Factors associated with readmissions in psychiatric inpatient care: a prospective cohort study based on hospital registers.

BACKGROUND: Readmissions in psychiatric inpatient care may reflect problems in the provision of care, but the underlying factors are not well known. We examined the associations of patient characteristics (sociodemographic factors, diagnoses), treatment (duration, previous episodes, neuromodulation) and ward overload with psychiatric inpatient readmissions and multiple readmissions in Finland. METHODS: We used a routinely collected data pool from one hospital district and followed all 2052 hospitalizations that started in 2018. The outcomes were readmission within 30 days and one year, and among those with readmission, the number of readmissions. RESULTS: Of the patients, 11% had readmission within 30 days and 33% had readmission within one year. Women, those with previous hospitalizations, those with an ICD-10 diagnosis from the 'behavioural syndromes associated with physiological disturbances and physical factors / disorders of adult personality and behaviour' group, those with a diagnosis from the 'neurotic, stress-related and somatoform disorders' group, those with psychotic disorders, and those who received neuromodulation treatment were more likely to have readmissions. Having a diagnosis of 'disorders of psychological development' or 'behavioural and emotional disorders with onset usually occurring in childhood and adolescence' was associated with a lower likelihood of readmission. The duration of treatment and ward overload during the index period were not associated with readmission. CONCLUSIONS: The findings of this study suggest possible risk factors for readmission and can be used to plan psychiatric care. To some degree, the risk factors varied between different readmission types. It is important to examine whether there are unmet treatment needs in psychiatric inpatient care for children and adolescents.

Physical activity and risk of workplace and commuting injuries: a cohort study.

OBJECTIVE: Leisure-time physical activity (PA) has been hypothesized to reduce the likelihood of occupational injuries, but it is unclear whether this association varies between workplace and commuting injuries. The aim of this study was to examine the association between PA and risk of workplace and commuting injuries. METHODS: Data were derived from the Finnish Public Sector study including 82 716 person-observations (48 116 participants). PA was requested repeatedly in four questionnaire surveys between 2000-2012. The average level of PA from two subsequent questionnaires was used to assess long-term PA. To obtain a 1-year incidence of injuries, participants were linked to occupational injury records from the national register. Logistic regression analysis with generalized estimating equations was used to examine the association between PA and injury risk. The analysis was adjusted for age, sex, education, work schedule, job demand, sleep difficulties, cardiovascular diseases, diabetes, and depression for workplace and commuting injuries, and workplace injuries were additionally adjusted for physical heaviness of an occupation and injury risk by occupation. RESULTS: Higher level of PA was associated with a lower risk of workplace injuries compared to inactive participants [odds ratio (OR) 0.85, 95% confidence interval (CI) 0.73-0.98]. This association was most marked in the ≥50-year-old age group (OR 0.78, 95% CI 0.64-0.99). No association between the PA and the risk for commuting injuries was observed. CONCLUSION: Higher PA is associated with lower risk of workplace injuries particularly among older employees.

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.

Validity of self-reported night shift work among women with and without breast cancer.

OBJECTIVES: This study aimed to estimate the validity of self-reported information on ever-night shift work among women with and without breast cancer and illustrate the consequences for breast cancer risk estimates. METHODS: During 2015-2016, 225 women diagnosed with breast cancer and 1800 matched controls without breast cancer employed within the Danish hospital regions during 2007-2016 participated in a questionnaire-based survey. Their reported night shift work status was linked with objective payroll register day-by-day working hour data from the Danish Working Hour Database and the Danish Cancer Registry. For the breast cancer patients and their matched controls, we estimated sensitivity and specificity for ever-working night shifts using the payroll data as the gold standard. We also used quantitative bias analysis to estimate the impact on relative risk estimates for a hypothetical population. RESULTS: For breast cancer patients, we observed a sensitivity of ever-night shifts of 86.2% and a specificity of never-night shifts of 82.6%. For controls, the sensitivity was 80.6% and the specificity 83.7%. Odds ratio for breast cancer in a hypothetical population decreased from 1.12 [95% confidence interval (CI) 1.03-1.21] to 1.05 (95% CI 0.95-1.16) when corrected by the sensitivity and specificity estimates. CONCLUSION: This study shows that female breast cancer patients had slightly better recall of previous night shift work than controls. Additionally, both breast cancer patients and controls recalled previous never-night shift work with low specificity. The net effect of this misclassification is a small over-estimation of the relative breast cancer risk due to night shift work.

