. The two most problematic domains were physical activity (n = 2631, 54%) and social connection (n = 2151, 44%), followed closely by daily activity (n = 1914, 39%). At the domain-level, the strongest association emerged between psychological distress and daily activity (r = 0.301). Psychological distress was the most central node in the network (as measured by strength and expected influence), followed closely by daily activity, sleep and circadian rhythms and then social connection. The item-level network revealed that the nodes with the highest centrality in the network were: hopelessness, depression, functional impairment, effortfulness, subjective energy, worthlessness, and social connectedness. Social connection, sleep and circadian rhythms, and daily activities may be critical targets for intervention due to their widespread associations in the overall network. While psychological distress was not among the most common problems, its centrality may indicate its importance for indicated prevention and early intervention. We showcase the capability of a new mobile app to monitor mental fitness and identify the interrelationships among multiple domains, which may help people develop more personalised insights and approaches.

Cultural and Contextual Adaptation of Digital Health Interventions: Narrative Review.

BACKGROUND: Emerging evidence suggests that positive impacts can be generated when digital health interventions are designed to be responsive to the cultural and socioeconomic context of their intended audiences. OBJECTIVE: This narrative review aims to synthesize the literature about the cultural adaptation of digital health interventions. It examines how concepts of culture and context feature in design and development processes, including the methods, models, and content of these interventions, with the aim of helping researchers to make informed decisions about how to approach cultural adaptation in digital health. METHODS: Literature searches for this narrative review were conducted across 4 databases. Following full-text article screening by 2 authors, 16 studies of interventions predominantly focused on the self-management of health were selected based on their detailed focus on the process of cultural adaptation. Key considerations for cultural adaptation were identified and synthesized through a qualitative narrative approach, enabling an integrative and in-depth understanding of cultural adaptation. RESULTS: The literature demonstrates varying approaches and levels of cultural adaptation across stages of intervention development, involving considerations such as the research ethos orienting researchers, the methodologies and models used, and the resultant content adaptations. In relation to the latter, culturally appropriate and accessible user interface design and translation can be seen as particularly important in shaping the level of adaptation. CONCLUSIONS: Optimizing cultural adaptation involves linking culture with other contextual factors such as economic conditions and social systems to ensure accessibility and the sustained use of digital health interventions. Culturally humble approaches that use the involvement of a broad range of participants, experts, and other stakeholders are demonstrated to spark vital insights for content development, implementation, and evaluation.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care.

There has recently been an increase in ongoing patient-report routine outcome monitoring for individuals within clinical care, which has corresponded to increased longitudinal information about an individual. However, many models that are aimed at clinical practice have difficulty fully incorporating this information. This is in part due to the difficulty in dealing with the irregularly time-spaced observations that are common in clinical data. Consequently, we built individual-level continuous-time trajectory models of suicidal ideation for a clinical population (N = 585) with data collected via a digital platform. We demonstrate how such models predict an individual's level and variability of future suicide ideation, with implications for the frequency that individuals may need to be observed. These individual-level predictions provide a more personalised understanding than other predictive methods and have implications for enhanced measurement-based care.

Different heart rate variability profile during sleep in mid-later life adults with remitted early-onset versus late-onset depression.

BACKGROUND: In mid-later life adults, early-onset and late-onset (i.e., onset ≥50 years) depression appear to be underpinned by different pathophysiology yet have not been examined in relation to autonomic function. Sleep provides an opportunity to examine the autonomic nervous system as the physiology changes across the night. Hence, we aimed to explore if autonomic profile is altered in mid-later life adults with remitted early-onset, late-onset and no history of lifetime depression. METHODS: Participants aged 50-90 years (n = 188) from a specialised clinic underwent a comprehensive clinical assessment and completed an overnight polysomnography study. General Linear Models were used to examine the heart rate variability differences among the three groups for four distinct sleep stages and the wake after sleep onset. All analyses controlled for potential confounders - age, sex, current depressive symptoms and antidepressant usage. RESULTS: For the wake after sleep onset, mid-later life adults with remitted early-onset depression had reduced standard deviation of Normal to Normal intervals (SDNN; p = .014, d = -0.64) and Shannon Entropy (p = .004, d = -0.46,) than those with no history of lifetime depression. Further, the late-onset group showed a reduction in high-frequency heart rate variability (HFn.u.) during non-rapid eye movement sleep stage 2 (N2; p = .005, d = -0.53) and non-rapid eye movement sleep stage 3 (N3; p = .009, d = -0.55) when compared to those with no lifetime history. LIMITATIONS: Causality between heart rate variability and depression cannot be derived in this cross-sectional study. Longitudinal studies are needed to examine the effects remitted depressive episodes on autonomic function. CONCLUSION: The findings suggest differential autonomic profile for remitted early-onset and late-onset mid-later life adults during sleep stages and wake periods. The differences could potentially serve as peripheral biomarkers in conjunction with more disease-specific markers of depression to improve diagnosis and prognosis.

