A5063021950- Mycobacterium research and diagnosis
- Cognitive Abilities and Testing
- Cognitive Functions and Memory
- Multiple Sclerosis Research Studies
- Misinformation and Its Impacts
- Rheumatoid Arthritis Research and Therapies
- Healthcare Policy and Management
- Lymphadenopathy Diagnosis and Analysis
- Parkinson's Disease Mechanisms and Treatments
- Health, Environment, Cognitive Aging
- Health Systems, Economic Evaluations, Quality of Life
- EEG and Brain-Computer Interfaces
- Neurological disorders and treatments
- Risk Perception and Management
- Hate Speech and Cyberbullying Detection
- Terrorism, Counterterrorism, and Political Violence
- Online Learning and Analytics
- Digital Imaging for Blood Diseases
- Crime, Deviance, and Social Control
Imperial College London
2022-2024
Abstract Automated online cognitive assessments are set to revolutionise clinical research and healthcare. However, their applicability for Parkinson’s Disease (PD) REM Sleep Behavioural Disorder (RBD), a strong PD precursor, is underexplored. Here, we developed an battery measure early changes in RBD. Evaluating 19 candidate tasks showed significant global accuracy deficits (0.65 SD, p = 0.003) RBD (0.45 0.027), driven by memory, language, attention executive underperformance, reaction time...
Abstract Online cognitive assessment technologies are gaining traction as scalable and cost-effective alternatives to traditional supervised testing. However, variability in peoples’ home devices, their visual motor abilities, confound the specificity of online task performance scores. To address these limitations, we develop IDoCT (Iterative Decomposition Cognitive Tasks), a novel method for estimating abilities trial-difficulty scales from timecourses data-driven manner while accounting...
Registries have the potential to tackle some of current limitations in determining long-term impact multiple sclerosis. Online assessments using patient-reported outcomes can streamline follow-up enabling large-scale, long-term, cost-effective, home-based, and patient-focused data collection. However, registry are sparsely sampled sensitivity relative clinician-reported scales is unknown, making it hard fully leverage their unique scope scale derive insights. This retrospective prospective...
Abstract Introduction People with multiple sclerosis (PwMS) exhibit a spectrum of needs that extend beyond solely disease-related determinants. Investigating unmet from the patient perspective may address daily difficulties and optimize care. Our aim was to identify patterns among PwMS their Methods We conducted cross-sectional multicentre study. Data were collected through an anonymous, self-administered online form. To cluster according main needs, we performed agglomerative hierarchical...
Abstract Online cognitive tasks are gaining traction as scalable and cost-effective alternatives to traditional supervised assessments. However, variability in peoples’ home devices, visual motor abilities, speed-accuracy biases confound the specificity with which online can measure abilities. To address these limitations, we developed IDoCT (Iterative Decomposition of Cognitive Tasks), a method for estimating domain-specific abilities trial-difficulty scales from task performance...
Prescribing guidance for disease-modifying treatment (DMT) in multiple sclerosis (MS) is centred on a clinical diagnosis of relapsing-remitting MS (RRMS). DMT prescription guidelines and monitoring vary across countries. Standardising the approach to disease course, example, assigning RRMS or secondary progressive (SPMS) diagnoses, allows examination impact health system characteristics stated access.We analysed registry data from six cohorts five countries (Czech Republic, Denmark, Germany,...
Neurological conditions present with cognitive impairment that greatly affects the quality of life patients and should be routinely evaluated. However, it can difficult to detect impractical monitor classic in person assessment due limitations sensitivity, scalability cost. Internet- app-based tools for are a potential solution this problem, offering superior sensitivity being deliverable remotely context clinical registries, providing an acces- sible cost-effective way combine large-scale...
Which population factors have predisposed people to disregard government safety guidelines during the COVID-19 pandemic and what justifications do they give for this non-compliance? To address these questions, we analyse fixed-choice free-text responses survey questions about compliance handling of pandemic, collected from tens thousands members UK public at three 6-monthly timepoints. We report that sceptical opinions mainstream-media narrative, especially as pertaining justification...
Abstract The COVID-19 pandemic represents a unique context for studying the spread of conspiratorial beliefs within general population and their role in mediating compliance with government guidance. Here, we apply multivariate machine learning methods to analyse data from tens thousands members British public at 6-monthly timepoints during pandemic. We report that distrust significantly predict non-compliant behaviours covary sociodemographic variables, being most prevalent disadvantaged...