[Secondary Data Analysis on the Factors Influencing Premenstrual Symptoms of Shift Work Nurses: Focused on the Sleep and Occupational Stress]

Premenstrual Syndrome's Impact on Work-Related Quality of Life Among Jordanian Nurses

Introduction Premenstrual syndrome (PMS) is a regular clinical condition that affects most women during their reproductive years. Its related symptoms may be linked to a decrease in women's quality of life. Female nurses may be more susceptible to PMS due to the demanding nature of their job. The importance of nurses' jobs and how their quality of life will affect patients and themselves in parallel make female nurses a population that is worth investigating. Our objective is to estimate the level of PMS among Jordanian nurses and assess the potential impact of PMS on work-related quality of life among them. Methods A cross-sectional study was conducted on 210 nurses who completed a questionnaire regarding demographic data, menstrual characteristics, the Premenstrual Symptoms Screening Tool (PSST), and the Work-Related Quality-of-Life Scale (WRQoL). The nurses were classified as having or not having PMS according to the PSST. Results The prevalence of PMS was 60.5%, the results showed a significantly lower mean WRQoL score for nurses with PMS (mean = 65.47, SD = 15.38) compared to nurses without PMS (mean = 70.54, SD = 14.47). The multivariable regression model revealed that the adjusted odds ratios for age, combined oral contraceptive pill (COCP) use, family history, severe dysmenorrhea, job and career satisfaction, and stress at work were 0.90 (95% CI = 0.84, 0.96), 5.18 (95% CI = 1.33, 20.17), 2.52 (95% CI = 1.23, 5.18), 11.78 (95% CI = 2.48, 56.02), 0.92 (95% CI = 0.85, 0.99), and 1.20 (95% CI = 1.01, 1.42), respectively. Conclusion PMS is quite prevalent among Jordanian nurses, with a negative impact on their work-related quality of life. Healthcare managers might implement special regulations for female nurses with PMS to improve their work-related quality of life. This research suggests that PMS is a substantial factor in the low work-related quality of life among Jordanian nurses.

Investigating influencing factors on premenstrual syndrome (PMS) among female college students

BACKGROUND

Premenstrual syndrome (PMS) affects women's physical and mental health. Depression, stress, sleep disturbance, and eating attitude problems have been known to influence PMS. Furthermore, restrictions of daily life due to the COVID-19 pandemic have led to changes in sleep patterns and eating attitudes. Thus, it is necessary to closely examine how these factors affect PMS. This study aimed to examine the levels of PMS, stress, depression, sleep disturbance, and eating attitude problems among female college students who experience dysmenorrhea and determine the factors associated with PMS.

METHODS

A cross-sectional online survey design was conducted using a convenience sample of 143 female college students in C City, South Korea. Data were collected from September 1 to 19, 2021 in South Korea using an online self-administered survey. Differences in participants' level of PMS according to physical health variables (e.g., smoking, water intake, menstrual pain intensity) and psychological issues (i.e., stress, depression, sleep disturbances, and eating attitude problems) were assessed with independent sample t-tests and one-way ANOVAs. Correlational analyses between these variables were also conducted. Additionally, multiple regression was performed to identify the factors influencing PMS.

RESULTS

PMS severity was between normal (27.3%) and premenstrual dysphoric disorder (PMDD) (72.7%). PMS was associated positively with depression (r = .284, p = 001), stress (r = .274, p = .001), sleep disturbance (r = .440, p < .001), and eating attitude problems (r = .266, p = .001). Additionally, menstrual pain intensity (β = 0.204), sleep disturbances (β = 0.375), and eating attitude problems (β = 0.202) were found to influence PMS. The regression model was significant (F = 16.553, p < .001) with an explanatory power of 24.7%.

CONCLUSIONS

Considering the influencing factors of PMS identified in this study, interventions for participants experiencing PMS should be made. We propose that further study should be conducted to examine whether the severity of PMS changes according to menstrual pain, the pattern and degree of its change, and the paths through which sleep quality and eating attitude problems affect PMS.

Development and validation of risk prediction model for premenstrual syndrome in nurses: results from the nurses-based the TARGET cohort study

Objective

Premenstrual syndrome (PMS) stands as a significant concern within the realm gynecological disorders, profoundly impacting women of childbearing age in China. However, the elusive nature of its risk factors necessitates investigation. This study, therefore, is dedicated to unraveling the intricacies of PMS by focusing on nurses, a cohort with unique occupational stressors, to develop and validate a predictive model for assessing the risk of PMS.

