Secondary Data Analysis on the Factors Influencing Premenstrual Symptoms of Shift Work Nurses:Focused on the Sleep and Occupational Stress
- Author:
Jihyun BAEK
1
;
Smi CHOI-KWON
Author Information
- Publication Type:Reserch Paper
- From:Journal of Korean Academy of Nursing 2020;50(4):631-640
- CountryRepublic of Korea
- Language:0
-
Abstract:
Purpose:This study aimed to examine premenstrual symptoms (PMS) of shift nurses and identify the association between PMS, sleep, and occupational stress.
Methods:This study was conducted with a secondary data analysis that used data from the Shift Work Nurse’s Health and Turnover study. The participants were 258 nurses who were working in shifts including night shifts. PMS, sleep patterns (sleep time and sleep time variability), sleep quality, and the occupational stress of each participant were measured using the Moos Menstrual Distress Questionnaire, a sleep diary, an actigraph, the Insomnia Severity Index, and the Korean Occupational Stress Scale, respectively. Data were analyzed using SPSS 23 and STATA 15.1 to obtain descriptive statistics, Pearson’s correlation coefficients, multiple linear regression with generalized estimating equations (GEE) and Baron and Kenny’s mediating analysis.
Results:The average PMS score, average sleep time, average sleep time variability, average sleep quality score, and average occupational stress score of the participants was 53.95 ± 40.45, 7.52 ± 0.89 hours, 32.84 ± 8.43%, 12.34 ± 5.95, and 49.89 ± 8.98, respectively. A multiple linear regression analysis with GEE indicated that sleep time variability (B = 0.86, p = .001), and sleep quality (B = 2.36, p < .001) had negative effects on nurses’ PMS. We also found that sleep quality had a complete mediating effect in the relationship between occupational stress and PMS.
Conclusion:These findings indicate that both sleep time variability and sleep quality are important factors associated with PMS among shift work nurses. To improve shift nurses’ PMS status, strategies are urgently needed to decrease sleep time variability and increase sleep quality.
