Search Results (632)

Hospital in the Home (HITH) programs are emerging as a key pillar of smart city healthcare infrastructure, leveraging technology to extend care beyond traditional hospital walls. The global healthcare sector has been conceptualizing the notion of a care without walls hospital, also called HITH, where virtual care takes precedence to address the multifaceted needs of an increasingly aging population grappling with a substantial burden of chronic disease. HITH programs have the potential to significantly reduce hospital bed occupancy, enabling hospitals to better manage the ever-increasing demand for inpatient care. Although many health providers and hospitals have established their own HITH programs, there is a lack of research that provides healthcare executives and HITH program managers with management models and frameworks for such initiatives. There is also a lack of research that provides strategies for improving HITH management in the health sector. To fill this gap, the current study ran a systematic literature review to explore state-of-the-art with regard to this topic. Out of 2631 articles in the pool of this systematic review, 20 articles were deemed to meet the eligibility criteria for the study. After analyzing these studies, nine management models were extracted, which were then categorized into three categories, namely, governance models, general models, and virtual models. Moreover, this study found 23 strategies and categorized them into five groups, namely, referral support, external support, care model support, technical support, and clinical team support. Finally, implications of findings for practitioners are carefully provided. These findings provide healthcare executives and HITH managers with practical frameworks for selecting appropriate management models and implementing evidence-based strategies to optimize program effectiveness, reduce costs, and improve patient outcomes while addressing the growing demand for home-based care. Full article

Background/Objectives: Collaboration in mental health care is essential for implementing a model oriented towards the psychosocial rehabilitation of people based on multifaceted interventions involving different actors and sectors of society to respond to demands. Despite the benefits presented by the scientific evidence, there are still many barriers to collaborative care, and professionals continue to struggle in reorienting their conduct. The current situation demands organization and the framing of well-founded action plans to overcome challenges, which in turn requires a detailed understanding of collaborative practices in mental health care and their conceptual boundaries. A concept analysis was undertaken to propose a working definition of collaborative practices in mental health care (CPMHC). Methods: This paper used the Walker and Avant concept analysis method. This includes identifying the defining concept attributes, antecedents, consequences, and empirical referents. A literature search was carried out from November 2024 to February 2025 in three databases (Medline, CINAHL, and LILACS), considering studies published between 2010 and 2024. Results: The final sample of literature investigated consisted of 30 studies. The key attributes were effective communication, building bonds, co-responsibility for care, hierarchical flexibility, articulation between services, providers and community, monitoring and evaluating of care processes, and attention to the plurality of sociocultural contexts. Conclusions: This comprehensive analysis contributes to guiding future research and policy development of collaborative practices in mental health, considering the individual, relational, institutional, and social levels. Further research is possible to deepen the understanding of the production of collaborative practices in mental health in the face of the complexity of social relations and structural inequities. Full article

Background/Objectives: Improving health outcomes for Indigenous people by strengthening the cultural safety of care is a vital challenge for the health sector. University Departments of Rural Health (UDRH), academic centres based in regional, rural, and remote (RRR) locations across Australia, are uniquely positioned to foster a culturally safe rural health workforce through training, education, and engagement with Indigenous communities. This narrative review examines the contributions of UDRHs to health workforce issues through analysis of their publications focused on Indigenous health. Methods: Research articles relating to workforce were identified from an established database of UDRH Indigenous health-related publications published 2010–2021. Results: Of 46 articles identified across the 12 years, 19 focused on developing the understanding and cultural safety skills of university students studying in a health field, including campus-based Indigenous health education and support for students undertaking rural clinical placements. Twelve articles investigated cultural safety skills and recruitment and retention of the rural health workforce. Fifteen articles focused on Indigenous people in the health workforce, examining clinical training and resources, and the enablers and barriers to retaining Indigenous students and workers. Conclusions: This analysis highlights the sustained efforts of UDRHs to improve Indigenous health through multiple areas within their influence, including curriculum design, health student training on campus, and rural placement opportunities to transform understanding of Indigenous strengths and disadvantages and rural health workforce development. A continuing effort is needed on ways UDRHs can support Indigenous health students during their studies and while on placement, how to improve cultural safety in the health workforce, and ways to better support Indigenous health professionals. Full article

