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How are midwifery students being taught about conducting consultation events? – Findings from an international survey questionnaire
No full textAims We sought to understand how and when student midwives received consultation skills education during their undergraduate programmes. Background International standards for midwifery practice demand that women are informed, advised and provided with a myriad of information throughout the childbirth continuum. A consequence of sub-optimal consultation events can lead to dissatisfaction on the woman’s part about her care, inaccurate information being provided and ultimately may result in poor care resulting in sub-optimal birth outcomes. Global evidence suggests that this area of education may be under-developed in midwifery programmes. Design A descriptive cross-sectional survey examined international approaches to teaching consultation skills in undergraduate midwifery programmes. Methods An online questionnaire was distributed to academics in the UK, continental Europe, Australia and New Zealand. Responses were collected between February and May 2023. Data were analysed using the Where–When–What–How framework to identify how consultation skills education was delivered, assessed and integrated into curricula. Results Thirty-two questionnaires were returned. Education was provided equally in clinical and academic environments and was threaded through curricula rather than taught as a discreet topic. Elements such as listening skills, shared decision making were included but consideration of structure, length and concluding the session were not prioritised. Various pedagogies were used to deliver the education. Significant variation in how skills were assessed and feedback provided were uncovered. Conclusion A definition of ‘midwifery consultation’ would likely support academic staff as they support student midwives to develop consultation skills, uphold professional standards and support the delivery of optimal care
IBM's AI-Driven Project Management
No full textWith the goals of enhancing efficiency, collaboration, and decision-making across its global operations, IBM has embraced artificial intelligence (AI) as a key driver in transforming its project management processes. The adoption of AI tools, such as IBM Watsonx, alongside integrated platforms such as Slack, Trello, and Asana, has enabled the organization to streamline tasks, automate scheduling, and improve resource allocation. The integration of AI into IBM operations has led to significant cost savings and improved project outcomes. However, the implementation of such advanced technologies also presents challenges, including workforce resistance, data privacy concerns, integration difficulties, and ethical implications. This case study explores initiatives of IBM AI-driven project management and related challenges. It also asks students to assess the associated risks and to develop effective risk management strategies to address these challenges. By analyzing IBM’s approach, students will gain insights into the broader implications of AI adoption in business and project management
An analytical framework of quantifying carbon emission impacts of construction and demolition waste circularity and trading: A case study of the UK
No full textDeveloping a circular economy (CE) for construction and demolition waste (CDW) presents a promising pathway to decarbonize the construction industry by reducing reliance on carbon-intensive primary material production. However, most existing studies rely on life cycle assessment (LCA) approaches and treat CDW flows as isolated processes, overlooking the broader economy-wide emission consequences and distributional effects arising from complex inter-sectoral and inter-regional material and energy flows. This limitation risks underestimating the full carbon mitigation potential of CDW circularity, thereby hindering progress toward the Net-Zero targets pledged by most global economies. This study introduces a novel analytical framework integrating LCA with environmentally extended input-output (EEIO) analysis to quantify the environmental impacts of CDW circularity, explicitly accounting for sectoral and regional trading linkages. Applying the framework to the United Kingdom (UK), this study estimates carbon emissions and potential savings under multiple CDW circularity scenarios for the year 2018. The results indicate that material use for domestic final demand and exports generates approximately 159 and 170 million tonnes of CO₂, respectively, while CDW circularity achieves only modest emission savings of 2–3 million tonnes (<1%). Reuse scenarios deliver greater reductions than recycling, with the most significant benefits observed in secondary and tertiary industries, particularly from the circular use of metallic and wood materials. Despite the UK's high CDW recovery rate, inefficient treatment pathways and weak alignment between recovered-material supply and industrial demand constrain the net-zero potential of CDW circularity. Enhancing recovery efficiency, advancing cleaner technologies, and improving material productivity are therefore critical for supporting the UK's net-zero transition. This study is novel in pioneering one of the first LCA–EEIO analytical frameworks for evaluating the economy-wide environmental impacts of CDW circularity, providing a scalable methodological foundation and system-level evidence for global economies seeking to accelerate their pathways toward Net-Zero targets
Effectiveness and cost-effectiveness of a peer-delivered, relational, harm reduction intervention to improve mental health, quality of life, and related outcomes, for people experiencing homelessness and substance use problems: protocol for the ‘SHARPS’ cluster randomised controlled trial
