Te Ōranga Ō Te Roro: kaumātua perspectives on the development of a mobile app for mate wareware (dementia) awareness.

Aim: Mate wareware (dementia) presents a significant social and economic burden for Māori in Aotearoa New Zealand. Previous literature has highlighted the need to improve health literacy for Māori regarding the causes and management of mate wareware, yet there is a lack of Māori-centred educational resources. It was determined that a mobile phone application (app) could meet this need and that early consultation with Māori was required to ensure the digital solution would be culturally safe and relevant.

Filter and Wrapper Stacking Ensemble (FWSE): a robust approach for reliable biomarker discovery in high-dimensional omics data.

Selecting informative features, such as accurate biomarkers for disease diagnosis, prognosis and response to treatment, is an essential task in the field of bioinformatics. Medical data often contain thousands of features and identifying potential biomarkers is challenging due to small number of samples in the data, method dependence and non-reproducibility. This paper proposes a novel ensemble feature selection method, named Filter and Wrapper Stacking Ensemble (FWSE), to identify reproducible biomarkers from high-dimensional omics data.

Usability and feasibility of PreventS-MD web app for stroke prevention.

Background: Most strokes and cardiovascular diseases (CVDs) are potentially preventable if their risk factors are identified and well controlled. Digital platforms, such as the PreventS-MD web app (PreventS-MD) may aid health care professionals (HCPs) in assessing and managing risk factors and promoting lifestyle changes for their patients.

Methods: This is a mixed-methods cross-sectional two-phase survey using a largely positivist (quantitative and qualitative) framework.

Enhancing precision of the Telephone Interview for Cognitive Status-Modified (TICS-M) using the Rasch model.

The Telephone Interview for Cognitive Status-modified (TICS-M) is a well-established and widely used screening instrument for dementia and assessment of global cognitive function in older people. This study aimed to evaluate the psychometric properties of the TICS-M and to enhance the accuracy of the instrument using Rasch methodology. Partial Credit Rasch model was applied to the TICS-M scores.

Using network analysis to validate domains of the modified telephone interview for cognitive status.

Background: The modified Telephone Interview for Cognitive Status (TICS-M) is a widely used tool for assessing global cognitive functions and screening for cognitive impairments. The tool was conceptualised to capture various cognitive domains, but the validity of such domains has not been investigated against comprehensive neuropsychological assessments tools. Therefore, this study aimed to explore the associations between the TICS-M domains and neuropsychological domains to evaluate the validity of the TICS-M domains using network analysis.

Investigation of social and cognitive predictors in non-transition ultra-high-risk' individuals for psychosis using spiking neural networks.

Finding predictors of social and cognitive impairment in non-transition Ultra-High-Risk individuals (UHR) is critical in prognosis and planning of potential personalised intervention strategies. Social and cognitive functioning observed in youth at UHR for psychosis may be protective against transition to clinically relevant illness. The current study used a computational method known as Spiking Neural Network (SNN) to identify the cognitive and social predictors of transitioning outcome.

A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients.

Introduction: Early determination of COVID-19 severity and health outcomes could facilitate better treatment of patients. Different methods and tools have been developed for predicting outcomes of COVID-19, but they are difficult to use in routine clinical practice.

Methods: We conducted a prospective cohort study of inpatients aged 20-92 years, diagnosed with COVID-19 to determine whether their individual 5-year absolute risk of stroke at the time of hospital admission predicts the course of COVID-19 severity and mortality.

Tobacco use among Kola Sámi, the indigenous people of the Murmansk region, Russia: A cross-sectional study.

Russia is among the top ten nations in terms of smoking prevalence. Little is known about smoking rates among Indigenous Peoples in Russia. Our aim was to assess the prevalence of tobacco and nicotine product use among Kola peninsula Sámi.

A novel approach to investigate depression symptoms in the aging population using generalizability theory.

As depression is common in older people and confers significant risk for dementia, its accurate assessment is essential. The 15-item Geriatric Depression Scale (GDS-15) is a widely used assessment tool for measuring depression in aged populations, and its psychometric properties have been recently improved using Rasch analysis. However, its temporal reliability and ability to distinguish between dynamic and enduring symptoms of depression have not been examined using the appropriate methodology.

Machine learning, artificial intelligence and the prediction of dementia.

