Search Results (274)

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. This paper presents a systematic review of the scientific literature published between 1 January 2020 and 31 May 2025. The paper is based on the applicability of ML techniques in the field of geriatrics. The study is conducted using the Web of Science database for a detailed discussion. The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. The performance metrics reported in the analyzed papers include the accuracy, sensitivity, F1-score, and Area under the Receiver Operating Characteristic Curve. Nine search categories are investigated through four databases: WOS, PubMed, Scopus, and IEEE. A comparative analysis shows that the field of geriatrics, through an ML approach in the context of elderly nutrition, is insufficiently explored, as evidenced by the 61 articles analyzed from the four databases. The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. The paper highlights the potential of ML models in transforming geriatrics within the context of personalized predictive care and outlines a series of future research directions, recommending the development of standardized databases, the integration of algorithmic explanations, the promotion of interdisciplinary collaborations, and the implementation of ethical norms of artificial intelligence in geriatric medical practice. Full article

Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article

Air pollution is linked to childhood mortality and morbidity in low- and middle-income countries globally. There is growing evidence linking air pollution to asthma and other respiratory diseases in children. Studies have shown that children are likely to experience asthma due to their narrow airways and their heightened sensitivity to environmental irritants. This study aims to investigate the relationship between ambient air pollution and respiratory diseases in children under the age of 5. The study will be conducted in the informal township of Alexandra, north of Johannesburg, South Africa. A quantitative approach will be used in this cross-sectional analytical study. Data will be collected using different tools that include a questionnaire to determine the prevalence of asthma and respiratory disease and potential risk factors. While environmental air pollution will be measured using Radiello passive samplers and Gillian pumps. Data will be analyzed using the latest version of the STATANow/MP 19.5 software. Furthermore, health risk assessment will be conducted for lifetime non-carcinogenic and carcinogenic risk estimation following the USEPA framework. The study will identify environmental triggers that exacerbate asthma and other respiratory conditions in other similar community settings and will contribute to the body of knowledge in public health. Ethical approval was obtained from the Research Ethics Committee, Faculty of Health Sciences at the University of Johannesburg. Full article

Although intracranial hypertension (ICH) has traditionally been framed as simply a numerical escalation of intracranial pressure (ICP) and usually dealt with in its clinical form and not in terms of its complex underlying pathophysiology, an emerging body of evidence indicates that ICH is not simply an elevated ICP process but a complex process of molecular dysregulation, glymphatic dysfunction, and neurovascular insufficiency. Our aim in this paper is to provide a complete synthesis of all the new thinking that is occurring in this space, primarily on the intersection of glymphatic dysfunction and cerebral vein physiology. The aspiration is to review how glymphatic dysfunction, largely secondary to aquaporin-4 (AQP4) dysfunction, can lead to delayed cerebrospinal fluid (CSF) clearance and thus the accumulation of extravascular fluid resulting in elevated ICP. A range of other factors such as oxidative stress, endothelin-1, and neuroinflammation seem to significantly impair cerebral autoregulation, making ICH challenging to manage. Combining recent studies, we intend to provide a revised conceptualization of ICH that recognizes the nuance and complexity of ICH that is understated by previous models. We wish to also address novel diagnostics aimed at better capturing the dynamic nature of ICH. Recent advances in non-invasive imaging (i.e., 4D flow MRI and dynamic contrast-enhanced MRI; DCE-MRI) allow for better visualization of dynamic changes to the glymphatic and cerebral blood flow (CBF) system. Finally, wearable ICP monitors and AI-assisted diagnostics will create opportunities for these continuous and real-time assessments, especially in limited resource settings. Our goal is to provide examples of opportunities that exist that might augment early recognition and improve personalized care while ensuring we realize practical challenges and limitations. We also consider what may be therapeutically possible now and in the future. Therapeutic opportunities discussed include CRISPR-based gene editing aimed at restoring AQP4 function, nano-robotics aimed at drug targeting, and bioelectronic devices purposed for ICP modulation. Certainly, these proposals are innovative in nature but will require ethically responsible confirmation of long-term safety and availability, particularly to low- and middle-income countries (LMICs), where the burdens of secondary ICH remain preeminent. Throughout the review, we will be restrained to a balanced pursuit of innovative ideas and ethical considerations to attain global health equity. It is not our intent to provide unequivocal answers, but instead to encourage informed discussions at the intersections of research, clinical practice, and the public health field. We hope this review may stimulate further discussion about ICH and highlight research opportunities to conduct translational research in modern neuroscience with real, approachable, and patient-centered care. Full article

