The predictors of fatigue among Iranian nurses during the COVID-19 pandemic

Nurses spend a significant amount of time caring for patients with COVID-19. This can result in increased fatigue and decreased performance in nurses. This study was conducted to determine the predictors of fatigue among nurses working in COVID-19 wards in Ardabil, Iran. This cross-sectional study included 231 nurses who worked in the COVID-19 wards of Ardabil University of Medical Sciences from May to September 2021. The census method was used to select the samples. The “Multidimensional Scale of Perceived Social Support,” the “NASA-TLX workload,” the “Nurse Job Stress,” and the “Nurse Fatigue Scale” were used to collect data. SPSS v.15 and descriptive (mean and standard deviation) and inferential (independent t -test, ANOVA, Pearson correlation coefficient, regression analysis) statistical methods were employed to analyze the data. The mean score for nurses’ fatigue was 67.55 ± 14.06, social support was 44.71 ± 7.86, the workload was 57.50 ± 14.23, and job stress was 81.54 ± 18.40. The results of linear regression analysis indicated that social support (p = 0.003), workload (p < 0.001), and work shift (p = 0.002) exhibited a significant relationship with fatigue among nurses working in COVID-19 wards so that 19/1% of the nurses’ fatigue in these wards was predicted by the above variables. Given the significant relationship between workload, work shift, and social support and fatigue, nursing managers should arrange shifts flexibly and use low rotational shifts to reduce nurses’ fatigue. Additionally, the number of patients per nurse should be decreased to reduce nurses’ workload on the wards. Moreover, health authorities should increase social support for nurses by sharing work experiences, listening to nurses’ concerns, and providing empathic support. Given the importance of the nursing profession and the knowledge that nurse fatigue and its related factors directly affect the organization’s ability to properly care for patients, using the results of this study, appropriate management measures can be taken to reduce nurse fatigue and thereby improve nurse satisfaction and the quality of nursing care.

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Publication Details

Journal
International Journal of Africa Nursing Sciences
Published
2025-11-16
DOI
https://doi.org/10.1016/j.ijans.2025.100917
Primary Topic
COVID-19 and Mental Health
Type
article
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article

The predictors of fatigue among Iranian nurses during the COVID-19 pandemic

Narges Mohsenzadeh, Mehdi Ajri‐Khameslou, Masoumeh Aghamohammadi
International Journal of Africa Nursing Sciences
COVID-19 and Mental Health
article

The predictors of fatigue among Iranian nurses during the COVID-19 pandemic

Narges Mohsenzadeh, Mehdi Ajri‐Khameslou, Masoumeh Aghamohammadi
article en

Abstract

Nurses spend a significant amount of time caring for patients with COVID-19. This can result in increased fatigue and decreased performance in nurses. This study was conducted to determine the predictors of fatigue among nurses working in COVID-19 wards in Ardabil, Iran. This cross-sectional study included 231 nurses who worked in the COVID-19 wards of Ardabil University of Medical Sciences from May to September 2021. The census method was used to select the samples. The “Multidimensional Scale of Perceived Social Support,” the “NASA-TLX workload,” the “Nurse Job Stress,” and the “Nurse Fatigue Scale” were used to collect data. SPSS v.15 and descriptive (mean and standard deviation) and inferential (independent t -test, ANOVA, Pearson correlation coefficient, regression analysis) statistical methods were employed to analyze the data. The mean score for nurses’ fatigue was 67.55 ± 14.06, social support was 44.71 ± 7.86, the workload was 57.50 ± 14.23, and job stress was 81.54 ± 18.40. The results of linear regression analysis indicated that social support (p = 0.003), workload (p < 0.001), and work shift (p = 0.002) exhibited a significant relationship with fatigue among nurses working in COVID-19 wards so that 19/1% of the nurses’ fatigue in these wards was predicted by the above variables. Given the significant relationship between workload, work shift, and social support and fatigue, nursing managers should arrange shifts flexibly and use low rotational shifts to reduce nurses’ fatigue. Additionally, the number of patients per nurse should be decreased to reduce nurses’ workload on the wards. Moreover, health authorities should increase social support for nurses by sharing work experiences, listening to nurses’ concerns, and providing empathic support. Given the importance of the nursing profession and the knowledge that nurse fatigue and its related factors directly affect the organization’s ability to properly care for patients, using the results of this study, appropriate management measures can be taken to reduce nurse fatigue and thereby improve nurse satisfaction and the quality of nursing care.

International Journal of Africa Nursing SciencesVol. 24
Ardabil University of Medical Sciences (IR), Iranshahr University (IR)
Openalex Percentile: Top 53%
COVID-19 and Mental Health
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