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The Profile of Saudi Nursing Workforce: A Cross-Sectional Study

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  • Mohammad Alboliteeh
  • Judy Magarey
  • Richard Wiechula

Abstract

Introduction . The Royal Monarchy in Saudi Arabia decreed that all sectors of the workforce would be subject to a policy of “Saudisation†to reduce the reliance on the expatriate workforce and to reduce the unemployment rate of Saudi nationals (Al-Mahmoud et al., 2012). Methodology . A cross-sectional design was chosen to investigate the research questions. The population of this study comprised Saudi Registered Nurses working in MOH hospitals in Riyadh which is the main health care provider in Saudi Arabia (Aboul-Enein, 2002; MOH, 2009). Results and Findings . A total number of 1,198 questionnaires were distributed and 61.2% ( ) were returned. The findings of the study showed that the questionnaires were collected from an equal portion of the study locale and that a sample of 741 is enough to create a strong conclusion and answer the problem set in this study and all the questions in the study have been provided with answers with enough data and literatures to supports its findings. Conclusion and Recommendations . The results indicate that an increase in the recruitment of Saudi males may simply reflect cultural issues such as gender specific facilities and the Saudisation program’s nondiscriminatory approach to employment of both genders into nursing.

Suggested Citation

  • Mohammad Alboliteeh & Judy Magarey & Richard Wiechula, 2017. "The Profile of Saudi Nursing Workforce: A Cross-Sectional Study," Nursing Research and Practice, Hindawi, vol. 2017, pages 1-9, October.
    • Handle: RePEc:hin:jnlnrp:1710686
    DOI: 10.1155/2017/1710686
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    References listed on IDEAS

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    1. Hillhouse, Joel J. & Adler, Christine M., 1997. "Investigating stress effect patterns in hospital staff nurses: Results of a cluster analysis," Social Science & Medicine, Elsevier, vol. 45(12), pages 1781-1788, December.
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    Cited by:

    1. Reem AL-Dossary & Abdulilah Mohammad Mayet & Javed Khan Bhutto & Neeraj Kumar Shukla & Ehsan Nazemi & Ramy Mohammed Aiesh Qaisi, 2023. "Proposing a Method Based on Artificial Neural Network for Predicting Alignment between the Saudi Nursing Workforce and the Gig Framework," Sustainability, MDPI, vol. 15(17), pages 1-12, August.
    2. Nahed Alquwez & Jonas Preposi Cruz & Farhan Alshammari & Ebaa Marwan Felemban & Joseph U. Almazan & Regie B. Tumala & Hawa M. Alabdulaziz & Fatmah Alsolami & John Paul Ben T. Silang & Hanan M. M. Tork, 2019. "A multi‐university assessment of patient safety competence during clinical training among baccalaureate nursing students: A cross‐sectional study," Journal of Clinical Nursing, John Wiley & Sons, vol. 28(9-10), pages 1771-1781, May.
    3. Abdualrahman Saeed Alshehry & Nahed Alquwez & Joseph Almazan & Ibrahim Mohammed Namis & Rainier C. Moreno‐Lacalle & Jonas Preposi Cruz, 2019. "Workplace incivility and its influence on professional quality of life among nurses from multicultural background: A cross‐sectional study," Journal of Clinical Nursing, John Wiley & Sons, vol. 28(13-14), pages 2553-2564, July.

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