Variable selection (VS) is a critical step in developing predictive binary classification (BC) models. Many traditional methods for assessing the added value of a candidate variable provide global performance summaries and lack an interpretable graphical summary of results. To address this limitation, we developed the U-smile method, a residual-based, post hoc evaluation approach for assessing prediction improvements and worsening separately for events and non-events. The U-smile method produces three families of interpretable BA-RB-I coefficients at three levels of generality and a standardized graphical summary through U-smile and prediction improvement–worsening (PIW) plots, enabling transparent, interpretable, and explainable VS. Validated in balanced and imbalanced BC scenarios, the method proved robust to class imbalance and collinearity, and more sensitive than traditional metrics in detecting subtle but meaningful effects. Moreover, the method’s intuitive visual output (U-smile plot) facilitates the rapid communication of results to non-technical stakeholders, bridging the gap between data science and applied decision-making. The U-smile method supports both local and global evaluations and complements existing explainable machine learning (XML) and artificial intelligence (XAI) tools without overlapping in their functions. The U-smile method offers a transparency-enhancing and human-oriented approach for ethical and fair VS, making it highly suited for high-stakes domains, e.g., healthcare and public health. Full article

RNA viruses pose significant threats to global health, causing diseases such as COVID-19, HIV/AIDS, influenza, and dengue. These viruses are characterized by high mutation rates, rapid evolution, and the ability to evade traditional antiviral therapies, making effective treatment and prevention particularly challenging. In recent years, CRISPR/Cas13 has emerged as a promising antiviral tool due to its ability to specifically target and degrade viral RNA. Unlike conventional antiviral strategies, Cas13 functions at the RNA level, providing a broad-spectrum and programmable approach to combating RNA viruses. Its flexibility allows for rapid adaptation of guide RNAs to counteract emerging viral variants, making it particularly suitable for highly diverse viruses such as SARS-CoV-2 and HIV. This review discusses up-to-date applications of Cas13 in targeting a wide range of RNA viruses, including SARS-CoV-2, HIV, dengue, influenza, and other RNA viruses, focusing on its therapeutic potential. Preclinical studies have demonstrated Cas13’s efficacy in degrading viral RNA and inhibiting replication, with applications spanning prophylactic interventions to post-infection treatments. However, challenges such as collateral cleavage, inefficient delivery, potential immunogenicity, and the development of an appropriate ethical framework must be addressed before clinical translation. Future research should focus on optimizing crRNA design, improving delivery systems, and conducting rigorous preclinical evaluations to enhance specificity, safety, and therapeutic efficacy. With continued advancements, Cas13 holds great promise as a revolutionary antiviral strategy, offering novel solutions to combat some of the world’s most persistent viral threats. Full article

Background/Objectives: Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes mellitus and a leading cause of vision impairment worldwide. Early detection and timely management are critical in preventing vision loss, yet current screening programs face challenges, including limited specialist availability and variability in diagnoses, particularly in underserved areas. This literature review explores the evolving role of artificial intelligence (AI) in enhancing the diagnosis, screening, and management of diabetic retinopathy. It examines AI’s potential to improve diagnostic accuracy, accessibility, and patient outcomes through advanced machine-learning and deep-learning algorithms. Methods: We conducted a non-systematic review of the published literature to explore advancements in the diagnostics of diabetic retinopathy. Relevant articles were identified by searching the PubMed and Google Scholar databases. Studies focusing on the application of artificial intelligence in screening, diagnosis, and improving healthcare accessibility for diabetic retinopathy were included. Key information was extracted and synthesized to provide an overview of recent progress and clinical implications. Conclusions: Artificial intelligence holds transformative potential in diabetic retinopathy care by enabling earlier detection, improving screening coverage, and supporting individualized disease management. Continued research and ethical deployment will be essential to maximize AI’s benefits and address challenges in real-world applications, ultimately improving global vision health outcomes. Full article

Airborne respiratory viruses (e.g., influenza, respiratory syncytial virus (RSV), and SARS-CoV-2) continue to pose a serious threat to global public health due to their ability to spread through multiple transmission pathways. Among these, aerosol transmission stands out as a key route, particularly in enclosed environments. However, current monitoring systems have major limitations in sensitivity, standardization, and high time resolution. This study provides a summary of the latest information on the monitoring technologies for respiratory virus aerosols. It discusses the technical and ethical challenges in real-world applications. In addition, this study proposes practical solutions and future development pathways. The aim of this study is to provide theoretical support for building a dynamic, precise, and effective early warning system for monitoring variants of airborne respiratory viruses Full article

The study examines how individual skills influence adolescents’ and young adults’ commitment to climate protection and global health. Based on 21st-century skills and transformative education, it focuses on competences in science, geography, mathematics, religion, ethics, and media. A representative online survey of 783 participants in Germany assessed topic relevance, information-seeking behavior, and active engagement. The results show that subject-specific skills significantly affect engagement, especially when closely related to the topics. Scientific, mathematical, and geographical competences enhance all three engagement dimensions. Media competence primarily increases perceived importance, while religious and ethical competences positively influence all areas. Structural equation modeling reveals a process: perceived relevance leads to information search, which then drives engagement. Thus, competences have both direct and indirect effects on active involvement. The findings highlight that long-term engagement is not only driven by campaigns but also by education that equips young people with the skills to recognize important issues, seek information, and take action independently. Full article

