Search Results (169)

The preparedness of healthcare workers for disaster situations depends on their technical skills, disaster knowledge, and psychosocial strength, including teamwork and emotional regulation. This study aims to assess disaster preparedness among healthcare professionals in primary healthcare centers (PHCs) in Alqurayat, Saudi Arabia, with a specific focus on evaluating technical competencies, psychosocial readiness, and predictive modeling of preparedness levels. A mixed-methods approach was employed, incorporating structured questionnaires, semi-structured interviews, and observational data from disaster drills to evaluate the preparedness levels of 400 healthcare workers, including doctors, nurses, and administrative staff. The results showed that while knowledge (mean: 3.9) and skills (mean: 4.0) were generally moderate to high, notable gaps in overall preparedness remained. Importantly, 69.5% of participants reported enhanced readiness following simulation drills. Machine learning models, including Random Forest and Artificial Neural Networks, were used to predict preparedness outcomes based on psychosocial variables such as emotional intelligence, teamwork, and stress management. Sentiment analysis and topic modeling of qualitative responses revealed key themes including communication barriers, psychological safety, and the need for ongoing training. The findings highlight the importance of integrating both technical competencies and psychosocial resilience into disaster management programs. This study contributes an innovative framework for evaluating preparedness and offers practical insights for policymakers, disaster planners, and health training institutions aiming to strengthen the sustainability and responsiveness of primary healthcare systems. Full article

The construction sector represents approximately 13% of global gross domestic product (GDP) and over 5% in Spain, employing more than one million workers. Despite its economic importance, the sector exhibits low digitalization levels and persistently high accident rates, contrasting with other industries that have successfully integrated digital technologies for safety improvement. Objective: This study evaluates the technical, operational, and regulatory feasibility of implementing digital tools and artificial intelligence (AI) in occupational risk prevention (ORP) within the Spanish construction sector. It focuses on identifying applicable technologies, assessing professionals’ perceptions of their practical utility, and analyzing key implementation barriers. Methodology: A mixed-method approach was employed in four stages: (1) a systematic literature review of digital safety tools; (2) a survey of 97 construction professionals using purposive sampling and validated through pretesting (Cronbach’s α = 0.82); (3) an analysis of official accident statistics; and (4) expert consensus using the Delphi method (three rounds, 75% consensus threshold). Results: Virtual reality (VR), augmented reality (AR), and mixed reality (MR) applications were identified as highly beneficial for training and awareness, with 78.2% of professionals supporting their use for safety training. Building Information Modeling (BIM) and drones were highlighted as the most valued tools for risk management and site supervision. Main implementation barriers include a lack of digital skills (35%), insufficient budget (30%), and high tool costs (25%). Contribution: This study proposes a mixed-method methodological framework—quantitative and qualitative—adapted to national contexts and validated through a Delphi consensus process. The framework prioritizes key technologies and identifies targeted strategies to overcome critical implementation barriers. Full article

Defect repair on custom-curved glulam beams is still performed manually because knots are irregular, numerous, and located on elements that cannot pass through linear production lines, limiting the scalability of timber-based architecture. This study presents Woodot, an autonomous mobile robotic platform that combines an omnidirectional rover, a six-dof collaborative arm, and a fine-tuned Segment Anything computer vision pipeline to identify, mill, and plug surface knots on geometrically variable beams. The perception model was trained on a purpose-built micro-dataset and reached an F1 score of 0.69 on independent test images, while the integrated system located defects with a 4.3 mm mean positional error. Full repair cycles averaged 74 s per knot, reducing processing time by more than 60% compared with skilled manual operations, and achieved flush plug placement in 87% of trials. These outcomes demonstrate that a lightweight AI model coupled with mobile manipulation can deliver reliable, shop-floor automation for low-volume, high-variation timber production. By shortening cycle times and lowering worker exposure to repetitive tasks, Woodot offers a viable pathway to enhance the environmental, economic, and social sustainability of digital timber construction. Nevertheless, some limitations remain, such as dependency on stable lighting conditions for optimal vision performance and the need for tool calibration checks. Full article

