卢旺达工作场所压力管理对机构绩效的影响建模:卢旺达 Kibogora 二级教学医院的案例证据

Oscar Nsengumuremyi, Mweruli Tubanambazi Fidèle, Jean Claude Amani
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引用次数: 0

摘要

该研究题为 "卢旺达工作场所压力管理对机构绩效的影响建模":卢旺达 Kibogora 二级教学医院的案例证据》,旨在评估工作场所压力管理对所研究地区机构绩效的贡献。这项研究的目的是探索如何利用多项式逻辑回归(MLR)来模拟工作场所压力管理对机构绩效的影响。为此,采用最大似然估计法对收集到的数据集进行了多项式逻辑回归建模,以找到描述自变量和因变量之间关系的模型参数估计值,并确定对所研究领域的机构绩效有重大影响的预测变量的显著性。本研究采用定性和定量两种方法向 321 名受访者收集数据。数据收集采用了问卷调查和访谈表技术,并使用 SPSS-23 进行了分析。分析结果表明,在总共 12 个解释变量中,年龄、性别、是否有执照和自身对工作场所压力的回避等解释变量被排除在对卢旺达基博戈拉二级教学医院的机构绩效有重大影响的预测变量培训集之外。在对数据进行总体拟合的模型选择中,获得的对因变量有显著贡献的变量包括:面临工作压力问题的工人的状况、研究对象工人的教育水平、工人的工作经验、在 Kibogora 二级教学医院采用的主要压力预防措施以及在 Kibogora 二级教学医院工作的工人对压力应对策略的了解。所选模型的参数估计结果显示,一旦工作场所的压力管理得到控制,最能预测基博戈拉二级教学医院提高机构绩效概率的解释变量是员工的教育水平、员工的工作经验和基博戈拉二级教学医院采用的主要压力预防措施。最后,研究建议,关于在研究领域采取的压力预防措施,基博戈拉二级教学医院的最高管理层应与其他资助方合作,确保所有员工都接受过如何避免职业危害的培训,最重要的是,医院需要为员工提供娱乐活动。在压力源识别方面,研究建议基博戈拉二级教学医院需要增加对员工的激励措施,以调动员工的工作积极性,同时也应增加医院的员工人数,以减少超负荷工作带来的挑战。 文章可视化:
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MODELLING THE EFFECT OF WORKPLACE STRESS MANAGEMENT ON INSTITUTION’S PERFORMANCE IN RWANDA: A CASE EVIDENCE FROM KIBOGORA LEVEL II TEACHING HOSPITAL, RWANDA
The study titled Modelling the effect of workplace stress management on institution’s performance in Rwanda: A case evidence from Kibogora Level II Teaching Hospital, Rwanda was about assessing the contribution of workplace stress management on institution’s performance in the area under study. The study was guided with the objective of exploring the utilization of multinomial logistic regression (MLR) in modeling the effect of workplace stress management on an institution’s performance. In this regard, the MLR model was performed using a maximum likelihood estimation method on the data set collected to find the parameter estimates of the model describing the relationship between the independent and the dependent variables and determine the significance of the predictor variables that contribute significantly to the institution’s performance in the area under study. The study adopted both qualitative and quantitative approaches to collect data from 321 respondents. Data were collected using questionnaire and interview schedule techniques and analyzed using SPSS-23. In this analysis, the results revealed that on the total of twelve explanatory variables, the explanatory variables such as age, gender, the status of licensed or not and own avoidance of stress at the workplace of the workers were dropped from the training set of predictors variables that contribute significantly to the institution’s performance at Kibogora Level II Teaching Hospital, Rwanda. In the model selection that overall fits well the data, the obtained variables that contributed significantly to the dependent variable were Status of workers who faced the issue of having a stress at the workplace, education level of the workers to whom the study was conducted, working experience of the workers, the main applied stress preventive measures at Kibogora Level II Teaching Hospital and knowledge on the strategies to use for coping with the stress of workers working at Kibogora Level II Teaching Hospital. The parameters estimate of the selected model revealed that the explanatory variables that best predicted the probability of increasing the institution’s performance at Kibogora Level II Teaching Hospital once the stress management is controlled at the workplace were education level of the workers, working experience of the workers and main stress preventive measures applied by Kibogora Level II Teaching hospital. Finally, the study recommended that regarding stress preventive measures adopted in the area under study, the top management of Kibogora Level II Teaching Hospital in partnership with other funders should be ensure that all employees are trained on how to avoid occupational hazards and most importantly, the hospital need to provide recreational activities to the employees. On stress source identification, the study recommends that Kibogora Level II Teaching Hospital needs to increase incentives to employees for motivation while on duty and the hospital staff should as well be increased so as to reduce the challenge of work overloaded.  Article visualizations:
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