In light of pressing global nutritional needs, the valorization of agri-food waste constitutes a vital strategy for enhancing human health and nutrition, while simultaneously supporting planetary health. This integrated approach is increasingly indispensable within sustainable and equitable food systems. Recently, a sustainability-driven focus has shifted attention toward the valorization of the agri-food by-products as rich sources of bioactive compounds useful in preventing or treating chronic diseases. Agri-food by-products, often regarded as waste, actually hold great potential as they are rich in bioactive components, dietary fiber, and other beneficial nutrients from which innovative food ingredients, functional foods, and even therapeutic products are developed. This review aims to provide a comprehensive analysis of the current advances in recovering and applying such compounds from agri-food waste, with a particular focus on their roles in human health, sustainable packaging, and circular economy strategies. Methods: This review critically synthesizes recent scientific literature on the extraction, characterization, and utilization of bioactive molecules from agri-food by-products. After careful analysis of the PubMed and Scopus databases, only English-language articles from the last 10 years were included in the final narrative review. The analysis also encompasses applications in the nutraceutical, pharmaceutical, and food packaging sectors. Results: Emerging technologies have enabled the efficient and eco-friendly recovery of compounds such as polyphenols, carotenoids, and dietary fibers that demonstrate antioxidant, antimicrobial, and anti-inflammatory properties. These bioactive compounds support the development of functional foods and biodegradable packaging materials. Furthermore, these valorization strategies align with global health trends by promoting dietary supplements that counteract the effects of the Western diet and chronic diseases. Conclusions: Valorization of agri-food by-products offers a promising path toward sustainable development by reducing waste, enhancing public health, and driving innovation. This strategy not only minimizes waste and supports sustainability, but also promotes a more nutritious and resilient food system. Full article

Background: The consumption of ultra-processed foods (UPFs) represents an important public health challenge, especially among education workers, whose intense routine can negatively impact eating habits. This study aimed to analyze the factors associated with the regular consumption of UPF among employees of the Federal Network of Professional, Scientific and Technological Education (RFEPCT) in Brazil. Methods: This was a cross-sectional study, with a quantitative approach, carried out with 1563 education workers. Validated instruments on eating habits (PeNSE), mental health (DASS-21) and quality of life (WHOQOL-bref) were used. The regular consumption of UPF was defined as intake on ≥5 days in the last seven days. The association between the regular consumption of UPF and sociodemographic, occupational, behavioral, mental health and quality of life variables was assessed by Poisson regression with robust variance, generating adjusted prevalence ratios (PRadj) and respective 95% confidence intervals. Results: The regular consumption of UPF was associated mainly with female gender, a lower age group, Southeast and Midwest regions, dissatisfaction with sleep and the body, physical inactivity and poor sleep quality. In addition, the findings suggested a significant relationship between the worst stress scores and soft drinks (PRadj: 2.11; CI: 1.43–3.13), anxiety and soft drinks (PRadj: 1.83; CI: 1.24–2.70) and depression and industrialized/ultra-processed salty foods (PRadj: 2.43; CI: 1.82–3.26). The same was observed in the scores for the worst perception of quality of life, where there was a prevalence of up to 2.32 in the psychological domain and the consumption of industrialized/ultra-processed salty foods. Conclusions: The findings indicate that multiple interrelated factors—individual, psychosocial and occupational—are associated with the consumption of UPF among education workers. These results reinforce the importance of institutional policies that integrate actions to promote dietary health, mental health care and improved working conditions in the education sector. Full article

