Search Results (636)

The evolving digital landscape, including artificial intelligence (AI) and its generative forms, is changing how younger generations learn. As students utilize generative AI systems, they cultivate trust in such technology to support their current and long-term learning. The objective of this study was to investigate the relationship between generative AI use among students in health professions and their trust in this technology to support their lifelong learning as future health professionals. This study employed a survey methodology using a cross-sectional study design. The survey included sociodemographic variables and questions regarding students’ generative AI use and their trust in this technology to support their lifelong learning. Descriptive and inferential statistical procedures were used to analyze the data. A total of 558 students representing various health professions responded to the survey. In the regression analysis, after controlling for student’s sex and location variables, greater generative AI use was associated with students’ increased trust in this technology to support their lifelong learning (beta = 0.58, p < 0.001), explaining close to 40% of the total variance. Given the rapidly evolving digital landscape, this finding warrants further study, with implications for training of the future health workforce. Full article

Lean Construction has become a key strategy for improving productivity, reducing waste, and increasing efficiency in civil engineering projects. In parallel, advances in digital technologies have transformed the way engineering design and project planning processes are conceived and managed. However, there remains a limited systematic understanding of how emerging technologies support engineering design practices and influence the implementation and performance of Lean Construction in diverse civil engineering scenarios. This study presents a systematic literature review of 70 peer-reviewed articles published between 2019 and 2025, following the PRISMA 2020 guidelines. The selected studies were examined using a structured classification framework consisting of three analytical categories: Technologies and Tools, Construction Methods and Sustainability, and Production Philosophies and Management. From an engineering design perspective, this framework allows the identification of technological trends, design-support tools, and management strategies that influence the planning, modeling, and optimization of construction processes. The results show that digital technologies, such as Building Information Modeling (BIM), automation systems, Artificial Intelligence, and Industry 4.0 tools, play a significant role in supporting engineering design activities by improving project visualization, coordination, and decision-making during the design and planning stages. These technologies contribute to more integrated design processes aligned with Lean Construction principles. At the same time, the analysis reveals that the adoption of Lean Construction technologies varies depending on project characteristics, levels of digital maturity, and regional industry conditions. The main barriers identified in the literature include interoperability limitations, insufficient workforce training, and organizational resistance to technological change. Overall, the review provides a structured synthesis of recent research trends and highlights the technological and managerial factors that influence the successful integration of Lean Construction with engineering design practices in civil engineering. The findings contribute to bridging the gap between technological innovation, design methodologies, and Lean Construction implementation, offering insights for both researchers and practitioners seeking to improve efficiency, sustainability, and design performance in construction projects. Full article

This study provides a practical and replicable improvement model for productivity and inspection reliability improvement in resource-constrained food logistics environments. This study presents an engineering-based optimization of productivity and process reliability in an agro-industrial post-harvest processing system for canned young green jackfruit using an integrated Define–Measure–Analyze–Improve–Control (DMAIC) and Failure Mode and Effects Analysis (FMEA) framework. The case-study production system experienced high raw-material loss, prolonged blanching cycles, and low inter-operator inspection agreement, which reduced process yield and logistics throughput. Root causes were identified through process mapping and fishbone analysis and prioritized using FMEA Risk Priority Number (RPN) scoring. Key improvement actions included optimizing blanching time, standardizing supplier grading to reduce material variability, and strengthening inspection decisions through Attribute Gage Repeatability and Reproducibility (Gage R&R)-based training and criteria alignment. After implementation, productivity increased by 2.31%, raw-material loss decreased by 1.90%, and inter-operator inspection agreement improved by 16%, exceeding the benchmark. Blanching time was reduced from 3 to 1 min at ≥90 °C, shortening cycle time by 67% and generating an estimated annual cost saving of USD 7200 without major capital investment. The results demonstrate that structured, risk-based improvement combined with validated measurement systems can enhance workforce consistency, process stability, and logistics flow efficiency in agro-industrial food processing environments, providing a replicable improvement model for agro-industrial processing small and medium-sized enterprises (SMEs). Full article