Digital rights and mobile health in Southeast Asia: A scoping review.

Objective: Digital technology has the potential to support or infringe upon human rights. The ubiquity of mobile technology in low- and middle-income countries (LMICs) presents an opportunity to leverage mobile health (mHealth) interventions to reach remote populations and enable them to exercise human rights. Yet, simultaneously, the proliferation of mHealth results in expanding sensitive datasets and data processing, which risks endangering rights. The promotion of digital health often centers on its role in enhancing rights and health equity, particularly in LMICs. However, the interplay between mHealth in LMICs and digital rights is underexplored. The objective of this scoping review is to bridge this gap and identify digital rights topics in the 2022 literature on mHealth in Southeast Asian LMICs. Furthermore, it aims to highlight the importance of patient empowerment and data protection in mHealth and related policies in LMICs. Methods: This review follows Arksey and O'Malley's framework for scoping reviews. Search results are reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Frequency and content analyses were applied to summarize and interpret the data. Results: Three key findings emerge from this review. First, the digital rights topics covered in the literature are sparse, sporadic, and unsystematic. Second, despite significant concerns surrounding data privacy in Southeast Asian LMICs, no article in this review explores challenges to data privacy. Third, all included articles state or allude to the role of mHealth in advancing the right to health. Conclusions: Engagement in digital rights topics in the literature on mHealth in Southeast Asian mHealth is limited and irregular. Researchers and practitioners lack guidance, collective understanding, and shared language to proactively examine and communicate digital rights topics in mHealth in LMIC research. A systematic method for engaging with digital rights in this context is required going forward.

Chronotype and subjective sleep quality predict white matter integrity in young people with emerging mental disorders.

Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity in emerging mental disorders. Young people (N = 364) accessing early-intervention clinics underwent assessments for chronotype, subjective sleep quality, and diffusion tensor imaging. Using machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity: fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD). We prioritised tracts that showed a univariate association with sleep quality or chronotype and considered predictors identified by ≥80% of machine learning (ML) models as 'important'. The most important predictors of WM integrity were demographics (age, sex and education) and diagnosis (depressive and bipolar disorders). Subjective sleep quality only predicted FA in the perihippocampal cingulum tract, whereas chronotype had limited predictive importance for WM integrity. To further examine links with mood disorders, we conducted a subgroup analysis. In youth with depressive and bipolar disorders, chronotype emerged as an important (often top-ranking) feature, predicting FA in the cingulum (cingulate gyrus), AD in the anterior corona radiata and genu of the corpus callosum, and RD in the corona radiata, anterior corona radiata, and genu of corpus callosum. Subjective quality was not important in this subgroup analysis. In summary, chronotype predicted altered WM integrity in the corona radiata and corpus callosum, whereas subjective sleep quality had a less significant role, suggesting that circadian factors may play a more prominent role in WM integrity in emerging mood disorders.

Staging 2.0: refining transdiagnostic clinical staging frameworks to enhance reliability and utility for youth mental health.

Globally, 75% of depressive, bipolar, and psychotic disorders emerge by age 25 years. However, these disorders are often preceded by non-specific symptoms or attenuated clinical syndromes. Difficulties in determining optimal treatment interventions for these emerging mental disorders, and uncertainties about accounting for co-occurring psychopathology and illness trajectories, have led many youth mental health services to adopt transdiagnostic clinical staging frameworks. In this Health Policy paper, an international working group highlights ongoing challenges in applying transdiagnostic staging frameworks in clinical research and practice, and proposes refinements to the transdiagnostic model to enhance its reliability, consistent recording, and clinical utility. We introduce the concept of within-stage heterogeneity and describe the advantages of defining stage in terms of clinical psychopathology and stage modifiers. Using examples from medicine, we discuss the utility of categorising stage modifiers into factors associated with progression (ie, potential predictors of stage transition) and extension (ie, factors associated with the current presentation that add complexity to treatment selection). Lastly, we suggest how it is possible to revise the currently used transdiagnostic staging approach to incorporate these key concepts, and how the revised framework could be applied in clinical and research practice.