Global data reveal ongoing inequalities faced by minorities, often reinforced by media portrayals that depict them as threats, victims, or passive individuals without agency. While media framing has been extensively studied, especially in terms of media content and representation, few studies have examined how journalists perceive and navigate the coverage of minorities. This study addresses that gap by examining how Greek journalists perceive mainstream media coverage of refugees and migrants, LGBTQ+ individuals, and people with mental health challenges, with particular attention to their sourcing practices and sense of ethical responsibility. Fourteen journalists participated in semi-structured interviews, and thematic analysis was applied to identify key patterns. Journalists described dominant media narratives as fragmented, stereotypical, and dehumanizing, noting the frequent use of linguistic inaccuracies, misinformation, and the absence of personal stories. At the same time, they reported opportunities within their own sourcing practices to promote more inclusive and accurate coverage. Ethical concerns were expressed on three levels—union; corporate; and personal—with calls for clearer editorial guidelines and dedicated training. Many participants emphasized the role of personal ethics as a guiding compass in navigating complex newsroom pressures. Full article

This article examines how the COVID-19 pandemic exposed and intensified global inequalities, particularly through the lens of vaccine distribution, thereby challenging the ideals of global citizenship. While the pandemic highlighted humanity’s interconnectedness and shared vulnerability, the unequal access to vaccines and resources revealed enduring structural disparities between nations. Drawing on a review of the existing literature from three national contexts, this study critiques the limitations of global citizenship as a framework for addressing such inequalities. In response, it proposes “glo-ubuntu citizenship”—a reimagined concept rooted in African philosophy and the idea of shared humanity—as a more culturally grounded and ethically responsive approach. This model blends the global and local dimensions of citizenship while emphasizing solidarity and mutual care. The article argues that while glo-ubuntu citizenship is not without its challenges, it holds greater potential than conventional models for fostering equity in global health governance and guiding more inclusive responses to future crises. Full article

Introduction: The health emergency caused by the pandemic led to severe health issues in populations across many countries worldwide, including widespread morbidity and significant mortality. Nevertheless, several countries succeeded in keeping infection rates remarkably low before the approval of vaccines and the initiation of vaccinations in early 2021. We aim to identify the success factors of health policies in managing the impact of the health emergency across a selection of countries, focusing on how they protected their populations. Our study presents outcomes of sustainable health policy measures, along with health and social system challenges, and economic responses during the global health emergency. We sometimes found it difficult to define what counted as a success factor in some countries. Method: Our study draws upon a selection of reports and documents published by various ministries and economic, social, and health authorities, which we collected online. We structured our study into three phases to frame and contextualize the impact of health policy measures and countermeasures as follows: (i) observations and content analysis; (ii) empirical support through illustrative examples; and (iii) development of a health emergency toolkit of assessment. The documents were not always easy to compare because they differed in format and detail. Results: Our study outlines ten success factors for sustainable health policy measures and countermeasures: (i) preparedness; (ii) control; (iii) precaution; (iv) proactive decision-making; (v) synchronization; (vi) adequate legislation; (vii) goal fulfillment; (viii) digital health technology; (ix) empirical evidence; (x) ethical and moral virtues. Sometimes we struggled to separate what was ethical guidance from what was simply practical advice. Conclusion: We argue that the relevance of the health emergency toolkit of assessment outlined in our study demonstrates clearly that the success factors related to sustainable health policy measures and countermeasures can be applied and adapted to the societal conditions of individual countries. These factors may form a foundation for the development of a health emergency toolkit of assessment for future health emergencies. We also maintain that these factors may serve as a platform for establishing sustainable plans across health, social, and economic domains, with clear guidelines for implementation, management, and control. It is our hope that future health systems will make use of these findings before the next crisis emerges. 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

The COVID-19 pandemic and its associated lockdowns had widespread psycho-social implications globally. However, the unique experiences of young adults in under-researched rural communities, such as Lonely Park in South Africa’s North West Province, remain poorly documented. This study explores the psycho-social well-being of young adults aged 18–24 in the Lonely Park community during the national COVID-19 lockdown from 23 March 2020 to 30 April 2020, with a particular focus on their emotional, psychological, and social experiences. Using a qualitative, phenomenological design rooted in Bronfenbrenner’s Ecological Systems Theory (EST), data were collected from 14 purposively sampled participants through two focus group discussions. Thematic analysis was conducted following Braun and Clarke’s six-phase framework. Ethical clearance was obtained from the Health Research Ethics Committee, and participants provided informed consent. Two main themes emerged, (1) psychological and (2) social well-being. Six sub-themes were identified: (1) negative emotions linked to lockdown, (2) fear of COVID-19 and its consequences, (3) rumination and anxiety, (4) disruption of social and educational routines, (5) coping strategies, and (6) structural limitations of healthcare and support systems. Participants experienced intense fear, boredom, isolation, and a sense of helplessness. Yet, coping mechanisms such as communication, spirituality, exercise, and adherence to public health regulations provided resilience. Some reported depression and financial strain due to job loss and school disruptions. The findings highlight the complex interplay of psychological, emotional, and social stressors in rural young adults during the pandemic. Policymakers and mental health practitioners must prioritise targeted psycho-social interventions for youth in under-resourced rural settings. A call is made for culturally responsive mental health programmes that incorporate local voices, especially in rural African contexts. Full article