随意的
劳动力
工作不安全感
危险工作
心理学
工作(物理)
心理健康
苦恼
心理困扰
竞赛(生物学)
睡眠(系统调用)
人口经济学
精神科
临床心理学
政治学
经济增长
经济
生物
操作系统
工程类
机械工程
法学
计算机科学
生态学
作者
Gillian Weston,Anne McMunn
出处
期刊:Handbook series in occupational health sciences
日期:2023-01-01
卷期号:: 319-341
标识
DOI:10.1007/978-3-031-30492-7_15
摘要
Precarious work is characterized by the absence of the standard employment relationship and by a degree of employment insecurity. It contributes to the flexible workforce which has grown to respond to competition, technical innovation, global crises, and 24/7 business operations. The aim of this chapter is to outline what is known about the associations between this work pattern and health. It focuses on the two main forms, temporary work and self-employment, and two health measures, mental health and sleep, because work-related psychological illness and insufficient sleep contribute to lost working days and work-related accidents. A review of the literature suggests that in comparison to permanent employees, temporary workers, particularly those considered most vulnerable to the labor market, such as casual workers, may experience more psychological distress, whereas self-employed workers have been found to experience more stress than employees, but also greater subjective and psychological well-being. Additionally, while job insecurity has been associated with poor sleep quality and sleeping less than and more than the recommended 7–8 h per night, there is no evidence that temporary workers experience poor or insufficient sleep, and only a little evidence that self-employed workers experience poor sleep quality and longer sleep durations than employees. However, this evidence, which is mainly cross-sectional, is somewhat sparse and contradictory, possibly because of the heterogeneity in how researchers measure precarious work, and their tendency mostly to study male workers and those working in specific occupations or workplaces, and to exclude the most precarious types of temporary and self-employed workers.
科研通智能强力驱动
Strongly Powered by AbleSci AI