Comprehensive Sex-Stratified Genetic Analysis of 28 Blood Biomarkers and Depression Reveals a Significant Association between Depression and Low Levels of Total Protein in Females.

Introduction: Major depression (MD) is more common amongst women than men, and MD episodes have been associated with fluctuations in reproductive hormones amongst women. To investigate biological underpinnings of heterogeneity in MD, the associations between depression, stratified by sex and including perinatal depression (PND), and blood biomarkers, using UK Biobank (UKB) data, were evaluated, and extended to include the association of depression with biomarker polygenic scores (PGS), generated as proxy for each biomarker. Method: Using female (N = 39,761) and male (N = 38,821) UKB participants, lifetime MD and PND were tested for association with 28 blood biomarkers. A GWAS was conducted for each biomarker and genetic correlations with depression subgroups were estimated. Using independent data from the Australian Genetics of Depression Study, PGS were constructed for each biomarker, and tested for association with depression status (n [female cases/controls] = 9,006/6,442; n [male cases/controls] = 3,106/6,222). Regions of significant local genetic correlation between depression subgroups and biomarkers highlighted by the PGS analysis were identified. Results: Depression in females was significantly associated with levels of twelve biomarkers, including total protein (OR = 0.90, CI = [0.86, 0.94], p = 3.9 × 10-6) and vitamin D (OR = 0.94, CI = [0.90, 0.97], p = 2.6 × 10-4), and PND with five biomarker levels, also including total protein (OR = 0.88, CI = [0.81, 0.96], p = 4.7 × 10-3). Depression in males was significantly associated with levels of eleven biomarkers. In the independent Australian Genetics of Depression Study, PGS analysis found significant associations for female depression and PND with total protein (female depression: OR = 0.93, CI = [0.88, 0.98], p = 3.6 × 10-3; PND: OR = 0.91, CI = [0.86, 0.96], p = 1.1 × 10-3), as well as with vitamin D (female depression: OR = 0.93, CI = [0.89, 0.97], p = 2.0 × 10-3; PND: OR = 0.92, CI = [0.87, 0.97], p = 1.4 × 10-3). The male depression sample did not report any significant results, and the point estimate of total protein (OR = 0.98, CI = [0.92-1.04], p = 4.7 × 10-1) did not indicate any association. Local genetic correlation analysis highlighted significant genetic correlation between PND and total protein, located in 5q13.3 (rG = 0.68, CI = [0.33, 1.0], p = 3.6 × 10-4). Discussion and Conclusion: Multiple lines of evidence from genetic analysis highlight an association between total serum protein levels and depression in females. Further research involving prospective measurement of total protein and depressive symptoms is warranted.

Mental health impacts of COVID-19: A retrospective analysis of dynamic modelling projections for Australia.

Background: In early 2020, we developed a dynamic model to support policy responses aimed at mitigating the adverse mental health effects of the COVID-19 pandemic in Australia. As the pandemic has progressed, it has become clear that our initial model forecasts overestimated the impacts of infection control measures (lockdowns, physical distancing, etc.) on suicide, intentional self-harm hospitalisation, and mental health-related emergency department (ED) presentation rates. Methods: Potential explanations for the divergence of our model predictions from observed outcomes were assessed by comparing simulation results for a set of progressively more refined models with data on the prevalence of moderate to very high psychological distress and numbers of suicides, intentional self-harm hospitalisations, and mental health-related ED presentations published after our modelling was released in July 2020. Results: Allowing per capita rates of spontaneous recovery and intentional self-harm to differ between people experiencing moderate to very high psychological distress prior to the pandemic and those developing comparable levels of psychological distress only as a consequence of infection control measures substantially improves the fit of our model to empirical estimates of the prevalence of psychological distress and leads to significantly lower predicted effects of COVID-19 on suicide, intentional self-harm hospitalisation, and mental health-related ED presentation rates. Conclusion: Accommodating the influence of prior mental health on the psychological effects of population-wide social and economic disruption is likely to be critical for accurately forecasting the mental health impacts of future public health crises as they inevitably arise.

Patterns of stressful life events and polygenic scores for five mental disorders and neuroticism among adults with depression.

