Current Issue : October-December Volume : 2026 Issue Number : 4 Articles : 5 Articles
The organized integration of research competencies into nursing curricula is still a global challenge and is key for preparing professionals to respond to complex clinical contexts, technological advancements, and contemporary societal demands. At the School of Health of the Polytechnic Institute of Setúbal, a longitudinal research axis was implemented across the four years of the undergraduate nursing program, involving epistemological foundations, the research process, evidence-based practice, and applied practice. Objective: The objective of this study was to describe the design and implementation of the longitudinal axis of research, analyzing institutional indicators of academic success and the progressive development of students’ scientific competencies. Methods: A descriptive documentary study based on institutional data analysis (the number of enrolled students, pass rates, and mean grades in the four research-related curricular units) was conducted, complemented by a review of pedagogical materials produced (two published course booklets: “Research I—From the origin to the dissemination of knowledge” and “Research II—(De)Constructing the Research Process: A Critical and Practical Analysis”) and evidence of scientific dissemination (conference presentations and published articles). Results: A continuous progression in academic performance was observed across the research curricular units, accompanied by increased complexity of student work and enhanced scientific literacy. The sequential structure proved essential: the articulation of epistemology, methodology, critical appraisal, and scientific production demonstrated strong coherence and pedagogical efficiency. Conclusions: The longitudinal research axis constitutes a curricular innovation that strengthens essential scientific competencies in undergraduate nursing education. Longitudinal models that reflect both conceptual and practical progression can significantly contribute to the development of nurses who are critical thinkers, reflective practitioners, and capable of integrating evidence into clinical decision-making....
Background: Specialized palliative care requires nursing professionals to address the complex physical, psychological, social and spiritual needs of patients with advanced incurable illness. This study aimed to assess the perceived adequacy of formal educational preparation among nurses working in specialized palliative care services in the Republic of Croatia and examine its association with self-assessed knowledge and the perceived need for additional education. Methods: A nationwide cross-sectional survey was conducted among nursing professionals employed in specialized palliative care services across Croatia. Data were collected using a structured questionnaire assessing sociodemographic characteristics, perceived adequacy of formal education, self-assessed knowledge, as well as the need for additional education in physical, psychological, social and spiritual care domains. An Educational Suciency Discrepancy Index (ESDI) was calculated to quantify the dierence between perceived educational suciency and continuing education needs. For inferential statistics signicance was set at p < 0.05 (twotailed). Results: Among the 194 nursing professionals who participated in the study, perceived educational suciency was highest in the physical domain (87.5%), where it exceeded the reported need for additional education (31.6%). Negative discrepancies were observed in social (–12.9) and spiritual care (–17.6), indicating perceived educational deficits. Representation of physical care content in formal education was signicantly associated with higher self-assessed knowledge across several domains (physical p < 0.001; psychological p = 0.008; social p < 0.001; spiritual p = 0.008). No signicant associations were found between self-assessed knowledge and age, work experience or level of education. Conclusions: Formal nursing education alone may not fully meet the multidimensional competency requirements of specialized palliative care practice. Strengthening structured continuing professional development, particularly in psychosocial and spiritual care, may support holistic palliative care delivery and sustained professional competence....
Background/Objectives: Artificial intelligence (AI) is rapidly transforming healthcare. Its integration into community health nursing—a discipline centered on population-level prevention, health promotion, and primary care in community settings—remains insufficiently explored. This narrative review examines the opportunities, ethical challenges, and future directions for integrating AI into community health nursing education and practice. Methods: A literature search was conducted across PubMed, CINAHL, Scopus, Web of Science, and IEEE Xplore for publications between January 2017 and March 2026. The initial search yielded 612 records; after the removal of duplicates and screening of titles, abstracts, and full texts against predefined criteria, 58 sources were retained for thematic synthesis, comprising empirical studies, systematic and umbrella reviews, scoping reviews, meta-analyses, and authoritative policy documents. Screening and data extraction were performed by two reviewers, with disagreements resolved by discussion. Results: AI offers opportunities for community health nursing across four interconnected domains: clinical decision support for community-based assessments, predictive analytics for population health management, enhanced disease surveillance and outbreak detection, and personalized health education delivery. Significant challenges persist, including algorithmic bias, data privacy concerns, threats to the therapeutic nurse–client relationship, inadequate AI literacy among nursing faculty, and regulatory gaps. Most empirical evidence originates from hospital or general nursing settings; transferability to community contexts is therefore inferred rather than directly demonstrated. Conclusions: Responsible integration of AI into community health nursing requires curriculum reform, ethical governance frameworks, faculty development, equitable access, and interdisciplinary collaboration. AI should augment, not replace, the relational and culturally sensitive care that defines this discipline. Given the narrative nature of the review and the limited community-specific evidence, conclusions are framed as a vision of the AI–community health nursing interface rather than a definitive synthesis....