Background and Objective: Despite growing emphasis on quality and safety in healthcare, there remains a limited understanding of how Quality Improvement and Patient Safety (QI/PS) training for health workers has evolved in response to global events like the COVID-19 pandemic and the WHO Global Patient Safety Action Plan. This rapid scoping review aimed to not only identify existing curricula but also uncover trends, innovation gaps, and global inequities in QI/PS education—providing timely insights for reshaping future training strategies. Methods: We searched MEDLINE and Scopus for English-language studies published between January 2020 and April 2024, describing QI and/or PS curricula across graduate, postgraduate, and continuing education levels. All healthcare worker groups were eligible, with no geographic limitations. Two reviewers conducted independent screening and data extraction; a third verified the results. Results: Among 3290 records, 74 curricula met inclusion criteria, with a majority originating from the US (58, 78.4%) and targeting physicians—especially residents and fellows (43/46, 93.5%). Only 27% of curricula were multidisciplinary. While traditional didactic (66.2%) and interactive (73%) approaches remained prevalent, curricula launched after 2020 introduced novel formats such as Massive Open Online Courses and gamification, with long-term programs uniformly leveraging web-based platforms. Common thematic content included Root Cause Analysis, Plan-Do-Study-Act cycles, QI tools, communication skills, and incident reporting. English-language peer-reviewed published literature indicated a marked lack of structured QI/PS training in Europe, Asia, and Africa. Conclusions: This review reveals both an uneven development and fragmentation in global QI/PS training efforts, alongside emerging opportunities catalyzed by digital transformation and pandemic-era innovation. The findings highlight a critical gap: while interest in QI/PS is growing, scalable, inclusive, and evidence-based curricula remain largely concentrated in a few high-income countries. By mapping these disparities and innovations, this review provides actionable direction for advancing more equitable and modern QI/PS education worldwide, whilst showcasing the need to systematically delve into QI/PS training in underrepresented regions. Full article

Traditional off-the-job training is becoming ineffective in high-end equipment research and development (R&D) projects due to the contradiction between rapid technological progress and the slow growth of newcomers, calling for “on-the-job mentoring” to enable synchronized advancement of project execution and newcomer cultivation. For this, we propose the multi-skilled project scheduling problem with newcomer cultivation under uncertain durations (MSPSP-NCU) and abstract it as a stochastic programming model. The model aims to minimize expected makespan and maximize newcomers’ skill efficiency by optimizing workforce assignment that enables experienced workers to mentor newcomers while simultaneously optimizing task scheduling. Solving the model is blocked by the inherently NP-hard nature of the project scheduling problem and the stochasticity of the durations. Therefore, we put forward an adaptive simulation–optimization approach featuring two-fold: a simulation module capable of dynamically adjusting sample sizes based on convergence feedback and evaluating solutions with improved efficiency and stable accuracy; a tailored non-dominated sorting genetic algorithm II (NSGA-II) with adaptive evolutionary operators that enhance search effectiveness and ensure the identification of a well-distributed Pareto front. By using data from an aerospace component R&D project, the proposed approach is validated for its performance in identifying Pareto-optimal solutions. Several personalized rules are designed by integrating workforce development strategies into the selection process, providing actionable guidelines for cultivating newcomers in technology-intensive projects. Full article

