Are psychologically healthy employees more proactive at work? Surprisingly, responses to this question are lacking as empirical research has overlooked the wellbeing-proactive performance relationship. Drawing insights from the conservation of resources theory and the motivational fit perspective, this study proposes that leader-member exchange and team-member exchange act as social resources that convey the benefits of psychological wellbeing to subsequent proactive performance. Moreover, job complexity and task interdependence-two job characteristics that enhance the motivational potential of social resources-are expected to amplify these positive indirect relationships. Data from a three-wave, time-lagged study conducted among employees (N = 318) from French-Canadian organizations were used to test our hypothesized model. The results indicated that leader-member exchange mediated a positive relationship between wellbeing and proactive performance and that the contribution of wellbeing to proactive performance via leader-member exchange was increased when job complexity was higher. We also found a negative indirect relationship between wellbeing and proactive performance via team-member exchange when team interdependence was lower. Theoretical and practical implications of this research are discussed.
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http://dx.doi.org/10.3390/ijerph18052492 | DOI Listing |
ISA Trans
January 2025
State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China; Beijing Key Laboratory of Transformative High-end Manufacturing Equipment and Technology, Tsinghua University, Beijing, 100084, China. Electronic address:
Multi-axis contouring control is crucial for ultraprecision manufacturing industries, contributing to meeting the ever-increasingly stringent performance requirements. In this article, a novel contouring adaptive real-time iterative compensation (CARIC) method is proposed to achieve extreme multi-axis contouring accuracy, remarkable trajectory generalization, disturbance rejection, and parametric adaptation simultaneously. Specifically, control actions generated by CARIC consist of robust feedback, adaptive feedforward, and online trajectory compensation components.
View Article and Find Full Text PDFPLoS One
January 2025
Institute of Visual Informatics, The National University of Malaysia (UKM), Bangi, Malaysia.
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enable adaptive insulin dosing control, they face numerous challenges, including safety and training efficiency, which have hindered their clinical application. This paper proposes a safe and efficient adaptive insulin delivery controller based on DRL.
View Article and Find Full Text PDFHeliyon
January 2025
Electrical and Information Engineering Department, Covenant University, P.M.B 1023, Ota, 112212, Ogun State, Nigeria.
Unplanned downtime in industrial sectors presents significant challenges, impacting both production efficiency and profitability. To tackle this issue, companies are actively working towards optimizing their operations and reducing disruptions that hinder their ability to meet customer demands and financial goals. Predictive maintenance, utilizing advanced technologies like data analytics, machine learning, and IoT devices, offers real-time equipment data monitoring and analysis.
View Article and Find Full Text PDFJ Adv Nurs
January 2025
Dipartimento Scienze Della Salute, Università degli Studi di Genova, Genova, Italy.
Aim(s): To adapt and validate the HSOPS 2 instrument for the Italian context and to describe the current patient safety culture amongst healthcare personnel working in Italian hospitals.
Design: Cross-sectional study.
Methods: We adapted and validated the HSOPS 2 instrument following the COSMIN guidelines: we performed a forward-backward translation, calculated the content validity index, evaluated face validity, acceptability (percentage of participants responding to all items on the questionnaire and to every specific item), construct validity (confirmatory factor analysis), and internal consistency (Cronbach's alpha for each dimension).
Background: The use of automated insulin delivery (AID) devices is now widespread in the management of type 1 diabetes (T1D), being used for younger and older children, adolescents and adults. The integration of insulin pumps with continuous glucose monitors (CGM) and smart management software in AID systems has significantly improved glycemic management compared to the separate application of each diabetes technology. The efficacy of AID systems has been demonstrated in randomized controlled trials (RCTs) but it is their application in real-world studies that fully demonstrates their impact for people with T1D.
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