Job Satisfaction among Transferred Nurses: Associations with Work Environment, Peer Support, and Grit

Objective This study aimed to estimate the prevalence of musculoskeletal symptoms and work-related musculoskeletal disorders (WMSDs) among orthopedic nurses, identify demographic, occupational, and lifestyle characteristics associated with WMSDs, and explore whether routinely collected characteristics could discriminate nurses with WMSDs from those without. Method A single-center cross-sectional study was conducted among nurses at a tertiary orthopedic specialty hospital in China between March and November 2023. Conventional analyses included multivariable logistic regression, modified Poisson regression with robust standard errors, and negative binomial regression. Logistic regression as a benchmark, elastic-net logistic regression, random forest, XGBoost, and support vector machine were compared using repeated 5-fold cross-validation with fold-specific preprocessing. Prediction performance was assessed using AUC with bootstrap 95% CIs, PR-AUC, Brier score, calibration intercept and slope, and descriptive threshold metrics; TreeSHAP was used for model interpretation. Result Among 948 nurses with valid questionnaires, 654 reported musculoskeletal symptoms in the previous 12 months, irrespective of work attribution (68.99%). After excluding 44 participants with uncertain work-related attribution, 604/904 participants were classified as having work-related WMSDs (66.81%). Each 1-point increase in the strict ergonomic risk score was associated with WMSDs in logistic regression (adjusted OR = 2.631, 95% CI 2.039–3.432; p < 0.001) and modified Poisson regression (adjusted PR = 1.283, 95% CI 1.203–1.369; p < 0.001). The highest observed AUC was 0.752 (95% CI 0.721–0.791) for the domain random forest model; the domain XGBoost model had the highest PR-AUC (0.841). Conclusion Musculoskeletal symptoms and WMSDs were common among orthopedic nurses in this single-center sample. Occupational exposure and postural load were associated with WMSDs. The exploratory prediction models showed limited-to-moderate discrimination and warrant prospective multicenter external validation before practical application.

The development of digital-based work systems has increased job demands and technology use, which may lead to burnout among workers, particularly in the telecommunications sector. This study aimed to determine the relationship between job demands and technostress with burnout levels among employees of PT Telkom Infrastruktur Indonesia in Medan. This study employed a quantitative cross-sectional design. The population consisted of 55 employees, and all members of the population were selected as samples using a total sampling technique. Data were collected using the Job Demands-Resources Questionnaire (JD-RQ), Technostress Creators Scale, and Oldenburg Burnout Inventory (OLBI). Data analysis was conducted using the Spearman Rank Correlation test with a significance level of 0.05. The results showed a significant and strong positive relationship between job demands and burnout, with a p-value = 0.001 and a correlation coefficient of r = 0.750. In addition, a significant and strong positive relationship was also found between technostress and burnout, with a p-value = 0.001 and a correlation coefficient of r = 0.687. High job demands and technostress were associated with increased burnout. The company is advised to strengthen burnout prevention efforts by optimizing workload evaluations that take actual working conditions into account, providing regular training on the use of digital systems, and enhancing employee recovery initiatives through the optimal utilization of annual leave and better management of work-related communication outside working hours.

This study aims to address an important gap in the literature by examining the effects of technostress and safety climate on employees' technological productivity and by evaluating the moderating role of perceived organizational support in these relationships.Analyses conducted on survey data collected from 425 employees working in the defense industry reveal that technostress has a significant negative effect on technological productivity, whereas safety climate has a positive effect on technological productivity.The findings further indicate that perceived organizational support moderates the relationship between safety climate and technological productivity, strengthening the positive impact of safety climate on technological productivity.However, perceived organizational support does not exhibit a significant moderating effect on the relationship between technostress and technological productivity.By examining technostress, safety climate, and perceived organizational support-constructs that are rarely addressed together in the literature-within an integrated framework, this study contributes to a more comprehensive understanding of technological productivity.Furthermore, its focus on the defense industry, characterized by high-technology intensity and high reliability requirements, fills an important gap in the literature and provides actionable insights for improving employee well-being, safety, and technological productivity.

