Background: Nurses face high levels of stress and work demands, which can affect their work engagement and psychological well-being. Resilience and self-efficacy have been identified as important resources to improve nurses’ adaptation and work engagement.Objective: This study aimed to evaluate the mediating role of self-efficacy in the relationship between resilience and stress on work engagement in Peruvian nurses.Methods: A cross-sectional design was used, and data were collected from a sample of 459 nurses. Self-report questionnaires were administered to measure self-efficacy, resilience, stress, and work engagement. SEM analyses were performed to examine the relationship between these variables, and a mediation analysis was conducted to evaluate the role of self-efficacy as a mediator in the relationship between resilience, stress, and work engagement.Results: The results indicated a positive relationship between resilience, self-efficacy, and work engagement, as well as a negative relationship between stress and work engagement. Additionally, self-efficacy mediated the relationship between resilience and work engagement, as well as the relationship between stress and work engagement in nurses.Conclusion: Personal resources such as self-efficacy are a key factor in the relationship between resilience (work resources), stress (work demands), and work engagement of Peruvian nurses. Strengthening self-efficacy and resilience can improve work engagement and personal satisfaction of nurses. Hospital administrators and nursing managers should consider the importance of resilience, stress, work engagement, and self-efficacy in registered nurses and develop effective strategies to improve them. This can have a positive impact on the quality of care provided to patients and on the job satisfaction of nurses.

Background: Artificial Intelligence (AI) has permeated various aspects of daily life, including education, specifically within higher education settings. These AI technologies have transformed pedagogy and learning, enabling a more personalized approach. However, ethical and practical concerns have also emerged, including the potential decline in cognitive skills and student motivation due to excessive reliance on AI.Objective: To develop and validate a Scale for Dependence on Artificial Intelligence (DIA).Methods: An Exploratory Factor Analysis (EFA) was used to identify the underlying structure of the DIA scale, followed by a Confirmatory Factor Analysis (CFA) to assess and confirm this structure. In addition, the scale’s invariance based on participants’ gender was evaluated.Results: A total of 528 university students aged between 18 and 37 years (M = 20.31, SD = 3.8) participated. The EFA revealed a unifactorial structure for the scale, which was subsequently confirmed by the CFA. Invariance analyses showed that the scale is applicable and consistent for both men and women.Conclusion: The DAI scale emerges as a robust and reliable tool for measuring university students’ dependence on AI. Its gender invariance makes it applicable in diverse population studies. In the age of digitalization, it is essential to understand the dynamics between humans and AI to navigate wisely and ensure a beneficial coexistence.

Background: It is essential to identify the factors that influence the work performance of health professionals working in health care facilities, especially in the context of the COVID-19 pandemic, since these factors have an impact on the quality of medical care provided to the population. Objective: This study aimed to analyze the mediating role of work engagement in the relationship between job burnout, professional self-efficacy, life satisfaction, and job performance in Peruvian health care workers. Methods: Cross-sectional explanatory study, with the voluntary participation of 508 health professionals (physicians and nurses) of both sexes (70.7% women, 29.3% men), and from different health facilities in the city of Lima. All participants were administered the Single Burnout Item questionnaire, the Professional Self-Efficacy Scale (AU-10), the Satisfaction with Life Scale (SWL), the Individual Work Performance Questionnaire (IWPQ), and the Utrecht Work Engagement Scale (UWES-9). Structural Equation Modeling (SEM) was used for data analysis. Results: In the SEM analysis, it was found that for the mediation model the incremental goodness-of-fit indices were significant (χ² = 2292.313, gl = 659, P < .001, χ²/gl = 2.788). Career self-efficacy (β = .557, P < .001) and life satisfaction (β = .289, P < .001) were positive predictors of work engagement. While burnout was a negative predictor (β = .878, P < .001). The consistent mediation of work engagement of professional self-efficacy, life satisfaction, and burnout had a positive predictor effect on job performance (β = .878, P < .001). Conclusion: Research provides evidence that professional self-efficacy, life satisfaction, and burnout could influence job performance through work engagement.

