The predictive role of common symptoms of premenstrual syndrome in the clinical practice of nurses: a cross-sectional study

Abstract

Abstract Background Female nurses with high occupational stress are one of the groups at risk of premenstrual syndrome (PMS). The symptoms of this syndrome may affect the reduction of work efficiency, accuracy in doing work, concentration, and increased absenteeism of nurses and can lead to significant economic losses. This study aimed to determine the predictive role of common PMS symptoms in the clinical performance of nurses in public hospitals in Sanandaj, Iran. Methods The present study was a descriptive-analytical and cross-sectional study. In this study, 318 nurses participated in the census method based on the inclusion criteria. Data collection tools were premenstrual symptom screening questionnaires and nurses’ clinical performance evaluations. Data analysis was done with Spearman’s correlation tests, simple linear regression, multiple regression, t-test, one-way variance analysis, Tukey’s post hoc tests, and LSD using SPSS version 22 statistical software. Results The average PMS score of the participants was 30.8 ± 11.45, which indicates severe PMS. Nurses’ average clinical performance score was 45.78 ± 35.29, indicating an average performance. The findings showed that PMS has a significant inverse correlation with clinical performance and its components. Simple linear regression showed that PMS can predict 26.5% of nurses’ clinical performance variance. Simple regression showed that with an increase of one standard deviation in the PMS score, the nurses’ clinical performance score decreased by 0.517 standard deviations and vice versa. However, by controlling confounding variables, with an increase of one standard deviation in the PMS score, the clinical performance score of nurses will decrease by 0.396 standard deviations and vice versa. Conclusions Paying attention to reducing or controlling PMS symptoms may help improve nurses’ performance. Therefore, hospital and nursing managers can improve the performance and efficiency of their workforce by identifying nurses and other employees suffering from PMS and planning and using different methods to reduce its symptoms.

Keywords

• Premenstrual syndrome
• Clinical performance
• Nurses