University of Bradford

Mental health in the United Kingdom is declining, whilst food bank use is increasing. This study uses data from the UK Household Longitudinal Survey (2009-2024) to examine associations between food bank use and mental health, measured by the General Health Questionnaire for which responses were on a 4-point scale and reverse-scored with potential scores of 0-36, with higher scores representing more favourable mental health. Propensity matching on demographic factors (gender; age; education level; income; employment status; marital status; number of children; UK region) was employed to compare mental health between households that used foodbanks, those not using food banks and those who were unable to access a food bank. Results indicated that people who used food banks had significantly lower mental health than those who did not. A novel finding was that people who sought but could not access food banks had even lower mental health than those who had accessed food banks. This implies that attending a food bank may be beneficial to mental health. policies and interventions that improve access to food banks could assist users in achieving better mental health and in meeting the United Nations (2012) Sustainable Development Goals related to food provision and mental health. • Mental health declining and food bank use increasing in UK (59 characters) • Results indicated food bank users had poorer mental health than wider population (81 characters) • Those unable to access food banks had poorer mental health than food bank users (79 characters) • Food banks are beneficial to mental health (44 characters) • Policies needed to support food banks in boosting mental health (65 characters)

Purpose Advanced technologies such as additive manufacturing (AM) play a critical role in transforming the healthcare sector by enabling sustainable and resilient solutions that improve patient services and operational efficiency. Yet, the adoption of AM in the healthcare sector is limited. Understanding the knowledge drivers behind its adoption is crucial for its successful implementation and better healthcare performance. This study aims to explore how effective knowledge processes impact innovation, resilience, sustainability and enhanced service quality in healthcare organisations. Design/methodology/approach Drawing on the dynamic capabilities theory, the motivating factors for AM adoption are identified from the literature and verified with industry experts using the fuzzy Delphi method. Then the factors are ranked and categorised into cause-and-effect using different multicriteria decision-making methods. Subsequently, the rationale for the cause-and-effect linkages has been explained using a qualitative approach. Findings This study presents a knowledge-driven decision-support framework that demonstrates how AM facilitates environmental sustainability, operational resilience and performance improvement. Healthcare organisations can leverage this knowledge-structured guidance to make informed decisions aligned with regulatory sustainability mandates. Originality/value Existing studies examine AM in healthcare through separate lenses (e.g. resilience, sustainability and performance) without explaining how organisations can integrate these objectives in practice. This study addresses that gap by developing a knowledge-driven decision-support framework that links knowledge processes and dynamic capabilities to AM adoption pathways, thereby offering actionable and innovative strategies for healthcare organisations.

Abstract This study investigated the wellbeing of UK police officers transitioning out of service, examining retirees, early leavers, and those within 12 months of retirement (N = 370). Using the Job Demands–Resources model, the research identifies a ‘wellbeing paradox’: leavers demonstrate high resilience and subjective wellbeing alongside significantly elevated psychological distress compared to general population norms. Findings reveal that recently retired (≤5 years) and soon-to-retire groups are particularly vulnerable, reporting lower quality of life and higher distress than long-term retirees. Perceived organisational support and resilience emerged as critical buffers against the psychological burden of a policing career. However, participants identified significant unmet needs for career, financial, and mental health guidance during the transition. The study highlights that the anticipatory retirement period is an acute window of vulnerability, suggesting that proactive, targeted organisational interventions are essential to mitigate the lasting psychological burden of policing and ensure successful civilian transitions.

