Search Results (846)

Introduction: The work-related quality of life affects employee satisfaction and organizational effectiveness, with a direct impact on the quality of healthcare. This study aims to investigate the work-related quality of life (WRQoL) among nurses in tertiary healthcare, as perceived by the nurses themselves, in relation to their demographic and professional characteristics. At the same time, it seeks to highlight the way in which the individual dimensions of WRQoL influence their sexual and mental health. Materials and Methods: A descriptive cross-sectional study was conducted in 2023 in a General Hospital in Greece. Data were collected using structured questionnaires assessing sociodemo-graphic and occupational characteristics, WRQoL, mental health (Depression, Anxiety and Stress Scale—DASS-21), and female sexual function (Female Sexual Function Index—FSFI-19). Pearson correlation analysis and multiple linear regression analysis were performed. The regression model was adjusted for age, marital status, number of children, and work experience. Results: The results demonstrated a significant negative association between depression and sexual function (β = −0.388, p = 0.029), while stress was positively associated with sexual function (β = 0.371, p = 0.038). The overall regression model was statistically significant (p = 0.001), explaining 18.6% of the variance in sexual function. Conclusions: The findings highlight the close interrelationship between work-related quality of life, mental health, and sexual function among nurses. Poorer psychological well-being was associated with reduced sexual function, emphasizing the impact of occupational and emotional burden on nurses’ overall health. These results underline the importance of supportive workplace environments and targeted interventions to promote mental and sexual well-being among healthcare professionals. Full article

Background: Healthcare systems globally continue to experience persistent workforce and system-level challenges as increased workloads, lasting wellbeing impacts, and retention issues remain following the pandemic. To inform strategies and interventions to address these issues, this paper explored the workplace experiences of Victorian (Australia) frontline healthcare workers with parenting responsibilities during the COVID-19 pandemic. Methods: A total of 39 frontline healthcare workers from a large metropolitan hospital were interviewed between October 2020 and February 2021. Reflexive thematic analysis was used to analyse transcripts. Results: Three superordinate themes and five subordinate themes were identified. Themes highlighted the significant pressure that rapid workplace changes placed on healthcare staff and leaders, affecting their physical, mental, and relational health. Support from peers and supervisors was protective, though this increased demands on supervisors themselves. While many staff reported pride in their work, some experienced reduced career satisfaction and concerns about lasting psychological impacts. Conclusions: This study identifies how workplace supports operate through communication transparency, leadership capacity, and protected peer-support space, translating to organisational priorities for the post-pandemic workforce. In the context of ongoing workforce shortages and heightened demands post-pandemic, these findings underscore the importance of strengthening leadership capacity, embedding sustainable workplace supports, and addressing the psychological needs of healthcare staff. Such system-level responses are essential for pandemic recovery, improving workforce retention and staff wellbeing in the modern healthcare environment. Full article

This systematic literature review synthesizes and integrates research on dysfunctional cognition (DC) in organizational settings, addressing the lack of a coherent model explaining how cognitive vulnerabilities shape work-related outcomes. Following the PRISMA guidelines, we analyzed 41 manuscripts (selected from more than 4523 initial and secondary search hits), leading to an integrative model of DC at work. Results show that DC is activated by job demands, alongside other demanding situational and contextual features. The model specifies maladaptive appraisal processes as the cognitive–affective mechanism through which DC shapes (dis)engagement in the task and relational domains at work and ultimately impacts outcomes such as well-being, stress, burnout, performance, and decision quality. It further incorporates job, personal, and social resources as buffering contingencies that promote adaptive appraisal and attenuate the detrimental role of DC. By integrating insights from clinical, cognitive–behavioral and organizational research, this review advances theory in three ways: (1) by emphasizing the role of appraisal as the cognitive–affective mechanism linking DC to work (dis)engagement, (2) by embedding DC in the job demands–resources model and identifying job demands as activating conditions and resources as regulatory factors for dysfunctional cognitive dynamics at work and (3) by differentiating between task and interpersonal (dis)engagement as domain-specific paths through which self-focused and relational schema impact work-related outcomes. The integrative DC model provides a foundation for future research using longitudinal and mixed-method designs, and for more fine-grained examinations of how specific forms of DC relate to distinct cognitive–affective pathways and work-related outcomes, while offering practical implications for developing schema-informed and resource-based interventions in organizations. Full article

