Which Shiftwork Pattern Is the Strongest Predictor for Poor Sleep Quality in Nurses?

Nurse rostering: understanding the current shift work scheduling processes, benefits, limitations, and potential fatigue risks

BACKGROUND

Implementing appropriate shift work schedules can help mitigate the risk of sleep impairment and reduce fatigue of healthcare workers, reducing occupational health and safety risks. In Australia, the organisation has a responsibility to make sure all reasonable measures are taken to reduce fatigue of staff. Therefore, it is important to assess what the current rostering processes is for staff responsible for creating the rosters for nurses.

AIM

The aims of the project were to understand (1) who creates the rosters and what the process is, (2) what training and knowledge these staff have in establishing rostering schedules that optimise the sleep and wellbeing of staff, and (3) what the benefits and limitations are of current rostering practices.

METHODS

Findings were generated through semi-structured interviews, using cluster coding to form categories. Twenty four nurses responsible for rostering staff were interviewed from three different sites in Victoria (one metropolitan and two regional/rural hospitals). Data was analysed using selected grounded theory methods with thematic analysis.

RESULTS

The common themes that came out of the interviews were that rostering staff were under prepared, unaware of fatigue and safety guidelines and polices from governing bodies and had not received any education or training before taking on the role. The most common rostering style was self-rostering, where staff could submit preferences. However, there were concerns about staff fatigue but were divided as to who should be responsible, with many saying it was up to staff to preference shifts that they could cope with. The final theme was cultural barriers to change.

CONCLUSION

While self-rostering resulted in staff having more freedom and flexibility,  shift preferences may be influenced more so by a need to fit with lifestyle rather than to minimise fatigue and increase safety in the workplace. Greater consideration of the impact of shift work schedules on fatigue is required to ensure that the layers of clinical governance in health care organisations minimise the risk of occupation health and safety issues for employees delivering direct patient care.

How our longitudinal employment patterns might shape our health as we approach middle adulthood-US NLSY79 cohort

Recent labor market transformations brought on by digital and technological advances, together with the rise of the service economy since the 1980s, have subjected more workers to precarious conditions, such as irregular work hours and low or unpredictable wages, threatening their economic well-being and health. This study advances our understanding of the critical role employment plays in our health by examining how employment patterns throughout our working lives, based on work schedules, may shape our health at age 50, paying particular attention to the moderating role of social position. The National Longitudinal Survey of Youth-1979 (NLSY79), which has collected 30+ years of longitudinal information, was used to examine how employment patterns starting at ages 22 (n ≈ 7,336) might be associated with sleep hours and quality, physical and mental functions, and the likelihood of reporting poor health and depressive symptoms at age 50. Sequence analysis found five dominant employment patterns between ages 22 and 49: "mostly not working" (10%), "early standard hours before transitioning into mostly variable hours" (12%), "early standard hours before transitioning into volatile schedules" (early ST-volatile, 17%), "mostly standard hours with some variable hours" (35%), and "stable standard hours" (26%). The multiple regression analyses indicate that having the "early ST-volatile" schedule pattern between ages 22 and 49 was consistently, significantly associated with the poorest health, including the fewest hours of sleep per day, the lowest sleep quality, the lowest physical and mental functions, and the highest likelihood of reporting poor health and depressive symptoms at age 50. In addition, social position plays a significant role in these adverse health consequences. For example, whereas non-Hispanic White women reported the most hours of sleep and non-Hispanic Black men reported the fewest, the opposite was true for sleep quality. In addition, non-Hispanic Black men with less than a high school education had the highest likelihood of reporting poor health at age 50 if they engaged in an employment pattern of "early ST-volatile" between ages 22 and 49. In comparison, non-Hispanic White men with a college degree or above education had the lowest likelihood of reporting poor health if they engaged in an employment pattern of stable standard hours. This analysis underscores the critical role of employment patterns in shaping our daily routines, which matter to sleep and physical and mental health as we approach middle adulthood. Notably, the groups with relatively disadvantaged social positions are also likely to be subject to nonstandard work schedules, including non-Hispanic Blacks and people with low education; hence, they were more likely than others to shoulder the harmful links between nonstandard work schedules and sleep and health, worsening their probability of maintaining and nurturing their health as they approach middle adulthood.

Differences in shift and work-related patterns between metropolitan and regional/rural healthcare shift workers and the occupational health and safety risks

OBJECTIVES

To explore if there are differences in shift patterns and work-related factors between metropolitan and regional/rural healthcare shift workers and their risk of poor sleep and mental health. Furthermore, explore whether these factors impact on medical errors, workplace and car/near car accidents.

DESIGN

A cross-sectional study.

SETTING

An anonymous online survey of healthcare shift workers in Australia.

PARTICIPANTS

A total of 403 nurses, midwives and paramedics completed the survey.

MAIN OUTCOME MEASURES

Sample characteristics, employment location, shift work-related features, sleep and mental health measurements, workplace accidents, medical errors and car/near car accident post shift.

RESULTS

Regional/rural healthcare shift workers were significantly older, had more years' experience, worked more nights, on-call and hours per week. Those in metropolitan areas took significantly longer (minutes) to travel to work, had higher levels of anxiety, increased risk of shift work disorder, reported significantly more workplace accidents and were more likely to have a car/near car accident when commuting home post shift. Both groups reported ~25% having a medical error in the past year. Workplace accidents were related to more on-call shifts and poor sleep quality. Medical errors were associated with fewer years' experience, more evening shifts and increased stress. Car accidents were associated with metropolitan location and increased depression.

CONCLUSION

Differences in work-related factors between metropolitan and regional/rural healthcare shift workers were observed. Some of these factors contributed to occupational health and safety risks. Further exploration is needed to understand how to reduce occupational health and safety risks, and improve employee and patient safety both in both regional/rural and metropolitan areas.

The Relationship between Working Night Shifts and Depression among Nurses: A Systematic Review and Meta-Analysis

BACKGROUND

For many years, occupational physicians have debated whether there is a link between working the night shift and depression and other co-occurring mental health issues, with an emphasis on work-related, biological, individual, and environmental factors. We performed this systematic review and meta-analysis to estimate the overall association between sleep deprivation and depression among nurses working night shifts.

METHODS

A systematic search was carried out across the electronic databases PubMed, Scopus, and Web of Science from inception to 30 September 2022, for studies that reported a relationship between estimated night shift work and depression in nurses. The outcomes were measured using the odds ratio (OR) and matching 95% confidence interval (CI). The I² statistic was used to assess heterogeneity. The Grading of Recommendations Assessment, Development and Evaluation technique was used to evaluate the quality of the evidence, and the Newcastle-Ottawa Scale was utilized to assess the methodological quality of each of the included studies. We determined the overall relationship between working nights and the onset of depression.

RESULTS

A total of 20 studies were included in the systematic review. Furthermore, 8 studies were included in the meta-analysis due to their common use of the OR as an effect measure. The 8 studies gave an overall estimate indicating a statistically significant association between night shift work and depression among nurses (OR = 1.49 95% CI: 1.26, 1.76). The prediction interval for the overall estimate was (0.995, 2.231). This implies that the true OR in a future study would most likely fall within this range, with a 95% certainty.

CONCLUSIONS

The outcome of this systematic review and meta-analysis showed a significant association between night shift work, the circadian and sleep disruption it causes, and the risk of depression in nurses. This demonstrates that nurses who work night shifts are at risk of developing depression.