Arts-based research and social justice in sport and leisure

The importance of social justice research is well recognised in current times, in particular the need for innovative studies that intervene into the complex challenges faced within twenty-first century societies. Research that makes a difference. Research that works with, on and around the political, economic and sociocultural obstacles that can conspire to inhibit change where it is most badly needed. As the chapters in this Handbook demonstrate, the importance of social justice scholarship across the field of sport, leisure and physical activity is recognised. Here, too, researchers, scholars and activists work in ways that strive to make a positive difference. In this chapter, we consider the utility of arts-based approaches to social justice research and reflect on examples of two film-based projects in sport, leisure and physical activity. We engage with public responses to these examples, demonstrating the personal, social and cultural meaning and impact of the work and showing how arts-based research can generate community, solidarity, and personal or social change. We propose that arts-based research offers a means to radically democratize social justice research and scholarship

Evaluating a model of best practice in primary care led post-diagnostic dementia care: feasibility and acceptability findings from the PriDem study

Objectives: To evaluate the feasibility and acceptability of a primary care-based intervention for improving post-diagnostic dementia care and support (PriDem), and implementation study procedures. Design: A non-randomised, mixed methods, feasibility study. Setting: Seven general practices from four primary care networks (PCNs) in the Northeast and Southeast of England. Participants: We aimed to recruit 80 people with dementia (PWD) and 66 carers. Intervention: Clinical Dementia Leads delivered a 12-month intervention in participating PCNs, to develop care systems, build staff capacity and capability, and deliver tailored care and support to PWD and carers. Outcomes: Recruitment and retention rates were measured. A mixed methods process evaluation evaluated feasibility and acceptability of the intervention and study procedures. Using electronic care records, researchers extracted service use data and undertook a dementia care plan audit, preintervention and postintervention, assessing feasibility of measuring the primary implementation outcome: adoption of personalised care planning by participating general practices. Participants completed quality of life, and service use measures at baseline, 4 and 9 months. Results: 60 PWD (75% of recruitment target) and 51 carers (77% of recruitment target) were recruited from seven general practices across four PCNs. Retention rate at 9 months was 70.0% of PWD and 76.5% of carers. The recruitment approach showed potential for including under-represented groups within dementia. Despite implementation challenges, the intervention was feasible and acceptable, and showed early signs of sustainability. Study procedures were feasible and accessible, although researcher capacity was crucial. Participants needed time and support to engage with the study. Care plan audit procedures were feasible and acceptable

Activation of LXRs alleviates neuropathic pain-induced cognitive dysfunction by modulation 2 of microglia polarization and synaptic plasticity via PI3K/AKT pathway.

Background Cognitive dysfunction is one of the most common comorbidities in patients with chronic pain. It has been shown that activation of Liver X receptors (LXRs) plays a potential role in improving cognitive disorders in multiple central nervous diseases by modulating neuroinflammation and synaptic plasticity. In this study, we mainly investigated whether LXRs could reverse cognitive deficits induced by neuropathic pain. Methods The spared nerve injury (SNI) model was established to explore the roles of LXRs in neuropathic pain induced-cognitive dysfunction. Pharmacological activation of LXRs by T0901317 or inhibition by GSK2033 was applied. In addition, the phosphatidylinositol 3-kinase (PI3K) inhibitor LY294002 was administered to examine the downstream mechanism of LXRs. Changes in neuroinflammation, microglia polarization, and synaptic plasticity were assessed using biochemical technologies. Results We found that SNI induced mechanical allodynia and novel object recognition dysfunction in mice, accompanied by the reduction in expression levels of LXRβ, synaptic proteins, and the PI3K/AKT pathway in the hippocampus. Microglia were activated in the hippocampus after SNI, with an increase in M1 phenotype and decrease in M2 phenotype, as well as upregulation of pro-inflammatory cytokines. Activation of LXRs with T0901317 significantly ameliorated SNI-induced cognitive dysfunction including anxiety, learning and memory. Neuroinflammation and microglia M1-polarization also induced by SNI were reversed after using T0901317. Moreover, T0901317 upregulated expression levels of synaptic proteins and phosphorylation of PI3K and AKT. However, administration of the LXRs inhibitor GSK2033 or PI3K inhibitor LY294002 abolished all the protective effects of T0901317 on cognitive dysfunction in SNI mice. Conclusion Our data indicate that LXRs activation alleviated neuropathic pain-induced cognitive dysfunction by modulating microglia polarization, neuroinflammation, and synaptic plasticity via the PI3K/AKT signaling pathway, and thus, LXRs may be identified as potential new targets for pain-related cognitive deficits. Keywords Liver X receptors; Neuropathic pain; Microglia polarization; Cognitive dysfunction; Neuroinflammatio