Population aging is a critical demographic trend in China, creating both challenges and opportunities for sustainable development. As aging alters the structure of the workforce and capital demand, understanding its effect on productivity is essential to managing demographic transitions in China. This study investigates the causal impact of population aging on labor productivity, with a focus on the mediating role of the capital–labor ratio and heterogeneities across industries, skill levels, and regions. Using data from Chinese listed firms between 2011 and 2018, this paper employs industry- and year-fixed effects regression models to control for unobservable heterogeneity and conducts a formal causal mediation analysis. The analysis reveals that population aging significantly enhances labor productivity. Specifically, a one-percentage-point increase in the old-age dependency ratio is associated with a 1.47% increase in firm-level labor productivity. The capital–labor ratio emerges as a critical mechanism, mediating the relationship between aging and productivity by incentivizing firms to increase capital intensity in response to labor shortages. Approximately 72.4% of the total effect is mediated through changes in capital intensity. The findings highlight notable heterogeneities. Labor-intensive firms and low-skilled worker segments experience stronger productivity gains from aging compared with their capital-intensive and high-skilled counterparts. At the regional level, the productivity effects are most pronounced in first- and second-tier cities, while third-tier cities show negligible impacts, reflecting resource and structural constraints. This study underscores the dual role of population aging as a challenge and an opportunity. Policy recommendations include (1) expanding targeted fiscal support for capital investment and automation in aging-intensive industries; (2) promoting vocational training programs tailored to older workers and digital skills development; and (3) strengthening infrastructure and institutional capacity in third-tier cities to better absorb productivity spillovers from demographic adjustment. By addressing these demographic and productivity linkages, the study contributes to achieving Sustainable Development Goals 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 10 (Reduced Inequalities), by promoting inclusive productivity growth, enhancing industrial adaptation to demographic change, and reducing regional and skill-based disparities.These findings offer valuable insights for policymakers and businesses navigating the complexities of aging economies. Full article

Rubber tapping robots represent a significant research direction in modern robotics in agricultural automation. Nevertheless, natural rubber tapping robots encounter considerable challenges in achieving precise tapping, particularly in controlling tapping depth, due to the lack of suitable control algorithms. To solve this problem, an improved Particle Swarm Optimization/Proportional–Integral–Derivative (PSO-PID) control method has been proposed in this paper. It enhances the inertia weight of the particle swarm by introducing adaptive inertia weight, solving the shortcomings of the traditional PSO algorithm, such as insufficient local search ability and early convergence. The experimental results show that the rubber tapping depth system based on the improved PSO-PID algorithm has high responsiveness and robustness, with an average settling time of 0.419 s and an overshoot that can be kept below 2.5%. The depth control accuracy, robustness and convergence speed of the system are significantly better than other well-known optimization algorithms. At a tapping depth of 3.0 mm, the injury rate was reduced to 2%, surpassing the level of skilled manual tapping workers. It has been proven that this method can effectively solve the key problem of accurate depth control in current rubber tapping. Full article

This study examines the asymmetric effects of foreign worker employment and low educational attainment on labor productivity across Malaysia’s three main economic sectors—agriculture, industry, and services—from 1991 to 2019 using the nonlinear autoregressive distributed lag (NARDL) model. Three sectoral models are estimated to capture how overdependence on foreign workers and low-skilled local labor influences productivity. Model 1 for agriculture underscores positive variations vis-à-vis how foreign worker employment boosts agricultural productivity in both the short and long term. However, negative variations lead to diminished productivity in the long run. Primary education negatively affects long-term agricultural productivity. In Model 2 for industry, neither foreign worker employment nor low educational attainment significantly affects productivity. Model 3 for services reveals a short-term boost in productivity with increased foreign workers’ employment, whereas reduced employment enhances long-term productivity. The absence of formal education is detrimental to long-term service productivity, while primary education affects it negatively in the short term. NARDL multiplier graphs and Wald tests confirm significant long-run asymmetric effects of foreign labor in the agriculture and services sectors. The findings highlight the need for Malaysia to reduce reliance on low-skilled labor and accelerate its transition toward a high-skilled workforce to sustain productivity growth and economic competitiveness. Full article

High levels of stigma among the healthcare workforce impede efforts to increase access to effective substance use disorder (SUD) treatments. Education on SUDs that (1) is tailored to physicians in training and (2) directly addresses and attempts to combat SUD stigma may help produce lasting reductions in SUD stigmatization within the healthcare setting. This study aims to describe the development of a technology-based, interactive SUD stigma intervention for medical students, created in collaboration with medical students, practicing clinicians, and experts in the fields of psychology and addiction medicine. This intervention is unique in its interactive application-based approach and the use of a computerized intervention authorizing system (CIAS) to guide the participant through the training. The final intervention includes four interactive online modules focused on SUD education using a biopsychosocial model, including stigma acknowledgment, an examination of patient perspectives, and the application of skills. Planned future studies will examine the feasibility, acceptability, and preliminary efficacy of the intervention among medical students. This intervention leverages the existing CIAS to provide interactive training that can be used as a part of medical student training and be expanded to other healthcare professionals (e.g., nurses and community health workers). Ultimately, this work will be used to drive a reduction in SUD stigma in medical settings. Full article

