Search Results (60)

African, Caribbean, and Black (ACB) communities face increased COVID-19 morbidity and mortality, coupled with significant barriers to vaccine acceptance and uptake. Addressing these challenges requires innovative, multifaceted strategies. Peer-led interventions, grounded in critical health literacy (CHL) and critical racial literacy (CRL), and integrating collaborative equity learning processes, can enhance community capacity, empowerment, and health outcomes, contributing to long-term health equity. This paper describes and presents the evaluative outcomes of a peer-led intervention aimed at enhancing COVID-19 vaccine confidence and acceptance. The Peer-Equity Navigator (PEN) intervention consisted of a specialized training curriculum grounded in CHL and CRL. Following training, PENs undertook a 5-month practicum in community or health settings, engaging in diverse outreach and educational activities to promote vaccine literacy in ACB communities. The evaluation utilized a modified Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) Framework, using quantitative and qualitative methods to collect data. Sources of data included tracking records with community feedback, and a PEN focus group, to assess program feasibility, outreach, and effectiveness. From 16 September 2022, to 28 January 2023, eight trained PENs conducted 56+ community events, reaching over 1500 community members. Both PENs and community members reported high engagement, endorsing peer-led, community-based approaches and increased vaccine literacy. The PEN approach proves feasible, acceptable, and effective in promoting positive health behaviors among ACB communities. This intervention has clear implications for health promotion practice, policy, and research in equity-deserving communities, including immigrants and refugees, who also face multiple and intersecting barriers to health information and care. Full article

Background/Objectives: Single-dose pre-operative antibiotic prophylaxis for cardiac-device implantation is recommended but extending antibiotic prophylaxis is common. Locally, 50–60% of patients had extended prophylaxis after pacemaker insertion or generator change. Our antimicrobial stewardship programme (ASP) incorporated behavioural change strategies in implementing a multi-pronged intervention bundle to address this and evaluated its effectiveness and safety. Methods: This single-centre, retrospective cohort study included patients aged 21 years old or older, undergoing uncomplicated pacemaker insertion or generator change at Singapore General Hospital (SGH) from October 2022 to March 2025. To improve antibiotic use, ASP interventions incorporating behaviour change strategies were implemented, namely (1) data-driven feedback, (2) targeted education, (3) identification and engagement of ASP champion, and (4) clinical pathway revision. Results: There were 779 patients evaluated; 380 (48.8%) received standard prophylaxis while 399 (51.2%) received extended prophylaxis with oral antibiotics (mean duration, 3.3 ± 0.8 days). Following ASP interventions, the practice of extended prophylaxis declined significantly from 43.8% to 24.0% (p < 0.01). The incidence of surgical site infections was low and similar in both groups (0.8%, p = 1.000); all infections were superficial. There was also significant reduction in the proportion of patients on all antibiotics from 20.7% to 16.3% (p < 0.01). Identification and engagement of ASP champion proved pivotal in changing prescribing behaviour through peer influence and credibility. Conclusions: The bundled ASP interventions, incorporating behavioural change strategies, have effectively and safely reduced the use of extended prophylaxis post-cardiac device implantation. Behavioural change interventions are essential to achieve sustained stewardship success. Full article

Higher Degree by Research (HDR) students in language and education disciplines, particularly those enrolled in thesis-only programmes, are increasingly expected to interpret complex statistical data. However, many lack the analytical skills required for independent statistical analysis, posing challenges to their research competence. This study investigated the pedagogical potential of ChatGPT-4o feedback and peer feedback in supporting students’ evaluative judgement during a 14-week doctoral-level statistical analysis course at a research-intensive university. Thirty-two doctoral students were assigned to receive either ChatGPT feedback or peer feedback on a mid-term assignment. They were then required to complete written reflections. Follow-up interviews with six selected participants revealed that each feedback modality influenced their evaluative judgement differently across three dimensions: hard (accuracy-based), soft (value-based), and dynamic (process-based). While ChatGPT provided timely and detailed guidance, it offered limited support for students’ confidence in verifying accuracy. Peer feedback promoted critical reflection and collaboration but varied in quality. We therefore argue that strategically combining ChatGPT feedback and peer feedback may better support novice researchers in developing statistical competence in hybrid human–AI learning environments. Full article