Coal mining is a hazardous occupation that can adversely affect both the physical and mental health of workers. This study aimed to estimate the pooled prevalence of various mental health outcomes and job burnout among coal miners and to summarize available intervention strategies addressing these conditions. A systematic search of scientific databases, including Scopus, Embase, PubMed and Cochrane Central, was conducted for studies published from 2000 onwards. The study protocol was registered in PROSPERO [CRD42024536144]. Methodological quality of the studies was evaluated using AXIS, ROBINS-I and RoB 2 tools. A random-effects model was applied to estimate pooled prevalences. Of the 14,048 studies identified, 34 studies were included, comprising a total of 38,996 coal miners. The pooled prevalence of job burnout was 53.75% (95% CI: 50.64–56.86%), while depressive symptoms were observed in 35.35% of coal miners (95% CI: 16.43–54.28%; I² = 97.41%). The pooled prevalence estimates were calculated with substantial heterogeneity (I² > 90%) and wide prediction intervals indicate considerable variability across studies. These findings should be interpreted with caution due to substantial heterogeneity across studies, which may limit the reliability of pooled estimates. A limited number of studies reported interventions, including an Integrated Approach of Yoga Therapy (IAYT) and peer-based mental health and suicide prevention programs with supervisor training, which demonstrated potential benefits; however, these findings are based on limited and methodologically heterogeneous evidence, and the overall certainty remains low. The findings highlight a substantial burden of mental health problems among coal miners and suggest important policy implications, particularly for integrating mental health screening into periodic occupational health assessments. Addressing personal, social, and work-related determinants through comprehensive workplace strategies may help improve mental well-being and support workforce sustainability in the mining sector. Full article

The rapid evolution of smart cities demands a transition from reactive healthcare systems to proactive, data-driven health management paradigms that support long-term urban sustainability. Predicting population health status based on lifestyle-related behavioral and physiological factors is critical for enabling early intervention, personalized healthcare, and efficient resource allocation directly contributing to the United Nations Sustainable Development Goals (SDG 3: Good Health and Well-being; SDG 11: Sustainable Cities and Communities). This study proposes an IoT-enabled Explainable Artificial Intelligence (XAI) framework for predictive health scoring as part of sustainable population health management, integrating real-time data acquisition, cloud-based analytics, and interpretable machine learning. To address the limitations of conventional ensemble models particularly the black-box nature and hyperparameter sensitivity of Extreme Gradient Boosting (XGBoost) a Bayesian optimization strategy is employed to automatically fine-tune model parameters, thereby enhancing predictive accuracy and generalization performance. Furthermore, Shapley Additive Explanations (SHAP) are incorporated to provide transparent, interpretable insights into model predictions by quantifying the contribution of individual lifestyle features. Using a publicly available Kaggle dataset (“Health and Lifestyle Data for Regression”), experimental evaluation demonstrates that the proposed Bayesian-Optimized XGBoost model achieves superior performance (Test R² = 0.878, RMSE = 4.983), outperforming ten benchmark models, including standard XGBoost, which exhibits signs of overfitting (Test R² = 0.832). The results further reveal that Body Mass Index (BMI) and diet quality are the most influential factors affecting health scores, providing actionable insights for urban health policymakers. The proposed framework highlights the synergy between IoT, optimization techniques, and explainable AI to develop transparent, reliable, and scalable predictive health systems. This work provides a practical foundation for next-generation smart healthcare applications and decision-support systems, advancing the vision of sustainable, data-driven, and human-centric smart cities. Full article