Background/Objectives: There is a need for randomized clinical trials with higher quality, especially for older people at high risk of falls, with interventions that consider individual needs, comprehensiveness of care, and connection with primary health care. We designed a randomized controlled trial to examine the effects of a case management intervention combined with a physical exercise protocol on risk factors for falls, falls data, adherence, satisfaction, costs, and implementation in community-dwelling older adults with high risk of falls. Methods: A minimum of 60 community-dwelling older people with high falls risk will participate in the randomized controlled assessor-blinded trial (MAGIC—v. 2). The trial will be conducted in a regional health department of São Paulo state (Brazil), which includes 6 cities. Participants will be randomized to the Intervention Group (case management intervention based on all individual risk factors for falls identified by a multidimensional assessment, over 16 weeks, once a week, by telephone calls). Both groups will perform a physical exercise protocol based on falls prevention for 16 weeks (twice a week) in Health Units. The assessment will be performed at baseline, after 16 weeks of intervention, after 6-month follow-up, and after 12-month follow-up. Primary outcome measures include falls data and potentially modifiable risk factors for falls. Discussion: This study has the potential to facilitate the future implementation of the intervention based on case management with a focus on fall prevention in the health sectors. Trial registration: Brazilian Registry of Clinical Trials (ReBEC). Full article

The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, these methodologies do not include the learning curve, a critical factor in operator-dependent technologies. This study presents an evaluation model incorporating the learning curve, developed from the domains of the AdHopHTA project. Using System Dynamics (SD), the model was validated and calibrated as a case study to evaluate the use of Point-of-Care Ultrasound (POCUS) in identifying dengue. This approach allowed for the analysis of the impact of the learning curve and patient demand on the revenues and costs of the healthcare system and the cost–benefit indicator associated with dengue detection. The model assesses physician competency and how different training strategies and frequencies of use affect POCUS adoption. The findings underscore the importance of integrating the learning curve into decision-making. This study highlights the need for further investigation into the barriers that limit the effective use of POCUS, particularly in resource-limited settings. It proposes a framework to improve the integration of this technology into clinical practice for early dengue detection. Full article

This article examines the relevance of Smart Specialisation Strategies (RIS3) in structurally weak but non-peripheral regions, using Poland’s Lubusz Voivodeship as a case study. Based on employment data from 2009 and 2021, this study uses Location Quotient (LQ) analysis to evaluate the alignment between the region’s economic structure and its RIS3 domains: Innovative Industry, Health and Quality of Life, and Green Economy. The findings show that while Innovative Industry and Health and Quality of Life strengthened their relative specialisation, the Green Economy domain made only limited progress. Notably, sectors such as metal fabrication and social care services emerged as new specialisations, while several traditional industries declined. These results support the hypothesis that RIS3 priorities only partially reflect endogenous economic strengths, and they highlight the challenges of implementing innovation strategies in territorially fragmented and capacity-constrained regions. This article calls for dynamic priority reviews, improved multi-level coordination, and targeted instruments to better align RIS3 frameworks with the structural realities of “in-between” regions in the EU. Full article

In recent years, cutting-edge technologies, such as artificial intelligence (AI), blockchain, and digital twin (DT), have revolutionized the healthcare sector by enhancing public health and treatment quality through precise diagnosis, preventive measures, and real-time care capabilities. Despite these advancements, the massive amount of generated biomedical data puts substantial challenges associated with information security, privacy, and scalability. Applying blockchain in healthcare-based digital twins ensures data integrity, immutability, consistency, and security, making it a critical component in addressing these challenges. Federated learning (FL) has also emerged as a promising AI technique to enhance privacy and enable decentralized data processing. This paper investigates the integration of digital twin concepts with blockchain and FL in the healthcare domain, focusing on their architecture and applications. It also explores platforms and solutions that leverage these technologies for secure and scalable medical implementations. A case study on federated learning for electroencephalogram (EEG) signal classification is presented, demonstrating its potential as a diagnostic tool for brain activity analysis and neurological disorder detection. Finally, we highlight the key challenges, emerging opportunities, and future directions in advancing healthcare digital twins with blockchain and federated learning, paving the way for a more intelligent, secure, and privacy-preserving medical ecosystem. Full article

