Work schedule characteristics and occupational fatigue/recovery among rotating-shift nurses: A cross-sectional study
Ari Min PhD, RN
Assistant Professor
Department of Nursing, Chung-Ang University, Seoul, South Korea
Search for more papers by this authorCorresponding Author
Hye Chong Hong PhD, RN
Assistant Professor
Department of Nursing, Chung-Ang University, Seoul, South Korea
Correspondence
Hye Chong Hong, PhD, RN, Assistant Professor, Department of Nursing, Chung-Ang University, 84 Heukseok-ro, Bldg 106, Dongjak-gu, Seoul 06974, South Korea.
Email: [email protected]
Search for more papers by this authorYoung Man Kim PhD, RN
Assistant Professor
College of Nursing, Research Institute of Nursing Science, Jeonbuk National University, Jeonju, South Korea
Search for more papers by this authorAri Min PhD, RN
Assistant Professor
Department of Nursing, Chung-Ang University, Seoul, South Korea
Search for more papers by this authorCorresponding Author
Hye Chong Hong PhD, RN
Assistant Professor
Department of Nursing, Chung-Ang University, Seoul, South Korea
Correspondence
Hye Chong Hong, PhD, RN, Assistant Professor, Department of Nursing, Chung-Ang University, 84 Heukseok-ro, Bldg 106, Dongjak-gu, Seoul 06974, South Korea.
Email: [email protected]
Search for more papers by this authorYoung Man Kim PhD, RN
Assistant Professor
College of Nursing, Research Institute of Nursing Science, Jeonbuk National University, Jeonju, South Korea
Search for more papers by this authorFunding information: National Research Foundation of Korea, Grant/Award Number: 2018R1D1A1B07042018
Abstract
Aims
To determine the effects of work schedule characteristics on occupational fatigue and recovery among rotating-shift nurses in South Korea.
Background
Understanding the effects of work schedule characteristics on occupational fatigue is important to prevent adverse nurse outcomes and to ensure patient safety.
Methods
This study used secondary data analysis with a cross-sectional design. Data were collected on 436 rotating-shift nurses in 2018. Nurses' occupational fatigue and recovery were measured using the Occupational Fatigue Exhaustion/Recovery Scale. We used quantile regression models.
Results
The scores for acute and chronic fatigue and intershift recovery were 70.40, 73.39, and 29.82, respectively. Overtime hours, number of night shifts, number of consecutive days off, and breaks were significant influential factors in some quantiles of acute fatigue, chronic fatigue, and intershift recovery, while total working hours was only associated with chronic fatigue in the 25th quantile.
Conclusions
The quantile and linear regression models revealed different results for work schedule factors that affect occupational fatigue and intershift recovery among rotating-shift nurses.
Implication for Nursing Management
These findings have important implications for developing targeted strategies and policies to reduce occupational fatigue and improve intershift recovery for rotating-shift nurses with different levels of occupational fatigue and recovery.
CONFLICT OF INTEREST
The authors have no conflicts of interest to declare.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
Supporting Information
| Filename | Description |
|---|---|
| jonm13511-sup-0001-Supplementary table_OFER_QR_jnm_amin.docxWord 2007 document , 631.4 KB |
Table S1. Descriptive statistics of work schedule characteristics and occupational fatigue exhaustion recovery (N = 436) Table S2. Results of one-way ANONA for occupational fatigue and recovery Figure S1. Association between work schedule characteristics and acute fatigue. Figures (a)–(e) show the relationship between the predictors and quantiles of acute fatigue in the final quantile regression model. The quantile regression model was adjusted for nurse characteristics (gender, age, marital status, parental status, education level, monthly income, work experience), unit characteristics (unit type, care model), and hospital characteristics (location, number of beds, teaching hospital, number of assigned patients). The red solid line represents the slope for each quantile, and the grey-shaded areas represent 95% confidence intervals. The black dotted line shows the regression line estimated by the least squares method. Figure S2. Association between work schedule characteristics and intershift recovery. Figures (a)–(e) show the relationship between the predictors and quantiles of intershift recovery in the final quantile regression model. The quantile regression model was adjusted for nurse characteristics (gender, age, marital status, parental status, education level, monthly income, work experience), unit characteristics (unit type, care model), and hospital characteristics (location, number of beds, teaching hospital, number of assigned patients). The blue solid line represents the slope for each quantile, and the grey-shaded areas represent 95% confidence intervals. The black dotted line shows the regression line estimated by the least squares method. Figure S3. Association between work schedule characteristics and chronic fatigue. Figures (a)–(e) show the relationship between the predictors and the quantiles of chronic fatigue in the final quantile regression model. The quantile regression model was adjusted for nurse characteristics (gender, age, marital status, parental status, education level, monthly income, work experience), unit characteristics (unit type, care model), and hospital characteristics (location, number of beds, teaching hospital, number of assigned patients). The red solid line represents the slope for each quantile, and the grey-shaded areas represent 95% confidence intervals. The black dotted line shows the regression line estimated by the least squares method. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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