Purpose Of Review: Artificial intelligence and its division machine learning are emerging technologies that are increasingly applied in medicine. Artificial intelligence facilitates automatization of analytical modelling and contributes to prediction, diagnostics and treatment of diseases. This article presents an overview of the application of artificial intelligence in dementia research.

Enhancing precision of the 16-item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE-16) using Rasch methodology.

Objective: This study aimed to investigate psychometric properties and enhance precision of the 16-item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE-16) up to interval-level scale using Rasch methodology.

Design: Partial Credit Rasch model was applied to the IQCODE-16 scores using longitudinal data spanning 10 years of biennial follow-up.

Setting: Community-dwelling older adults aged 70-90 years and their informants, living in Sydney, Australia, participated in the longitudinal Sydney Memory and Ageing Study (MAS).

General hospital specialists' attitudes toward psychiatry: a cross-sectional survey in seven countries.

Objective: Psychiatric comorbidities are common in physical illness and significantly affect health outcomes. Attitudes of general hospital doctors toward psychiatry are important as they influence referral patterns and quality of care. Little is known about these attitudes and their cultural correlates.

Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia.

Background: Longitudinal neuroimaging provides spatiotemporal brain data (STBD) measurement that can be utilised to understand dynamic changes in brain structure and/or function underpinning cognitive activities. Making sense of such highly interactive information is challenging, given that the features manifest intricate temporal, causal relations between the spatially distributed neural sources in the brain.

Methods: The current paper argues for the advancement of deep learning algorithms in brain-inspired spiking neural networks (SNN), capable of modelling structural data across time (longitudinal measurement) and space (anatomical components).

Cross-cultural validation of the stroke riskometer using generalizability theory.

The Stroke Riskometer mobile application is a novel, validated way to provide personalized stroke risk assessment for individuals and motivate them to reduce their risks. Although this app is being used worldwide, its reliability across different countries has not yet been rigorously investigated using appropriate methodology. The Generalizability Theory (G-Theory) is an advanced statistical method suitable for examining reliability and generalizability of assessment scores across different samples, cultural and other contexts and for evaluating sources of measurement errors.

Clinical investigation of dynamic and enduring aspects of global cognition in aged population.

Background: A major issue in evaluating the cognitive status of ageing populations is a clear distinction between enduring and dynamic aspects of global cognition necessary for evaluating risks of dementia and effectiveness of preventive interventions.

Materials And Methods: Generalizability Theory was applied to investigate dynamic and enduring aspects of global cognition using longitudinal data over 10 years of follow-up. Measures included the Mini-Mental Status Examination (MMSE) and the Telephone Interview for Cognitive Status-modified (TICS-M).

Trends in tobacco smoking and smoking cessation in Russia with a focus on Indigenous populations: A narrative review.

Introduction: Tobacco smoking is one of the main preventable causes of illness and premature death. Globally, more than 7 million people die annually from diseases associated with smoking, and this number is projected to increase to 8 million per year by 2030. Wide disparities in smoking prevalence exist by gender, age, socioeconomic status, rurality and ethnicity.

Can we stop the stroke tsunami? Mitigating the barriers, amplifying the facilitators.

In this narrative review article, by critically appraising the Global Burden of Disease 1990-2017 data on stroke and currently used primary stroke prevention strategies, we show that the global burden of stroke will continue to rise unless new primary stroke and cardiovascular disease (CVD) prevention strategies are urgently implemented. We provide an overview of the advantages and disadvantagesof population-wide and high CVD risk prevention strategies and mobile technologies available for stroke and CVD prevention on individual and population levels. Our recent NZ pilot RCT demonstrated the feasibility, consumer acceptability, motivational value and a clinically important, albeit statistically non-significant, behaviour change, improvement in diet, and awareness of stroke symptoms.

New avenue for the geriatric depression scale: Rasch transformation enhances reliability of assessment.

Background: Depression is a common problem in older adults. The 15-item Geriatric Depression Scale (GDS-15) is a widely used psychometric tool for measuring depression in the elderly, but its psychometric properties have not been yet rigorously investigated. The aim was to evaluate psychometric properties of the GDS-15 and improve precision of the instrument by applying Rasch analysis and deriving conversion tables for transformation of raw scores into interval level data.