Odense Municipality

Massive open online courses (MOOCs) have emerged as powerful educational tools for disseminating complex scientific knowledge. This study examines the RECONECT MOOC, an innovative online learning platform designed to educate stakeholders about nature-based solutions (NbS) for hydrometeorological risk reduction. Developed by a multidisciplinary team of international experts, the course drew on diverse professional and geographical perspectives, across a range of national and sectoral contexts. Its primary aim to bridge the knowledge gap in climate adaptation strategies across diverse professional sectors. The research investigated the effectiveness of interactive, multimedia-based learning approaches in communicating advanced NbS concepts. Using the Sharable Content Object Reference Model (SCORM) framework, the course integrated multiple learning methods, including reading, listening, inquiry-based learning, discussion forums and practical application exercises. The MOOC was divided into six modules and targeted local authorities, policymakers, academics, postgraduate students and other stakeholders interested in climate resilience. Findings revealed that 90% of participants gained additional NbS knowledge, 69% reported a shift in perception and 62% felt confident applying what they learned. Participants valued the interactive resources and flexible, self-paced format. Overall, the study demonstrates that MOOCs can effectively support scientific knowledge dissemination and strengthen understanding of complex environmental solutions.

Currently, the early detection of cerebral palsy (CP) or risk of CP is recommended to enable targeted and specific intervention. The provision of early therapy is a complex practice that places high demands on both parents and therapists. More knowledge about the perceptions of parents and therapists is needed to help the implementation of family-centred early therapy interventions that are based on recent evidence in clinical practice. This scoping review aims to identify the extent of literature and summarize the evidence exploring parents' and therapists' experiences of early occupational and physical therapy for infants with or at risk of CP. The scoping review was conducted in accordance with the JBI methodology for scoping reviews and reported following the PRISMA Extension for Scoping Reviews checklist. The experiences of parents and therapists were categorized using qualitative content analysis. In total, 16 studies published between 2018 and 2024 were included. Parent-reported experiences were included in 15 studies and therapist-reported experiences in three. The content analysis resulted in five categories reflecting perceptions of valued and challenging aspects of early therapy. Four categories concerned parents' perceptions: parental commitment, parent-therapist collaboration, parents as training providers and parental education. One category concerned therapists' perceptions: providing guidance and educating parents. Insight into perceptions of early therapy highlights the importance of professional coordination of intervention, specific training of therapists, managing parents' feelings of uncertainty and balancing parents' engagement in their role as treatment providers and the pressure they may experience from the responsibility this role entails. This finding contributes important knowledge for the successful implementation of family-centred and evidence-based early therapy interventions in clinical practice for infants with or at risk of CP. A limited number of studies exploring therapists' perceptions were identified, which indicates a knowledge gap and a need for further research.

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Introduction and Objective: Diabetic retinopathy (DR) is a serious microvascular complication of diabetes and a leading cause of preventable blindness worldwide. With the global rise in diabetes prevalence, especially in low- and middle-income countries, early detection and timely treatment of DR have become critical. This paper reviews the evolving role of artificial intelligence (AI) in the automated detection of DR, evaluating its clinical effectiveness, implementation challenges, and potential impact on global preventive eye care. Review Methods: A narrative review was conducted using PubMed, Scopus, and Web of Science databases to identify relevant literature published between 2016 and 2021. Search terms included combinations of “diabetic retinopathy,” “artificial intelligence,” “deep learning,” and “automated detection.” Articles were selected based on their relevance and contribution to advances, clinical applications, and challenges in AI-based DR screening. State of Knowledge: Deep learning algorithms have demonstrated high accuracy in retinal image analysis, often matching expert ophthalmologists in detecting referable DR. AI enables scalable, rapid, and accessible screening, especially in regions with limited specialist availability. Challenges include data quality and diversity, algorithm transparency, patient privacy, clinical acceptance, and evolving regulatory frameworks. Conclusion: AI represents a transformative opportunity to improve early diagnosis and management of diabetic retinopathy globally. To fully realize its benefits, ethical, technical, and regulatory issues must be addressed to ensure safe, effective, and equitable integration of AI into healthcare systems worldwide.

Lung cancer has, for several decades, been the second most frequently diagnosed malignancy and the leading cause of cancer death worldwide. It continues to pose a significant burden on healthcare systems and a serious challenge for clinicians and patients. The majority of patients present with advanced disease at diagnosis, and most survive less than five years. Although novel targeted therapies have been introduced in recent years, there remains a significant demand for treatments capable of improving response and prolonging survival while having minimal impact on quality of life. Recent clinical evidence supporting immunotherapeutic approaches indicates that they may represent the next major therapeutic breakthrough in lung cancer management. Non-small cell lung cancer (NSCLC), which accounts for about 85% of lung cancers, was once considered a non-immunogenic disease; yet, as with several other malignancies, emerging data suggest that in most cases, the lack of immune response is functional and can be therapeutically overcome. Purpose: To provide a comprehensive review of immunotherapy as an innovative therapeutic approach for non-small cell lung cancer (NSCLC), highlighting the role of key immune mechanisms and checkpoint inhibitors. Material and Methods: The authors conducted a detailed literature review examining the immune context of NSCLC, discussing the significance of PD-1/PD-L1 and CTLA-4 checkpoints, relevant clinical trials, and emerging biomarkers like PD-L1 expression and tumor mutational burden. Findings: Immunotherapy, particularly PD-1/PD-L1 inhibitors, substantially improves survival in advanced NSCLC and can be enhanced by combination strategies. Biomarkers help identify patients most likely to benefit while guiding treatment choices.