Despite growing advocacy for youth-led and inclusive physical activity provision, there remains limited evidence on how to effectively support underserved young women aged (16-25) and those from minoritised genders into Physical Activity leadership roles. We used a two-phase sequential design. Phase 1 involved systematic mapping of 53 PA leadership programmes in England to describe programme focus, target populations, delivery models and stated outcomes. Phase 2 comprised seven online focus groups with 41 practitioners involved in designing, delivering or overseeing such programmes. Mapping data were summarised using descriptive statistics and narrative synthesis; focus group data were analysed using hybrid inductive-deductive framework analysis informed by Critical Positive Youth Development and feminist-intersectional lenses. Only a minority of mapped programmes were explicitly designed for girls and young women from underserved groups. Programmes most commonly operated through school- or club-based delivery, using modular learning, mentoring and cascaded models, with fewer incorporating financial support, digital delivery or clearly defined progression routes. Practitioners described how recruitment frequently relied on institutional gatekeepers and digital communication, raising concerns about who is reached and who is missed. They emphasised the importance of relational and culturally grounded recruitment and support, care-oriented infrastructures, and broader conceptualisations of leadership that include advocacy, representation and community influence. Combining systematic mapping with practitioner insights provides an integrated descriptive and interpretive picture of current provision. The findings indicate uneven targeting of underserved girls and young women and variable support for their progression into leadership roles. Enhancing equity in PA leadership development will require attention to recruitment practices, relational support and progression pathways that recognise diverse forms of youth leadership.

The construction sector plays a pivotal role in achieving the objectives of the European Green Deal and the UN Sustainable Development Goals, yet the transition toward a circular economy (CE) remains constrained by fragmented frameworks and inconsistent implementation. This study presents a multi-criteria review and synthesis of regulatory, methodological, and policy frameworks governing circularity in the built environment. Using a Multi-Criteria Decision Analysis (MCDA) approach, selected frameworks at national, European, and international levels were assessed across four interrelated dimensions—environmental, economic, social, and technical—to evaluate their capacity to enable resource conservation, waste prevention, and material recirculation. The analysis reveals that while current frameworks strongly promote energy efficiency and waste management, they insufficiently address design for adaptability, modularity, disassembly, and lifecycle traceability. Moreover, the lack of operational indicators and cross-dimensional integration limits their effectiveness in guiding implementation and monitoring progress. By systematically identifying overlaps, complementarities, and gaps, this study provides evidence for the need to develop a harmonised and operational CE framework that connects policy ambitions with measurable outcomes. The findings offer strategic insights for policymakers, industry stakeholders, and researchers aiming to accelerate circular transformation in construction and contribute to climate-neutral, resource-efficient, and resilient built environments.

This article presents a state-of-the-art review of recent advances aimed at transforming traditional Failure Mode and Effects Analysis (FMEA) into a more intelligent, data-driven, and semantically enriched process. As engineered systems grow in complexity, conventional FMEA methods, which are largely manual, document-centric, and expert-dependent, have become increasingly inadequate for addressing the demands of modern systems engineering. We examine how techniques from Artificial Intelligence (AI), including machine learning and natural language processing, can transform FMEA into a more dynamic, data-driven, intelligent, and model-integrated process by automating failure prediction, prioritisation, and knowledge extraction from operational data. In parallel, we explore the role of ontologies in formalising system knowledge, supporting semantic reasoning, improving traceability, and enabling cross-domain interoperability. The review also synthesises emerging hybrid approaches, such as ontology-informed learning and large language model integration, which further enhance explainability and automation. These developments are discussed within the broader context of Model-Based Systems Engineering (MBSE) and function modelling, showing how AI and ontologies can support more adaptive and resilient FMEA workflows. We critically analyse a range of tools, case studies, and integration strategies, while identifying key challenges related to data quality, explainability, standardisation, and interdisciplinary adoption. By leveraging AI, systems engineering, and knowledge representation using ontologies, this review offers a structured roadmap for embedding FMEA within intelligent, knowledge-rich engineering environments.

Abstract Choquet integrals are used for the analysis of annual reports of companies, with a focus on their use of positive words. It is shown that the Choquet integral is able to distinguish one report from another by taking into account of the potential latent relationships of different sections of the annual reports. The robustness of the results in the presence of random noise in the data is discussed. The uniformity of use of positive tone in annual reports is also analysed using entropy and the Gini index. The inverse problem of calculating the capacities from known values of the Choquet integral linked to a certain set of data is also studied (and called ‘training’ of the Choquet integral). These capacities can then be used for the calculation of the Choquet integral for different sets of ‘similar data’. This is exemplified with data related to solar flares.