Care home staff are routinely exposed to stressful and traumatic events, increasing risks of psychological distress, burnout, and reduced workforce resilience. Psychological First Aid (PFA), recommended by the World Health Organization, provides an evidence-based framework for delivering immediate emotional and practical support; however, its adaptation for care home contexts is limited. This study aimed to co-produce and adapt an existing PFA training resource for care home staff using a person-based approach (PBA) to enhance contextual relevance, acceptability, and feasibility. A two-phase qualitative design guided by PBA principles was used. Phase 1 integrated stakeholder workshops, semi-structured interviews, and literature review to generate guiding principles, a logic model, and preliminary training content. We adapted the WHO PFA “Look–Listen–Link” framework alongside existing open-access materials. Phase 2 used think aloud interviews to optimize usability and contextual fit. Thematic and sentiment analysis identified key needs: high exposure to traumatic events, inconsistent organisational support, desire for measurable skill development, the importance of transferable competencies, and motivational factors. Participants emphasized the need for flexibility, inclusivity, and realistic care-home-specific examples. Adaptations included bite-sized interactive modules, blended delivery options, and reflective exercises. The final co-produced intervention aligns with trauma-informed principles and organisational realities. Further work is needed to access feasibility, acceptability, and fidelity in real-world settings, offering a transferable model for adapting psychological interventions in other high-stress care environments internationally. Full article

Background: Mental health needs are rising globally, while workforce shortages constrain access to timely care. Israel launched formal training for Psychiatric–Mental Health Nurse Practitioners (PMHNPs) in 2023 as part of broader efforts to strengthen the public mental health system. This narrative review provides a focused synthesis of international and Israeli literature on PMHNP roles, models of practice, outcomes, and implementation considerations relevant to the Israeli context. Methods: We conducted a narrative, non-systematic literature review of international and Israeli literature on Psychiatric–Mental Health Nurse Practitioners (PMHNPs). Searches were conducted in PubMed/MEDLINE, CINAHL, PsycINFO, and Scopus (January 2000–December 2024), alongside targeted policy and regulatory documents. Eligible sources addressed NP/PMHNP roles, scope of practice, clinical and service outcomes, implementation processes, workforce implications, or policy considerations in high-income health systems. Findings were synthesized thematically. Results: Across the reviewed literature, particularly in primary care and community-based settings, PMHNP/NP-delivered care was generally associated with comparable outcomes on selected quality and safety indicators, alongside improved accessibility, continuity, and high patient satisfaction. Successful implementation depended on regulatory clarity, organizational readiness, interprofessional collaboration, and the development of a clear professional identity. In Israel, the role is emerging within a cautious regulatory framework and may face early barriers related to role ambiguity, variable organizational support, and limited stakeholder awareness. Conclusions: PMHNP implementation may offer an important strategy for strengthening mental health service capacity in Israel. However, the extent of its contribution will depend on regulatory clarity, organizational support, implementation quality, and future empirical evaluation in the Israeli context. Full article

The global shortage of qualified cybersecurity professionals continues to intensify, underscoring the need for targeted and practice-oriented education and training. This study examines and compares the cybersecurity competencies emphasized in higher education with those prioritized by employers. The findings reveal notable discrepancies between academic and industry expectations. Employers, particularly larger organizations, assign the greatest importance to competencies related to organizational and human security, whereas higher education institutions tend to prioritize technical cybersecurity domains. These insights provide a foundation for designing more comprehensive and industry-aligned cybersecurity curricula and can support the development of educational pathways tailored to specific learner groups and workforce needs. Full article