Teacher performance is a key determinant of educational quality and the successful implementation of learning processes. Among the factors that may influence teacher performance are the adequacy of educational facilities and infrastructure, as well as the quality of the working environment. This study aims to examine the influence of facilities and infrastructure, together with the work environment, on teacher performance at SMA Negeri 1 Batukliang Utara, Central Lombok Regency. A quantitative approach with a descriptive research design was employed. The study involved all 33 active teachers using a total sampling technique. Data were collected through a structured questionnaire based on a five-point Likert scale and analyzed using multiple linear regression with IBM SPSS Statistics version 26. The findings reveal that facilities and infrastructure do not have a significant partial effect on teacher performance (β = 0.017; p = 0.933), whereas the work environment has a positive and statistically significant effect (β = 0.770; p = 0.003). Simultaneously, both independent variables significantly influence teacher performance (F = 10.840; p < 0.001), explaining 41.9% of the variance in teacher performance, while the remaining 58.1% is attributable to other factors not included in the research model. These findings indicate that a supportive and conducive work environment plays a more substantial role than educational facilities in improving teacher performance. Therefore, school management should prioritize the creation of a positive work environment while continuing to improve educational facilities to support teachers' professional responsibilities.

This study examines how emotional intelligence (EI) affects work–life balance (WLB), job satisfaction, and work engagement among Lebanese employees, drawing on the job demands–resources (JD–R) and spillover theories. Data were collected through an online survey from 244 Lebanese employees and analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that emotional intelligence positively predicts job satisfaction (β = 0.366, p < 0.001) and work engagement (β = 0.307, p < 0.001). Emotional intelligence also significantly predicts work–life balance (β = 0.251, p < 0.001). Furthermore, work–life balance and job satisfaction sequentially mediate the relationship between emotional intelligence and work engagement (indirect effect β = 0.046, p = 0.008), indicating partial mediation. These findings highlight the complementary roles of personal resources (emotional intelligence) and contextual resources (work–life balance) in shaping employee attitudes and behaviors. This research contributes to the limited literature and extends the study of emotional intelligence and employee well-being by offering fresh insights and practical implications. The research concludes with recommendations for policymakers by emphasizing the importance of aligning employee needs with organizational goals to create more effective and human-centered workplace policies. The study also includes limitations and recommendations for future research.

این مطالعه به بررسی تأثیر هوش هیجانی (EI) بر تعادل کار–زندگی (WLB)، رضایت شغلی و درگیری شغلی در میان کارکنان لبنانی می‌پردازد و از نظریه‌های تقاضا–منابع شغلی (JD–R) و سرریز بهره می‌گیرد. داده‌ها از طریق یک پرسشنامه آنلاین از ۲۴۴ نفر از کارکنان لبنانی جمع‌آوری و با استفاده از مدل‌سازی معادلات ساختاری حداقل مربعات جزئی (PLS-SEM) تحلیل شدند. نتایج نشان داد که هوش هیجانی به طور مثبت رضایت شغلی (β = ۰.۳۶۶، p < ۰.۰۰۱) و درگیری شغلی (β = ۰.۳۰۷، p < ۰.۰۰۱) را پیش‌بینی می‌کند. همچنین، هوش هیجانی به طور معناداری تعادل کار–زندگی (β = ۰.۲۵۱، p < ۰.۰۰۱) را پیش‌بینی می‌کند. افزون بر این، تعادل کار–زندگی و رضایت شغلی به صورت متوالی رابطه بین هوش هیجانی و درگیری شغلی را میانجی‌گری می‌کنند (اثر غیرمستقیم β = ۰.۰۴۶، p = ۰.۰۰۸) که نشان‌دهنده میانجی‌گری جزئی است. این یافته‌ها نقش‌های مکمل منابع فردی (هوش هیجانی) و منابع زمینه‌ای (تعادل کار–زندگی) را در شکل‌دهی نگرش‌ها و رفتارهای کارکنان برجسته می‌کند. این پژوهش به ادبیات محدود موجود افزوده و مطالعه هوش هیجانی و بهزیستی کارکنان را با ارائه بینش‌های نو و پیامدهای عملی گسترش می‌دهد. پژوهش با ارائه توصیه‌هایی برای سیاست‌گذاران و تأکید بر اهمیت همسویی نیازهای کارکنان با اهداف سازمانی به منظور ایجاد سیاست‌های محیط کار مؤثرتر و انسان‌محور به پایان می‌رسد. همچنین، محدودیت‌ها و پیشنهادهایی برای پژوهش‌های آتی ارائه شده است.