Artificial Intelligence (AI) is reshaping mental healthcare by enabling new forms of diagnosis, therapy, and patient monitoring. Yet this digital transformation raises complex policy and ethical questions that remain insufficiently addressed. In this paper, we critically examine how AI-driven innovations are being integrated into mental health systems across different global contexts, with particular attention to governance, regulation, and social justice. The study follows the PRISMA-ScR methodology to ensure transparency and methodological rigor, while also acknowledging its inherent limitations, such as the emphasis on breadth over depth and the exclusion of non-English sources. Drawing on international guidelines, academic literature, and emerging national strategies, it identifies both opportunities, such as improved access and personalized care, and threats, including algorithmic bias, data privacy risks, and diminished human oversight. Special attention is given to underrepresented populations and the risks of digital exclusion. The paper argues for a value-driven approach that centers equity, transparency, and informed consent in the deployment of AI tools. It concludes with actionable policy recommendations to support the ethical implementation of AI in mental health, emphasizing the need for cross-sectoral collaboration and global accountability mechanisms. Full article

Older adults make up about 12% of the public sector, primary care, and hospital use and represent a large proportion of the users of healthcare services. Older people are also more vulnerable to serious injury from unexpected falls due to tripping, slipping, or illness. This underscores the immediate necessity of stable and cost-effective e-health technologies in maintaining independent living. Artificial intelligence (AI) and machine learning (ML) offer promising solutions for early fall prediction and continuous health monitoring. This paper introduces a novel cooperative AI model that forecasts the risk of future falls in the elderly based on behavioral and health abnormalities. Two AI models’ predictions are combined to produce accurate predictions: The ${AI}_1$ model is based on vital signs using Fuzzy Logic, and the ${AI}_2$ model is based on Activities of Daily Living (ADLs) using a Deep Belief Network (DBN). A meta-model then combines the outputs to generate a total fall risk prediction. The results show 85.71% sensitivity, 100% specificity, and 90.00% prediction accuracy when compared to the Morse Falls Scale (MFS). This emphasizes how deep learning-based cooperative systems can improve well-being for older adults living alone, facilitate more precise fall risk assessment, and improve preventive care. Full article

Intersectoral collaboration between health care, social care and other sectors has been widely advocated to improve population health outcomes. Similarly, the active role of citizens as coproducers is increasingly described in the literature as an important element for improving people’s health and well-being. Yet, there is little understanding of the role of coproduction in intersectoral collaboration, particularly in neighborhoods with low socioeconomic scores (SESs). In this empirical study, we analyze two aspects of coproduction that potentially drive positive health outcomes in intersectoral collaboration: How do coproducers in neighborhoods with low socioeconomic scores actively contribute to intersectoral collaboration, and what role does the relationship between professionals and citizens play in shaping these contributions? The study was conducted in a low-SES neighborhood in The Hague, the Netherlands. In this study, we explored the team ‘the Connectors’, an intersectoral collaboration of professionals and citizens with various (professional) backgrounds, focusing on accessible support for mental health services. The cause of mental health problems in low-SES neighborhoods varies; therefore, intersectoral collaboration is required in the approach to addressing these mental health problems. Using an action research approach, we demonstrated the importance of a reciprocal relationship between coproducers and professionals. We also found that ‘boundary spanners’ can help to improve this relationship, regardless of whether they are professionals or coproducers. We conclude that citizens in a low-SES neighborhood can not only benefit from coproduction, but can also contribute to it, because they have a high incentive to improve their neighborhood together with professionals in the intersectoral collaboration. Full article