Noise in industrial buildings affects workers’ productivity and can seriously impair their physical and mental health, yet existing studies often overlook workers’ subjective perceptions and rely on a single method. Therefore, this study recruited 263 workers from four industrial buildings in Beijing and adopted a mixed-methods approach. First, 30 semi-structured interviews were analyzed using grounded theory’s three-level coding procedure to construct a conceptual framework of a healthy acoustic environment and its influencing factors. Next, a 30-item subjective questionnaire was developed, and structural equation modeling was conducted on 256 valid responses. Finally, Spearman correlation analysis and multidimensional scaling were used to examine relationships between subjective evaluations and eight physical and psychoacoustic indicators. The results identified nine major dimensions, including Sound Source Localization, Physiological Effects at Work, and Regulatory Control, as well as 15 relational pathways. Compared with existing frameworks, Communication Barrier emerged as a more prominent dimension in industrial building contexts. Structural equation modeling confirmed that 12 pathways were statistically significant. Correlation analysis further showed that only a few objective–subjective associations were significant, indicating that objective acoustic indicators alone cannot explain workers’ multidimensional perceptions. In conclusion, this study developed an evaluation model for healthy acoustic environments in industrial buildings, highlighting the need to emphasize controllability, communication support, and integrated subjective–objective evaluation in acoustic design to better enhance workers’ well-being. Full article

Despite the growing integration of artificial intelligence (AI) into workplace operations, how AI usage influences employees’ affective work well-being remains underexplored. To address this gap, this study draws on self-determination theory to propose a moderated mediation model. We conducted a three-wave time-lagged survey of 360 employees and our results indicate that AI usage positively predicts affective work well-being, and this relationship is fully mediated through two parallel paths—work meaningfulness and work engagement. Moreover, human–AI collaboration quality positively moderates these indirect effects. Collectively, these findings extend self-determination theory to AI-augmented work contexts, clarify the psychological mechanisms linking AI usage to employee affective well-being, and provide actionable insights for human-centered AI implementation. Full article

Background: Malnutrition is a universal challenge in long-term care, significantly affecting vulnerable populations. Residents with Intellectual Developmental Disability (IDD) rely heavily on Direct Support Professionals (DSPs) for assisted feeding. Understanding DSP’s mealtime experiences is essential for improving nutritional care and well-being. Objective: To examine multilevel factors associated with DSPs’ mealtime experiences. Methods: This exploratory cross-sectional case study used a survey administrated to DSPs working in a long-term residential setting. Statistical analyses examined the associations between multilevel factors and DSP’s positive and negative mealtime experiences. Results: The sample included 46 DSP’s (98% women) from a single facility in Israel. Although DSPs reported high levels of positive feelings and satisfaction with their daily work efficacy, negative feelings were significantly associated with some organizational, environmental and resident-related factors. Negative feelings were higher among DSPs caring for residents who use wheelchairs compared to those working with residents who do not use wheelchairs (t = −2.99, p < 0.01). Negative feelings were negatively associated with institutional support (r = −0.49, p < 0.001), and perceived accessibility and adaptability of the environment (r = −0.46, p = 0.001), and showed a more modest association with communication with residents (r = −0.38, p = 0.01). DSPs’ seniority, education level, and prior feeding-related training were not significantly associated with mealtime experience. Conclusions: The findings highlight that negative mealtime experiences among DSPs are associated with organizational, environmental, and resident-related factors, rather than with individual DSP’s characteristics. Policy and practical adjustments to address mealtime experiences for residents with IDD are suggested. Full article

The vulnerability of many Pacific communities is impacted by rising sea levels and exposure to extreme weather patterns. This qualitative research study was conducted with focus groups of Māori and Pacific youth in Aotearoa New Zealand. I am a Pacific researcher, and I examine research and report on findings from Pacific youth focus groups. Employing a Talanoa methodology, a key question posed was how educators in Aotearoa New Zealand supported the wellbeing of Pacific youth in the face of increasing climate extremes within their schools and communities. Engaging a Pacific values framework, this discussion emphasizes the critical role of teachers and education in eliminating concerns, working collectively, listening respectfully, and collaborating with Pacific youth in confronting the complexity of issues surrounding climate change, thereby creating a shift from a position of despair and helplessness to a place of hope and optimism. Findings from the study reveal that, in the education sector, climate change is not well addressed, teachers could do more to acknowledge and address climate crises faced in the Pacific region in the curriculum, and little attention is paid to the wellbeing of Pacific youth facing climate change in the Pacific. An implication is that teachers need to support Pacific youth and understand that education about climatic variance affects Pacific learners’ wellbeing. Full article

