Department of Statistics & Business, University of Cordoba, Cordoba, Spain.
PLoS One. 2022 Aug 4;17(8):e0271134. doi: 10.1371/journal.pone.0271134. eCollection 2022.
The present work aims to analyze the properties of the working conditions recorded in the Sixth European Working Conditions Survey (EWCS); with it, it has being built seven independent indexes about different aspects of work' quality in the health sector, and these constructs are used to evaluate their effects on work engagement (WE). In this sense, the originality of incorporating teamwork as a modulating variable is included. To analyze the effects of the job quality index (JQI) on the WE, a logistic regression model is proposed for a total of 3044 workers within the health sector, differentiating between those who work or not in a team; in a first stage and these estimates are compared with those obtained using an artificial neural network model, and both are used for the consideration of the research hypotheses about several causal factor. An important contributions of the study, it is related to how work commitment is mainly influenced by prospects, social environment, intensity and earnings, all of them related to job performance. Therefore, knowledge of the determinants of work commitment and the ability to modulate its effects in teamwork environments is necessary for the development of truly sustainable Human Resources policies.
本研究旨在分析第六届欧洲工作条件调查（EWCS）中记录的工作条件的属性；借此构建了七个关于卫生部门工作质量不同方面的独立指标，并利用这些指标来评估其对工作投入的影响。在这方面，纳入团队合作作为调节变量的创新性也包含在内。为了分析工作质量指数（JQI）对工作投入的影响，针对卫生部门的 3044 名员工提出了一个逻辑回归模型，区分了是否在团队中工作的员工；在第一阶段，将这些估计值与使用人工神经网络模型获得的估计值进行比较，并将两者都用于考虑关于几个因果因素的研究假设。本研究的一个重要贡献是，它涉及到工作投入主要受前景、社会环境、强度和收入的影响，所有这些都与工作绩效有关。因此，了解工作投入的决定因素以及在团队合作环境中调节其影响的能力，对于制定真正可持续的人力资源政策是必要的。