Background/Objectives: Clinical incivility is a persistent issue in nursing education and practice, with negative impacts on students, educators, and clinicians. Uncivil behaviors—such as belittling, exclusion, and dismissiveness—compromise communication, teamwork, and patient safety. Although various interventions have been implemented, their effectiveness remains inconsistent. This systematic review aimed to evaluate the effectiveness of interventions addressing clinical incivility in nursing and to identify common trends, gaps, and implications for future practice and research. Methods: Following PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Web of Science, and EBSCOhost (CINAHL) for peer-reviewed empirical studies published between 2014 and 2024. Search terms included “clinical incivility” and (“intervention” or “program” or “training”) and “nursing”. Studies were eligible if they evaluated interventions aimed at reducing incivility among nursing students, faculty, or practicing nurses. Seventeen studies met the inclusion criteria and were analyzed for intervention types, target populations, delivery methods, and outcomes. Results: The review identified five main intervention types: educational modules (n = 9), cognitive rehearsal (n = 5), simulation and role-play (n = 5), team-based strategies (n = 3), and feedback/communication strategies (n = 2). Many studies used multiple strategies. Fourteen studies reported positive outcomes such as improved awareness, communication, and self-efficacy. Eight studies demonstrated statistically significant reductions in perceived incivility, particularly those with simulation-based, multi-session, or institutionally supported formats. Three studies showed limited or mixed results due to insufficient follow-up or lack of leadership engagement. Conclusions: Experiential and multi-component interventions appear effective in reducing clinical incivility. Long-term success requires leadership engagement, institutional support, and integration into ongoing professional development. Full article

Recent advances in large language models (LLMs) have triggered rapid growth in AI-powered educational agents, yet researchers and practitioners still lack a consolidated view of how these systems are engineered and validated. To address this gap, we conducted a systematic literature review of 82 peer-reviewed and industry studies published from January 2023 to February 2025. Using a four-phase protocol, we extracted and coded them along six groups: technical and pedagogical frameworks, tutoring systems, assessment and feedback, curriculum design, personalization, and ethical considerations. Synthesizing these findings, we propose design principles that link technical choices to instructional goals and outline safeguards for privacy, fairness, and academic integrity. Across all domains, the evidence converges on a key insight: hybrid human–AI workflows, in which teachers curate and moderate LLM output, outperform fully autonomous tutors by combining scalable automation with pedagogical expertise. Limitations in the current literature, including short study horizons, small-sample experiments, and a bias toward positive findings, temper the generalizability of reported gains, highlighting the need for rigorous, long-term evaluations. Full article

Evaluation in education is a complex and multifaceted process, linked to teaching and planning. It represents a powerful tool for regulating behaviors, refining actions, and adapting educational interventions to the specific context in which they are implemented. In this evaluation framework, the work aims to highlight the educational value of assessment, considered a moment in which both the teacher and the student are involved in the teaching-learning process. In particular, formative assessment allows you to find essential information to understand the progress of the actions implemented, highlighting strengths and weaknesses to intervene in educational planning. In this sense, it becomes a valid support for both teachers and students as it allows them to monitor the progress of the teaching/learning process. The work is divided into two parts: the first is theoretical, in which the transition from the assessment of learning (summative) to the assessment for learning (formative) is presented; the second is focused on formative assessment and feedback practices. From a methodological perspective, the literature review emphasizes the potential of assessment that involves students both as recipients and active participants through peer assessment. The paper highlights potential and challenges aimed at improving and experimenting with ways to enhance evaluation competence, which prepares students for professional life. Full article

The advent of generative artificial intelligence (GenAI) has significantly transformed the educational landscape. While GenAI offers benefits such as convenient access to learning resources, it also introduces potential risks. This study explores the phenomenon of learning burnout among university students resulting from the misuse of GenAI in this context. A questionnaire was designed to assess five key dimensions: information overload and cognitive load, overdependence on technology, limitations of personalized learning, shifts in the role of educators, and declining motivation. Data were collected from 143 students across various majors at Shandong Institute of Petroleum and Chemical Technology in China. In response to the issues identified in the survey, the study proposes several teaching strategies, including cheating detection, peer learning and evaluation, and anonymous feedback mechanisms, which were tested through experimental teaching interventions. The results showed positive outcomes, with students who participated in these strategies demonstrating improved academic performance. Additionally, two rounds of surveys indicated that students’ acceptance of additional learning tasks increased over time. This research enhances our understanding of the complex relationship between GenAI and learning burnout, offering valuable insights for educators, policymakers, and researchers on how to effectively integrate GenAI into education while mitigating its negative impacts and fostering healthier learning environments. The dataset, including detailed survey questions and results, is available for download on GitHub. Full article

