Predicting public mental health needs in a crisis using social media indicators: a Singapore big data study.

Mental health issues have increased substantially since the onset of the COVID-19 pandemic. However, health policymakers do not have adequate data and tools to predict mental health demand, especially amid a crisis. Using time-series data collected in Singapore, this study examines if and how algorithmically measured emotion indicators from Twitter posts can help forecast emergency mental health needs.

Elucidating salient site-specific functional connectivity features and site-invariant biomarkers in schizophrenia via deep neural networks.

Schizophrenia is a highly heterogeneous disorder and salient functional connectivity (FC) features have been observed to vary across study sites, warranting the need for methods that can differentiate between site-invariant FC biomarkers and site-specific salient FC features. We propose a technique named Semi-supervised learning with data HaRmonisation via Encoder-Decoder-classifier (SHRED) to examine these features from resting state functional magnetic resonance imaging scans gathered from four sites. Our approach involves an encoder-decoder-classifier architecture that simultaneously performs data harmonisation and semi-supervised learning (SSL) to deal with site differences and labelling inconsistencies across sites respectively.

SMARThealth PRegnancy And Mental Health study: protocol for a situational analysis of perinatal mental health in women living in rural India.

Introduction: The situation for women experiencing mental health problems during pregnancy and postpartum in rural India is critical: a high burden of disease, a high estimated number of women are undiagnosed and untreated with mental health problems, a substantial gap in research on women's perinatal health, and severe stigma and discrimination. The SMARThealth Pregnancy study is a cluster randomised trial using a digital intervention to identify and manage anaemia, hypertension, and diabetes in the first year after birth in rural India. Within this study, the SMARThealth Pregnancy and Mental Health (PRAMH) study is a situational analysis to understand mental health problems during pregnancy and in the first year following birth in this population.

Asthma Prevalence and its Risk Factors Among a Multi-Ethnic Adult Population.

Asthma is a substantial global health problem characterized by chronic airway inflammation, leading to intermittent symptoms. This study aims to establish the prevalence and risk factors of asthma in a multi-ethnic adult population. Data for the study were extracted from the Singapore Mental Health Study 2016, a population-based, cross-sectional, epidemiological study of Singapore residents aged 18 years and above.

Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks.

The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data.

Prevalence and comorbidity of migraine headache: results from the Singapore Mental Health Study 2016.

Background And Aim: Migraine is a highly prevalent and disabling neurological disorder associated with a wide range of psychiatric comorbidities. Studies have revealed that those with migraine headache and coexisting psychiatric disorders have poorer treatment outcomes and increased disability. The study aims to establish the prevalence, correlates, and comorbidities of migraine headache among the multi-ethnic Asian population in Singapore.

Dynamic Reorganization of Functional Connectivity Reveals Abnormal Temporal Efficiency in Schizophrenia.

Emerging evidence suggests that schizophrenia is associated with brain dysconnectivity. Nonetheless, the implicit assumption of stationary functional connectivity (FC) adopted in most previous resting-state functional magnetic resonance imaging (fMRI) studies raises an open question of schizophrenia-related aberrations in dynamic properties of resting-state FC. This study introduces an empirical method to examine the dynamic functional dysconnectivity in patients with schizophrenia.

Comparison of DSM-IV-TR and DSM-5 Criteria in Diagnosing Autism Spectrum Disorders in Singapore.

Our study examines the Diagnostic and Statistical Manual-Fifth Edition (DSM-5) and Diagnostic and Statistical Manual-Fourth Edition, Text Revision (DSM-IV-TR) when applied concurrently against the best estimate clinical diagnoses for 110 children (5.1-19.6 years old) referred for diagnostic assessments of Autism Spectrum Disorder (ASD) in a Singaporean outpatient speciality clinic.

Modular-level alterations of structure-function coupling in schizophrenia connectome.

Convergent evidences have revealed that schizophrenia is associated with brain dysconnectivity, which leads to abnormal network organization. However, discrepancies were apparent between the structural connectivity (SC) and functional connectivity (FC) studies, and the relationship between structural and functional deficits in schizophrenia remains largely unknown. In this study, resting-state functional magnetic resonance imaging and structural diffusion tensor imaging were performed in 20 patients with schizophrenia and 20 matched healthy volunteers (patients/controls = 19/17 after head motion rejection).

Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study.

Despite convergent neuroimaging evidence indicating a wide range of brain abnormalities in schizophrenia, our understanding of alterations in the topological architecture of brain anatomical networks and how they are modulated over time, is still rudimentary. Here, we employed graph theoretical analysis of longitudinal diffusion tensor imaging data (DTI) over a 5-year period to investigate brain network topology in schizophrenia and its relationship with clinical manifestations of the illness. Using deterministic tractography, weighted brain anatomical networks were constructed from 31 patients experiencing schizophrenia and 28 age- and gender-matched healthy control subjects.

Reduced Hemispheric Asymmetry of Brain Anatomical Networks Is Linked to Schizophrenia: A Connectome Study.

Despite convergent evidence indicating a variety of regional abnormalities of hemispheric asymmetry in schizophrenia, patterns of wider neural network asymmetry remain to be determined. In this study, we investigated alterations in hemispheric white matter topology in schizophrenia and their association with clinical manifestations of the illness. Weighted hemispheric brain anatomical networks were constructed for each of 116 right-handed patients with schizophrenia and 66 matched healthy participants.

Progressive gender differences of structural brain networks in healthy adults: a longitudinal, diffusion tensor imaging study.

Sexual dimorphism in the brain maturation during childhood and adolescence has been repeatedly documented, which may underlie the differences in behaviors and cognitive performance. However, our understanding of how gender modulates the development of structural connectome in healthy adults is still not entirely clear. Here we utilized graph theoretical analysis of longitudinal diffusion tensor imaging data over a five-year period to investigate the progressive gender differences of brain network topology.

Predictors of treatment outcome among Asian pathological gamblers (PGs): clinical, behavioural, demographic, and treatment process factors.

Research on predictors of treatment outcome among pathological gamblers (PGs) is inconclusive and dominated by studies from Western countries. Using a prospective longitudinal design, the current study examined demographic, clinical, behavioural and treatment programme predictors of gambling frequency at 3, 6 and 12-months, among PGs treated at an addiction clinic in Singapore. Measures included the Hospital anxiety and depression scale, gambling symptom assessment scale (GSAS), personal well-being index (PWI), treatment perception questionnaire and gambling readiness to change scale.

Effectiveness of interventions for the assessment and prevention of falls in adult psychiatric patients: A systematic review.

Background: Patient fall is among the top five sentinel events in hospitals due to the resultant functional loss and injury sustained. Precise fall risk assessment and prevention strategies are important components of a fall prevention program. Due to psychiatric conditions and medications, these patients may require a different fall management program compared to other patient populations.

Stress-coping morbidity among family members of addiction patients in Singapore.

Unlabelled: INTRODUCTIONS AND AIMS: Research from western countries indicates that family members of addiction patients report heightened stress and psychological morbidity. This current study aimed to examine stress, coping behaviours, related morbidity and subsequent resource utilisation among family members of patients attending a national treatment program in Singapore.

Design And Methods: The study used a matched case-control design.