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A pilot project to explore the mental health and wellbeing among cardiothoracic staff and the impact of virtual reality guided mindfulness
Full text linkBackground: The Cardio-Thoracic (CT) professional group experienced a significant increase in stress and workload during and after the COVID-19 pandemic. The Society for Cardiothoracic Surgery (SCTS) in Great Britain and Ireland with the aim of endorsing positive change. Aim of this project was to understand the Mental Health (MH) and wellbeing status of the CT professionals and to explore Virtual Reality Mindfulness as an intervention to improve MH and wellbeing. Methods: In February 2022, the SCTS created a Mental Health and Wellbeing Working Group to identify the problem and find solutions. This exploratory project was carried out in two stages. Stage one was an online survey conducted in March 2022 and stage two was a Virtual Reality (VR) mindfulness workshop in March 2023, using the Rescape™ VR mindfulness tool. Results: Stage one: An online QR code survey was sent out to 150 members with 129 (86%) completed responses. 92% expressed that SCTS should create awareness about mental health and wellbeing. 99% said that they should be allowed to speak up and create interventions for members to access, support and relax. Three main themes identified about why CT staff do not discuss their Mental Health problems were fear of lack of awareness (72%), lack of confidentiality (60%) and impact on career (60%). Stage two: 88 members attended the VR session of which 76 (86%) completed the anonymous questionnaire. 97% reported usage was a pleasurable experience, 91% felt more relaxed, 82% felt less stressed, 90% felt calmer and 89% had their mood enhanced. Conclusion: Our study findings indicate that CT staff experience considerable effects on their mental health and wellbeing. However, there is a hesitancy to recognise and seek assistance due to concerns about confidentiality and career repercussions. The virtual reality mindfulness session served as a beneficial supplement, with a positive impact in this pilot cohort
Accelerating disaster recovery: an agile approach to enhancing community disaster resilience
Full text linkPurposeDisasters are inevitable, and their increasing frequency and intensity due to climate change necessitate stronger community disaster resilience (CDR) strategies. The ability to reduce recovery time can be achieved through an agile approach. However, existing research lacks a systematic approach. The purpose of this study is to integrating CDR characteristics with an agile approach to enhance adaptability and efficiency in disaster recovery.Design/methodology/approachThis study uses systematic literature review and meta-analysis to categorise CDR characteristics and analyse their influence on recovery time. The population, intervention, comparison and outcome framework was used to develop a structured search strategy, leading to the selection and analysis of 960 research articles from Scopus and Web of Science databases. Data were analysed using both quantitative and qualitative approaches, using tools such as MS Excel, RAW Graphs 2.0, Lucid Chart and VISIO Professional 2021 to visualise findings.FindingsThe research identifies seven key CDR dimensions; human, economic, environmental, social, infrastructural, governance and technological resilience. Findings highlight that applying agile principles such as adaptability, stakeholder engagement, continuous improvement and resource optimisation can significantly enhance recovery efficiency. The study provides a novel methodological contribution by integrating agile approaches into CDR, offering a structured framework for disaster management strategies.Originality/valueTo the best of the authors’ knowledge, this research is among the first to systematically examine the role of agile approach in minimising disaster recovery time. It recommends further empirical validation through case studies and field research, particularly in underrepresented regions like Asia. In addition, leveraging AI-driven data analytics and emerging technologies can enhance real-time resilience strategies, ensuring faster and more effective disaster response and recovery
Dual domain adaptation for infrared ship segmentation
Full text linkUnsupervised Domain Adaptation (UDA) is vital for infrared (IR) ship segmentation due to the high cost of annotation, yet its effectiveness is often hindered by unreliable pseudo-labels. To overcome this, we propose the Dual Domain Adaptation Network (DDANet), a novel framework centered on a Consistency-Driven Curricular Intra-Domain Adaptation paradigm. It progressively refines segmentation through a structured two-stage process. First, in an inter-domain adaptation stage, we perform initial feature alignment between visible and IR domains using adversarial learning. Crucially, we introduce a consistency regularization term between dual classifiers to enhance the initial quality and confidence of the generated pseudo-labels. Second, we pioneer an intra-domain adaptation stage guided by a curriculum learning strategy. Here, we dynamically partition the target domain into “easy” (high-consistency) and “hard” (low-consistency) subsets based on their pseudo-label quality. The high-consistency set then acts as a reliable source to fine-tune the model on the more challenging low-consistency set via a second round of adversarial learning. This dual-stage approach enables the model to first learn general domain-invariant features and then master target-specific variations. Experimental results on a visible-infrared ship dataset and a public benchmark demonstrate that DDANet achieves superior segmentation accuracy compared to state-of-the-art methods, validating the effectiveness of our dual adaptation strategy