Accurate and reproducible chronic wound assessment remains challenging in community healthcare, where environmental variability and subjective visual evaluation may introduce substantial measurement errors. Although multi-sensor technologies, including RGB–D imaging, mobile Light Detection and Ranging (LiDAR), thermal infrared imaging, and hyperspectral sensing, as well as artificial intelligence (AI)-based analytics, have advanced considerably, real-world adoption remains limited because of workflow misalignment, insufficient interpretability, and regulatory complexity. This study presents NURSE-AI, a Nurse-by-Design methodological framework for evaluating and preparing multi-sensor, AIenabled wound assessment systems for deployment in community healthcare. NURSE-AI is proposed as a pre-implementation methodological framework supported by a feasibility study based on a synthetic dataset; therefore, it is not a clinical validation study, and no patient data were used. The framework integrates: (i) a GDPR-compliant synthetic multimodal dataset including RGB, depth, thermal, and hyperspectral-proxy layers; (ii) workflow-embedded acquisition modeling tailored to Family and Community Nurses (FCNs); (iii) a Wound Bed Preparation (WBP)-aligned interpretability layer; and (iv) a governance-by-design checklist addressing interoperability, metadata traceability, and regulatory readiness under Regulation (EU) 2017/745. A mixed-method feasibility evaluation was conducted with community nurses within AUSL Toscana Centro (Italy). The System Usability Scale (SUS) yielded a mean score of 74.5 ± 6.2, indicating good usability. Synthetic multimodal evaluation demonstrated promising segmentation performance under controlled synthetic conditions, with Intersection over Union (IoU) values ranging from 0.87 to 0.93, and simulated Intraclass Correlation Coefficient (ICC) values ≥ 0.90 for wound area estimation. Agreement between AI-generated WBP mappings and nurse interpretation ranged from κ = 0.80 to κ = 0.84. The NURSE-AI framework proposes a structured and reproducible pathway connecting sensor innovation, AI interpretability, nursing workflow integration, and regulatory preparedness, thereby providing structured groundwork for future clinical validation and scalable deployment in community healthcare....
Background/Objectives: Therapeutic communication is a core competency in mental health nursing, yet clinical placements often offer limited opportunities for undergraduate students to practise relational skills in a safe and structured way. Simulation, particularly when aligned with the Healthcare Simulation Standards of Best Practice™ (INACSL), may provide a useful context for fostering empathy, emotional presence, and professional communication. This study aimed to evaluate undergraduate nursing students’ satisfaction and self-confidence following participation in a standardised-patient simulation designed to address therapeutic relationship competencies. Methods: A descriptive cross-sectional study was conducted with 142 third-year nursing students at a public university. Participants completed two INACSL-aligned simulation encounters involving psychiatric scenarios that required therapeutic engagement. After the sessions, students completed a questionnaire based on the Student Satisfaction and Self-Confidence in Learning Scale, adapted to the context of the simulation. Data were analysed using descriptive statistics. Results: Students reported high levels of satisfaction and self-confidence following the simulation experience. Between 88.0% and 92.9% of participants agreed or strongly agreed with items related to realism, relevance, and motivation. High levels of agreement were also observed for items related to therapeutic communication, critical thinking (98.6%), clinical competence (95.8%), and teamwork (93.6%). Lower levels of agreement were found for the usefulness of video-based debriefing (61.9%) and the adequacy of material resources (57.1%), suggesting areas for improvement in future implementation. Conclusions: Standardised-patient simulation was positively evaluated by nursing students and was associated with high levels of satisfaction and self-confidence in learning. The findings suggest that this type of educational strategy may support students’ perceived development of therapeutic communication and relational skills in mental health nursing education. However, these results are based on self-reported data collected using an adapted measurement approach and should be interpreted with caution. Further research using validated instruments and performance-based measures is needed to assess competence development more directly....
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