Tell-Tall Signs of Voice and Exit’s Hirschman Theory in this Digital Age: Analysis of the Zimbabwean Healthcare Sector

The Zimbabwean healthcare sector has faced a challenging shortage of health professionals in recent days. This study investigates the phenomenon of health professionals leaving the country, and to understand the situation, this review used (Hirschman, Exit, voice, and loyalty: Responses to decline in firms, organizations, and states, Harvard University Press, 1970) voice and exit theory. The researchers took advantage of the digital age and obtained relevant reports on the internet; after a vigorous selection process, the six most relevant reports on Zimbabwean health professionals were selected and analysed in this review. The findings indicate that Hirschman’s theory applies to understanding the employment relations in the Zimbabwean healthcare sector. The data shows that Zimbabwean health professionals used their voices to challenge the status quo before leaving the country. However, the evidence from the data obtained highlighted that these health professionals had no option but to exit the country since the Zimbabwean government’s reaction was powerful and gave no room for active voice behaviours. However, this study recommends the Zimbabwean government consider allowing some voices in the healthcare sector to get a meaningful chance to sort the situation in this sector, as the reports will always be available due to this digital age. Despite limitations in this study, such as the limited data used, the findings are valid, although future researchers should consider larger samples to get an in-depth understanding of the employment relationship in the Zimbabwean healthcare sector

Architectural Strategies for Flood Mitigation in Urban Environments: A Study of Traditional Elements and Contemporary Resilience

Natural disasters cause extensive losses worldwide annually. Flood events are responsible for economic and life-threatening damages[1]. To mitigate flood risks and resulting damages, particularly in the construction of residential buildings, two approaches exist. First: constructing in areas with lower flood susceptibility, and second: implementing architectural solutions to fortify structures against floods and associated hazards. Due to the presence of water resources, rivers, etc., prompting urban expansion due to reasons like transportation, trade, agricultural use, household consumption, etc., construction near rivers and flood-prone areas becomes inevitable[2]. This underscores the importance of the second approach—architectural fortification. In this study, areas highly susceptible to flooding were identified from flood zoning maps using artificial intelligence to adapt these maps and estimate the most hazardous regions[3]. Subsequently, by examining the specific elements of traditional architecture in each of these areas and exploring the cause and function of each element in facing floods over time, attention is given to the particular and regional (indigenous) architectural features that have responded to floods. Finally, appropriate architectural measures and responses to reduce flood risks, such as constructing at elevation or suitable gradients, is combined with early warning systems to provide a proper route for the future construction projects

Supporting safe swallowing of care home residents withdysphagia: How does the care delivered compare withguidance from speech and language therapists?

Introduction: Dysphagia affects up to 70% of care home residents, increasingmorbidity and hospital admissions. Speech and language therapists make recom-mendations to support safe nutrition but have limited capacity to offer ongoingguidance. This study aimed to understand if recommendations made to supportsafe and effective care are implemented and how these relate to the actual caredelivered.Methods: Eleven mealtimes with residents with dysphagia were observed dur-ing 2020 using a tool capturing 12 elements of expected practice. Staff actionsduring mealtimes were compared with adherence to residents’ care plans andspeech and language therapist recommendations.Results: Written recommendations predominantly focused on food and fluidmodification. Observations (n = 66) revealed food texture, posture, and alertnesswere adhered to on 90% of occasions, but alternating food and drink, promptingand ensuring swallow completed adherence was less than 60%. Thickened fluidsfrequently did not align with required International Dysphagia Diet Standardi-sation Initiative levels. Nutrition care provided in the dining room was less safedue to a lack of designated supervision.Conclusion: Care homes need to be supported to establish a safe swallowingculture to improve residents’ safety and care experience

