Suliman S. Olayan School of Business, American University of Beirut, Lebanon; Evidence-based Healthcare Management Unit, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Int J Nurs Stud. 2014 Jan;51(1):93-110. doi: 10.1016/j.ijnurstu.2013.06.018. Epub 2013 Aug 5.
Absenteeism and turnover among healthcare workers have a significant impact on overall healthcare system performance. The literature captures variables from different levels of measurement and analysis as being associated with attendance behavior among nurses. Yet, it remains unclear how variables from different contextual levels interact to impact nurses' attendance behaviors.
The purpose of this review is to develop an integrative multilevel framework that optimizes our understanding of absenteeism and turnover among nurses in hospital settings.
We therefore systematically examine English-only studies retrieved from two major databases, PubMed and CINAHL Plus and published between January, 2007 and January, 2013 (inclusive).
Our review led to the identification of 7619 articles out of which 41 matched the inclusion criteria. The analysis yielded a total of 91 antecedent variables and 12 outcome variables for turnover, and 29 antecedent variables and 9 outcome variables for absenteeism. The various manifested variables were analyzed using content analysis and grouped into 11 categories, and further into five main factors: Job, Organization, Individual, National and inTerpersonal (JOINT). Thus, we propose the JOINT multilevel conceptual model for investigating absenteeism and turnover among nurses.
The JOINT model can be adapted by researchers for fitting their hypothesized multilevel relationships. It can also be used by nursing managers as a lens for holistically managing nurses' attendance behaviors.
医疗保健工作者的旷工和离职对整体医疗系统的绩效有重大影响。文献从不同的测量和分析层面捕捉到与护士出勤行为相关的变量。然而,不同的上下文层面的变量如何相互作用以影响护士的出勤行为仍不清楚。
本综述的目的是开发一个综合的多层次框架,以优化我们对医院环境中护士旷工和离职的理解。
因此,我们系统地检查了从两个主要数据库PubMed 和 CINAHL Plus 中检索到的仅英文的研究,这些研究发表于 2007 年 1 月至 2013 年 1 月(包括在内)。
我们的综述导致确定了 7619 篇文章,其中 41 篇符合纳入标准。分析产生了总共 12 个离职的 91 个前因变量和 9 个旷工的 29 个前因变量。各种表现出来的变量使用内容分析进行分析,并分为 11 类,进一步分为五个主要因素:工作、组织、个人、国家和人际(JOINT)。因此,我们提出了 JOINT 多层次概念模型,以调查护士的旷工和离职。
JOINT 模型可以被研究人员适应于他们假设的多层次关系。护理经理也可以将其作为一个整体管理护士出勤行为的视角。