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School life during COVID-19: a qualitative study exploring English secondary school staff and pupils’ experiences of the school-based mitigation measures
Get PDFBackground In England, the national Government was responsible for balancing the risks of COVID-19 infection, transmission and illness against the known risks of school closures. The Department for Education (DfE) issued guidance to schools, however, there is limited empirical evidence on the experiences of staff and pupils affected by the guidance and accompanying COVID-19 mitigation measures. Methods This qualitative study explored secondary school staff and pupils’ views and experiences of COVID-19 guidance and mitigation measures. There were two main objectives: (i) to examine implementation effectiveness, and (ii) to explore their effectiveness at promoting safety. Participants were purposively sampled from English schools serving diverse communities participating in the CoMMinS (COVID-19 Mapping and Mitigation in Schools) study. Semi-structured interviews were conducted remotely, and data were analysed thematically. Results Interviews took place between January and August 2021 with participants from five secondary schools (20 staff and 25 pupils); staff represented a range of roles within the school and pupil demographics varied. Main themes were: (i) negative views of the DfE guidance; (ii) negative experiences of the DfE guidance; (iii) ineffectiveness of the DfE guidance and school mitigation measures at promoting safety and reducing risk; (iv) ineffective implementation of the mitigation measures due to poor adherence and acceptability (with sub-themes for Lateral Flow Testing (LFT), face coverings, physical distancing and ventilation); and (v) positive perceptions (with sub-themes for hygiene measures, and approaches that facilitated implementation and safety which included staff enforcing compliance, having an ethos of co-operation, addressing inconsistencies, and minimising change). Conclusions Insights from this research will help understand effectiveness of the measures in the ‘real-world school setting’. Understanding the experiences of staff and pupils will help to support policymakers and school leaders in future pandemic decision-making. This research identified challenges with the guidance and measures, minimal impact on perceived safety, and a negative impact on wellbeing. These challenges should be considered when assessing the benefit of the measures in keeping schools safe
'She didn't know what to do with me': the experience of seeking community mental health support after spinal cord injury
Get PDFContext/Objectives: Adults with spinal cord injury in the UK do not currently have specialized access to SCI-informed community-based mental health support, despite their elevated risk of mental health decline. The lack of SCI-informed therapeutic support may increase the likelihood of mental health treatment failure. This study sought to qualitatively explore the experience of accessing, or attempting to access, generic (non-SCI-informed) mental health support when living with a spinal cord injury. Design: Qualitative, exploratory study using thematic analysis. Setting: Community-based sample in the UK. Participants: Twenty people with spinal cord injury (10 female, 10 male) were recruited from a UK-based, SCI-specific support charity. Interventions: Semi-structured interviews (mean length = 83 min, SD = 13.5 min). Outcome Measures: 9-item semi-structured interview schedule, addressing mental health service use. Results: Three themes were identified: (1) Therapeutic timeliness; (2) A disconnect with standard services; and (3) Successful systems for support. The inpatient-to-outpatient transition represents a critical time window during which mental health is vulnerable to decline, requiring responsive access to mental health services throughout the lifespan. The lack of tailored, SCI-informed mental health services inhibits therapeutic engagement and limits perceived treatment outcomes. Conclusions: Without SCI-informed care, generic mental health service referrals risk early termination of support and treatment disengagement. Mental health treatment withdrawal is initiated by both patients and their allocated healthcare professionals. This study demonstrates an evident need to develop programs for people with SCI to train as (peer) mental health practitioners, and to develop SCI-specific training modules for mental health care practitioners.</p
Digital language learning: the cognitive, affective and social rewards for older adults
Get PDFDigital technology has transformed the way we learn and access educational materials. While digital technology offers new opportunities for language learning, it also presents new challenges for older adults. However, when older adult learners are supported and encouraged by participatory and collaborative activities that address their interests and needs, their learning motivation can increase. This chapter begins by examining the theoretical background of sociocultural theory and second language acquisition, before discussing the cognitive, affective, and social dimensions of learning. The chapter explores the definitions of older adults and digital language learning and highlights the benefits of blended learning, which provides a context and a platform for interpersonal learning and collective learning autonomy. The chapter concludes by presenting a case study that demonstrates how digital technology can provide older adults with individualised support, making language learning cognitively, emotionally, and socially rewarding for each learner
Carbon equality could play a positive role in mitigating the climate crisis
Get PDFHumans needs to solve the urgent problem of analyzing the severe climate crisis and studying its profound impacts on the Earth. This paper introduces the concept of “carbon equality.” By detailing the concept, manifestations, and hazards of the climate crisis, as well as explaining the connotation and practical advantages of carbon equality, and combining this with real-life cases, it demonstrates the crucial role that carbon equality could play as a core solution in responding to the climate crisis. Based on the research results, this paper puts forward practical solutions to provide new ideas for global sustainable development
A complex systems view on physical activity with actionable insights for behaviour change
