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Speech and Language Therapists’ Perspectives of Virtual Reality as a Clinical Tool for Autism: Cross-Sectional Survey
Full text linkBackground:Persistent difficulties with social skills form part of the diagnostic criteria for autism and in the past have required speech and language therapy (SLT) management. However, many speech and language therapists are moving toward neuro-affirmative practices, meaning that social skills approaches are now becoming redundant. Research demonstrates that virtual reality (VR) interventions have shown promise in overcoming challenges and promoting skill generalization for autistic children; however, the majority of these focus on social skills interventions. While VR is emerging as an SLT intervention, its application for autism remains unexamined in clinical practice.Objective:This research aimed to examine speech and language therapists’ knowledge and attitudes toward immersive VR as a clinical tool for autistic children and explore the reasons for its limited integration into clinical practice.Methods:A web-based cross-sectional survey was available from April 3, 2023 to June 30, 2023. The survey, consisting of 23 questions, focused on VR knowledge, attitudes, and the support required by speech and language therapists to incorporate VR into clinical practice. Dissemination occurred through the Royal College of Speech and Language Therapists Clinical Excellence Networks to recruit speech therapists specializing in autism.Results:Analysis included a total of 53 responses from the cross-sectional survey. Approximately 92% (n=49) of speech and language therapists were aware of VR but had not used it, and 1.82% (n=1) had used VR with autistic children. Three key themes that emerged were (1) mixed general knowledge of VR, which was poor in relation to applications for autism; (2) positive and negative attitudes toward VR, with uncertainty about autism specific considerations for VR; and (3) barriers to adoption were noted and speech and language therapists required an improved neuro-affirming evidence base, guidelines, and training to adopt VR into clinical practice.Conclusions:While some speech and language therapists perceive VR as a promising intervention tool for autistic children, various barriers must be addressed before its full integration into the clinical toolkit. This study establishes a foundation for future co-design, development, and implementation of VR applications as clinical tools for autistic children.This study is the first to explore clinical implementation factors for the use of VR in SLT field, specifically with autistic children. Poor autism-specific VR knowledge, and mixed attitudes toward VR, highlight that specific barriers must be addressed before the technology can successfully integrate into the SLT clinical toolkit.Speech and language therapists require support from employers, funding, a robust neuro-affirming evidence base, and education and training to adopt VR into practice. Recommendations for a SLT VR education and training program for use with autistic children, are provided
Global, regional, and national prevalence of adult overweight and obesity, 1990–2021, with forecasts to 2050:a forecasting study for the Global Burden of Disease Study 2021
Full text linkBackground: Overweight and obesity is a global epidemic. Forecasting future trajectories of the epidemic is crucial for providing an evidence base for policy change. In this study, we examine the historical trends of the global, regional, and national prevalence of adult overweight and obesity from 1990 to 2021 and forecast the future trajectories to 2050. Methods: Leveraging established methodology from the Global Burden of Diseases, Injuries, and Risk Factors Study, we estimated the prevalence of overweight and obesity among individuals aged 25 years and older by age and sex for 204 countries and territories from 1990 to 2050. Retrospective and current prevalence trends were derived based on both self-reported and measured anthropometric data extracted from 1350 unique sources, which include survey microdata and reports, as well as published literature. Specific adjustment was applied to correct for self-report bias. Spatiotemporal Gaussian process regression models were used to synthesise data, leveraging both spatial and temporal correlation in epidemiological trends, to optimise the comparability of results across time and geographies. To generate forecast estimates, we used forecasts of the Socio-demographic Index and temporal correlation patterns presented as annualised rate of change to inform future trajectories. We considered a reference scenario assuming the continuation of historical trends. Findings: Rates of overweight and obesity increased at the global and regional levels, and in all nations, between 1990 and 2021. In 2021, an estimated 1·00 billion (95% uncertainty interval [UI] 0·989–1·01) adult males and 1·11 billion (1·10–1·12) adult females had overweight and obesity. China had the largest population of adults with overweight and obesity (402 million [397–407] individuals), followed by India (180 million [167–194]) and the USA (172 million [169–174]). The highest age-standardised prevalence of overweight and obesity was observed in countries in Oceania and north Africa and the Middle East, with many of these countries reporting prevalence of more than 80% in adults. Compared with 1990, the global prevalence of obesity had increased by 155·1% (149·8–160·3) in males and 104·9% (95% UI 100·9–108·8) in females. The most rapid rise in obesity prevalence was observed