Measures of sexual orientation and family functioning are widely used among sexual minority populations. However, data on whether these measures are culturally syntonic and responsive to the needs of a particular population, such as Hispanic sexual minority youth (HSMY), are lacking. Therefore, this study assessed whether HSMY understand measures of sexual orientation and family functioning as intended. Authors conducted individual interviews with five HSMY to evaluate the face validity of a measure of sexual orientation (i.e., Klein Sexual Orientation Grid) and measures of family functioning (i.e., Parent–Adolescent Communication Scale, Parenting Practices Scale, Parental Monitoring of Peers). Data were analyzed using a general inductive approach. For the sexual orientation measure, five themes were identified related to the: (1) clarity of questions, (2) challenging nature of questions, (3) difficulty of responses, (4) suggestions to improve response options, and (5) need for questions to include gender identity. For family functioning, three themes were identified: (1) relevance of the measures to sexual minority youth, (2) the importance of understanding family history and cultural context, and (3) capturing the context of how sexual minority status and disclosure impact family functioning. HSMY had generally positive feedback regarding these measures; however, they also suggested specific changes associated with wording and specificity of the measures to make them more relevant to HSMY’s unique needs. Full article

As security issues in vehicular networks continue to intensify, ensuring the trustworthiness of message exchanges among vehicles, infrastructure, and cloud platforms has become increasingly critical. Although trust authentication serves as a fundamental solution to this challenge, existing models fail to effectively address the specific requirements of vehicular networks, particularly in defending against malicious evaluations. This paper proposes a novel multidimensional trust evaluation framework that integrates both static and dynamic metrics. To tackle the issue of malicious ratings in peer assessments, a rating reversal mechanism based on K-means clustering is designed to effectively identify and correct abnormal trust feedback. In addition, the framework incorporates an entropy-based trust weight allocation mechanism and a time decay model to enhance adaptability in dynamic environments. The simulation results demonstrate that, compared with traditional approaches, the proposed scheme improves the average successful information rate by 12% and reduces the false positive rate to 6.1%, confirming its superior performance in securing communications within the vehicular network ecosystem. Full article

Laboratory medicine is crucial for clinical decision-making, yet result interpretation often remains challenging for patients. This study evaluates the effectiveness of an Artificial Intelligence (AI)-powered conversational system in interpreting laboratory test results, utilizing a closed-box training approach for a Claude-based virtual chatbot focused exclusively on laboratory data interpretation without clinical diagnosis. The system was tested using 100 laboratory reports from three Italian laboratories, encompassing diverse biochemical parameters and measurement standards. The laboratories employed different analytical platforms and methodologies, enabling evaluation of the chatbot’s ability to interpret results across varied instrumental settings. The interpretation accuracy was rigorously assessed through peer review by three independent medical experts with extensive laboratory medicine experience. The Claude model demonstrated complete accuracy with zero hallucinations, attributed to the controlled training environment, domain-specific prompts, and pure generation mechanisms without external data access. Patient feedback from 70 participants showed high satisfaction rates, with 90% providing positive ratings. This study demonstrates that carefully designed AI models can effectively bridge the gap between raw laboratory data and patient understanding, potentially transforming laboratory reporting systems while maintaining high accuracy and avoiding diagnostic territory. These findings have significant implications for patient empowerment and healthcare communication efficiency. Full article

This paper proposes a new approach to integrating Q learning into the fuzzy linear programming (FLP) paradigm to improve peer selection in P2P networks. Using Q learning, the proposed method employs real-time feedback to adjust and update peer selection policies. The FLP framework enriches this process by dealing with imprecise information through fuzzy logic. It is used to achieve multiple objectives, such as enhancing the throughput rate, reducing the delay, and guaranteeing a reliable connection. This integration effectively solves the problem of network uncertainty, making the network configuration more stable and flexible. It is also important to note that throughout the use of the Q-learning agent in the network, various state metric indicators, including available bandwidth, latency, packet drop rates, and connectivity of nodes, are observed and recorded. It then selects actions by choosing optimal peers for each node and updating a Q table that defines states and actions based on these performance indices. This reward system guides the agent’s learning, refining its peer selection policy over time. The FLP framework supports the Q-learning agent by providing optimized solutions that balance conflicting objectives under uncertain conditions. Fuzzy parameters capture variability in network metrics, and the FLP model solves a fuzzy linear programming problem, offering guidelines for the Q-learning agent’s decisions. The proposed method is evaluated under different experimental settings to reveal its effectiveness. The Erdos–Renyi model simulation is used, and it shows that throughput increased by 21% and latency decreased by 40%. The computational efficiency was also notably improved, with computation times diminishing by up to five orders of magnitude compared to traditional methods. Full article