Background: Artificial intelligence (AI) is poised to fundamentally reshape healthcare delivery, offering unprecedented advancements in diagnostics, treatment personalization, and operational efficiency. However, a growing body of international research reveals a critical “optimism–knowledge gap”: healthcare professionals are enthusiastic about AI’s potential but possess limited technical knowledge and practical experience. This gap compromises the safe and effective implementation of AI tools. The Italian healthcare context presents a unique and amplifying challenge, as it is defined by the stringent “human-in-the-loop” oversight mandated by the Garante per la protezione dei dati personali (Italy’s Data Protection Authority). This legal framework makes clinician competence not just a goal, but a prerequisite for regulatory compliance. Objective: This study aimed to provide an exploratory quantitative assessment of AI awareness, practical application, and understanding of its limitations among a sample of clinicians in Italy. It specifically sought to compare the preparedness of hospital-based clinicians and general practitioners (GPs) and to identify the workforce’s perceived educational needs within this unique legal environment. Methods: A descriptive, cross-sectional survey was conducted from February to August 2025. Using a non-probability convenience sampling method via professional networks, the survey yielded 362 total responses. Data were analyzed descriptively and inferentially using Chi-square (${\chi }^2$) tests to compare cohort responses on familiarity, practical exposure, knowledge of limitations, and interest in further training. Results: A universal and high demand for education was found, with 89.9% of all respondents being “Moderately” or “Very” interested in learning more about AI. This optimism coexists with dangerously low practical exposure. The gap was most profound among GPs, 44.1% of whom have “Never” used an AI tool—a rate significantly higher than hospital clinicians (34.9%; ${\chi }^2=3.14$, p = 0.045). Furthermore, 32.6% of GPs admitted that they “understand some benefits but not the limitations.” Conclusions: Italian clinicians mirror the global optimism–knowledge gap. These findings underscore the urgent need for structured, continuous education in AI literacy to address ethical and regulatory imperatives within the Italian healthcare system. Full article

Purpose: This study examines (1) the change in partnership between local health departments (LHDs) and schools of public health or public health programs (SPHs/PHPs) from 2016 to 2019, and (2) the LHD characteristics associated with this partnership. Background: The Council on Education for Public Health updated accreditation criteria in 2016, shifting from core curricula to competencies to better prepare public health graduates for the workforce. Strong partnerships between LHDs and SPHs/PHPs can enhance practical training and employment opportunities for students, ultimately bolstering the public health workforce. Methods: We analyzed the 2016 and 2019 National Profiles of Local Health Departments, using descriptive statistics to evaluate partnership levels and multivariable logistic regression to identify LHD characteristics associated with collaboration. Results: The partnership between LHDs and SPHs/PHPs was suboptimal and unevenly distributed. Engagement in activities like formal training agreements and advisory roles declined. Notably, the presence of formal written agreements for staff training and active recruitment of SPH/PHP graduates by LHDs showed significant improvements (χ² = 3.84; p = 0.049; χ² = 8.19; p = 0.004). Factors such as top executive characteristics, workforce capacity, and governance context influenced these partnerships. Conclusions: The study identifies gaps in LHD engagement with SPHs/PHPs and highlights opportunities for advocacy. Addressing these gaps can lead to a more competent workforce, thereby benefiting both LHDs and SPHs/PHPs in their service to communities. Full article

HRC is increasingly adopted in industrial and logistics environments, while workforce preparation often remains constrained by instructional approaches that provide limited embodied understanding of safety and ergonomics. This study examines the architectural design and system integration of a modular, human-centred XR platform intended to support safe and ergonomics-aware collaboration within smart logistics contexts. The proposed system integrates XR training scenarios deployed on consumer-grade hardware and follows a structured pedagogical progression from conceptual familiarisation through experiential task execution to reflective ergonomic evaluation. Multimodal feedback mechanisms based on posture-oriented guidance, attention-aware interaction design, and context-sensitive safety cues are incorporated without reliance on intrusive sensing technologies. A structured evaluation framework is defined to examine usability, task performance, and ergonomics-aligned posture indicators using standardised instruments and system-generated telemetry. The architectural design indicates that the framework supports scalable deployment, consistent interaction fidelity, and privacy-conscious data handling across educational and vocational settings. The proposed framework suggests that human-centred XR architectures can strengthen safety-oriented and ergonomically informed HRC within Industry 4.0 logistics environments. Full article

The growing complexity and interdependence of critical infrastructures (CIs), increasingly exposed to natural and technological hazards, call for educational approaches to enhance resilience and risk management. This study examines trends, patterns, and challenges in integrating digital and immersive technologies into education and training for stakeholders in critical infrastructure management. A systematic review of peer-reviewed literature was conducted using Scopus as the primary source, covering the last decade and analyzing the corpus across six dimensions: technological approach, pedagogical model, hazard typology, infrastructure domain, stakeholder category, and implementation phase. Following the PRISMA framework, 5635 records were identified and screened through a multistage process combining rule-based filtering and manual review, resulting in 105 papers meeting the inclusion criteria. The analysis reveals a shift from classroom instruction and physical drills toward immersive, simulation-based, and data-informed learning ecosystems that strengthen situational awareness, procedural accuracy, and decision-making under stress. However, the review identifies persistent gaps in evaluation metrics, cross-sector frameworks, and collaborative learning environments that limit adoption. The findings underscore that digital and immersive technologies can reconfigure education and training frameworks, enabling the formation of Resilient Operators endowed with adaptive cognition, continuous learning capacities, and responsiveness to natural hazard-induced technological risks. Full article

