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Information Journal Paper

Title

Predictability of Nurses Ethical Behavior from Human Resource Management Practices

Pages

  48-56

Abstract

 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.

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    APA: Copy

    NIKKHAH FARKHANI, ZAHRA, & ARABASADI, ZEYNAB. (2019). Predictability of Nurses Ethical Behavior from Human Resource Management Practices. ETHICS IN SCIENCE & TECHNOLOGY, 14(2 ), 48-56. SID. https://sid.ir/paper/122723/en

    Vancouver: Copy

    NIKKHAH FARKHANI ZAHRA, ARABASADI ZEYNAB. Predictability of Nurses Ethical Behavior from Human Resource Management Practices. ETHICS IN SCIENCE & TECHNOLOGY[Internet]. 2019;14(2 ):48-56. Available from: https://sid.ir/paper/122723/en

    IEEE: Copy

    ZAHRA NIKKHAH FARKHANI, and ZEYNAB ARABASADI, “Predictability of Nurses Ethical Behavior from Human Resource Management Practices,” ETHICS IN SCIENCE & TECHNOLOGY, vol. 14, no. 2 , pp. 48–56, 2019, [Online]. Available: https://sid.ir/paper/122723/en

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