Background: Extensive research has been conducted treating burnout as an independent variable and performance as a dependent variable to proffer possible solutions to burnout and job performance among academics. Despite this, the burnout crises persist and are exacerbated by the ongoing global proliferation of higher education. Acknowledging this, the current study explored whether performance may contribute to the emergence of burnout.
Methods: The study's sample population comprised 689 academics from Jiangsu province, China. Key Performance Indicator (KPI) results served to measure performance. Psychological counselling and Burnout were calculated using mental health results garnered from the universities. Data was collected on respondents' demographic characteristics and work situations. The mean scores were 0.517 (SD = 0.5) for gender and 1.586 (SD = 1.103) for age. The relationship among performance, job burnout, and psychological counselling was analysed via a cross-sectional survey deploying grouped regression.
Results: Academics' job performance was found to regulate their burnout (β = -0.058, P < 0.01). Higher performance of academics was significantly associated with lower job burnout and psychological counselling. Furthermore, psychological counselling significantly moderated job burnout (β = -0.012, P < 0.05) among academics without regulating their job performance.
Conclusion: The paper supplements the discourse on job burnout and academic performance by suggesting a pre-counselling measure as a strategy to address the crises of burnout. The paper argued that the continued competence of employees should prevent burnout in Higher education and ensure better job performance.
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http://dx.doi.org/10.1186/s12889-024-19224-z | DOI Listing |
Sci Rep
December 2024
School of Electrical Engineering, Vellore Institute of Technology, Chennai, 600127, India.
Spherical tanks have been predominantly used in process industries due to their large storage capability. The fundamental challenges in process industries require a very efficient controller to control the various process parameters owing to their nonlinear behavior. The current research work in this paper aims to propose the Approximate Generalized Time Moments (AGTM) optimization technique for designing Fractional-Order PI (FOPI) and Fractional-Order PID (FOPID) controllers for the nonlinear Single Spherical Tank Liquid Level System (SSTLLS).
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December 2024
Department of Physics, Laghman University, Mehtarlam City, Laghman, 2701, Afghanistan.
Aluminum alloys have promising characteristics which make them more useful in industrial applications for thermal management and entropy of the fluidic system. Hence, the current research deals with the analysis of entropy and thermal performance of (CHO-HO)/50:50% saturated by (AA7072/AA7076/TiAIV) alloys. Traditional problem modified using enhanced characteristics of ternary alloys and hydrocarbon 50:50% base fluid.
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December 2024
Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.
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December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
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December 2024
Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Reservoir computing (RC) is a powerful machine learning algorithm for information processing. Despite numerous optical implementations, its speed and scalability remain limited by the need to establish recurrent connections and achieve efficient optical nonlinearities. This work proposes a streamlined photonic RC design based on a new paradigm, called next-generation RC, which overcomes these limitations.
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