Association of nurse understaffing and limited nursing work experience with in-hospital mortality among patients: A longitudinal register-based study.

BACKGROUND: Although nurse understaffing and limited nursing work experience may affect hospital patients' risk of mortality, relatively little longitudinal patient-level evidence on these associations is available. Hospital administrative data could provide important information about the level of staffing, nurses' work experience and patient mortality over time. OBJECTIVE: To examine whether daily exposure to nurse understaffing and limited nursing work experience is associated with patient mortality, using patient-level data with different exposure time windows and accounting for several patient-related characteristics. METHODS: This longitudinal register-based study combined administrative data on patients (clinical database Auria) and employees (Titania® shift-scheduling) from one hospital district in Finland in 2013-2019, covering a total of 254,446 hospital stays in 40 units. We quantified nurse understaffing as the number of days with low nursing hours in relation to target hours (<90 % of the annual unit median), and limited work experience as the number of days with a low proportion of nurses with >3 years of in-hospital experience, and those aged over 25 (<90 % of the annual unit median). We used two survival model designs to analyze the associations between nurse understaffing and limited nursing work experience and the in-hospital mortality of the patients: we considered these exposures during the first days in hospital and as a cumulative proportion of days with suboptimal staffing during the first 30 days. RESULTS: In total, 1.5 % (N = 3937) of the hospital stays ended in death. A 20 % increase in the proportion of days with nurse understaffing was associated with an increased, 1.05-fold mortality risk at the patient level (95 % confidence interval, 1.01-1.10). The cumulative proportion of days with limited nursing work experience, or the combination of nurse understaffing and limited work experience were not associated with increased risk of death among all patients. However, both indicators of limited nursing work experience were associated with an increased mortality risk among patients with comorbidities (HR 1.05, 95 % CI 1.02-1.08 and HR 1.05, 95 % CI 1.00-1.10, respectively). CONCLUSIONS: Nurse understaffing was associated with a slight, but a potentially critical increase in patient in-hospital mortality. Limited nursing work experience was associated with increased in-hospital mortality in a subgroup of patients with comorbidities. Increased use of administrative data on planned and realized working hours could be a routine tool for reducing avoidable in-hospital mortality.

The Role of Continuing Professional Training or Development in Maintaining Current Employment: A Systematic Review.

The impact of continuing job education and professional development on early exit from the labor market is unclear. This systematic review examined how continuing job education or professional development influences the retention of current employment. We searched the PubMed and Embase databases from their start dates to January 2023. Two reviewers screened the full texts of relevant reports and assessed the methodological quality of the included studies using the adapted Effective Public Health Practice Project quality assessment. We qualitatively synthesized the results of the included studies. We screened 7338 publications and included 27 studies consisting of four cohort and 23 cross-sectional studies in the review. The participants of the selected studies were mostly from the health sector (24 studies). There were 19 studies on staying or leaving a current job, six on employee turnover intention, two on job change, one on return to work, one on early retirement, and one on employment. Continuing employee development or training opportunities were associated with increased intention to stay in a current job, decreased intention to leave a current job, decreased employee turnover intention, job change, or early retirement and with faster return to work. One of the two studies that examined the role of age showed that continuing employee development is a more important factor for retaining current employment among younger than older employees. A few studies found that job satisfaction and commitment fully mediated the relationship between employee development and employee intention to leave current employment. This study suggests that participating in professional training/development is related to a lower risk of leaving current employment.

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.

Concurrent trajectories of part-time work and sickness absence: a longitudinal cohort study over 11 years among shift working hospital employees.

