VIA University College

This review aims to identify and synthesize existing literature on non-pharmacological interventions in cancer patients in which perceived appetite was assessed as a specific outcome, either alone or as part of broader symptom or quality-of-life measures. Systematic searches were performed using Embase, PubMed, CINAHL, and PsycINFO databases. Eligible studies included quantitative research involving adult cancer patients with poor appetite. All records were screened independently by two reviewers. A total of 3021 records were screened, and 29 studies met the inclusion criteria. These studies were grouped into four categories: mindfulness and relaxation, psychological or psychosocial, education and self-care, and multicomponent/comprehensive supportive-care programs. Interventions were heterogeneous in type, intensity, and delivery. Across categories, structured, repeated, and actively guided interventions were more consistently associated with improvements in perceived appetite, whereas brief or passive interventions showed limited effects. Interventions that incorporated personalization and required active patient engagement demonstrated greater effectiveness, suggesting the importance of sustained and individualized support. To support interpretation of these heterogeneous findings, results were synthesized using a conceptual framework linking intervention characteristics to psychological, sensory, physiological, and behavioral mechanisms influencing appetite perception. Within this framework, non-pharmacological appetite support appears to operate indirectly through pathways such as emotional regulation, sensory engagement, stress reduction, and active coping, rather than through appetite-specific mechanisms alone. Structured, actively guided, and repeated non-pharmacological interventions show potential to improve perceived appetite in cancer patients, whereas brief or passive interventions appear less effective. Findings suggest that appetite support operates primarily through indirect psychological, sensory, and behavioral pathways, as captured in a conceptual framework. Further research should develop and evaluate well-defined, mechanism-informed interventions.

In this article, we explore how national curriculum guidelines for early childhood education and care stipulate practices of early childhood education institutions in education for sustainability through a cross-cultural analysis of the latest curriculum guidelines in Norway, Denmark, China, and the United States of America (the USA). The analysis focuses on the concepts of outdoors, nature, and sustainability. Our study reveals that while outdoors is mentioned equally frequently across countries, nature is more frequently mentioned in Nordic countries and China than in the USA. Sustainability is the least mentioned across all countries, with no mention in the Chinese and American curriculum guidelines. Mentions of outdoors and nature are connected to the ecological, social and cultural, and political dimensions of sustainability, with the economic dimension rarely mentioned. Our findings also indicate that the curriculum guidelines in the four countries are anthropocentric, rather than ecocentric. We propose that the concepts of the outdoors, nature, and sustainability be more explicitly and multidimensionally integrated into these national curriculum guidelines. We also call for a shift from an anthropocentric to an ecocentric perspective in formulating national curriculum guidelines, as these guidelines serve as foundational references for local governments and early childhood education institutions when developing their local curricula.

Older patients living with frailty are particularly vulnerable to adverse outcomes during hospitalization and transitions in care. Comprehensive Geriatric Assessment (CGA) has been shown to improve outcomes for these patients. To address the increasing demand for geriatric methodology and improve care quality, the nationwide quality database DANFRAIL was established with a cross-sectoral and interdisciplinary focus, first of its kind worldwide. DANFRAIL aims to monitor and enhance quality of care for older patients with frailty across healthcare settings in Denmark. Thus, development involved a co-creation process with expert clinicians and patient representatives from all sectors, guided by a specialist team from the Danish Healthcare Quality Institute. The indicator set, derived from CGA domains, was refined through consensus meetings and public consultation. The initial indicator set includes 6 process indicators and 2 result indicators, focusing on key aspects of care for older patients living with frailty. The public consultation revealed concerns about implementation, workload, registration requirements, and data integration across sectors. Adjustments were made to address these issues and ensure the feasibility of data collection and use. DANFRAIL represents a significant step towards improving the quality of care for older patients living with frailty in Denmark. Grounded in the principles of CGA, the database offers a structured, data-driven framework to monitor and enhance care delivery across sectors. By supporting continuous quality improvement and better health outcomes, DANFRAIL sets a national standard for caring for older people in vulnerable situations and may serve as an exemplary approach for international adoption.

Introduction:Vulnerability is a fundamental human condition shaped by existential interdependence and social structures. In nursing, it is experienced by both patients and nurses, influenced by care relationships, institutional norms, and ethical responsibilities. This review explores how the phenomenon of vulnerability is reflected in the research literature on nursing clinical practice, from both patient and nurse perspectives. Methods:A qualitative literature search of eight bibliographic databases (inception to 13 May 2025) identified 29 papers, assessed using the Critical Appraisal Skills Programme Qualitative Checklist (CASP-QC). Data were analysed through qualitative content analysis inspired by Graneheim, Lundman and Lindgren. Results:Socioeconomic and sociopolitical conditions shape vulnerability by influencing care needs and perceptions of healthcare and nursing. Physical changes that compromise bodily autonomy expose patients to undignified care, as loss of control over one's body can lead to embarrassment, shame, and diminished dignity. A lack of holistic care increases patient vulnerability when professionals fail to recognise patients as unique individuals. Nurses' vulnerability is portrayed as a significant burden, shaped by personal suffering, grief, and contextual work factors. This suffering may result in emotional distancing from patients when nurses lack the courage to engage. Conclusion:Vulnerability is multifaceted, shaped by personal, relational, and sociopolitical conditions. Patients often experience vulnerability through lack of recognition of individuality and dignity, while nurses face emotional strain, knowledge gaps, ethical tensions and limited support. Vulnerability can also be viewed as a strength, fostering ethical sensitivity, moral courage and deeper nurse-patient relationships.

INTRODUCTION:Accurate positioning in lateral knee radiographs is essential for diagnostic quality but prone to inter-observer variability. Artificial intelligence (AI) may standardize quality assessment, yet its influence on radiographers' critical reasoning and decisions is unclear. The purpose of this study was to externally validate a pre-trained hybrid convolutional neural network for assessing femoral condyle alignment and to evaluate its effect on radiographers' classification performance. METHODS:A previously developed AI model (Xception architecture, area under the curve [AUC] = 0.97) was applied to 400 consecutive weight-bearing lateral knee radiographs. Nine clinical diagnostic radiographers from three different institutions independently classified images as accepted or rejected according to predefined positioning criteria, first without AI support and again after a one-month wash-out period with AI assistance consisting of color-coded feedback (green = accepted, red = rejected). Reader performance was compared with a consensus reference using Chi-square tests, diagnostic accuracy measures, fixed-effects meta-analysis, and intra-/inter-reader intraclass correlation coefficients (ICC). RESULTS:According to the reference standard, 77.7 % of images were acceptable. The AI alone achieved 78.4 % accuracy (sensitivity 52.3 %, specificity 85.8 %). Across readers, AI support increased accepted classifications from 73.4 % to 77.2 % (P < 0.001) and correct classifications from 84.5 % to 89.8 % (P < 0.001). Sensitivity decreased while specificity increased with the use of AI. Inter-reader agreement improved from ICC 0.52 to 0.59. CONCLUSION:AI decision support modestly improved accuracy and specificity but did not override professional judgment and clinical reasoning. Radiographers maintained independent decision-making, demonstrating that experienced clinical practitioners were not overruled by AI despite real-time feedback. IMPLICATION FOR PRACTICE:AI decision support can enhance radiographic quality assessment consistency while preserving radiographers' independent clinical judgment.