Patterns of working hour characteristics and risk of sickness absence among shift-working hospital employees: a data-mining cohort study

Under pressure - Nursing staff's perspectives on working hours and recovery during the COVID-19 pandemic: A qualitative study

Background

The COVID-19 pandemic contributed to increased pressure on healthcare systems. During periods when the demands exceed the capacity of healthcare organizations, adaptive strategies are used to meet these demands. During the COVID-19 pandemic, working hours for nursing staff were reorganized and extended. This has posed challenges for recovery, which may be a key factor for maintaining health and safety under such conditions.

Objectives

The aim of the study was to bring insights into how nursing staff perceived their working hours and recovery during the COVID-19 pandemic, and if they experienced any changes in their sleep and well-being.

Design

A qualitative descriptive design was chosen, as it is suitable for gaining insight into perceptions and experiences.

Methods

Qualitative semi-structured interviews were conducted using an interview guide. The interviews were analyzed using thematic analysis. Sixteen registered nurses and six certified nursing assistants from four Swedish hospitals participated in the study.

Results

The organization of working hours during the COVID-19 pandemic was considered suboptimal and resulted in more demanding working hours and poor recovery. Nursing staff experienced loss of control as they lost influence over working hours, working hours became more unpredictable and the boundaries between work and leisure became blurred. Nursing staff also experienced a decline in their health and well-being, including extreme fatigue, impaired sleep and physical/mental changes.

Conclusion

The strategies used by healthcare organizations to meet increasing demands during the COVID-19 pandemic contributed to impaired recovery and well-being of nursing staff, which could generate negative feedback loops contributing to depletion of resources at the organizational level.

Workload and short sickness absences in a cohort of Finnish hospital employees

This article used register data on day-to-day working hours of hospital employees combined with patient characteristics at work unit (wards) level to measure workload and its implications for short, self-certified sickness absences. We measured statistically the average nursing treatment burden of different patient mixes in hospital wards, and then analyzed the overall workload (intensity) of working days by comparing it to the actual available nursing workforce. We found that a significant part of the workload variation occurred between working days, and it was related to unexpected changes in the number of employees. In atypical situations a long work shift was associated with caring for patients with fewer resources. The high workload of a day increased the risk of short sickness absences along the following 3-week period. The results show that managing short-term workload variability should be a key aim from the perspective of well-being at work, and that combining different data sources can provide novel, important insights to the measurement of workload.

Working hours and health - key research topics in the past and future

OBJECTIVE

This paper discusses the past and present highlights of working hours and health research and identifies key research needs for the future.

METHOD

We analyzed over 220 original articles and reviews on working hours and health in the Scandinavian Journal of Work, Environment & Health published during the last 50 years. Key publications from other journals were also included.

RESULTS

The majority of identified articles focussed on the effects of shift and night work, with fewer studying long and reduced working hours and work time control. We observed a transition from small-scale experimental and intensive field studies to large-scale epidemiological studies utilizing precise exposure assessment, reflecting the recent emergence of register-based datasets and the development of analytic methods and alternative study designs for randomized controlled designs. The cumulative findings provide convincing evidence that shift work and long working hours, which are often associated with night work and insufficient recovery, increase the risk of poor sleep and fatigue, sickness absence, occupational injuries, and several chronic health conditions such as cardiovascular diseases and cancer. The observed risks are strongly modified by individual and work-related factors.

CONCLUSIONS

Although the observed health risks of shift work and long working hours are mostly low or moderate, the widespread prevalence of exposure and the hazardousness of the many associated potential outcomes makes such working time arrangements major occupational health risks. Further research is needed to identify exposure-response associations, especially in relation to the chronic health effects, and to elucidate underlying pathways and effective personalized intervention strategies.

Differential impacts of reduced worktime on work-life balance in Korea

This study analyzes the heterogenous effects of reducing weekly work hour on workers' quality of life in Korea. Using longitudinal household data from the Korean Labor and Income Panel Study (KLIPS) from 2001 to 2017, this study aims to shed light on how the work hour reduction policy may differently affect workers with different levels of resources and support by demographic and socioeconomic status. Our estimates from the difference-in-differences approach exploiting the staggered implementation of the work hour reduction policy indicate that the policy increased leisure satisfaction of female workers with low educational level and female workers in regular or inflexible work setting. Given Korea's exceedingly long working hours and inequities in the labor market, a better understanding of the complex factors that affect work-life balance can be helpful in developing policies supportive of healthy work-life balance for workers. This study, to our knowledge, is the first to investigate the composition of workers in the Korean labor market and examine differential impacts of the workhour reduction policy by demographic and socioeconomic status.

Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees

OBJECTIVE

This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers.

METHODS

This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up.

RESULTS

The C-index of 0.73 [95% confidence interval (CI) 0.70-0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67-0.75) for an administrative records-only model, and 0.79 (95% CI 0.76-0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome.

CONCLUSIONS

The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.

Shift work with and without night shifts and breast cancer risk in a cohort study from Finland

OBJECTIVES

To examine the association of shift work with and without night work with breast cancer among women in the public sector.

METHODS

Using the Finnish Public Sector cohort study (N=33 359, mean age of 40.6 years at baseline), we investigated the associations of shift work and potential confounders with incident breast cancer. Exposure to permanent day work or shift work was defined from first two consecutive surveys from 2000, 2004, 2008 or 2012 and past information on exposure in a subcohort (n=20 786). Incident cases of breast cancer (n=1129) were retrieved from the National Cancer Register and the cohort members were followed to the end of 2016. HR and 95% CI from Cox proportional hazard regression models were calculated.