Full text linkBackground: Those experiencing homelessness and problem substance use find it challenging to access the healthcare and treatment they need. The Supporting Harm Reduction through Peer Support (SHARPS) feasibility study demonstrated that Peer Navigators can help these individuals to improve their service engagement, increase access to opioid substitution therapy, and lead to reductions in drug use and risky injection practices. Specifically, participants indicated that the lived experience of Peer Navigators was particularly helpful by enabling the development of trusting relationships. A cluster randomised controlled trial (cRCT) will now assess the effectiveness and cost-effectiveness of a Peer Navigator intervention with this population. Methods: A two-arm, pragmatic, cRCT will be conducted with embedded cost-effectiveness and mixed methods process evaluations. Individuals will be recruited who are as follows: over the age of 18 years; experiencing/at risk of homelessness and self-report problem substance use; and attending The Salvation Army (TSA) homelessness services across 20 included clusters (towns/cities). Each cluster will be randomised (1:1) to either the intervention or control arm using covariate-constrained allocation based on area-level characteristics. The target sample size is 550 participants in total. A co-produced peer-delivered harm reduction, relational intervention lasting 12 months will be delivered to those in the intervention arm. Usual care will be social care via TSA Support Workers delivered within homelessness services. The co-primary outcomes will be mental health and quality of life, with harmful substance use, risk taking behaviours, social functioning, physical health, social outcomes, housing status, therapeutic alliance/accessibility, service utilisation, and relational empathy chosen as secondary outcomes. Data collection points are baseline, 6 and 12 months, for all measures. The primary timepoint of interest is 12 months after baseline measurement. Economic outcomes will be incremental cost per quality-adjusted life year (QALY) and per year in full capability (YFC) gained with the intervention versus standard homelessness service care, inclusive of costs to the NHS, local government and criminal justice, and the third-sector host organisation. The EQ-5D-5L and ICECAP-A will be used to calculate QALYs and YFC respectively. We will also conduct a cost-consequence analysis. Discussion: The results of this trial will be used to inform whether the SHARPS intervention has a positive impact on those experiencing homelessness and problem substance use and if it is cost-effective to roll it out across social care services. Trial registration: ISRCTN11094645 (https://doi.org/10.1186/ISRCTN11094645, registered April 5, 2024)
Multimodal Cognitive Load Estimation With Radio Frequency Sensing and Pupillometry in Complex Auditory Environments
Full text linkThe detection of listening effort or cognitive load (CL) has been a major research challenge in recent years. Most conventional techniques utilise physiological or audio-visual sensors and are privacy-invasive and computationally complex. The challenges of synchronization, data alignment and accessibility limitations potentially increase the noise and error probability, compromising the accuracy of CL estimates. This innovative work presents a multi-modal, non-invasive and privacy-preserving approach that combines Radio Frequency (RF) and pupillometry sensing to address these challenges. Custom RF sensors are first designed and developed to capture blood flow changes in specific brain regions with high spatial resolution. Next, multi-modal fusion with pupillometry sensing is proposed and shown to offer a robust assessment of cognitive and listening effort through pupil size and pupil dilation. Our novel approach evaluates RF sensing to estimate CL from cerebral blood flow variations utilizing pupillometry as a baseline. A first-of-its-kind, multi-modal dataset is collected as a new benchmark resource in a controlled environment with participants to comprehend target speech with varying background noise levels. The framework is statistically evaluated using intraclass correlation for pupillometry data (average ICC> 0.95). The correlation between pupillometry and RF data is established through Pearson's correlation (average PCC> 0.79). Further, CL is classified into high and low categories based on RF data using K-means clustering. Future work involves integrating RF sensors with glasses to estimate listening effort for hearing-aid users and utilising RF measurements to optimize speech enhancement based on individual's listening effort and complexity of acoustic environment
A novel deep semantic- and vision-based self-attention architecture for skin cancer classification