OBJECTIVES: To investigate the concurrent changes in part-time work and sickness absence (SA) in healthcare. Another aim was to investigate the role of age and sex on different concurrent trajectory groups. DESIGN: Prospective cohort study. SETTING: Public hospital districts (n=10) and cities (n=11) in Finland. PARTICIPANTS: Payroll-based objective working hour data of the healthcare sector in Finland for 28 969 employees in 2008-2019 were used. The final sample included those working shifts with 3 consecutive years of data and without baseline (≥14 days) SA. PRIMARY OUTCOMES: Part-time work (yes or no) and months of SA. MEASURES: Group-based trajectory modelling to identify concurrent changes in part-time work, and months of SA while controlling the time-variant amount of night work and multinomial regression models for relative risk (RR) with 95% CIs were used. RESULTS: Four-group trajectory model was the best solution: group 1 (61.2%) with full-time work and no SA, group 2 (16.9%) with slowly increasing probability of part-time work and low but mildly increasing SA, group 3 (17.6%) with increasing part-time work and no SA, and group 4 (4.3%) with fluctuating, increasing part-time work and highest and increasing levels of SA. Men had a lower (RR 0.49-0.75) and older age groups had a higher likelihood (RRs 1.32-3.79) of belonging to trajectory groups 2-4. CONCLUSIONS: Most of the sample were in the trajectory group with full-time work and no SA. The probability of part-time work increased over time, linked with concurrent low increase or no SA. A minor group of employees had both an increased probability of part-time work and SA. Part-time work and other solutions might merit attention to promote sustainable working life among healthcare employees.

Night shift work characteristics and risk of incident coronary heart disease among health care workers: national cohort study.

BACKGROUND: Night work has been associated with coronary heart disease. The present study examined exposure-response relations between quantitative night work characteristics and coronary heart disease (angina pectoris or myocardial infarction) with the aim to contribute to evidence-based recommendations for low-risk night work schedules. METHODS: We followed 100 149 night workers (80% women) and 153 882 day workers (78% women), all health care workers in Denmark with day by day payroll information on night shifts from 2007 to 2015. We analysed data with Poisson regression stratified by sex and adjusted for age, calendar year, diabetes, family history of cardiovascular disease, educational level, occupation, indicators for obesity, hypercholesterolaemia, and hypertension. RESULTS: Female and male night workers worked on average 1.7 and 1.8 night shifts per month for an average duration of less than 4 years. During follow-up, 1198 night and 2128 day workers were hospitalized with first-time coronary heart disease. When compared with day workers, the overall incidence rate ratios for female and male night workers were 1.06 [95% confidence interval (CI): 0.97, 1.17] and 1.22 (95% CI 1.07, 1.39). Highest risks were observed in top exposure categories for several night work characteristics. However, no consistent exposure-response relations by number of monthly night shifts, cumulative night shifts, years with rotating night shifts, years with any night shift and consecutive night shifts were observed among the night workers of either sex. CONCLUSIONS: This study of a population with low exposure to night work does not indicate that reducing extent of monthly night shifts, cumulative night shifts, years with rotating night shifts, years with any night shift and consecutive night shifts would reduce the risk of coronary heart disease.

Night and shift work patterns and incidence of type 2 diabetes and hypertension in a prospective cohort study of healthcare employees.

OBJECTIVES: This study aimed to evaluate effects of night and shift work patterns on type 2 diabetes (T2D) and hypertension in a longitudinal study, with detailed information on working hours. METHODS: The cohort comprised about 28 000 nurses and nursing assistants employed for more than one year 2008-2016 in Stockholm, Sweden. The employee register held detailed individual information on daily working hours. Information on diagnoses came from national and regional registers. Hazard ratios (HR) and confidence intervals (CI) were estimated by discrete-time proportional hazard models, adjusting for sex, age, country of birth, and profession. RESULTS: During follow-up in 2013-2017, we identified 232 cases of T2D and 875 of hypertension. We observed an increased risk of T2D, but not hypertension, among employees who worked only night shifts the previous year (HR 1.59, 95% CI 1.02-2.43) and those with intensive shift work (>120 afternoon and/or night shifts the previous year: HR 1.67, 95% CI 1.11-2.48) compared to only day work. There was a non-significantly increased risk of T2D related to mixed day and afternoon shifts (HR 1.34, 95% CI 0.97-1.88). We observed tendencies in increased risk of T2D related to frequent spells of ≥3 consecutive night shifts and with number of years with exclusive (but not mixed) night work. CONCLUSIONS: Permanent night work and frequent afternoon and/or night shifts were associated with an increased risk of T2D the following year, but not hypertension. The T2D risk was, to some extent, affected by frequent spells of several night shifts in a row and by cumulative years with permanent night work.

