Rodwell John, Noblet Andrew, Demir Defne, Steane Peter
Deakin University, Burwood, Melbourne, Victoria, Australia.
J Nurs Scholarsh. 2009;41(3):310-9. doi: 10.1111/j.1547-5069.2009.01285.x.
To examine the predictive capability of the demand-control-support (DCS) model, augmented by organizational justice variables, on attitudinal- and health-related outcomes for nurses caring for elderly patients.
The study is based on a cross-sectional survey design and involved 168 nurses working with elderly patients in facilities of a medium to large Australian organization.
Participants were asked to complete a questionnaire consisting of scales designed for measuring independent (e.g., demand, control, support, organizational justice) and dependent (e.g., job satisfaction, organizational commitment, wellbeing and psychological distress) variables. Multiple regression analyses were undertaken to identify significant predictors of the outcome variables.
The DCS model explains the largest amount of variance across both the attitudinal and health outcomes with 27% of job satisfaction and 49% of organizational commitment, and 33% of psychological distress and 35% of wellbeing, respectively. Additional variance was explained by the justice variables for job satisfaction (5%), organizational commitment (4%), and psychological distress (23%).
Using organizational justice variables to augment the DCS model was valuable in better understanding the work conditions experienced by nurses caring for elderly patients. Inclusion of curvilinear effects added clarity to the potentially artifactual nature of certain interaction variables.
The results indicated practical implications for managers of nurses caring for elderly patients in terms of developing and maintaining levels of job control, support, and fairness, as well as monitoring levels of job demands. The results particularly show the importance of nurses' immediate supervisors.
探讨由组织公正变量增强的需求 - 控制 - 支持(DCS)模型对护理老年患者的护士的态度和健康相关结果的预测能力。
该研究基于横断面调查设计,涉及澳大利亚一个大中型机构中168名护理老年患者的护士。
参与者被要求完成一份问卷,其中包括用于测量自变量(如需求、控制、支持、组织公正)和因变量(如工作满意度、组织承诺、幸福感和心理困扰)的量表。进行多元回归分析以确定结果变量的显著预测因素。
DCS模型分别解释了态度和健康结果中最大比例的方差,工作满意度的27%、组织承诺的49%、心理困扰的33%和幸福感的35%。组织公正变量对工作满意度(5%)、组织承诺(4%)和心理困扰(23%)的方差有额外解释。
使用组织公正变量增强DCS模型有助于更好地理解护理老年患者的护士所经历的工作条件。纳入曲线效应使某些交互变量潜在的人为性质更加清晰。
结果表明,对于护理老年患者的护士的管理者而言,在制定和维持工作控制、支持和公平水平以及监测工作需求水平方面具有实际意义。结果特别显示了护士直属上级的重要性。