Vol. 3 No. 2 (2024): Sustainable Healthcare: Balancing Quality, Equity, and Efficiency

Original Research Article

Nursing care delivery models and their impact on emotional exhaustion and practice environment: A cross-sectional study in Saudi Arabia

Ali Al Alwi
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Rabab Almutair
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Lulua Alyousef
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
Bio
Hibah Albahrani
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
Bio
Eman Almotter
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Aminah Bu Owaynah
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Huda Almoaibed
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Amanh Alfayez
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Mariam Alqanbar
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Ruqayyah Alessa
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
Bio
Sarah Alawadh
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
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Abdullah Aljaber
Prince Saud Bin Jalawi Hospital, Alhassa, Saudi Arabia
Bio

Keywords

Saudi Arabia, job satisfaction, emotional exhaustion, team nursing, models of nursing, patient care, practice environment, nurses

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Abstract

Background: Nursing staff outcomes, such as job satisfaction, work quality, emotional well-being, intent to leave, and the practice environment, have been linked to improvements in patient outcomes and staff job satisfaction. However, existing studies have not captured the impact of nursing models on emotional exhaustion and practice environments in the context of Saudi Arabia. Additionally, there is a gap in empirical evidence regarding the effectiveness of organizing nursing work within a total nursing or team nursing care model in ensuring staff well-being.

Objective: This study aimed to examine the nursing care models used in a government hospital and their association with nurses’ emotional exhaustion and perceptions of the practice environment.

Methods: A cross-sectional study was conducted with 314 nurses working at a hospital.  Data were collected from January to May 2024 using the Maslach Burnout Inventory™ (MBI) to measure emotional exhaustion and the Practice Environment Scale of the Nursing Work Index (PES-NWI) to assess perceptions of the practice environment. Regression analyses were performed to examine the relationships between the nursing care model, emotional exhaustion, and the practice environment.

Results: Among the 314 nurses surveyed, 201 (64%) reported using a total care model, 103 (32.8%) used a team nursing model, and 10 (3.2%) were unsure of the model used. Regression analysis revealed a significant association between the nursing care model and emotional exhaustion (p <0.001), with 42.5% of the variance in emotional exhaustion explained by the nursing care model ( = 0.425). For the practice environment, a significant association was observed with the nursing care model (p <0.001), explaining 85.9% of the variance in the practice environment ( = 0.859).

Conclusion:  The findings may guide nurse managers and policymakers in adopting nursing care models that best suit their organizations to enhance the quality of care. It is essential for hospitals to implement more flexible nursing care delivery models to enable nurses to utilize their full range of training and capabilities. These results have implications for healthcare administration and strategies that support the effective delivery of sustainable and holistic nursing care.


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Declaration of Conflicting Interest

The authors declare no conflict of interest.

Acknowledgment

The authors are grateful to all the staff at Prince Saud Bin Jalawi Hospital, Kingdom of Saudi Arabia and their contribution to this study and the nurses for voluntarily participating in the study.

Authors’ Contributions

All authors equally substantially contributed to the work design, acquisition, analysis, and interpretation of the data; Drafting or revising it critically for important intellectual content; Final approval of the version to be published; Agreement to be accountable for all aspects of the work.

Data Availability Statement

The dataset generated during and analyzed during the current study is available from the corresponding author upon reasonable request.

Declaration of the Use of AI in Scientific Writing

None.

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