The dominant ('general') version of the diathesis-stress theory of depression views stressors and genetic vulnerability as independent risks. In the Australian Genetics of Depression Study (N = 14,146; 75% female), we tested whether polygenic scores (PGS) for major depression, bipolar disorder, schizophrenia, anxiety, ADHD, and neuroticism were associated with reported exposure to 32 childhood, past-year, lifetime, and accumulated stressful life events (SLEs). In false discovery rate-corrected models, the clearest PGS-SLE relationships were for the ADHD- and depression-PGSs, and to a lesser extent, the anxiety- and schizophrenia-PGSs. We describe the associations for childhood and accumulated SLEs, and the 2-3 strongest past-year/lifetime SLE associations. Higher ADHD-PGS was associated with all childhood SLEs (emotional abuse, emotional neglect, physical neglect; ORs = 1.09-1.14; p's < 1.3 × 10-5), more accumulated SLEs, and reported exposure to sudden violent death (OR = 1.23; p = 3.6 × 10-5), legal troubles (OR = 1.15; p = 0.003), and sudden accidental death (OR = 1.14; p = 0.006). Higher depression-PGS was associated with all childhood SLEs (ORs = 1.07-1.12; p's < 0.013), more accumulated SLEs, and severe human suffering (OR = 1.17; p = 0.003), assault with a weapon (OR = 1.12; p = 0.003), and living in unpleasant surroundings (OR = 1.11; p = 0.001). Higher anxiety-PGS was associated with childhood emotional abuse (OR = 1.08; p = 1.6 × 10-4), more accumulated SLEs, and serious accident (OR = 1.23; p = 0.004), physical assault (OR = 1.08; p = 2.2 × 10-4), and transportation accident (OR = 1.07; p = 0.001). Higher schizophrenia-PGS was associated with all childhood SLEs (ORs = 1.12-1.19; p's < 9.3-8), more accumulated SLEs, and severe human suffering (OR = 1.16; p = 0.003). Higher neuroticism-PGS was associated with living in unpleasant surroundings (OR = 1.09; p = 0.007) and major financial troubles (OR = 1.06; p = 0.014). A reversed pattern was seen for the bipolar-PGS, with lower odds of reported physical assault (OR = 0.95; p = 0.014), major financial troubles (OR = 0.93; p = 0.004), and living in unpleasant surroundings (OR = 0.92; p = 0.007). Genetic risk for several mental disorders influences reported exposure to SLEs among adults with moderately severe, recurrent depression. Our findings emphasise that stressors and diatheses are inter-dependent and challenge diagnosis and subtyping (e.g., reactive/endogenous) based on life events.

Promoting social, emotional, and cognitive development in early childhood: A protocol for early valuation of a culturally adapted digital tool for supporting optimal childrearing practices.

Objective: The Thrive by Five app promotes positive interactions between children and parents, extended family, and trusted community members that support optimal socio-emotional and cognitive development in the early years. This article aims to describe the protocol for a prospective mixed-methods multi-site study evaluating Thrive by Five using surveys, interviews, workshops, audio diaries from citizen ethnographers and app usage data. Methods: The study activities and timelines differ by site, with an extensive longitudinal evaluation being conducted at two sites and a basic evaluation being conducted at five sites. The learnings from the more comprehensive evaluations inform the iterative research and development processes while also ensuring ongoing evaluation of usability, acceptability and effectiveness of the app and its content across varying contexts. The study evaluates: (1) the impact of the Thrive by Five content on caregiver knowledge, behaviours, attitudes and confidence; (2) how the content changes relationships at the familial, community and system level; (3) how cultural and contextual factors influence content engagement and effectiveness and (4) the processes that facilitate or disrupt the success of the implementation and dissemination. Results: All in-country partners have been identified and data collection has been completed in Indonesia, Malaysia, Afghanistan, Kyrgyzstan, Uzbekistan, Namibia and Cameroon. Conclusions: Very few digital health solutions have been trialled for usability and effectiveness in diverse cultural contexts. By combining quantitative, qualitative, process and ethnographic methodologies, this innovative study informs the iterative and ongoing optimisation of the cultural and contextual sensitivity of the Thrive by Five content and the processes supporting implementation and dissemination.

Social and joint attention during shared book reading in young autistic children: a potential marker for social development.