Acknowledgement of the importance of students interacting with faculty in a social context has prompted the development of Learning Communities (LCs) in many medical schools. Understanding successful LC and fruitful mentor–mentee relationships is essential to recognize the perspective of multiple stakeholders, i.e., both mentors and mentees. This study used inductive qualitative analysis methods to compare the key attributes and competencies of mentors that are most important to mentors with those most important to mentees in LCs. Six mentor focus groups (N = 50) and four mentee focus groups (N = 22) were conducted. Thematic analysis revealed twelve distinct themes. Three were categorized as mentor/mentee similarities: (1a) individualized approach, (1b) history and physical skills, and (1c) group interaction. Three were categorized as mentor/mentee differences: (2a) teaching versus relationship competence, (2b) mentor as a relatable figure, and (2c) faculty development. Four themes were unique to mentees: (3a) cultural competence and role modeling, (3b) feedback to students, (3c) one-on-one sessions, and (3d) clinical pearls, and two themes were unique to mentors: (4a) communication and (4b) peer development. Formative evaluation is needed to recognize new styles of learning preferences and new forms of feedback. Awareness of the similarities and differences in the perspectives of mentors and mentees can inform modifications to LCs that can potentially improve the experience of both mentors and mentees. Full article

Background: Interdialytic weight gain (IDWG), defined as the accumulation of salt and water intake between dialysis sessions, is a critical parameter of fluid management and a marker of adherence to dietary and fluid restrictions in hemodialysis patients. Excessive IDWG has been strongly associated with increased cardiovascular risk, including left ventricular hypertrophy, cardiac dysfunction, and cerebrovascular complications. Additionally, it necessitates more aggressive ultrafiltration, potentially compromising hemodynamic stability, impairing quality of life, and escalating healthcare costs. Despite international guidelines recommending an IDWG target of <4–4.5% of body weight, many patients struggle to achieve this due to barriers in adhering to dietary and fluid restrictions. This review explores the current state-of-the-art strategies to mitigate IDWG and evaluates emerging diagnostic and therapeutic perspectives to improve fluid management in dialysis patients. Methods: A literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science to identify studies on IDWG in hemodialysis. Keywords and MeSH terms were used to retrieve peer-reviewed articles, observational studies, RCTs, meta-analyses, and systematic reviews. Non-English articles, case reports, and conference abstracts were excluded. Study selection followed PRISMA guidelines, with independent screening of titles, abstracts, and full texts. Data extraction focused on IDWG definitions, risk factors, clinical outcomes, and management strategies. Due to study heterogeneity, a narrative synthesis was performed. Relevant data were synthesized thematically to evaluate both established strategies and emerging perspectives. Results: The current literature identifies three principal strategies for IDWG control: cognitive–behavioral interventions, dietary sodium restriction, and dialysis prescription adjustments. While educational programs and behavioral counseling improve adherence, their long-term effectiveness remains constrained by patient compliance and logistical challenges. Similarly, low-sodium diets, despite reducing thirst, face barriers to adherence and potential nutritional concerns. Adjustments in dialysate sodium concentration have yielded conflicting results, with concerns regarding hemodynamic instability and intradialytic hypotension. Given these limitations, alternative approaches are emerging. Thirst modulation strategies, including chewing gum to stimulate salivation and acupuncture for autonomic regulation, offer potential benefits in reducing excessive fluid intake. Additionally, technological innovations, such as mobile applications and telemonitoring, enhance self-management by providing real-time feedback on fluid intake. Biofeedback-driven dialysis systems enable dynamic ultrafiltration adjustments, improving fluid removal efficiency while minimizing hemodynamic instability. Artificial intelligence (AI) is advancing predictive analytics by integrating wearable bioimpedance sensors and dialysis data to anticipate fluid overload and refine individualized dialysis prescriptions, driving precision-based volume management. Finally, optimizing dialysis frequency and duration has shown promise in achieving better fluid balance and cardiovascular stability, suggesting that a personalized, multimodal approach is essential for effective IDWG management. Conclusions: Despite decades of research, IDWG remains a persistent challenge in hemodialysis, requiring a multifaceted, patient-centered approach. While traditional interventions provide partial solutions, integrating thirst modulation strategies, real-time monitoring, biofeedback dialysis adjustments, and AI-driven predictive tools represent the next frontier in fluid management. Future research should focus on long-term feasibility, patient adherence, and clinical efficacy, ensuring these innovations translate into tangible improvements in quality of life and cardiovascular health for dialysis patients. Full article