RESULTS

Shift work with and without night shifts was not overall associated with breast cancer. When stratified according to age, both shift work without nights (HR 2.01, 95% CI 1.12 to 3.60) and shift work with nights (OR 2.05, 95% CI 1.04 to 4.01) were associated with an increased risk after a period of 10 years or more follow-up among women aged 50 years or older, when adjusted for age, socioeconomic status, children, smoking, alcohol and body mass index. In a subgroup with past information on exposure to shift work, the increased risk by longer exposure to shift work was not significant.

CONCLUSIONS

This study provides support for an increased risk of breast cancer among elderly shift workers. However, insufficient information on exposure and intensity of night work may attenuate the risk estimates.

Sequence analysis of the combinations of work shifts and absences in health care - comparison of two years of administrative data

BACKGROUND

In health care, the shift work is arranged as irregular work shifts to provide operational hours for 24/7 care. We aimed to investigate working hour trends and turnover in health care via identification of time-related sequences of work shifts and absences among health care employees. The transitions between the work shifts (i.e., morning, day, evening, and night shifts), and absences (days off and other leaves) over time were analyzed and the predictors of change in irregular shift work were quantified.

METHODS

A longitudinal cohort study was conducted using employer-owned payroll-based register data of objective and day-to-day working hours and absences of one hospital district in Finland from 2014 to 2019 (n = 4931 employees). The working hour data included start and end of work shifts, any kind of absence from work (days off, sickness absence, parental leave), and employee's age, and sex. Daily work shifts and absences in 2014 and 2019 were used in sequence analysis. Generalized linear model was used to estimate how each identified sequence cluster was associated with sex and age.

RESULTS

We identified four sequence clusters: "Morning" (60% in 2014 and 56% in 2019), "Varying shift types" (22% both in 2014 and 2019), "Employee turnover" (13% in 2014 and 3% in 2019), and "Unstable employment (5% in 2014 and 19% in 2019). The analysis of transitions from one cluster to another between 2014 and 2019 indicated that most employees stayed in the same clusters, and most often in the "Varying shift types" (60%) and "Morning" (72%) clusters. The majority of those who moved, moved to the cluster "Morning" in 2019 from "Employee turnover" (43%), "Unstable employment" (46%) or "Varying shift types" (21%). Women were more often than men in the clusters "Employee turnover" and "Unstable employment", whereas older employees were more often in "Morning" and less often in the other cluster groups.

CONCLUSION

Four clusters with different combinations of work shifts and absences were identified. The transition rates between work shifts and absences with five years in between indicated that most employees stayed in the same clusters. The likelihood of a working hour pattern characterized by "Morning" seems to increase with age.

Working Time Control and Variability in Europe Revisited: Correlations with Health, Sleep, and Well-Being

Working time control (WTC) and working time variability (WTV) are two important dimensions of working times, especially with regard to the dynamics of irregular working hours in a changing world of work. Both dimensions are closely related, and the terms are sometimes used synonymously. However, a high degree of WTC does not automatically lead to variable or irregular working hours. On the contrary, WTV is often imposed by the employer and does not necessarily occur in conjunction with high WTC. This article gives an overview of different European WTC and WTV regimes using a typological approach. Based on the European Working Conditions Survey 2015 (EWCS, n = 27,607), four employee groups are compared: those with (1) high WTC and high WTV, (2) high WTC and low WTV, (3) low WTC and high WTV, and (4) low WTC and low WTV. Firstly, the analyses aim to assess whether WTC and WTV vary across European countries due to different working time regimes and in different occupational sectors, i.e., hospitality, retail, and health and social work. Secondly, multi-level analyses are used to describe correlations with health (self-rated health, psychosomatic complaints), sleep (sleep problems), and well-being (WHO-5-Scale). The analyses suggest that WTC and WTV differ between European countries: in the northern countries, high WTC/high WTV is most prevalent, whereas low WTV/low WTC is more common in the other countries. As far as employee health and sleep are concerned, high WTV is associated with poor health, i.e., a greater number of psychosomatic health complaints, worse self-rated health status, and more sleep problems. However, the correlation appears to be weaker for psychosomatic health complaints when employees have high WTC. Significant correlations could not be found for WTC. Low WTC and high WTV is more common in occupational sectors in hospitality, retail, and health and social care; however, these occupational sectors show the same correlations regarding health, sleep, and well-being. The analyses indicate that it is crucial to consider WTV and WTC together in order to understand the dynamics of irregular working hours and health.

A survey of train driver schedules, sleep, wellbeing, and driving performance in Australia and New Zealand

Train drivers work long hours on 24 h schedules and many factors impact their fatigue risk at work, creating a clear imperative for good rostering practice. Adopting a systems approach, this study investigated the relationship between multiple interrelated factors (train drivers’ schedule, sleep, wellbeing, and fatigue) and the perceived influence of these factors on train driving performance and safety using an online survey distributed in Australia and New Zealand. In addition to demographics and work schedule, passenger and freight train drivers (n = 751) answered questions about: (1) Sleep duration; (2) wellbeing, including physical and mental health, the extent to which shiftwork causes sleep, social, domestic, and work problems, and (3) the extent to which ten fatigue, health and wellbeing factors in the work and home environment negatively impact their driving performance. The key factor that emerged from analyses, with the largest and most consistent negative effects (and controlling for other factors) was schedule irregularity. Approved rosters were ranked as having the most important impact on day-to-day driving performance, followed by physical and mental health, and outside work factors. Results also suggested that schedule irregularity may amplify the negative impacts of the roster, impaired physical and mental health, and outside work factors on driving performance. As shift variability and schedule irregularity are often poorly represented in existing industry guidance, these results provide evidence for increased reflection on current fatigue management guidelines for train drivers and suggest a need for greater focus on schedule irregularity through the lens of a systems approach.