In the context of occupational environments and sustainable employment, this review explores the effects of declining workers’ health, environmental degradation, and the depletion of marine resources on workers’ psychological well-being. As seas and oceans are increasingly exploited and used as dumping sites for both solid and liquid waste, marine ecosystems are severely degraded, with negative impacts on biodiversity, water quality, and ecosystem processes. Marine biodiversity is crucial to maintaining global food security and supporting the livelihoods of millions of people worldwide. Moreover, this study examines the role of digital technology in the marine industry in safeguarding workers’ sustainable well-being. It emphasizes the complementary roles of law and technology in promoting it. The risks to the health and well-being of marine workers are greatly increased by the occupational consequences of climate change on the sustainable environment and the effects of working in marine environments. Working conditions, incomes, and even unemployment among marine workers have been directly affected by the degradation of marine environments and the depletion of marine resources. Anxiety, panic, depression, rage, and other unpleasant emotions that affect workers’ health and pose mental health risks are detrimental to the psychological well-being of marine workers. The challenges of employment in the marine industry adversely affect the physical and mental well-being of marine employees and hinder economic growth. However, digital technology in marine environments has fundamentally altered the regulations governing marine operations. Full article

Background: Professional identity formation (PIF) and wellbeing are increasingly being recognised in postgraduate Family Medicine (FM) education. Role models are central to both, yet traditional learning activities often struggle to implement them effectively. Podcasts offer a flexible medium that may support these goals. This study examines the potential of postgraduate medical education (PGME) podcasts, such as the European Young Family Doctor’s Movement (EYFDM) podcast, to promote PIF and wellbeing. Methods: This mixed-methods study analyses podcast use, role modelling effects, and PIF among young general practitioners (GPs). In 2024, 57 participants, including students, FM trainees, and specialists, completed an online questionnaire with quantitative and qualitative items. Descriptive and analytical statistics were combined with qualitative content analysis (Kuckartz). Sentiment analysis was conducted using artificial intelligence, and triangulation enhanced credibility. Results: Within the trainees and specialists of the study population, most participants (70%; 32/46 SPs) reported regularly using podcasts for PGME, and particularly young female GPs in Western Europe. In our study population, 90% (27/30 SPs) agreed that the podcasts broadened their perspective on professional opportunities in FM. Many participants reported reflections on potential career pathways and PIF. Exposure to role models significantly increased motivation to work in FM (χ² (1) = 10.7, p < 0.001). Conclusions: Podcasts may help address gaps in affective competency training, including wellbeing and PIF, while integrating easily into busy routines. Findings suggest a positive influence on career attitudes, with role modelling supporting PIF and motivation in FM. Full article

Employee happiness has become a central concern for the social dimension of sustainability, particularly within small and medium-sized enterprises (SMEs) operating in emerging economies. However, empirical evidence remains limited regarding how advanced organizational self-management practices—especially when integrating holacracy-inspired practices and broader self-management mechanisms that show a positive and significant association with employee happiness in SME contexts, particularly in Latin America. Addressing this gap, this study examines the relationship between organizational self-management practices and employee happiness in Peruvian SMEs, adopting a predictive approach based on Partial Least Squares Structural Equation Modeling (PLS-SEM). Organizational Self-Management Practices (OSMPs) are modeled as a higher-order construct integrating holacracy-inspired and broader self-management practices. Data were collected from 383 SME employees through a structured questionnaire. The findings indicate that organizational self-management practices exert a positive and significant association with employee happiness, operating through an underlying mechanism in which self-management-oriented practices foster greater employee autonomy, participatory decision-making, role clarity, and shared responsibility, thereby supporting fundamental psychological needs and enhancing employees affective and cognitive well-being at work. By promoting these autonomy-supportive organizational conditions, Organizational Self-Management Practices (OSMPs) strengthen employee happiness in resource-constrained SME contexts, highlighting how Organizational Self-Management Practices function as internal governance mechanisms that enhance employee well-being and contribute to social sustainability by strengthening psychologically supportive, autonomy-enhancing, and socially sustainable work environments in emerging economy SMEs. These findings demonstrate that employee happiness represents a micro-level manifestation of social sustainability, linking internal organizational governance mechanisms with broader sustainable development outcomes in emerging economy contexts. Full article