In a media-saturated online ecosystem, educational technology that fosters virtual interactions and learning opportunities, unlike those taking place face-to-face, has to bear special characteristics that facilitate the way we build our connection with others or access, consume, and produce new information. The present study focuses on the design and implementation of a rubric for the peer assessment of collaborative educational Virtual Reality (VR) environments that were built with the aim to provide immersive-triggered meaningful learning instances. It presents the methodology employed to create the tool, its use in peer evaluation processes, and the implementation findings. The stages of the methodology employed involve the review of existing tools, the rationale lying in the creation of the certain tool, and the recruitment of educators and/or trainers to pilot test it. To this end, there was a purposeful recruitment of participants of a postgraduate program in immersive technologies, with diverse demographics and from different disciplines, who were invited to work collaboratively, in pairs or groups of three, with the intent to design and develop an educational intervention of their choice in Spatial.io software. The stages of the methodology further involved microteaching sessions with other groups, peer evaluation based on the quality criteria provided, and self-reflection and evaluation of their educational interventions. The study outcomes revealed (i) the key evaluation criteria that proved to be critical for the design of quality immersive experiences, (ii) the usefulness of the rubric created to facilitate the pilot testing of the prototypes, and (iii) challenges and benefits that arise from peer evaluation practices. In the context of interdisciplinary, diverse age and professional experience demographics peer evaluation, digital, content, and pedagogical concerns arose providing fruitful feedback to their peers for the refinement of the design of their VR environments. Challenges and recommendations of the peer review processes are also discussed. Full article

Background/Objectives: The use of simulated learning as a teaching approach has been used and embedded in nursing theoretical curriculum for many years. There is a wealth of evidence to support the positive impact simulated learning or simulated-based education can have on the student experience, developing skill competency and enhancing patient outcomes. However, the evidence on the use of simulation as a replacement for clinical practice learning in undergraduate nursing education is limited. In response to the challenges posed by the COVID-19 pandemic, the authors introduced virtual simulated practice learning experiences (SPLE) for a cohort of year one pre-registration adult and mental health nursing students. The SPLE project aimed to assess the effectiveness of simulated practice learning as a viable alternative to traditional clinical practice learning and to explore student satisfaction with the new practice learning experience approach. Methods: All year one student nurses attending the four simulated practice learning experience (SPLE) weeks were invited to participate and complete a generated questionnaire within the virtual practice environment on their final day of each SPLE week. The questionnaire employed a mix of both quantitative and qualitative questions across key areas to evaluate the effectiveness of the SPLE and explore student satisfaction with their overall practice learning experience. Results: A total of 216 students participated in the simulated practice learning weeks across the spring semester in 2023 with a response rate of 98–100% across all four SPLE weeks. Students reported an overall satisfaction score of 88%, highlighting their preparedness and positive feedback on the organisation, delivery, and content of the SPLE. Qualitative analysis revealed key themes, including the development of transferable skills and personal growth, the value of peer learning, the benefits of a virtual environment, and appreciation of service user and healthcare professional input. Students reported significant personal growth, improved communication skills, and a deeper understanding of holistic care through interactive and collaborative learning experiences. Conclusions: This evaluation underscores the innovative potential of simulated practice learning to enhance nursing practice education, emphasising the importance of integrating emerging technologies and diverse pedagogical approaches. The findings suggest that SPLEs can effectively prepare nursing students for the complexities of clinical practice while addressing the evolving demands of healthcare. Future research should focus on longitudinal studies to assess the sustained impact of simulated learning on clinical experiences and professional development. Full article