Background: Health literacy (HL) promotes the achievement of skills and information useful to endorse health. Food Literacy (FL) is a subtype of HL related to the knowledge necessary to achieve a healthy diet. Methods: This pilot study aimed to assess and improve FL of hospital workers through a survey before and after an educational intervention consisting of nutrition courses, infographics, and updates to the canteen service. FL was evaluated with a questionnaire, and Kruskal–Wallis, Friedman and Wilcoxon test was performed to assess group differences. Results: Of 897 participants, 375 (T1) completed both surveys, while 522 completed only T0. A pairwise comparison stratified by role, age and education revealed a significant improvement in FL scores in the T1 group. Improvements were observed in the T1 group, with overall scores rising from 6.2 ± 2.7 to 6.9 ± 2.1 (p-value < 0.001). An upgrade was noted in healthcare workers (T0 = 6.5 ± 2.2 vs. T1 = 7 ± 2, p-value < 0.001), administrative workers (T0 = 5.5 ± 2.5 vs. T1 = 6.2 ± 2.4, p-value = 0.008), all age groups (T0 = 6.3 ± 2.4 vs. T1 = 6.8 ± 2, p-value = 0.03, T0 = 6.2 ± 2.3 vs. T1 = 6.7 ± 2.2, p-value = 0.02, T0 = 6.2 ± 2.3 vs. T1 = 7 ± 2, p-value = 0.003), low and high education (T0 = 5.7 ± 2.3 vs. T1 = 6.6 ± 2.1, p-value < 0.001, T0 = 6.6 ± 2.3 vs. T1 = 7.1 ± 2 p-value = 0.03). Conclusions: Our survey highlights the efficacy of a multifactorial intervention in enhancing FL and proves the importance of food health promotion within workplaces. Full article

With the rapid advancement of artificial intelligence (AI) technology, the global employment structure is undergoing profound transformations, significantly impacting social sustainability. This study utilizes panel data from 30 Chinese provinces spanning the years 2010 to 2022 and applies a two-way fixed-effects model to analyze the impact of AI development on the employment skills structure. The findings indicate that advancements in AI technology significantly suppress the demand for low-skilled labor while markedly enhancing the demand for both middle- and high-skilled labor. The threshold effect analysis reveals a nonlinear relationship between AI advancements and the demand for low-skilled workers. Mediation effect tests demonstrate that technological innovation serves as a mediating factor in AI’s impact on low- and middle-skilled labor but has no significant effect on high-skilled labor. The heterogeneity analysis further indicates that AI’s negative impact on low-skilled female employment is more severe than for males, while its positive impact on high-skilled male workers is significant. Additionally, the employment effects of AI are mainly observed in labor-intensive provinces, with minimal influence in capital-intensive areas. This study suggests harnessing AI’s potential to promote employment while proactively mitigating its disruptive effects on the labor market through enhanced research and development support, strengthened employment security, and coordinated regional economic development, thereby advancing sustainable economic and social progress. Full article

The choice between domestic and foreign production is one of the most important decisions not only for international business management but also for economic diplomacy and industrial policy. The reality is not a binary choice, but some firms use both. Why do companies maintain labour-intensive production in developed countries in the globalised world? To understand business challenges and strategies, this study examines small and medium-sized enterprises (SMEs) in the garment factory agglomeration in the North (Kenpoku) area of Iwate Prefecture, Japan. The in-depth case study, with a special focus on the six competitiveness factors of Japanese apparel firms, recognises that the ‘Made in Japan’ branding strategy is one of the effective ways to attract Japanese customers. This marketing strategy may motivate some firms to consider international market development. However, most Japanese SME apparel manufacturers play the role of original equipment manufacturer (OEM) for specific domestic market-oriented apparel companies. To meet customers’ strict delivery requirements, our case SMEs are developing multi-skilled workers to cope with high-mix small-lot production and fast delivery simultaneously. This management innovation is essential for building long-term business relationships and trust with corporate apparel buyers and surviving competition from products made in China and other developing countries. Full article