Work unit level personnel working hours and the patients' length of in-hospital stay-An administrative data approach.

Administrative data accumulating daily from hospitals would provide new possibilities to assess work shifts and patient care. We aimed to investigate associations of work unit level average work shift length and length of patient in-hospital stay, and to examine the role of nurse-patient-ratio, year, night work, age, work units and working hours at the work units for these estimations. The data for this study were based on combined administrative day-to-day patient and pay-roll based objective working hour data of employees of one hospital district in Finland for 2013-2019. Three patient measures were calculated: the overall length of in-hospital stay, the length of in-hospital stay before a medical procedure and the length of in-hospital stay after a medical procedure. A Generalized Linear Mixed Model (GLMM) with multivariate normal random effects was used with Penalized Quasi-Likelihood for relative risk ratios (RR) with 95% confidence intervals (CI). The results showed that compared to <8 hours work shifts, 8-10 hours work shifts were associated with an increased likelihood of overall length of in-hospital stay (RR 1.16, 95%CI 1.15, 1.16), and the length of in-hospital stay after a medical procedure (RR 1.28, 95%CI 1.27, 1.30). The >10 hours work shifts were associated with a decreased likelihood of the overall length of in-hospital stay (RR 0.94, 95% CI 0.94, 0.95) and length of in-hospital stay after a medical procedure among all occupations (RR 0.94, 95% CI 0.92, 0.97). These associations retained the magnitude and direction in the models additionally adjusted for work, employee, and patient characteristics, and the associations were weaker for nurses than among all occupations. To conclude, compared with the standard work shifts, 8-10 hours work shifts seem to be associated with longer, and >10 hours work shifts with shorter length of in-hospital stay. Administrative data provides feasible possibilities to investigate working hours and length of in-hospital stay.

Night work and breast cancer risk in a cohort of female healthcare employees in Stockholm, Sweden.

OBJECTIVES: Night work has been classified as probably carcinogenic to humans by the International Agency for Research on Cancer, but epidemiological evidence was considered limited due to variability in findings and potential bias. This study aimed to investigate the risk of breast cancer in a cohort with detailed and registry-based data on night work. METHODS: The cohort comprised 25 585 women (nurses and nursing assistants) employed 1 year or more between 2008 and 2016 in the healthcare sector in Stockholm. Information on work schedules was obtained from employment records. Breast cancer cases were identified from the national cancer register. HRs were estimated by a discrete time proportional hazards model, adjusting for age, country of birth, profession and childbirth. RESULTS: There were 299 cases of breast cancer, 147 in premenopausal and 152 in postmenopausal women. The adjusted HR of postmenopausal breast cancer in association with ever versus never working nights was 1.31 (95% CI 0.91 to 1.85). Eight or more years of night work was associated with an increased risk of postmenopausal breast cancer, HR=4.33 (95% CI 1.45 to 10.57), based on five cases only, though. CONCLUSIONS: This study is limited by a short period of follow-up and a lack of information on night work before 2008. Most exposure metrics showed no association with breast cancer risk, but there was an elevated risk of postmenopausal breast cancer in women after 8 or more years of night work.

Nurse Staffing Level, Length of Work Experience, and Risk of Health Care-Associated Infections Among Hospital Patients: A Prospective Record Linkage Study.