BACKGROUND: Atypical patterns of social engagement and joint attention behaviors are diagnostic criteria for people with autism spectrum disorder. Experimental tasks using eye-tracking methodologies have, however, shown inconsistent results. The development of tasks with greater ecological validity and relevance for developmentally appropriate social milestones has been identified as important for the field. METHODS: We developed a novel, dynamic eye-tracking task emulating a shared book reading (SBR) scenario. Four SBR videos of an adult reader engaging with the viewer while reading a children's picture book and including sequenced bids for joint attention were developed. Participants included 90 children (N = 56 autistic children, N = 34 neurotypical children; aged 3-12). Social attention was also measured in a live free play task between participants and an experimenter. RESULTS: Compared to neurotypical children, autistic children displayed reduced attention to socially salient stimuli including the reader's face and picture book across SBR videos and during joint attention bids specifically. In contrast, they showed increased attention to nonsalient background stimuli compared to their neurotypical peers. These attention patterns in autistic children were associated with reduced verbal and nonverbal cognitive skills and increased symptoms associated with autism. Interestingly, positive correlations in the frequency of eye gaze between SBR and free play suggested a potential predictive value for social attention in live social interactions. CONCLUSIONS: Findings highlight the utility of SBR eye-tracking tasks in understanding underlying divergences in social engagement and joint attention between autistic and neurotypical children. This commonly practiced early childhood activity may provide insights into the relationship between social engagement and learning to reveal how such attentional patterns might influence broader developmental and educational outcomes.

The influence of economic policies on social environments and mental health.

Despite increased advocacy and investments in mental health systems globally, there has been limited progress in reducing mental disorder prevalence. In this paper, we argue that meaningful advancements in population mental health necessitate addressing the fundamental sources of shared distress. Using a systems perspective, economic structures and policies are identified as the potential cause of causes of mental ill-health. Neoliberal ideologies, prioritizing economic optimization and continuous growth, contribute to the promotion of individualism, job insecurity, increasing demands on workers, parental stress, social disconnection and a broad range of manifestations well-recognized to erode mental health. We emphasize the need for mental health researchers and advocates to increasingly engage with the economic policy discourse to draw attention to mental health and well-being implications. We call for a shift towards a well-being economy to better align commercial interests with collective well-being and social prosperity. The involvement of individuals with lived mental ill-health experiences, practitioners and researchers is needed to mobilize communities for change and influence economic policies to safeguard well-being. Additionally, we call for the establishment of national mental wealth observatories to inform coordinated health, social and economic policies and realize the transition to a more sustainable well-being economy that offers promise for progress on population mental health outcomes.

Malgré une meilleure sensibilisation et des investissements accrus dans les systèmes de santé mentale à travers le monde, les progrès en matière de réduction du degré de prévalence des troubles mentaux demeurent très limités. Dans le présent document, nous estimons que, pour réaliser des avancées au niveau de la santé mentale des populations, il est impératif de s'attaquer aux sources de cette détresse collective. En adoptant une perspective systémique, force est de constater que les politiques et structures économiques constituent les causes potentielles d'une mauvaise santé mentale. Les idéologies néolibérales, qui privilégient l'optimisation économique et la croissance ininterrompue, contribuent à promouvoir l'individualisme, l'insécurité professionnelle, la pression pesant sur les travailleurs, le stress parental, l'isolement social et un large éventail de facteurs associés à une dégradation de la santé mentale. Nous insistons sur la nécessité de faire appel à des chercheurs et défenseurs actifs dans ce domaine, afin de jouer un rôle dans la politique économique en attirant l'attention sur les implications pour le bien-être et la santé mentale. Nous plaidons pour une transition vers une économie du bien-être visant à rapprocher les intérêts commerciaux de la prospérité sociale et collective. L'intervention de personnes ayant été confrontées à des troubles mentaux, de praticiens et de chercheurs est nécessaire pour mobiliser les communautés en faveur d'un changement et influencer les politiques économiques pour préserver le bien-être. Par ailleurs, nous militons pour la création d'observatoires nationaux de la santé mentale qui serviront à orienter des politiques économiques, sociales et sanitaires coordonnées, mais aussi à favoriser l'évolution vers une économie du bien-être plus durable, laissant entrevoir une amélioration de la santé mentale au sein de la population.