Methods

This investigation employed a multi-center cross-sectional analysis drawing upon data from the TARGET Nurses' health cohort. Utilizing online survey versions of the Premenstrual Syndrome Scale (PMSS), a comprehensive dataset encompassing physiological, social, psychological, occupational, and behavioral variables was collected from 18,645 participants. A stepwise multivariate logistic regression analysis was conducted to identify independent risk factors for PMS. Furthermore, a refined variable selection process was executed, combining the Least Absolute Shrinkage and Selection Operator (LASSO) method with 10-fold cross-validation. The visualization of the risk prediction model was achieved through a nomogram, and its performance was evaluated using the C index, receiver operating characteristic (ROC) curves, and the calibration curves.

Results

Among the diverse variables explored, this study identified several noteworthy predictors of PMS in nurses, including tea or coffee consumption, sleep quality, menstrual cycle regularity, intermenstrual bleeding episodes, dysmenorrhea severity, experiences of workplace bullying, trait coping style, anxiety, depression and perceived stress levels. The prediction model exhibited robust discriminatory power, with an area under the curve of 0.765 for the training set and 0.769 for the test set. Furthermore, the calibration curve underscored the model's high degree of alignment with observed outcomes.

Conclusion

The developed model showcases exceptional accuracy in identifying nurses at risk of PMS. This early alert system holds potential to significantly enhance nurses' well-being and underscore the importance of professional support.

Depressive symptoms and menstrual distress according to the menstrual phase in nurses: the Korea Nurses' Health Study

OBJECTIVE

This study aimed to identify the level of menstrual distress among nurses during the premenstrual and menstrual phases and to investigate associations between depressive symptoms and menstrual distress.

METHODS

This was a cross-sectional study conducted using data from the Korea Nurses' Health Study. We used data from December 2018 to September 2019. A total of 6878 nurses was selected for final analysis. Data on demographic characteristics, women's health-related variables, shift work, sleep quality, depressive symptoms and menstrual distress were collected. Descriptive statistics, and hierarchical multiple regression analysis were used.

RESULTS

Depressive symptoms were significantly correlated with menstrual distress in both premenstrual and menstrual phases (premenstrual phase B = 1.60, 95% CI = 1.49-1.71; menstrual phase B = 1.65, 95% CI = 1.54-1.76) after controlling for demographic characteristics, women's health-related variables, shift work and sleep quality.

CONCLUSION

The results of this study indicate the importance of tailored care for menstrual distress based on the menstrual phase and the significance of depressive symptoms in the management of menstrual distress.

[Secondary Data Analysis on the Quality of Sleep and Related Factors of Novice and Experienced Shift Work Nurses]

PURPOSE

The purpose of this study was to identify the quality of sleep in novice and experienced shift work nurses and compare the factors associated with their quality of sleep.

METHODS

We analyzed the data of 192 and 256 novice and experienced nurses, respectively. The quality of sleep, sleep hygiene, job stress, and fatigue were measured using Insomnia Severity Index, Sleep Hygiene Practice Scale, the Korean Occupational Stress Scale, and Fatigue Severity Scale. Data were analyzed using SPSS 25.0 to calculate descriptive statistics and logistic regression.

RESULTS

Sleep quality was lower in experienced nurses (12.55 ± 5.71) than in novice nurses (11.18 ± 5.78). Fatigue was more severe in experienced nurses (4.47 ± 1.13) than in novice nurses (4.23 ± 1.12). In the logistic regression, factors related to sleep quality in novice nurses were sleep hygiene (odds ratio; OR = 1.06, p < .001) and fatigue (OR = 2.49, p < .001). Factors related to sleep quality in the experienced nurses were also sleep hygiene (OR = 1.04, p = .001) and fatigue (OR = 1.53, p = .012).

CONCLUSION

Sleep quality of experienced nurses is lower than those of novice nurses. Factors associated with sleep quality in novice and experienced nurses are equally identified as sleep hygiene and fatigue. Therefore, personal efforts to improve sleep hygiene, such as providing comfortable sleep environment, are needed. Furthermore, organized efforts to decrease fatigue, such as constructing a working environment with a bright light at night and providing a fatigue-decreasing program that includes meditation, are required.