Dyrbye Liselotte N, Satele Daniel, Shanafelt Tait
Division of Primary Care Internal Medicine, Department of Medicine (Dr Dyrbye), Biomedical Statistics and Informatics, Department of Health Sciences Research (Mr Satele), and Division of Hematology, Department of Medicine (Dr Shanafelt), Mayo Clinic College of Medicine, Rochester, Minnesota.
J Occup Environ Med. 2016 Aug;58(8):810-7. doi: 10.1097/JOM.0000000000000798.
To determine whether the well-being index (WBI) can identify US workers in distress and stratify quality of life (QOL).
We used data from 5392 US workers and 6880 physicians to evaluate the efficacy of the WBI and an expanded version of the WBI (eWBI) to identify individuals with distress (high fatigue, burnout, low QOL, and suicidal ideation) and high QOL.
Individuals with distress were more likely to endorse each of the WBI items as well as a greater number of total items (all P < 0.001). The eWBI improved stratification among individuals with low scores and also identified individuals with high QOL in both samples.
The eWBI appears to be a useful screening tool to identify individuals in distress across a variety of domains and identify individuals with high well-being.
确定幸福指数（WBI）是否能够识别处于困境中的美国劳动者，并对生活质量（QOL）进行分层。
我们使用了来自5392名美国劳动者和6880名医生的数据，以评估WBI及其扩展版本（eWBI）识别处于困境（高疲劳、倦怠、低生活质量和自杀意念）和高生活质量个体的功效。
处于困境中的个体更有可能认可WBI的每一项内容以及更多的总项目数（所有P<0.001）。eWBI改善了低分个体之间的分层，并且在两个样本中都识别出了高生活质量的个体。
eWBI似乎是一种有用的筛查工具，可用于识别各个领域中处于困境的个体以及幸福度高的个体。