Voluntary turnover represents a critical challenge in essential public services, where workforce attrition affects both employee well-being and service quality. The primary objective of this study was to identify the psychosocial predictors of well-being profiles and turnover intention among public transport workers, using the Job Demands–Resources model as a theoretical framework. A cross-sectional study design was employed, with 131 employees of an Italian public transport company completing a questionnaire assessing turnover intention and key psychosocial factors (job satisfaction, perceived work-related stress, work engagement, meaning of work, and perceived workplace safety). The analytical strategy integrated Latent Profile Analysis (LPA), logistic regression, and path analysis. LPA identified two distinct well-being profiles: a “low well-being profile,” with high perceived stress and low engagement and meaning of work; and a “high well-being profile,” with low stress and high engagement and work meaning. Logistic regression analyses showed that satisfaction with pay and the intrinsic nature of work tasks predicted membership in the high well-being profile. Path analysis indicated that profile membership significantly predicted turnover intention, with employees in the high well-being profile reporting lower turnover intention. Additionally, satisfaction with supervision, perceived workplace safety, and age showed direct effects on turnover intention. These findings highlight the organizational and psychological resources that can increase employee well-being and retention in the public transport sector, offering insights for preventive interventions and for promoting safer and more sustainable public transport systems. Full article

Social determinants of health (SDoH) are non-medical factors shaped by the socioeconomic status of individuals or communities that influence the onset and progression of diseases and affect their outcomes. We have narratively analyzed the most important findings relating chronic kidney disease (CKD) and SDoH, evaluating the following items: (i) medical care and social determinants of health, (ii) socioeconomic risk for kidney disease at the individual level and (iii) socioeconomic risk for kidney disease at the population level. SDoH can be categorized by how they influence a person’s daily life. Individual factors include personal lifestyle choices such as smoking habits, alcohol consumption, and how a patient spends their non-working time. Community factors include structural elements such as average household income, educational attainment, employment rates, and the quality of the surrounding physical environment. Research consistently shows that a low socioeconomic status is a primary driver of poor clinical outcomes. While healthcare systems vary globally, the negative impact of socioeconomic deprivation on CKD patients remains a constant. Disadvantaged patients experience a faster loss of renal function, and there is a significantly higher incidence of cardiovascular events and mortality compared to those with financial stability. Financial hardship often leads to a “double burden,” where the struggle to afford care triggers a decline in both physical health and mental well-being. To improve patient care, it is essential to raise awareness among healthcare providers regarding the profound impact of these social factors. More precise data and thorough research are needed to fully understand these associations and develop targeted interventions. Full article

Human-centered entrepreneurship considers employee well-being and uses the Sustainable Development Goals as its fundamental pillars. However, existing research predominantly focuses on institutional interventions and fails to provide integrated intelligent solutions for tackling human–machine collaboration issues in the context of digital transformation. Large language models (LLMs) offer potential for affective computing and personalized support, but face critical gaps in ethical governance, privacy protection, and real-time risk intervention in sensitive entrepreneurial contexts. Our proposed Human-Centered Entrepreneurial Intelligent Agent (HCEA) framework achieves the unified optimization of task utility, empathetic expression, and ethical security by integrating a large language model core fine-tuned via a multi-objective hybrid loss function and a cluster of task-specialized intelligent agents. HCEA integrates retrieval-enhanced generation to ensure suggestion accuracy, a hierarchical data governance system for sensitivity-based privacy protection, and an independent risk detection module for real-time intervention and referral. We build the framework by constructing a hybrid entrepreneurial dataset, design the multi-agent architecture of decision support, emotion understanding and ethical risk tracking, and empirically evaluate both comparisons and ablation experiments. The results demonstrate that HCEA outperforms five baseline models across six key metrics, including entrepreneurship guidance relevance, emotion recognition, and high-risk recall. This study contributes to the intersection of digital transformation and sustainable entrepreneurship by providing a technically feasible, ethically grounded intelligent framework that empowers enterprises to reconcile efficiency with human-centric values, advancing SDG 8 (decent work and economic growth) and SDG 9 (industry, innovation, and infrastructure). Full article