in the north Africa and the Middle East super-region, where age-standardised prevalence rates in males more than tripled and in females more than doubled. Assuming the continuation of historical trends, by 2050, we forecast that the total number of adults living with overweight and obesity will reach 3·80 billion (95% UI 3·39–4·04), over half of the likely global adult population at that time. While China, India, and the USA will continue to constitute a large proportion of the global population with overweight and obesity, the number in the sub-Saharan Africa super-region is forecasted to increase by 254·8% (234·4–269·5). In Nigeria specifically, the number of adults with overweight and obesity is forecasted to rise to 141 million (121–162) by 2050, making it the country with the fourth-largest population with overweight and obesity. Interpretation: No country to date has successfully curbed the rising rates of adult overweight and obesity. Without immediate and effective intervention, overweight and obesity will continue to increase globally. Particularly in Asia and Africa, driven by growing populations, the number of individuals with overweight and obesity is forecast to rise substantially. These regions will face a considerable increase in obesity-related disease burden. Merely acknowledging obesity as a global health issue would be negligent on the part of global health and public health practitioners; more aggressive and targeted measures are required to address this crisis, as obesity is one of the foremost avertible risks to health now and in the future and poses an unparalleled threat of premature disease and death at local, national, and global levels. Funding: Bill & Melinda Gates Foundation.</p
Reconfiguring Gene Regulatory Neural Network Computing for Regulating Biofilm Formation
Full text linkThe Gene Regulatory Network (GRN) in biological cells orchestrates essential functions for adaptation and survival in diverse environments, drawing on structural similarities with the Artificial Neural Network (ANN), which can be transformed into a Gene Regulatory Neural Network (GRNN). This transformation enables exploration of their natural computing capabilities regarding network reconfigurability and controllability, facilitating dynamic adjustments of gene-gene interaction weights to regulate biological processes. In this paper, we present a control-theoretic model for the GRNN that determines optimal chemical input concentrations, steering the GRNN towards desired weight configurations using the Linear Quadratic Regulator (LQR) approach. This method enhances network robustness by balancing stability and reconfigurability, ensuring responsive weight adjustments in dynamic environments. We develop mathematical models to identify critical genes using a Continuous-Time Markov Chain (CTMC) and derive temporal weight configurations, providing insights into the system's reconfiguration dynamics, while also quantifying stability and reconfigurability. Our findings demonstrate the effectiveness of the control model in mitigating Clostridioides difficile biofilm formation, outperforming sub-optimal and stochastic perturbation inputs, and highlighting the importance of determining optimal inputs for robust network behavior across diverse complexities
Integrating AI into medical imaging curricula: Insights from UK HEIs
Full text linkIntroduction With artificial intelligence (AI) becoming increasingly integrated into medical imaging, the Health and Care Professions Council (HCPC) updated its Standards of Proficiency for Radiographers in Autumn 2023. These changes require clinicians to be both competent and confident in operating AI and related technologies within their role. Responsibility for meeting these standards extends beyond individual clinicians to higher education institutions (HEIs), which play a crucial role in preparing future professionals. This study examines the current and planned provision of AI education for medical imaging students and staff, identifying potential challenges in its implementation. Methods An electronic survey was developed and hosted on the Joint Information Systems Committee (JISC) platform. It was disseminated in April 2023 by the Society of Radiographers to UK HEIs offering medical imaging programmes. Results 24 HEIs responded, with representation from all four UK nations. Of these, 71 % (n = 17) had already integrated AI into their curriculum. Reported challenges included timetabling constraints and the need to upskill staff. 21 % (n = 5) indicated that AI would be incorporated following course revalidation in the 2024/25 academic year, while the remaining two HEIs were unaware of planned changes. Conclusion Most UK HEIs have begun integrating AI education into medical imaging programmes. However, significant disparities exist in the depth and scope of AI content across institutions. Further efforts are needed to develop a comprehensive and standardised AI curriculum for medical imaging in the UK. Implications for practice This study highlights key areas for improvement in AI education within medical imaging programmes. Further research into content and delivery methods is essential to ensure radiography professionals adequately equipped to navigate the evolving clinical environment
Public Service Broadcasting in Northern Ireland: Research Monitoring Report – 2025
Full text linkResearch Brief for ‘The Future of Public Service Mediain Northern Ireland: the Policy Implications of Researchand Practice’, 9 May 2025.Funded by Ulster University’s Research Impact Fund, and supported by theCentre for Communication, Media and Cultural Studies, within the Schoolof Communication and Media