Full text linkObjectives: In the world, skin cancer is a significant health concern, and early diagnosis of this cancer plays a key role in improving patient outcomes. The early detection of this cancer reduces the death rate, but due to the complexity of the diagnosis, incorrect detection and prediction are provided by the experts. Therefore, it is essential to propose a computer-aided diagnostic system based on deep learning and explainable Artificial Intelligence (XAI) techniques that can be used as a second opinion in clinics and help physicians more accurately detect and predict this type of cancer. Methods: This work presents the proposed deep learning architecture consisting of two modules—skin lesion segmentation and lesion type classification. The proposed architecture is interpreted using XAI techniques to better evaluate the black-box model. In the skin lesion segmentation phase, we implemented DeepLab V3 architecture for semantic segmentation. The ResNet-18 model was used as the backbone, and later hyperparameters were optimized using Bayesian Optimization (BO). In the classification phase, we design a FusedNet architecture called Inverted self-attention with Vision Transformer (ISAwViT). The proposed fused network combines an inverted self-attention residual architecture with a vision transformer. The proposed fused network extracted feature information more deeply than performing an accurate prediction in a later stage. The design model is trained, and later in the testing phase, extracted features are classified using Softmax and several other classifiers. Results: The lesion segmentation and classification experiment was conducted on the HAM10000 dataset. The accuracy achieved by the HAM10000 dataset was 95.16% for lesion segmentation and 97.5% for lesion classification. Conclusion: Compared with recent techniques, the proposed model is more effective and efficient. In addition, the interpretation of the proposed model was performed using LIME and Grad-CAM, which show how the fused model makes correct classifications
Navigating Thematic Analysis: Practical Strategies Grounded in Abductive Reasoning
Full text linkAbductive thematic analysis blends empirical observations with theoretical frameworks, fostering a continuous and dynamic exchange between research evidence and theory. It is distinct from other forms of analysis as it is underpinned by pragmatism and is flexible in its adoption of theory to best answer the research question. As a result of an interplay between theory and data, a surprising, puzzling, or anomalous finding may lead to new insights. This flexible approach to inquiry can draw from theories dependent upon what is best able to explain the data. This results in a theoretically informed explanation for empirical phenomena, which may in turn unveil unique insights about theories, making it a valuable tool across diverse research domains in medical science. The guidelines in this paper aim to illuminate abductive thematic analysis, steering the reader through each step toward maximizing novel theoretical contributions and fostering a comprehensive understanding for researchers and educators
Dual Role Executives and Corporate Membership of Emission Trading Schemes: The Role of Board Structure
Full text linkThis study examines the impact of CEO duality on the likelihood of corporate participation in an emissions trading scheme. The results indicate that firms led by dual‐role executives are less likely to participate in emissions trading schemes. However, we document that the core relationship is moderated by board composition, including board tenure, board size, the nationality mix of board members, and the proportion of independent directors. Firms' continent of operation and law of origin also affect the probability of joining emission trading schemes. Financing frictions such as bankruptcy risk, degree of financial constraint, and firm growth opportunities are also important considerations
From consensus to action: Implementing cardiovascular prevention guidelines in primary healthcare
Full text linkCardiovascular prevention guidelines are based on robust evidence, yet their implementation in primary healthcare remains inconsistent due to systemic barriers, workload pressures and insufficiently adapted tools. The 2025 European consensus emphasizes the need for multidisciplinary teamwork, digital innovation and equity-focused strategies to strengthen prevention across diverse healthcare systems. Translating these recommendations into actionable, context-specific approaches is essential to close the evidence-practice gap and improve population cardiovascular outcomes
Exploring the Qualities of Talent Development Environments within a Jordanian Football Context
No full textIntroduction: Governing bodies, clubs, and academies responsible for the development of young people could become more effective and accountable in their designated tasks through the comprehension of the processes that take place in effective talent identification and development (TID). This study examined Arabic TDEQ Validation, Evaluation of TDE Quality (The Individualized Long-term Development Focus, Goal Setting and Coherent Support, Holistic Quality Preparation). Method: The Arabic translated Talent Development Environment Questionnaire (TDEQ-5) was used in obtaining data from 564 young football players (319 males and 245 females) between 12 and 18 years of age, from clubs and academies across Jordan. Exploratory factor analysis showed a three-factor, 26 valid and reliable item solution (Arabic TDEQ-3). Result: Results showed Individualised Long Term Development Focus, and Goal Setting and Coherent Support as the highest scoring factors of Jordanian football TDEs, while Holistic Quality Preparation was the weakest factor. In all three factors, males experienced better quality environments than females. Coaches should improve the development of psychological attributes, planning and clarity around progression requirements and communication with other coaches. Conclusions: This study can be a headstart to the researchers and practitioners in Arab nations in their TDEs research and evaluation. Future work should consider cultural nuances in expanding the Arabic TDEQ. Recommendation: Jordan Football Federation may consider expanding the support provided to the female teams at various age groups. Coaches need better communication skills and strategies to help female players improve their weaknesses, as this can influence positively their development
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