Beyond safety to wellbeing: How local authorities can mitigate the mental health risks of living in houses in multiple occupation

The regulation of houses in multiple occupation (HMOs) by local authorities focuses on ensuring the physical safety of occupants through adequate standards of building quality, safety provision and management suitability. However, it has been suggested that HMOs may also pose a particular threat to the mental health of residents. In this paper we consider the suitability of current regulations to tackle the possible risks to the mental health of HMO residents and then outline how the current public health agenda may present an opportunity for environmental health professionals to tackle these issues in new ways. Using a framework which encompasses the psychosocial processes thought to link residents? mental health with their housing conditions, we describe how local authorities can address some of the mental health risks posed by HMOs but that the current enforcement culture, in which prosecution is seen as a last resort makes decisive action against landlords very difficult. In recognising the many vulnerable households living in HMOs, we argue that local authorities dealing with housing standards and environmental management are strategically placed to be more ambitious and proactive in protecting the health of local residents particularly through the developing public health and wellbeing partnerships. We call for empirical research to look at how local authorities actually use current legislation as well as other strategies to manage HMOs and protect the mental health of tenants

Exploring the potential of contemplative pedagogy in health professional education

Introduction: Although interest in and use of contemplative pedagogy is growing, particularly in the US, its potential to contribute to current dialogues about higher education and, in particular, the development of education for health professionals has not received much attention. The aim of this paper is to introduce contemplative pedagogy to educators working within health professional education so that the merits of such an approach can be more extensively debated. What is contemplative pedagogy? The aim of contemplative pedagogy is the development of students? first-person experience of knowing as a counterbalance and compliment to the objective, third-person, didactic approach, which dominates higher education. Through contemplative practice, students? learning becomes connected to their own sense of meaning and personal values. I start by exploring the concept of contemplative pedagogy. Examples of contemplative practices are briefly introduced so that the reader can better envisage how contemplation can be introduced into the classroom. Discussion and conclusions: I argue that contemplative pedagogy could help overcome the gap between theory and practice and assist educators in equipping students to care compassionately and effectively in dynamic and demanding healthcare contexts. I finish by emphasising the need for more research to investigate the efficacy of incorporating contemplative pedagogy in the education of health professionals

Data and Predictive Analytics Use for Logistics and Supply Chain Management

Purpose The purpose of this paper is to explore the social process of Big Data and predictive analytics (BDPA) use for logistics and supply chain management (LSCM), focusing on interactions among technology, human behavior and organizational context that occur at the technology’s post-adoption phases in retail supply chain (RSC) organizations. Design/methodology/approach The authors follow a grounded theory approach for theory building based on interviews with senior managers of 15 organizations positioned across multiple echelons in the RSC. Findings Findings reveal how user involvement shapes BDPA to fit organizational structures and how changes made to the technology retroactively affect its design and institutional properties. Findings also reveal previously unreported aspects of BDPA use for LSCM. These include the presence of temporal and spatial discontinuities in the technology use across RSC organizations. Practical implications This study unveils that it is impossible to design a BDPA technology ready for immediate use. The emergent process framework shows that institutional and social factors require BDPA use specific to the organization, as the technology comes to reflect the properties of the organization and the wider social environment for which its designers originally intended. BDPA is, thus, not easily transferrable among collaborating RSC organizations and requires managerial attention to the institutional context within which its usage takes place. Originality/value The literature describes why organizations will use BDPA but fails to provide adequate insight into how BDPA use occurs. The authors address the “how” and bring a social perspective into a technology-centric area

Multimodality Biomedical Image Registration using Free Point Transformer Networks

We describe a point-set registration algorithm based on a novel free point transformer (FPT) network, designed for points extracted from multimodal biomedical images for registration tasks, such as those frequently encountered in ultrasound-guided interventional procedures. FPT is constructed with a global feature extractor which accepts unordered source and target point-sets of variable size. The extracted features are conditioned by a shared multilayer perceptron point transformer module to predict a displacement vector for each source point, transforming it into the target space. The point transformer module assumes no vicinity or smoothness in predicting spatial transformation and, together with the global feature extractor, is trained in a data-driven fashion with an unsupervised loss function. In a multimodal registration task using prostate MR and sparsely acquired ultrasound images, FPT yields comparable or improved results over other rigid and non-rigid registration methods. This demonstrates the versatility of FPT to learn registration directly from real, clinical training data and to generalize to a challenging task, such as the interventional application presented.Comment: 10 pages, 4 figures. Accepted for publication at International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) workshop on Advances in Simplifying Medical UltraSound (ASMUS) 202

The Role of Physical Activity in Cancer Recovery: An Exercise Practitioner’s Perspective

Less than 20% of cancer patients meet the recommended physical activity (PA) guidelines, partially due to poor knowledge and enforcement/encouragement amongst health-care professionals (HCPs). The primary aim of this study was to explore the perceptions of exercise practitioners on the role of PA and the physiological and psychological benefits to recovering cancer patients; the secondary aim was to understand the barriers and facilitators of promoting PA to cancer survivors. The third aim was to, seek the perspectives on the effectiveness of referral systems between the hospitals and PA structures. A purposive sample of five exercise practitioners’ (four male and one female) with experience with cancer patients participated in a semi-structured interview (45–60 min). Interviews addressed five key topics: intervention procedures, patient well-being, patient education on PA, effectiveness of referrals from hospitals, and post-intervention PA. Interviews were transcribed verbatim and analysed via thematic analysis. The participants believed that recovering cancer patients possess a knowledge of the physiological benefits of PA, yet psychological understanding remains unknown. Social environments are key to participation in PA and most HCPs lacked knowledge/awareness of the benefits of engaging in PA. There is a need to improve HCPs knowledge of the benefits of PA, whilst providing standardised training on how PA can improve cancer patients’ outcomes

