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Views and experiences of young people, their parents/carers and healthcare professionals of the advance care planning process: A summary of the findings from a qualitative study
Get PDFBackground:: Advance care planning for young people is relatively new in the UK. There is a lack of understanding about the engagement of young people in their own planning process, optimal timing of discussions and the facilitators and barriers to the engagement of young people. Aim:: To explore the views and experiences of young people, their parents/carers and HCPs of the advance care planning process. Design:: A qualitative study, using semi-structured interviews with young people, their parents/carers and healthcare professionals across four case series. Data were analysed using thematic analysis. Participants:: Fifteen participants were interviewed: young people (n = 2), parents/carers (n = 5) and healthcare professionals (n = 8). Results:: Three themes were identified from the findings. Key findings related to barriers and facilitators of engaging young people in their own care planning were apparent in the following areas: misperception of terms; hierarchies of power in relationships; and a flexible and innovative organisational structure and culture. Conclusion:: Participants expressed a variety of views and experiences of advance care planning. Advance care planning was thought to be best initiated by a consultant when the young person is in their mid-teens, their condition is stable, and before they transition to adult care. Engagement was also considered to be facilitated by appropriate communication, developing relationships prior to initiating advance care planning, and written support for everyone involved in the process. These factors were supported by training and education for healthcare professionals and a flexible and innovative structure and cultures of organisations
An efficient and privacy-preserving scheme for disease prediction in modern healthcare systems.
Get PDFWith the Internet of Things (IoT), mobile healthcare applications can now offer a variety of dimensionalities and online services. Disease Prediction Systems (DPS) increase the speed and accuracy of diagnosis, improving the quality of healthcare services. However, privacy is garnering an increasing amount of attention these days, especially concerning personal healthcare data, which are sensitive. There are a variety of prevailing privacy preservation techniques for disease prediction that are rendered. Nonetheless, there is a chance of medical users being affected by numerous disparate diseases. Therefore, it is vital to consider multi-label instances, which might decrease the accuracy. Thus, this paper proposes an efficient privacy-preserving (PP) scheme for patient healthcare data collected from IoT devices aimed at disease prediction in the modern Health Care System (HCS). The proposed system utilizes the Log of Round value-based Elliptic Curve Cryptography (LR-ECC) to enhance the security level during data transfer after the initial authentication phase. The authorized healthcare staff can securely download the patient data on the hospital side. Utilizing the Herding Genetic Algorithm-based Deep Learning Neural Network (EHGA-DLNN) can test these data with the trained system to predict the diseases. The experimental results demonstrate that the proposed approach improves prediction accuracy, privacy, and security compared to the existing methods
Building construction based on video surveillance and deep reinforcement learning using smart grid power system
No full textNew trendy neighborhoods require trimming scientific and technological methods and equipment. Smart buildings (SB) use resources efficiently, save energy, and provide services to the community more easily for their occupants while reducing their environmental footprint. Smart cities have benefited from this growth in terms of smart buildings. Maximum accuracy and reduced latency are both required for smart building monitoring systems. Poor scheduling rules can lead to network congestion and latency that is too high for real-time monitoring on construction sites, which have restricted computing and networking capabilities. These devices can collect the data on on-site actions, achievements, and circumstances and send it back to the central dashboard for analysis. Model predictive control and Deep Reinforcement Learning (DRL) have significant drawbacks, and DRL addresses some drawbacks. Researchers are intrigued by DRL, a brand-new approach to quality control. The most important considerations for developing smart power grid systems are energy conservation, renewable energy integration, and a streamlined control system. Experiments have shown that the new video surveillance has a low loss rate and a consistent latency. The DRL-SB-IoT technique can successfully track multiple cameras in a wide monitoring situation. This technique results in excellent tracking performance and meets the criteria for developing an intelligent campus in the best way possible. Researchers analyzed studies using supervised learning to solve common building issues, such as health monitoring, security on building sites, accommodation modeling, and energy consumption prediction. Reinforcement learning has been used to solve these issues. The proposed method advances the smart gateway channel of 97.5%, the energy storage ratio of 96.9%, and the overall surveillance performance ratio of 98.6%
PE teachers’ perceived expertise and professional development requirements in the delivery of muscular fitness activity: PE Teacher EmPOWERment Survey
Get PDFMuscular fitness (MF) is an important modifiable factor to improve overall health. Schools offer a unique opportunity to deliver MF activity during physical education (PE) and develop competence to engage in various activities across the life course. However, the implementation of school-based MF activity may be impaired by some teachers reporting a lack of expertise and low confidence in the delivery of MF activity. Understanding teachers’ thoughts and perceptions regarding the delivery of MF in schools may help guide future research and policy to support MF delivery in UK schools. Following ethical approval, a survey of secondary school PE teachers across the UK was distributed via Twitter. Survey responses were analysed and reported descriptively and thematically. Completed surveys were returned by 194 teachers (61.9% male) from England, Scotland, Wales, and Northern Ireland. Relative to less experienced teachers, those with at least five years’ service were 2.2 times more likely to have completed continued professional development (CPD) in MF activity (OR = 2.16; ß = 0.77; 95% CI: 1.25-3.74; p < 0.01), and 1.8 times more likely to use assessments of MF to inform PE programme decision-making (OR = 1.83; ß = 0.60; 95% CI: 1.18-2.82; p < 0.01). Despite the promising contribution school-based PE may have to developing MF, we report a poor understanding of MF activity amongst UK-based PE teachers. CPD is warranted to deliver successful MF interventions in a school setting
Graduate employability within the Higher Education framework: The Ghanaian perspective
No full textReport commissioned by the British Council.