Developing a Data-Driven AI Model to Enhance Energy Efficiency in UK Residential Buildings

Residential buildings contribute to 30% of the UK’s total final energy consumption. However, with less than one percent of its housing stock being replaced annually, retrofitting existing homes has significant importance in meeting energy efficiency targets. Consequently, many physics-based and data-driven models and tools have been developed to analyse the effects of retrofit strategies from various points of view. This paper aims to develop a data-driven AI model that predicts buildings’ energy performance based on their features under various retrofit scenarios. In this context, four different machine learning models were developed based on the Energy Performance Certificate (EPC) dataset for residential buildings and Standard Assessment Procedure (SAP) guidelines in the UK. Additionally, an interface was designed that enables users to analyse the effect of different retrofit strategies on a building’s energy performance using the developed AI models. The results of this study revealed the artificial neural network as the most accurate predictive model, with a coefficient of determination (R^2) of 0.82 and a mean percentage error of 11.9 percent. However, some conceptual irregularities were observed across all the models when dealing with different retrofit scenarios. In summary, such tools can be further improved to offer a potential alternative or support to physics-based models, enhancing the efficiency of retrofitting processes in buildings. Keywords: machine learning, energy performance certificate, building energy consumptio

Challenges Encountered by Healthcare Professionals as Frontline Fighters during the COVID-19 Pandemic in Bangladesh: A Qualitative Study

Throughout the pandemic, healthcare professionals (HCPs) around the world encountered numerous challenges. This study was conducted in the middle of the pandemic, from June to November 2021, and explored the multiple issues that HCPs faced in Dhaka, Bangladesh. Thirty doctors and nurses, covering a wide range of workplaces and experiences, were interviewed. A qualitative investigation was performed to assess the influence that diverse organizational, familial, social, and religious factors had on their commitment to fulfil their professional duties. Thematic content analysis was performed on the findings. The results emphasize the physical and mental health problems of HCPs, the vital role of organizations in addressing the wellbeing of HCPs, and the necessity of providing training for them, along with workloads and PPE-related problems. It also explores the roles of families, the influence of society, and the impact of religious beliefs on their commitment during the pandemic

Real-time operation of municipal anaerobic digestion using an ensemble data mining framework

This study presents a novel approach for real-time operation of anaerobic digestion using an ensemble decision-making framework composed of weak learner data mining models. The framework utilises simple but practical features such as waste composition, added water and feeding volume to predict biogas yield and to generate an optimised weekly operation pattern to maximise biogas production and minimise operational costs. The effectiveness of this framework is validated through a real-world case study conducted in the UK. Comparative analysis with benchmark models demonstrates a significant improvement in prediction accuracy, increasing from the range of 50–80% with benchmark models to 91% with the proposed framework. The results also show the efficacy of the weekly operation pattern, which leads to a substantial 78% increase in biogas generation during the testing period. Moreover, the pattern contributes to a reduction of 71% in total days required for feeding and 30% in total days required for pre-feeding

Automated mitral inflow Doppler peak velocity measurement using deep learning

Doppler echocardiography is a widely utilised non-invasive imaging modality for assessing the functionality of heart valves, including the mitral valve. Manual assessments of Doppler traces by clinicians introduce variability, prompting the need for automated solutions. This study introduces an innovative deep learning model for automated detection of peak velocity measurements from mitral inflow Doppler images, independent from Electrocardiogram information. A dataset of Doppler images annotated by multiple expert cardiologists was established, serving as a robust benchmark. The model leverages heatmap regression networks, achieving 96% detection accuracy. The model discrepancy with the expert consensus falls comfortably within the range of inter- and intra-observer variability in measuring Doppler peak velocities. The dataset and models are open-source, fostering further research and clinical application