Advanced Cardiac Life Support (ACLS) utilizing Man-Tended Capability (MTC) hardware onboard Space Station Freedom

Because of the time and distance involved in returning a patient from space to a definitive medical care facility, the capability for Advanced Cardiac Life Support (ACLS) exists onboard Space Station Freedom. Methods: In order to evaluate the effectiveness of terrestrial ACLS protocols in microgravity, a medical team conducted simulations during parabolic flights onboard the KC-135 aircraft. The hardware planned for use during the MTC phase of the space station was utilized to increase the fidelity of the scenario and to evaluate the prototype equipment. Based on initial KC-135 testing of CPR and ACLS, changes were made to the ventricular fibrillation algorithm in order to accommodate the space environment. Other constraints to delivery of ACLS onboard the space station include crew size, minimum training, crew deconditioning, and limited supplies and equipment. Results: The delivery of ACLS in microgravity is hindered by the environment, but should be adequate. Factors specific to microgravity were identified for inclusion in the protocol including immediate restraint of the patient and early intubation to insure airway. External cardiac compressions of adequate force and frequency were administered using various methods. The more significant limiting factors appear to be crew training, crew size, and limited supplies. Conclusions: Although ACLS is possible in the microgravity environment, future evaluations are necessary to further refine the protocols. Proper patient and medical officer restraint is crucial prior to advanced procedures. Also emphasis should be placed on early intubation for airway management and drug administration. Preliminary results and further testing will be utilized in the design of medical hardware, determination of crew training, and medical operations for space station and beyond

Research and evidence based environmental health

Environmental health (EH) professionals have often spoken of the need to become more research active (Burke et al., 2002; McCarthy, 1996) and make their work more evidence based, but to date little has been written about how to achieve this in practice. This chapter is therefore written as an introductory guide to research for EH professionals, students, and policy makers. By developing your knowledge it is hoped you will feel more confident navigating the world of research; motivated towards making your own work more evidence based; and enthused about contributing to the evidence base from which others can learn. This chapter is not a research methods textbook, a step by step guide to research or evidence based environmental health, nor does it seek to make definitive statements about these complex areas. However it highlights the most important issues regarding research in environmental health, considers the importance of research to the environmental health profession and provides useful signposts towards further resources. The chapter is divided into three sections. The first defines evidence based environmental health and why it remains a priority for EH professionals. The second section explores the key stages of environmental health research and provides guidance on the development of your reading skills. The final section suggests ways to become more research active and evidence based, acknowledging the many challenges EH professionals face and concluding with a vision for evidence based environmental health. The chapter ends with an annex including a glossary of environmental health research terms, a list of references and suggested further reading

Systems Chemistry and Parrondo’s Paradox: Computational Models of Thermal Cycling

A mathematical concept known as Parrondo’s paradox motivated the development of several novel computational models of chemical systems in which thermal cycling was explored. In these kinetics systems we compared the rates of formation of product under cycling temperature and steady-sate conditions. We found that a greater concentration of product was predicted under oscillating temperature conditions. Our computational models of thermal cycling suggest new applications in chemical and chemical engineering systems

Meta-Registration: Learning Test-Time Optimization for Single-Pair Image Registration

Neural networks have been proposed for medical image registration by learning, with a substantial amount of training data, the optimal transformations between image pairs. These trained networks can further be optimized on a single pair of test images - known as test-time optimization. This work formulates image registration as a meta-learning algorithm. Such networks can be trained by aligning the training image pairs while simultaneously improving test-time optimization efficacy; tasks which were previously considered two independent training and optimization processes. The proposed meta-registration is hypothesized to maximize the efficiency and effectiveness of the test-time optimization in the "outer" meta-optimization of the networks. For image guidance applications that often are time-critical yet limited in training data, the potentially gained speed and accuracy are compared with classical registration algorithms, registration networks without meta-learning, and single-pair optimization without test-time optimization data. Experiments are presented in this paper using clinical transrectal ultrasound image data from 108 prostate cancer patients. These experiments demonstrate the effectiveness of a meta-registration protocol, which yields significantly improved performance relative to existing learning-based methods. Furthermore, the meta-registration achieves comparable results to classical iterative methods in a fraction of the time, owing to its rapid test-time optimization process.Comment: Accepted to ASMUS 2022 Workshop at MICCA

Meta-Learning Initializations for Interactive Medical Image Registration

We present a meta-learning framework for interactive medical image registration. Our proposed framework comprises three components: a learning-based medical image registration algorithm, a form of user interaction that refines registration at inference, and a meta-learning protocol that learns a rapidly adaptable network initialization. This paper describes a specific algorithm that implements the registration, interaction and meta-learning protocol for our exemplar clinical application: registration of magnetic resonance (MR) imaging to interactively acquired, sparsely-sampled transrectal ultrasound (TRUS) images. Our approach obtains comparable registration error (4.26 mm) to the best-performing non-interactive learning-based 3D-to-3D method (3.97 mm) while requiring only a fraction of the data, and occurring in real-time during acquisition. Applying sparsely sampled data to non-interactive methods yields higher registration errors (6.26 mm), demonstrating the effectiveness of interactive MR-TRUS registration, which may be applied intraoperatively given the real-time nature of the adaptation process.Comment: 11 pages, 10 figures. Paper accepted to IEEE Transactions on Medical Imaging (October 26 2022