Suppr超能文献

健康、工作环境与工作事故。

Well being, work environment and work accidents.

作者信息

Kirschenbaum A, Oigenblick L, Goldberg A I

机构信息

Faculty of Industrial Engineering and Managment, Technion-Israel Institute of Technology, Haifa.

出版信息

Soc Sci Med. 2000 Mar;50(5):631-9. doi: 10.1016/s0277-9536(99)00309-3.

Abstract

We examine factors that influence accident proneness among employees. We agree that the determinants of accident proneness include organizational, emotional and personal factors. Using logistic regression we estimated three models, and their predictability for accident proneness among sample of 200 injured workers interviewed upon entering hospital emergency wards in Israel. Work injuries were not contingent on age, religion, nor education. The effects of gender were strong but non-significant. Subcontracted and higher-paid workers are more likely to get repeat injuries. Prior injury experience sensitized employees to stronger perceptions of risk associated with unsafe practices. Large family households, ameliorates stress feelings and lessens the likelihood of accident proneness while poor housing conditions have the opposite effect. The full model demonstrates considerable prediction of injuries when focusing on type of employment, personal income level, being involved in dangerous jobs, emotional distress and a poor housing environment. The model contains most of the significant results of interest and provides a high level of predictability for work injuries.

摘要

我们研究了影响员工事故倾向的因素。我们认同事故倾向的决定因素包括组织、情绪和个人因素。我们使用逻辑回归估计了三个模型,以及它们对在以色列进入医院急诊病房时接受访谈的200名受伤工人样本中事故倾向的预测能力。工伤与年龄、宗教或教育无关。性别的影响很大但不显著。分包工和高薪工人更有可能再次受伤。先前的受伤经历使员工对与不安全行为相关的风险有更强的认知。大家庭能缓解压力情绪,降低事故倾向的可能性,而恶劣的住房条件则有相反的效果。完整模型在关注就业类型、个人收入水平、从事危险工作、情绪困扰和恶劣住房环境时,对受伤情况有相当大的预测能力。该模型包含了大部分感兴趣的显著结果,并为工伤提供了较高水平的预测能力。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验