Background: Life satisfaction as well as job satisfaction of teachers has a significant impact on educational outcomes.Objective: To evaluate a model of factors predicting life satisfaction through the mediating role of job satisfaction.Methods: This was a cross-sectional study, with a sample of 300 primary school teachers of both sexes (68% female, 32% male) and with a mean age of 42.52 years (SD = 10.04). They were administered the General Self-Efficacy Scale, the Satisfaction with Life Scale (SWLS), the Workload Scale (ECT), the Generic Job Satisfaction Scale, and the Organizational Commitment Questionnaire (OCQ). Structural equation modeling (SEM) was used for data analysis.Results: The SEM analysis found significant goodness-of-fit indices: (χ2 = 13.739; df = 5; p = <0.001; CFI = 0.99, TLI = 0.98, RMSEA = 0.05, SRMR = 0.04). Specifically, self-efficacy and organizational commitment were positive predictors of job satisfaction, while workload was a negative predictor of job satisfaction. The mediating effect of job satisfaction between self-efficacy, life satisfaction, workload, and overall life satisfaction was confirmed.Conclusion: The results confirm the importance of self-efficacy, organizational commitment, and workload in job satisfaction and overall life satisfaction of elementary education teachers. Job satisfaction acts as a mediator in this relationship. It is important to reduce workload and promote self-efficacy and organizational commitment to improve the well-being and satisfaction of teachers.

(1) Background: In university contexts, the effectiveness of work teams is vital for institutional success and the personal development of an institution’s members. Objective: Our aim is to understand the relationships between emotional intelligence, team leadership, organizational culture, work climate, and creative synergy with team effectiveness. (2) Methods: We used a cross-sectional predictive design study using structural equation modeling (SEM), in which 512 surveys of employees of a private Peruvian university were analyzed. (3) Results: Leadership and emotional intelligence were found to significantly improve team effectiveness. In addition, organizational culture, work climate, and creative synergy act as mediators in these relationships, enhancing team effectiveness. The adjusted model presented adequate incremental $(x^2=9452.498,\mathrm{g}\mathrm{l}=3391,p<0.001)$ and comparative $(\mathrm{T}\mathrm{L}\mathrm{I}=0.998,\mathrm{C}\mathrm{F}\mathrm{I}=0.998,\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}\mathrm{A}=0.017\mathrm{y}\mathrm{S}\mathrm{R}\mathrm{M}\mathrm{R}=0.033)$ goodness-of-fit indices. (4) Conclusions: The results showed that the development of emotional competencies and leadership skills is essential to optimize the effectiveness of work teams in universities. This integrated model not only provides a solid theoretical framework for future research, but also offers practical recommendations for improving the management and performance of work teams.

Background: The Job Demands and Resources (JD-R) model is used to examine predictors of well-being, work engagement, and individual or organizational outcomes. According to the model, work engagement and communication skills play a mediating role between work-family conflict and resilience to job satisfaction in nurses. Methods: A cross-sectional study was conducted considering 431 Peruvian nurses of mean age ( M = 40.31 years; SD = 10.94) ranging from 22 to 68 years working in public hospitals in the Lima region. Data were collected using a self-reported form of the Job Satisfaction Scale, communication skills, work engagement, work-family conflict, and resilience. The theoretical model was evaluated using structural equation modeling (SEM). Results: A theoretical model with adequate fit was obtained [χ²(2) = 6.0, P < .001, CFI = 0.995, RMSEA = 0.068, SRMR = 0.015]. Results indicated an inverse relationship between work-family conflict with communication skills (β = −.24, P < .001) and work engagement (β = −.10, P = .003). Likewise, resilience had an influence on communication skills (β = .55, P < .001) and work engagement (β = .33, P < .001). In addition, the model explains 71% of job satisfaction. Also, the results indicate the influence of work-family conflict and resilience through the mediating role of work engagement and work-family conflict on job satisfaction. Conclusions: The model confirmed that work engagement and communication skills are valid moderators to mitigate work-family conflict and strengthen resilience that favors job satisfaction in nurses.