On the Frontlines: The Impact of the COVID-19 Pandemic on Social Workers' Well-Being

被引:12
|
作者
Tayri, Talia Meital Schwartz [1 ]
机构
[1] Bengur Univ Negev, Dept Social Work, Artificial Intelligence Social Welf Res Lab, IL-46379 Beer Sheva, Israel
关键词
COVID-19; pandemic; machine learning emotion detection; moral distress; moral injury; social work services; JOB DEMANDS; STRESS; DISASTER; SUPPORT;
D O I
10.1093/sw/swac050
中图分类号
C916 [社会工作、社会管理、社会规划];
学科分类号
1204 ;
摘要
The crisis created by the spread of COVID-19 brought increasing needs and referrals to social welfare services in many countries. However, at the same time, social services suffered from staff cutbacks and service closures, resulting in significant workload increases to address the hardships associated with the pandemic. This article investigates the impact of the COVID-19 pandemic on Israeli social workers' well-being, using a mixed-methods design with a sample of 2,542 licensed social workers. Findings show that over 70 percent of social workers suffered from at least one health problem related to their work. Path analysis findings indicated that social workers who experienced greater service restrictions reported a greater decrease in job satisfaction and experienced higher levels of stress and work-related problems. Machine learning emotion-detection analysis revealed that the pandemic affected their lives, causing feelings of fear, frustration, and sadness. This article demonstrates how social workers whose work was characterized by greater service restrictions were less satisfied with their jobs, more stressed, and experienced greater job-related health problems, and concludes with a discussion of the implications for social work practice in times of crisis.
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页码:69 / 80
页数:12
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