Background The integration of preventative health services into England’s National Health Service is one of the cornerstones of current health policy. This integration is primarily envisaged through the removal of legislation that blocks collaborations between NHS organisations, local government, and community groups. Aims and objectives This paper aims to illustrate why these actions are insufficient through the case study of the PrEP judicial review. Methods Through an interview study with 15 HIV experts (commissioners, activists, clinicians, and national health body representatives), we explore the means by which the HIV prevention agenda was actively blocked, when NHS England denied responsibility for funding the clinically effective HIV pre-exposure prophylaxis (PrEP) drug in 2016, a case that led to judicial review. We draw on Wu et al.’s (Policy Soc 34:165–171, 2016) conceptual framing of ‘policy capacity’ in undertaking this analysis. Results The analyses highlight three main barriers to collaborating around evidence-based preventative health which indicate three main competence/capability issues in regard to policy capacity: latent stigma of ‘lifestyle conditions’ (individual-analytical capacity); the invisibility of prevention in the fragmented health and social care landscape related to issues of evidence generation and sharing, and public mobilisation (organizational-operational capacity); and institutional politics and distrust (systemic-political capacity). Discussion and conclusion We suggest that the findings hold implications for other ‘lifestyle’ conditions that are tackled through interventions funded by multiple healthcare bodies. We extend the discussion beyond the ‘policy capacity and capabilities’ approach to connect with a wider range of insights from the policy sciences, aimed at considering the range of actions needed for limiting the potential of commissioners to ‘pass the buck’ in regard to evidence-based preventative health.
Stress is a complex multifaceted concept that is the result of adverse or demanding circumstances. Workers, especially health care workers, suffer significantly from distress, burnout, and other physical illnesses such as hypertension and diabetes caused by stress. Numerous stress detection systems are realized but they only help in detecting the stress in early stages, and, for regularizing it, these systems employ other means. These systems lack any inherent feature for regularization of stress. In contributing toward this aim, a novel system “EEG-Based Aptitude Detection System” is proposed. This system will help in considering working aptitude of employees working in work places with an intention to help them in assigning proper job roles based on their working aptitude. Selection of right job role for workers not only helps in uplifting productivity but also helps in regulating stress level of employees caused by improper job role assignments and reduces fatigue. Being able to select right job role for workers will help them in providing productive working environment. This paper presents detail layered architecture, implementation details, and outcomes of the proposed novel system. Integration of this system in work places will help supervisors in utilizing the human resource more suitably and will help in regulating stress related issues with improvement in overall performance of entire office. In this work, different implementation architectures based on KNN, SVM, DT, NB, CNN, and LSTM are tested, where LSTM has provided better results and achieved accuracy up to 94% in correctly classifying an EEG signal. The rest of the details can be seen in Sections 3 and 5.
This paper presents a novel architecture for native process migration (PM) in wireless sensor networks (WSNs) without the use of virtual execution environment. Resources in WSN are scarce; therefore creating virtual execution environment puts extra burden on already stringent resources. In addition, the proposed architecture is migrating with complete process instead of code only which also saves resources. The proposed architecture makes process migration decisions by continuously monitoring resources, such as remaining battery life and free memory space on a node. The architecture is suitable for networks with fewer expensive sensor nodes as it allows for better utilization of network resources. Transferring a live executing process from one node to another to meet processing demands dynamically improves fault tolerance, resource utilization, and network management in WSN. The architecture has been successfully tested and implemented on both COOJA simulator and a test bed of TelosB motes.
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