Background: The digital transformation in dentistry is increasingly reshaping treatment procedures, offering new opportunities and advancements. While digitalization promises enhanced efficiency and quality of care through the standardization, acceleration, and simplification of workflows, it also introduces challenges related to mental health. Studies investigating digitization-associated stressors and resources, as well as health- and work-related outcomes, in the dental sector are still rare. In the context of ongoing digitalization, further studies are needed to examine the need for and the current status of the implementation of measures preventing techno-stress and stress-related outcomes. This study explores the use of digital tools in dental practices and their relationship to the techno-stress among German dentists. It identifies key stressors and resources associated with digital technologies, aiming to inform preventive measures, as well as training and support strategies to mitigate digital stress. Methods: A qualitative study was employed, involving ten problem-centered, guideline-based expert interviews with German dentists. The interviews were analyzed using MAXQDA software, following the focused interview analysis framework by Kuckartz and Rädiker. Coding and thematic analysis adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist and qualitative research quality criteria by Mayring. Results: This study identified a dual impact of digitalization in dentistry. On the one hand, digital tools significantly enhance workflow efficiency, diagnostic accuracy, and patient outcomes. On the other hand, they pose challenges like technostress, high financial costs, and the need for continuous learning. Findings reveal that the perceived usefulness of digital technologies is closely linked to the level of techno-stress experienced, while the amount, intuitiveness, and ease of use significantly influence stress levels. Conclusions: Digital transformation offers substantial benefits for dental practices but requires a balanced approach to implementation. Participants highlighted the need for proactive measures, such as targeted training, technical support, and stress-reducing interventions to reduce techno-stress levels. The digital transformation must be supported by coordinated efforts across academia, industry, and policy to strengthen digital competencies—creating a healthier, more resilient digital work environment. Future research should focus on the causal relationship between techno-stress and adverse long-term consequences, such as burnout or mental disorders, among dentists. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly integrated into everyday life, including the complex and highly regulated healthcare sector. Given healthcare’s essential role in safeguarding human life and well-being, AI deployment requires careful oversight to ensure safety, effectiveness, and ethical compliance. This paper aims to examine the current regulatory landscapes governing AI in healthcare, particularly in the European Union (EU) and the United States (USA), and to propose practical tools to support the responsible development and implementation of AI systems. Methods: The study reviews key regulatory frameworks, ethical guidelines, and expert recommendations from international bodies, professional associations, and governmental institutions in the EU and USA. Based on this analysis, the paper develops structured questionnaires tailored for AI developers and implementers to help operationalize regulatory and ethical expectations. Results: The proposed questionnaires address critical gaps in existing frameworks by providing actionable, lifecycle-oriented tools that span AI development, deployment, and clinical use. These instruments support compliance and ethical integrity while promoting transparency and accountability. Conclusions: The structured questionnaires can serve as practical tools for health technology assessments, public procurement, accreditation processes, and training initiatives. By aligning AI system design with regulatory and ethical standards, they contribute to building trustworthy, safe, and innovative AI applications in healthcare. Full article

Objectives: This study investigates the presence of crowding-in or crowding-out effects of long-term care insurance (LTCI) on older adults’ care in Korea. Additionally, it examines the influence of old-age income security and private systems, including private transfer income and private health insurance, on these effects. The analysis focuses on three aspects: family-provided care, private non-family care, and total care expenses. Methods: This study conducted logistic and linear regression. Logistic regression was used to examine the likelihood of receiving family-provided and private non-family care, while linear regression analyzed factors associated with total care expenditures. Results: The results reveal a crowding-in effect for family care, as greater utilization of public LTCI is positively associated with family-provided care. However, the relationship between public LTCI and private non-family care was not statistically significant, suggesting that the crowding-in effect on private care systems remains limited. Lastly, LTCI utilization was significantly associated with higher care expenditures. It is noteworthy that the current public LTCI in Korea has low coverage, resulting in insufficient care provision. Consequently, there is growing activity in the private care sector. Conclusions: These findings highlight the need for a more integrated approach to long-term care in Korea, balancing public, private, and family care resources. To achieve quality integrated long-term care for older people, policymakers should focus on expanding public LTCI coverage while fostering coordination between family caregivers and professional care services, ensuring a comprehensive and high-quality care system that meets the diverse needs of Korea’s aging population. Full article