The European Green Deal is Europe’s ambitious and multi-layered response to climate change. Translating its objectives into action for a green transition has created a need for new skills and competencies. Vocational and Education Training (VET) systems are uniquely positioned to equip learners with these emerging green and transversal competences through their dual focus on knowledge dissemination and applied practice. However, current VET curricula remain oriented towards traditional occupations and are not adequately aligned with the sustainability and skills needs of the agri-food sector. This study, as part of a joint European-funded project (2023-1-IE01-KA220-VET-00156916: Train to Sustain), aimed to: (1) identify practical strategies for integrating sustainability concepts and innovative pedagogy into VET programs, and (2) gather multi-stakeholder perspectives on how VET agri-food education can be adapted for greater alignment with the green skills required by the sector. Following ethical approval, data were collected through semi-structured focus groups involving key agri-food stakeholder groups across Ireland, Slovenia, Poland and Italy. The data were qualitatively analysed using Reflexive Thematic Analysis (RTA). Five themes were identified: (1) Innovative and Sustainable Practices in Agri-Food systems, (2) Education, Awareness and Consumer Engagement, (3) Institutional and Structural Approaches, (4) Community and Localised Responses, and (5) Barriers, Opportunities and Future Directions. The findings highlight the significant potential VET offers in preparing a workforce with the cross-cutting sustainability competences and sector-specific skills needed to drive the innovation and growth of the agri-food sector. However, achieving this requires institutional change, strengthened collaboration, and a shift from traditional technical training toward curriculum models that embed sustainability principles across diverse local and regional contexts. Full article

Background: Generative artificial intelligence (GenAI) is rapidly permeating healthcare; yet, U.S. clinicians still report mixed feelings about its reliability, impact on workflow, and ethical implications. Current data on provider sentiment are needed to guide safe, patient-centered AI implementation in healthcare. Objective: This study aimed to assess U.S. healthcare providers’ perceptions of generative AI adoption, perceived usefulness, training needs, barriers, and strategies for safe integration. Methods: A nationwide, IRB-approved, cross-sectional survey was administered to healthcare professionals using Qualtrics. A convenience sample of clinicians was recruited via professional listservs and e-mail invitations. The 20-page questionnaire captured demographics, GenAI exposure, organizational adoption status, perceived usefulness (5-point scale), barriers, and mitigation strategies. SPSS v27 and Microsoft Excel were used for statistical analysis. Results: Of 130 respondents, 109 completed the core survey (completion rate 83.8%). Participants were 38.5% physicians, 16.5% nurses, 12.8% allied professionals, and 32.2% other providers; 54.2% were women, and 64.8% were ≥50 years. Overall, 86.9% agreed that GenAI is useful in current patient care, rising to 92.9% when asked about future usefulness. Only 42.4% had received formal GenAI training, and just 23.2% reported that their organization had begun adopting AI. The top perceived benefits were improved documentation/clerking (57.0%) and error reduction (49.4%). Dominant barriers included limited AI knowledge (24.7%) and fear of job loss (16.9%). Despite concerns, 72% expressed willingness to support broader GenAI adoption, favoring human oversight (67.1%) and staff training (60.8%) as key safeguards. There were statistically significant findings in perceived AI usefulness by gender (χ² = 29.2; p < 0.001); organizational adoption of AI (χ² = 31.6.2; p = 0.047) and where AI is most useful (χ² = 101.1; p < 0.001) by qualifications; and support for AI adoption by age (χ² = 18.0; p = 0.02). Conclusions: U.S. clinicians in our survey viewed GenAI as useful but reported limited training and organizational infrastructure needed for confident use while also expressing concerns regarding data privacy and ethical risk. Education programs and transparent, provider-led implementation strategies may accelerate responsible GenAI assimilation while addressing ethical and workforce concerns. Also, health administrators should use the efficiency gains to improve provider–patient relationships and clinicians’ work–life balance while reducing clinician burnout rates. Full article

