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:: Volume 14, Issue 2 (9-2019) ::
2019, 14(2): 48-56 Back to browse issues page
Predictability of Nurses Ethical Behavior from Human Resource Management Practices
Abstract:   (2182 Views)
Background: Today, commitment to ethical behavior is one of the most important concerns of patient care and medical field. The HR managers try to improve the ethical climate in this domain by using effective strategies and practices. Therefore, the aim of this study was to examine the predictability of nurses' ethical behavior by HRM activities by using the public health service networks.
Method: The research method was descriptive- correlation. Population of study includes all of nurses of Mashhad University of Medical Sciences. Sample size was calculated about 153 nurses by Cochran formula. 180 questionnaires were distributed to ensure that the questionnaires were completed and 176 questionnaires were analyzed. Data were collected by a questionnaire. Data were analyzed by artificial neural network through MATLAB2015 software.
Results: The results of this study showed that human resource management practices predict nurses’ ethical behavior.
Conclusion: The results of the neural network sensitivity analysis showed that in human resource management practices, "employee relations" most of and "performance evaluation" have the lowest impact on nurses ethical behavior
 
Keywords: Ethics, Ethical behavior, Human resource management, Artificial neural network
Full-Text [PDF 880 kb]   (642 Downloads)    
Type of Study: Research | Subject: Special
Received: 2019/09/10 | Accepted: 2019/09/10 | Published: 2019/09/10
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Predictability of Nurses Ethical Behavior from Human Resource Management Practices. Ethics in Science and Technology 2019; 14 (2) :48-56
URL: http://ethicsjournal.ir/article-1-1447-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 2 (9-2019) Back to browse issues page
فصلنامه اخلاق در علوم و فناوری Ethics in Science and Technology
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