This study examines the intentions of foreign workers living in Okayama, Japan, to stay long-term in Japan. Utilizing a Bayesian multinomial logistic regression model, this research provides a novel analytical approach that captures parameter uncertainty and accommodates the categorical nature of migrants’ settlement intentions using primary data collected via a questionnaire survey from January to March 2024. The findings reveal that residence status, previous experience of living in Japan, and graduation from a Japanese education institution significantly influence long-term settlement intentions. In addition, respondents aged 26–35 intend to stay longer than those of other ages, and those from less developed countries, such as Myanmar and Vietnam, intend to stay longer than those from China. Conversely, highly educated migrants express lower settlement intentions, suggesting a potential loss of skilled foreign labor in Japan. Notably, migrants in the Technical Intern Training Program are more likely to stay longer than those with other residence statuses, such as Highly Skilled Professional. In contrast, workers with higher education levels tend to have less intention to stay long-term, indicating a high probability of Japan losing educated foreign labor in the future. These findings contribute to understanding the dynamics of migrant workers in Japan, which is crucial for creating policies for foreign workers that can attract and support long-term settlement. These findings have important implications for policy, particularly in enhancing community integration, reducing workplace discrimination, and designing residence pathways that support long-term retention. Full article

Objectives: to systematically examine and synthesize qualitative evidence on adult patients’ psychological distress during an intensive care unit stay to inform development of interventions tailored to their needs. Method: We conducted systematic literature searches in CINAHL, MEDLINE, EMBASE, PsycINFO, Scopus, Dissertations and Theses Global, and Google Scholar databases using predefined eligibility criteria. We synthesized primary qualitative research evidence using Noblit and Hare’s meta-ethnographic approach. Reporting was based on the eMERGe framework. The quality of included articles was assessed by the Critical Appraisal Skills Program tool. Findings: We identified 31 primary studies from 19 countries. The studies were of moderate to high quality. Data analysis revealed five themes: “disempowerment”, “altered self-identity” “fighting”, “torment”, and “hostile environment”. One overarching theme, “the disempowered warrior”, captured the perpetual tension between the need to fight for their lives and the need to succumb to the care process. Our synthesis discloses that critically ill patients perceive themselves to be in a battle for their lives; while at the same time they may feel helpless and disempowered. Conclusions: Our review revealed the tension between the need to fight for one’s life and the sense of powerlessness in the intensive care unit environment. Although participants recognize the important role of healthcare workers, they desired more involvement, collaboration, control, empathy, and empowerment in the care process. These findings can inform approaches to empowering critically ill patients and managing their psychological responses. Care standards must include distress assessment and management that maximize patients’ empowerment and emotional safety with the care process. Full article

Heritage conservation projects involve diverse stakeholders, such as property owners, communities, NGOs, and governments, whose “misaligned” incentives produce high transaction costs and often pose persistent challenges. Considering heritage sites as analogous to common pool resources (CPR), this study examines whether sustainable heritage projects adhere to Elinor Ostrom’s design principles for managing CPRs. The UNESCO Asia-Pacific Awards for Cultural Heritage Conservation are used as a benchmark to identify best practices in private–public collaborations over the past two decades. Through content analysis of award application dossiers, the researchers assess whether the design principles are applied differently between successful and unsuccessful projects and evaluate the sufficiency of Ostrom’s principles in the heritage conservation context. The findings indicate that four design principles are more consistently balanced in award-winning projects: “Collective Choice Arrangements”, “Congruence with Local Conditions”, “Monitoring Mechanisms”, and “Minimum Recognition of Rights”. Additionally, successful projects tend to incorporate “people growth-oriented activities”, such as skills training and education for local workers and youth, benefiting current and future project beneficiaries. These insights suggest that adapting Ostrom’s design principles can enhance the sustainability of heritage conservation efforts by better aligning stakeholder incentives and addressing the “misalignment of incentives” challenge commonly encountered in such projects. Full article