A pesar del aumento de la promoción y las inversiones en sistemas de salud mental en todo el mundo, los avances en la reducción de la prevalencia de los trastornos mentales han sido limitados. En este documento, sostenemos que para lograr avances significativos en la salud mental de la población es necesario abordar las fuentes fundamentales de la angustia compartida. Mediante una perspectiva sistémica, las estructuras y políticas económicas se identifican como la posible causa de los problemas de salud mental. Las ideologías neoliberales, que priorizan la optimización económica y el crecimiento continuo, contribuyen al fomento del individualismo, la inseguridad laboral, el aumento de las exigencias a los trabajadores, el estrés parental, la desconexión social y una gran variedad de manifestaciones bien reconocidas que perjudican la salud mental. Insistimos en la necesidad de que los investigadores y los defensores de la salud mental se impliquen cada vez más en el discurso de la política económica para atraer la atención sobre las implicaciones para la salud mental y el bienestar. Pedimos un cambio hacia una economía del bienestar para alinear mejor los intereses comerciales con el bienestar colectivo y la prosperidad social. Para movilizar a las comunidades en favor del cambio e influir en las políticas económicas con el fin de salvaguardar el bienestar, es necesaria la participación de personas que han padecido enfermedades mentales, profesionales e investigadores. Además, pedimos la creación de observatorios nacionales de bienestar mental que sirvan de base a las políticas sanitarias, sociales y económicas coordinadas y permitan la transición a una economía del bienestar más sostenible, que ofrezca perspectivas de progreso en los resultados de salud mental de la población.

Evening Chronotypes With Depression Report Poorer Outcomes of Selective Serotonin Reuptake Inhibitors: A Survey-Based Study of Self-Ratings.

BACKGROUND: Preliminary evidence suggests that evening chronotype is related to poorer efficacy of selective serotonin reuptake inhibitors. It is unknown whether this is specific to particular medications, self-rated chronotype, or efficacy. METHODS: In the Australian Genetics of Depression Study (n = 15,108; 75% women; 18-90 years; 68% with ≥1 other lifetime diagnosis), a survey recorded experiences with 10 antidepressants, and the reduced Morningness-Eveningness Questionnaire was used to estimate chronotype. A chronotype polygenic score was calculated. Age- and sex-adjusted regression models (Bonferroni-corrected) estimated associations among antidepressant variables (how well the antidepressant worked [efficacy], duration of symptom improvement, side effects, discontinuation due to side effects) and self-rated and genetic chronotypes. RESULTS: The chronotype polygenic score explained 4% of the variance in self-rated chronotype (r = 0.21). Higher self-rated eveningness was associated with poorer efficacy of escitalopram (odds ratio [OR] = 1.04; 95% CI, 1.02 to 1.06; p = .000035), citalopram (OR = 1.03; 95% CI, 1.01 to 1.05; p = .004), fluoxetine (OR = 1.03; 95% CI, 1.01 to 1.05; p = .001), sertraline (OR = 1.02; 95% CI, 1.01 to 1.04; p = .0008), and desvenlafaxine (OR = 1.03; 95% CI, 1.01 to 1.05; p = .004), and a profile of increased side effects (80% of those recorded; ORs = 0.93-0.98), with difficulty getting to sleep the most common. Self-rated chronotype was unrelated to duration of improvement or discontinuation. The chronotype polygenic score was only associated with suicidal thoughts and attempted suicide (self-reported). While our measures are imperfect, and not of circadian phase under controlled conditions, the model coefficients suggest that dysregulation of the phenotypic chronotype relative to its genetic proxy drove relationships with antidepressant outcomes. CONCLUSIONS: The idea that variation in circadian factors influences response to antidepressants was supported and encourages exploration of circadian mechanisms of depressive disorders and antidepressant treatments.

Cost-effectiveness of system-level mental health strategies for young people in the Australian Capital Territory: a dynamic simulation modelling study.