No full textPhysical inactivity and its associated health and economic burdens continue to rise despite decades of interdisciplinary research aimed at promoting physical activity. This Perspective takes a complex systems view on physical activity, proposing that at least two layers of complexity should be considered: (1) interactions between various physiological, psychological, social and environmental systems; and (2) their dynamic interactions across time. To address this complexity, all stages of the research process—from theory and measurement to study design, analysis and interventions—must be aligned with a complex systems perspective. This alignment requires intensive interdisciplinary collaboration and an integration of basic and applied research beyond current research practices to create transdisciplinary solutions. We offer actionable insights that bridge the gap between abstract theoretical approaches (for example, complex systems and attractor landscape frameworks of behaviour change) and practical research on physical activity, thereby laying a foundation for more effective behaviour change interventions
Bayesian learning strategies for reducing uncertainty of decision-making in case of missing values
Get PDFBackground: Liquidity crises pose significant risks to financial stability, and missing data in predictive models increase the uncertainty in decision-making. This study aims to develop a robust Bayesian Model Averaging (BMA) framework using decision trees (DTs) to enhance liquidity crisis prediction under missing data conditions, offering reliable probabilistic estimates and insights into uncertainty. Methods: We propose a BMA framework over DTs, employing Reversible Jump Markov Chain Monte Carlo (RJ MCMC) sampling with a sweeping strategy to mitigate overfitting. Three preprocessing techniques for missing data were evaluated: Cont (treating variables as continuous with missing values labeled by a constant), ContCat (converting variables with missing values to categorical), and Ext (extending features with binary missing-value indicators). Results: The Ext method achieved 100% accuracy on a synthetic dataset and 92.2% on a real-world dataset of 20,000 companies (11% in crisis), outperforming baselines (AUC PRC 0.817 vs. 0.803, p < 0.05). The framework provided interpretable uncertainty estimates and identified key financial indicators driving crisis predictions. Conclusions: The BMA-DT framework with the Ext technique offers a scalable, interpretable solution for handling missing data, improving prediction accuracy and uncertainty estimation in liquidity crisis forecasting, with potential applications in finance, healthcare, and environmental modeling.</p
Advanced machine learning algorithms for blood pressure classification: early detection or prevention could save lives
Get PDFObjectives: The primary objective of the study is to classify the blood pressure (BP) levels using advanced machine learning (ML) techniques for predictive purposes. The study assesses the efficacy of the Naïve Bayes, AdaBoost, feedforward neural networks (FNNs), and long short-term memory (LSTM) algorithms over the conventional multinomial logistic model using standard performance evaluation metrics. Methods: The dataset comprised 15,000 entries obtained from the National Health Service, England, each containing eight variables. The variables include BP, age, weight, height, gender, smoking habit, alcohol consumption, and fitness level. The Naïve Bayes, AdaBoost, FNN, LSTM, and multinomial logistic models were employed in the study. Each model underwent training, testing, validation, and evaluation using suitable metrics such as accuracy, F1-Score, kappa statistics, sensitivity, specificity, and area under the curve score. Results: The FNN model gives the highest test accuracy of 89.47% and balanced performance, making it the most appropriate model for predicting BP levels. The LSTM model demonstrated strong proficiency in capturing temporal patterns. AdaBoost was highly effective for dealing with class imbalance, but Naïve Bayes was a dependable benchmark. The multinomial logistic model established a reliable and stable reference point. The results represented a notable improvement over previous research, which typically reported median accuracy rates in the 80–85% range. Conclusion: The study reveals that knowing an individual’s age, weight, height, gender, smoking habit, alcohol consumption, and fitness level is useful in predicting his/her BP level. Thus, the advanced ML algorithms demonstrate potential in accurately classifying BP levels and can aid in the prevention, detection, and management of hypertension
Implications of cyber-stalking law on male victims: evaluating the sociological perspective
No full textCyberstalking is an increasingly prevalent form of harassment in the digital age. On the outside, it has laws and regulations that are designed to protect victims. However, the sociological implications of these laws, particularly as they pertain to male victims, have received limited attention. This conference paper aims to shed light on the challenges faced by male victims of cyberstalking and to evaluate the sociological impact of existing laws and regulations. Based on an in-depth analysis of the experiences of male victims, this paper would explore the ways in which gender norms, stereotypes, and societal perceptions intersect with cyberstalking laws and their enforcement
Increasing phytochemical-rich foods and Lactobacillus probiotics in men with low-risk prostate cancer: a randomised, double-blind, placebo-controlled trial
Get PDFMen on active surveillance (AS), with prostate cancer, are very interested in dietary strategies that could improve their symptoms and help prevent progression of their disease. In this real-world trial involving 208 men, intake of phytochemical-rich food capsules helped slow prostate-specific antigen (PSA) progression significantly, and improved urinary symptoms and erectile function. What was novel about this study was that men randomised to take an additional blend of five Lactobacillus probiotics had a further three-fold slowing of PSA progression as well as reduction of inflammation. Currently, nearly 50% of men opt out of AS within 5 yr. If confirmed with further follow-up, these dietary interventions, alongside other lifestyle manoeuvres, could reassure men to remain on AS, and hence avoid the risks of radiotherapy, hormones, or surgery
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