Management of work stress and burnout among community nurses arising from the COVID-19 pandemic

The COVID-19 pandemic has increased workload demands for many NHS staff including those working in the community. Nurse managers can make a difference by being authentic leaders, nurturing a supportive organisation where the workload is managed participatively and self-kindness is legitimate. Unfortunately some staff may experience burnout and this article presents a personal management plan to address the symptoms of burnout and aid recovery, although it cannot promote a total recovery if the cause of the symptoms remains unaddressed.

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Nurse Managers Attributes and Work Stress Levels at Assiut University Hospitals

Assiut Scientific Nursing Journal ◽

10.21608/asnj.2020.27933.1009 ◽

2020 ◽

Vol 0 (0) ◽

pp. 0-0

Author(s):

noura esmail ◽

noura esmail

Keyword(s):

Work Stress ◽

Nurse Managers ◽

University Hospitals ◽

Stress Levels

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The Organization’s Sustainable Work Stress and Maladjustment Management Plan by Predicting Early Retirement through Big Data Analysis: Focused on the Case of South Korea

Sustainability ◽

10.3390/su14010434 ◽

2021 ◽

Vol 14 (1) ◽

pp. 434

Author(s):

Hyunjung Ham ◽

Eunbee Kim ◽

Daeyeon Cho

Keyword(s):

Big Data ◽

Predictive Model ◽

Work Stress ◽

Early Retirement ◽

Data Analytics ◽

Nearest Neighbor ◽

Big Data Analytics ◽

Management Plan ◽

Big Data Analysis ◽

K Nearest Neighbor

The purpose of this study is to verify the predictive model of early retirees’ responses to work stress and maladjustment to the company by utilizing big data analytics and to extract the reasons for early retirement from the personnel information. Company A’s personnel information of employees working in the company for 10 years was used, K-Nearest Neighbor (K-NN) algorithm was used to verify the predictive model of early retirees, and Decision Tree Analysis algorithm was used to extract the causing factors. According to the analysis results, first, the verification of the predictive model of early retirees based on the personnel information data showed 98% accuracy. Second, among the personnel information items, the ranking of items with high relevance for early retirement was the distance between the company and the residence (first place), the recent promotion history (second place), and whether or not to have the license (third place) out of a total of 18 items. The results of the analysis conducted in this study suggest that HRD intervention is required in the provision of problem-solving solutions involved in the HRM field, which is expected to be effective as a basic diagnostic tool for HR diagnosis involving HRD and HRM. In addition, this study may provide a detailed analysis of early retirement due to work stress and maladjustment of young people.

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