BACKGROUND: Regional mental health planning is a key challenge for decision makers because mental health care is a complex, dynamic system. Economic evaluation using a system dynamics modelling approach presents an opportunity for more sophisticated planning and important evidence on the value of alternative investments. We aimed to investigate the cost-effectiveness of eight systems-based interventions targeted at improving the mental health and wellbeing of children, adolescents, and young adults in the Australian Capital Territory (ACT). METHODS: We assessed eight interventions for children and young people (aged ≤25 years) with low, moderate, and high-to-very-high psychological distress: technology-enabled integrated care, emergency department-based suicide prevention, crisis response service, family education programme, online parenting programme, school-based suicide prevention programme, trauma service for youths, and multicultural-informed care. We developed a system dynamics model for the ACT through a participatory process and calibrated the model with historical data, including population demographics, the prevalence of psychological distress, and mental health services provision. We calculated incremental cost-effectiveness ratios compared with business as usual for cost (AU$) per: quality-adjusted life-year (QALY), suicide death avoided, self-harm related hospital admissions avoided, and mental health-related emergency department presentation, using a 10-year time horizon for health-care and societal perspectives. We investigated uncertainty through probabilistic sensitivity analysis and deterministic sensitivity analysis, including using a 30-year timeframe. FINDINGS: From a societal perspective, increased investment in technology-enabled integrated care, family education, an online parenting programme, and multicultural-informed care were expected to improve health outcomes (incremental QALYs 4517 [95% UI -3135 to 14 507] for technology-enabled integrated care; 339 [91 to 661] for family education; 724 [114 to 1149] for the online parenting programme; and 137 [88 to 194] for multicultural-informed care) and reduce costs ($-91·4 million [-382·7 to 100·7]; $-12·8 million [-21·0 to -6·6]; $-3·6 million  [-6·3 to 0·2]; and $-3·1 million [-4·5 to -1·8], respectively) compared with business as usual using a 10-year time horizon. The incremental net monetary benefit for the societal perspective for these four interventions was $452 million (-351 to 1555), $40 million (14 to 74), $61 million (9 to 98), and $14 million (9 to 20), respectively, compared with business as usual, when QALYs were monetised using a willingness to pay of $79 930 per QALY. Synergistic effects are anticipated if these interventions were to be implemented concurrently. The univariate and probabilistic sensitivity analyses indicated a high level of certainty in the results. Although emergency department-based suicide prevention and school-based suicide prevention were not cost effective in the base case (41 QALYs [0 to 48], incremental cost $4·1 million [1·2 to 8·2] for emergency department-based suicide prevention; -234 QALYs [-764 to 12], incremental cost $90·3 million [72·2 to 111·0] for school-based suicide prevention) compared with business as usual, there were scenarios for which these interventions could be considered cost effective. A dedicated trauma service for young people (9 QALYs gained [4 to 16], incremental cost $8·3 million [6·8 to 10·0]) and a crisis response service (-11 QALYs gained [-12 to -10], incremental cost $7·8 million [5·1 to 11·0]) were unlikely to be cost effective in terms of QALYs. INTERPRETATION: Synergistic effects were identified, supporting the combined implementation of technology-enabled integrated care, family education, an online parenting programme, and multicultural-informed care. Synergistic effects, emergent outcomes in the form of unintended consequences, the capability to account for service capacity constraints, and ease of use by stakeholders are unique attributes of a system dynamics modelling approach to economic evaluation. FUNDING: BHP Foundation.

Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study.

INTRODUCTION: Regional gray matter (GM) alterations have been reported in early-onset psychosis (EOP, onset before age 18), but previous studies have yielded conflicting results, likely due to small sample sizes and the different brain regions examined. In this study, we conducted a whole brain voxel-based morphometry (VBM) analysis in a large sample of individuals with EOP, using the newly developed ENIGMA-VBM tool. METHODS: 15 independent cohorts from the ENIGMA-EOP working group participated in the study. The overall sample comprised T1-weighted MRI data from 482 individuals with EOP and 469 healthy controls. Each site performed the VBM analysis locally using the standardized ENIGMA-VBM tool. Statistical parametric T-maps were generated from each cohort and meta-analyzed to reveal voxel-wise differences between EOP and healthy controls as well as the individual-based association between GM volume and age of onset, chlorpromazine (CPZ) equivalent dose, and other clinical variables. RESULTS: Compared with healthy controls, individuals with EOP showed widespread lower GM volume encompassing most of the cortex, with the most marked effect in the left median cingulate (Hedges' g = 0.55, p = 0.001 corrected), as well as small clusters of lower white matter (WM), whereas no regional GM or WM volumes were higher in EOP. Lower GM volume in the cerebellum, thalamus and left inferior parietal gyrus was associated with older age of onset. Deficits in GM in the left inferior frontal gyrus, right insula, right precentral gyrus and right superior frontal gyrus were also associated with higher CPZ equivalent doses. CONCLUSION: EOP is associated with widespread reductions in cortical GM volume, while WM is affected to a smaller extent. GM volume alterations are associated with age of onset and CPZ equivalent dose but these effects are small compared to case-control differences. Mapping anatomical abnormalities in EOP may lead to a better understanding of the role of psychosis in brain development during childhood and adolescence.