Effects of professor swearing on learning and perceptions: a pilot field study
Full text linkIntroduction: The purpose of this pilot study was to provide preliminary evidence on the effects of an instructor swearing during a lecture on learning and student perceptions in a field classroom setting. Methods: First-year doctoral students (n = 36) who were enrolled in a Human Anatomy course within a physical therapist education program were randomly assigned to a non-swearing lecture (NSL; n = 18) or a swearing lecture (SL; n = 18) on basic human anatomy. A single instructor provided identical 40-min lectures to each student group except for two inserted phrases to emphasize content which differed between NSL and SL. For the NSL, the instructor emphasized the content by stating: “Anatomy just makes sense sometimes” and “Anatomy is interesting.” For the SL, the content was emphasized by saying “Anatomy just makes f***ing sense sometimes” and “This s**t is interesting.” Following the lectures, a 10-question post-lecture knowledge retainment assessment (“pop” quiz) was given to the NSL and SL groups. The SL group also completed a 14-item mixed methods survey with 12 Likert and 2 open-ended questions regarding student perceptions. Results: There were no differences in knowledge retainment on the “pop” quiz scores between the NSL and SL (p = 0.780). Results from the mixed methods survey suggested an overall neutral to positive response to the SL whereby swearing did not negatively impact learning or perception of the instructor or the class. Discussion: Collectively, this pilot field study provides preliminary evidence suggesting that swearing during a lecture in higher education neither helps nor hurts student learning or perceptions of instructors and may positively impact student perceptions of the class. Future studies with additional control and larger diverse populations are warranted
MEDERED: Medical Error Reduction Method for Drugs Prescription
Full text linkMedicines play a pivotal role in healthcare and errors in medications certainly influence the quality and safety of healthcare. Currently, the healthcare industry is provided with various technologies that have enabled them to streamline and optimize the healthcare process. However, there are a number of factors that need to be synchronized further to obtain and enhance patient safety. In this research, an attempt is made to develop an intelligent method for smart diagnosis and medication prescription encompassing input, data process, and drug prescription output. The architectural design and prototype for the system model has a database that is referred to as Medical Health Record (MHR). The patient's medical history will be integrated with the prevailing symptoms in MHR. The MHR will help healthcare professionals to diagnose a particular disease based on his/her current symptoms, medical signs, and investigational data. Further, physician and pharmacist heuristic can be utilized for drug determination, drug allergy, adverse reaction, and possible drugdrug/herb/food interaction. The medical dataset was extracted from PubMed. This new AI based approach will re-engineer intelligent smart methods to develop quality healthcare in the most appropriate fashion. The learning results demonstrated an accuracy of 75.37%, providing a solid baseline for future model improvements
From awareness to action: How to ELEVATE Student AI Literacy through a Business School living lab.
Full text linkWhen students at Ulster University were asked how confident they felt using AI, many admitted they were unsure where to start and even less certain about what was “allowed.” After a workshop, those same students had almost doubled their confidence in applying AI tools ethically and effectively. That transformation was the aim of ELEVATE (Empowering Learning and Efficacy via AI Through Education), a Business School initiative designed to build practical, ethical AI literacy for students, staff and industry partners. Drawing on a “Living Lab” approach (Bergvall-Kåreborn et al., 2009), ELEVATE created an open, hands-on space where learners could experiment, reflect and apply AI in varying contexts (Purcell et al., 2019). Our motivation came from earlier successes with the MarTech Laboratory (Bustard etal., 2023), where authentic challenges proved that students learn best when they engage creatively, test ideas and see the real-world impact from their work (Tercanli & Jongbloed, 2022)
Counteracting the Inactivity Epidemic:Should We Ring-Fence Paid Work Time for Physical Activity?
Full text linkExploring the Fire Behaviour of Intumescent Coatings for Steel Structures Under Different Exposure Conditions
Full text linkThe paper compares the performance at elevated temperatures of three water based intumescent coatings (IC) exposed to constant heat flux in a cone calorimeter with the performance of a water-based IC which has been heated in a gas furnace according tothe standard and the smouldering nominal heating curves, during a previous experimental program. The tests herein presented were carried out on steel plates, with different thickness to vary their section factors, protected with IC layer characterized by different dryfilm thickness. Despite the IC activated at about 120 °C regardless the heating conditions (i.e., under the cone or in the gas furnace), the type of heating affected the structure of the IC char that formed during the heat exposures: both the expansion of the IC and its equivalent thermal conductivity seems to be dependent on the fire exposure scenarios