Sustainable Food Procurement: Legal, Social and Organisational Challenges
Full text linkThe book examines sustainable food procurement policy and practice in the European Union and beyond, exploring the extent to which sustainability objectives have been achieved and evaluating the new developments taking place at both EU and national levels.While there is a growing recognition that public authorities can use public procurement as a policy tool to pursue multiple environmental, health and socio-economic objectives, contracting authorities still face many challenges. This volume investigates the scope for pursuing sustainable objectives in public procurement of food and catering services, examining different regulatory contexts and organisational models to answer the overall question of how to integrate sustainability concerns into the various phases of public food procurement processes. Contributions in the book examine the policy and legal procurement framework and practices for sustainable public catering in three EU Member States: Italy, France and Spain. There is a comparative survey of the Baltic Region, including Denmark, Estonia, Finland, Poland and Russia, and moving beyond the EU, there is examination of the UK and Brazil, as well as a cross country comparison of the UK with Denmark and Sweden. Drawing on the expertise of an interdisciplinary and intersectoral team of contributors allows the book to benefit from the insights of different disciplines, including business sciences, anthropology and law. Tapping into the global discussion on public food procurement as a means to achieve multiple social and environmental goals, this work will stimulate readers looking for new creative ways to create value through public food purchasing.This book will be of great interest to students, researchers, policymakers and public- and private-sector representatives interested in public procurement, food policy and law, sustainable food sourcing and supply chain management
Force and Power Testing During Anterior Cruciate Ligament Reconstruction Rehabilitation: A World-Wide Survey of Current Practices.
No full textDuring rehabilitation, the importance of restoring strength and power in a stage-based framework highlights the paramount role of testing and monitoring. Despite theoretical understanding of an optimal recovery pathway, it is unclear and inconsistent as to how practitioners implement force and power assessment following anterior cruciate ligament reconstruction (ACLR). We aimed to examine current worldwide practices with evaluating patients post-ACLR, identify the relative utilisation of different devices and methodologies across the rehabilitation process, and to explore the interactions between the implemented devices and respondents' self-perceived testing quality (evaluated by participants via a Likert scale). Data were collected via an international online survey composed of 100 items, organised across 12 sections, exploring the demographics of respondents and implemented testing devices to assess individuals after ACLR and their perceived testing quality. A total of 1154 practitioners from 78 different countries completed the survey. According to the pre-defined eight categories, 157 different combinations were recorded among practitioners. Respondents tended to use multiple devices (95.8%), with a mean of 3.6 ± 1.4. Patient assessments were most often repeated longitudinally throughout the recovery process post-ACLR (96.4%). Specific devices were used as part of "criteria-based" testing by 46.4% of respondents, "criteria- and time-based" testing by 30.8% and solely "time-based" testing by 21.9%. A significant but weak direct correlation was observed between the number of implemented devices and self-perceived testing quality (ρ = 0.32, p < 0.001), with force plates, an isokinetic dynamometer, Nordic hamstrings device and a hand-held dynamometer significantly associated with increased self-perceived testing quality (R = 0.21, p < 0.001). A high degree of variability in test device implementation existed among practitioners. According to the eight pre-defined device categories, over 150 different device combinations were recorded among respondents. Device use was different throughout the stages of rehabilitation and testing was primarily performed as criteria to advance patients throughout the recovery process. While acknowledging that these findings may be influenced by self-serving bias, they suggest that practitioners involved in force and power testing post-ACLR may benefit from implementing a wide range of devices, including more quantitative and objective instruments such as force plates and the isokinetic dynamometer, as these appeared to be related to higher levels of self-perceived testing quality. [Abstract copyright: © 2025. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Preventing and countering extremism in the educational sector: Interrogating policy, challenging practices