It is estimated that 230,000 Ghanaians seek to enter the labour market annually. However, the formal economy can only offer jobs to about 2% of this number. Consequently, 225,000 are left without employment. Furthermore, about 50% of those employed are underutilised as they lack entrepreneurial skills. Additionally, the current infrastructure is prohibitive to start-up and small-medium scale enterprises. This situation has an adverse effect on socioeconomic development, exacerbated by the impact of COVID-19. With the associated global economic recession, an approach to address unemployment is needed to equip the labour force with appropriate employability skills
Social enterprise as a model for change: mapping a global cross-disciplinary framework
Get PDFSince the outbreak of COVID-19, social enterprise has experienced a renaissance. In public policy circles, entrepreneurship and innovation are perceived as economic development tools, and in many parts of the world, as catalysts for change that can have a real impact by increasing employment in communities as well as environmental challenges. At a local level, entrepreneurship and innovation enable communities to stay vibrant due to social enterprise organisations offering much-needed goods and services. Social enterprise has been acknowledged as a solution to social inequality and environmental issues in society as it develops new areas of empowerment in local communities. Central to the success of social enterprise is education, training, and the engagement of the higher education sector. Traditionally, entrepreneurship and innovation have fundamentally been entrenched within the business subject area, but have now emerged within other disciplines such as criminology, health and social care, geography, sociology, and politics. The aim of this paper is to map out a new, global, cross-disciplinary framework from a teaching and learning perspective. The authors of this paper call for global empowerment of entrepreneurship education in the higher education sector, using examples from different countries across the world, specifically Ghana, India, and the UK. This paper sets out the vital importance of entrepreneurship in teaching and learning, by showcasing what can be achieved. In this paper, the authors develop and propose a new pedagogical social enterprise model that incorporates and emphasises the ethos of ‘think globally, act locally’ in a sustainability context
Nietzsche, Nihilism, and the “new materialist” thought
Get PDFThis paper draws connections between Nietzsche’s diagnosis of nihilism, his philosophy of the
“nearest things” and issues of orientation in contemporary thought. The trajectory which Nietzsche
traces from “the devaluation of the highest values” to the task of transvaluation, supplies an
overarching context for addressing nihilism as a crisis of orientation. It is argued that Nietzsche’s
turn towards the “closest” things as a new direction for thought shares priorities named as the
“keywords” of our time: “embodiment, affect, the quotidian, singularity, contingency, intimacy,
precarity” (Laura Marcus, 2016). In order to pursue the deeper implications of this affinity, some
recent engagement with Nietzsche in new materialist writings are considered. It is claimed that
Nietzsche’s ideas about the nearest things provide these theories with resources to contest nihilism
at the level of value, without reinstating an uncritical appeal to the authority of “lived experience.
Examining the occupational stress among supervisors in the hotel industry
No full textThe hotel industry has always been seen as vibrant, glamorous, and profitable. However, the novelty of working in the hotel industry is wearing off due to the demands and expectations from both the management and customers. The pressure to deliver high quality services and the expense to maintain the status quo in a hotel have become problematic. Employees are experiencing a wide range of issues including work related stress. Occupational stress as commonly known is one of the contributory factors connected to poor health, psychological and mental well-being. Using a qualitative data approach from 3-4-5-star hotels in Cyprus and the United Kingdom, the supervisors' pleasant demeanour shadowed by social, physical, and psychological issues is unveiled. By also unraveling occupational stress through the lenses of supervisors in the hotel industry, this study will help the hotel management to take appropriate action to address the occupational stress amongst employees which is a huge issue in the sector
Smart analysis of learners performance using learning analytics for improving academic progression: A case study model
Get PDFIn the current Covid-19 pandemic era, Learning Management Systems (LMS) are commonly used in e-learning for various learning activities in Higher Education. Learning Analytics (LA) is an emerging area of LMS, which plays a vital role in tracking and storing learners’ activities in the online environment in Higher Education. LA treats the collections of students’ digital footprints and evaluates this data to improve teaching and learning quality. LA measures the analysis and reports learners’ data and their activities to predict decisions on every tier of the education system. This promising area, which both teachers and students can use during this pandemic outbreak, converges
LA, Artificial Intelligence, and Human-Centred Design in data visualization techniques, semantic
and educational data mining techniques, feature data extraction, etc. Different learning activities of
learners for each course are analysed with the help of LA plug-ins. The progression of learners can be monitored and predicted with the help of this intelligent analysis, which aids in improving the academic progress of each learner in a secured manner. The Object-Oriented Programming course
and Data Communication Network are used to implement our case studies and to collect the analysis
reports. Two plug-ins, local and log store plug-ins, are added to the sample course, and reports are observed. This research collected and monitored the data of the activities each students are involved in. This analysis provides the distribution of access to contents from which the number 16
of active students and students’ activities can be inferred. This analysis provides insight into how many assignment submissions and quiz submissions were on time. The hits distribution is also provided in the analytical chart. Our findings show that teaching methods can be improved based on
these inferences as it reflects the students’ learning preferences, especially during this Covid-19 era.
Furthermore, each student’s academic progression can be marked and planned in the departmen