What drives persistent urban–rural tourism satisfaction gaps: whether from promotional over-promising or structural service deficits? This distinction fundamentally determines whether territorial development resources should target marketing sophistication or productive capacity, yet remains empirically unresolved. Text-mining for 33,174 attractions across 349 Chinese cities reveals that both rural and urban destinations systematically under-promise, with description sentiment falling consistently below actual ratings, contradicting the “digital facade” hypothesis. Urban attractions nonetheless generate more positive surprises through superior service delivery (gap = 0.62 vs. 0.55). Sentiment measurement robustness is validated through triangulation of two independent dictionary-based methods ($r=0.58$, $p<0.001$) and cross-paradigm verification using a pre-trained BERT transformer ($\tau =1.000$ ranking stability). SHAP decomposition quantifies the policy implication: controllable service quality indicators, including description quality (23.2%), information richness (30.7%), and price positioning (16.5%), collectively explain over 70% of the variance in satisfaction, while fixed geographic factors (rural classification 14.9% and city-tier 14.7%) account for 29.6%, yielding a controllable-to-geographic ratio of 2.4:1. Propensity score matching with six covariates confirms a 0.074–0.100-point rural penalty persists after controlling for confounders, while non-linear analysis demonstrates that rural attractions face no marginal productivity disadvantage, and the challenge is baseline capacity, not investment efficiency. For policymakers pursuing Sustainable Development Goals 8, 10, and 12 through tourism-led regional strategies, these results mandate redirecting resources from demand-side expectation management toward supply-side infrastructure and workforce development, the true binding constraint on rural competitiveness. Full article

There is a need to enhance the behavioral health (BH) workforce. Paraprofessionals and peers are often on the “front lines” working with families affected by substance misuse. While they possess valuable lived experience, they often lack the requisite education to be most effective, resulting in high burnout and turnover. This study describes a novel training program for paraprofessionals working in family BH that included three online, 8-week courses (Level I) and a 12-month supervised apprenticeship (Level II). This study measured program satisfaction and effectiveness (knowledge, confidence, and perceived competence) and explored effects on career intention. A sample of paraprofessionals in the BH workforce provided data at baseline, after Level I, and after Level II. After Level II, 87% of participants rated their satisfaction with the program as high. Statistically significant improvements were found for knowledge, confidence, and competence across all domains. Almost all participants reported increased confidence after each level (93% and 94%, respectively). The majority (69%) reported increased interest in continuing their BH career and education. Overall, results suggest that the program was well-received by participants and was associated with improvements. Results provide preliminary support for apprenticeship-based training to enhance the BH workforce and address workforce challenges. Full article

Background/Objectives: Climate change and environmental degradation pose increasing public health threats, while healthcare systems significantly contribute through high energy use, water consumption, and waste generation. In hospital settings, healthcare technicians play a critical role, as their routine practices directly influence environmental sustainability. Despite this central role, healthcare technicians remain an under-recognized group in sustainability research and health policy. Green hospital practices therefore constitute a key public health strategy, requiring strategic management attention to this operational workforce. This study aimed to assess green hospital awareness among healthcare technician students in Türkiye and to examine associated sociodemographic factors from a public health perspective. Methods: This descriptive cross-sectional study included 313 students enrolled in health services vocational programs who were receiving hospital-based practical training. Data were collected using a personal information form and the validated Green Hospital Awareness Scale. Descriptive statistics, independent t-tests, one-way ANOVA, and Spearman correlation analyses were conducted using SPSS version 26.0, with statistical significance set at p < 0.05. Results: Although most participants reported no prior knowledge of the green hospital concept, overall awareness levels were moderate to high. The highest mean scores were observed in indoor environmental quality and materials–resources subdimensions, whereas water efficiency scores were the lowest. Female students demonstrated significantly higher total awareness and materials–resources scores (p < 0.05). No significant differences were observed by age or academic department. Conclusions: Healthcare technician students exhibit measurable green hospital awareness; however, important gaps remain in resource- and infrastructure-related sustainability domains. Strengthening educational and policy initiatives targeting this often-overlooked yet operationally essential workforce may improve environmentally responsible practices, enhance resource efficiency, and support sustainable healthcare systems and population health. Full article