Full text linkSince the introduction of the Prevent Duty Guidance (PDG) in 2015, public-facing organisations have been legally obligated to report concerns about individuals suspected of engaging in extremism or being at risk of radicalisation. Since inception, critical commentators have argued that implementation of this directive has intensified extant problems created by the Prevent Strategy and accelerated unwarranted processes of securitisation within education, healthcare, and welfare sectors. To extend critical social policy research in this area, in this article we present findings from a qualitative empirical study involving schoolteachers responsible for implementing PDG in the United Kingdom. Our aim is to elucidate two interconnected and recurrent concerns expressed by participants responsible for counter-extremism safeguarding: the ‘suspectification’ of young Muslims and the deleterious effects of ‘false positive’ referrals. Our analysis illuminates ongoing and significant challenges encountered by educators implementing counter-extremism policies and highlights problematic effects on targeted individuals and communities
The Geometric-Logistic Distribution: A Versatile New Generalised Logistic Distribution
Full text linkThe Champernowne distribution is a little-known generalised logistic distribution, useful for modelling data defined on the whole real line, where it can model both leptokurtic and playtkurtic data. We present a similar distribution, the GGL distribution, which also fits data well, but is much more tractable and so has a broad range of uses. The distribution function is simple, and hence so is random number generation and the computation of quantiles and expected shortfall. We describe the properties of the new distribution, and show that it fits long-tailed data comparably to the t-distribution, with the advantage that all moments and the moment generating function exist. It can also fit short-tailed and even bimodal data, enabling a parametric test for bimodality.It also yields a test of goodness of fit for logistic regression, a generalised version of logistic regression, and a generalised growth-model
Time to belong: Why management education needs a pedagogy of contemporaneity
Full text linkCalls to ‘transform’ management education often presume a linear temporal trajectory, from a deficient present towards a better future, while leaving the present itself unexamined. Drawing on philosophical accounts of contemporaneity as a conjunctively disjunctive historical condition, we argue that transformation must be grounded in how the present is lived and shared, not merely measured or projected beyond. Through auto-ethnographic vignettes of life under late Communism and subsequent migration to Britain, we show how ostensibly progressive narratives can reproduce exclusionary temporal politics, creating experiences of temporal displacement even among those chronologically ‘present’ in academic communities. We then propose a pedagogy of contemporaneity for management education – an adaptive scaffolding organised around three principles: commitment to the layered present (refusing nostalgic or utopian escape routes); collaboration across different temporal trajectories (not only across perspectives or disciplines) and contextualisation of learning within situated historical, social and political timescales. Rather than offering a blueprint for the future, this pedagogy equips educators and students to recognise and navigate temporal multiplicity as the condition of belonging in time. Our contribution is to recast transformation not as an endpoint but as the means of working with the temporal complexity that already constitutes our classrooms and institutions
A Non-invasive Mental Health Risk Predictor Using Machine Learning Models Utilising Music Listening Habits
Full text linkGlobally, there has been a rise in mental health issues such as insomnia, anxiety, and depression. However, the stigma that is associated with such a diagnosis makes individuals not want to seek help. Recent research has explored the relationship between music listening habits and mental health status, offering promising insights into the potential of leveraging this data for predictive modelling. This research proposes a non-invasive approach that integrates features extracted from music listening patterns including demographic and lifestyle data to build machine learning models that detect mental health conditions such as insomnia, depression and anxiety levels The results show that Random Forest achieved an accuracy of 76.35%, which highlights the potential of using music listening habits to predict mental health states. The findings of this study provide valuable insight into the relationship between music and mental health predictors- namely depression, anxiety and insomnia across different age groups
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