BACKGROUND: Nurse understaffing may have several adverse consequences for patients in hospitals, such as health care-associated infections (HAIs), but there is little longitudinal evidence available on staffing levels and HAIs with consideration of incubation times to confirm this. Using daily longitudinal data, we analyzed temporal associations between nurse understaffing and limited work experience, and the risk of HAIs. METHODS: The study was based on administrative data of 40 units and 261,067 inpatient periods for a hospital district in Finland in 2013-2019. Survival analyses with moving time windows were used to examine the association of nurse understaffing and limited work experience with the risk of an HAI 2 days after exposure, adjusting for individual risk factors. We reported hazard ratios (HRs) with 95% CIs. RESULTS: Neither nurse understaffing nor limited work experience were associated with the overall risk of HAIs. The results were inconsistent across staffing measures and types of HAIs, and many of the associations were weak. Regarding specific HAI types, 1-day exposure to low proportion of nurses with >3 years of in-hospital experience and low proportion of nurses more than 25 years old were associated with increased risk of bloodstream infections (HR=1.30; 95% CI: 1.04-1.62 and HR=1.40; 95% CI: 1.07-1.83). Two-day exposure to low nursing hours relative to target hours was associated with an increased risk of surgical-site infections (HR=2.64, 95% CI: 1.66-4.20). CONCLUSIONS: Data from time-varying analyses suggest that nursing staff shortages and limited work experience do not always increase the risk of HAI among patients.

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.

The association between the use of shift schedule evaluation tool with ergonomics recommendations and occupational injuries: A 4-year prospective cohort study among healthcare workers.

OBJECTIVE: This study aimed to find out whether utilizing a shift schedule evaluation tool with ergonomics recommendations for working hours has favorable effects on the incidence of occupational injuries. METHODS: This 4-year prospective cohort study (2015-2018) consisted of a dynamic cohort of healthcare shift workers (N=29 237) from ten hospital districts and six cities in Finland. Working hour characteristics and occupational injuries were measured with daily registry data. Multilevel generalized linear model was used for the analyses, and the estimates were controlled for hierarchical structure of the data and confounders. RESULTS: Ward heads of the cities used the shift schedule evaluation tool 3.2 times more often than ward heads of the hospital districts. Overall incidence of workplace and commuting injuries did not differ between users and non-users of the evaluation tool. The incidence of dislocations, sprains, and strains was lower in the users than non-users [adjusted odds ratio (OR) 0.88, 95% confidence interval (CI) 0.78-0.99]. Approximately 13% of this association was mediated by increase in realized shift wishes and 10% by increase in single days off. In subgroup analyses, the incidence of workplace injury (OR 0.83, 95% CI 0.69-0.99), and among types of injuries, the incidence of dislocations, sprains, and strains (OR 0.69, 95% CI 0.55-0.85) and falling, slipping, tripping, or overturning (OR 0.75, 95% CI 0.58-0.99) were lower in users than non-users among employees of the cities, but no association was found among employees of the hospital districts. CONCLUSION: The use of ergonomics recommendations for working hours is associated with a reduced risk of occupational injuries.

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.

The Time-Varying Effect of Participatory Shift Scheduling on Working Hour Characteristics and Sickness Absence: Evidence from a Quasi-Experiment in Hospitals.

Participatory shift scheduling for irregular working hours can influence shift schedules and sickness absence. We investigated the effects of using participatory shift scheduling and shift schedule evaluation tools on working hour characteristics and sickness absence. We utilized a panel data for 2015-2019 with 16,557 hospital employees (6143 in the intervention and 10,345 in the control group). Difference-in-differences regression with ward-level clustered standard errors was used to estimate the average treatment effect on the treated coefficients relative to timing of the intervention with 95% confidence intervals (CI). Using participatory scheduling tool increased long working hours and weekend work and had delayed effects on the short (1-3 days) sickness absences. Increased effects were observed: 0.2 [95% CI 0.0-0.4] days for the second, and 0.8 [95% CI 0.5-1.0] for the third year after the onset of intervention. An average increase of 0.5 [95% CI 0.1-0.9] episodes on all sickness absence episodes was observed for the third year. Using the shift schedule evaluation tool with the participatory shift scheduling tool attenuated the adverse effects. To conclude, participatory shift scheduling increased some potentially harmful working hour characteristics but its effects on sickness absence were negligible, and further attenuated by using the shift schedule evaluation tool.

Concurrent trajectories of self-rated health and working hour patterns in health care shift workers: A longitudinal analysis with 8-year follow-up.

Background: The association between health and working hours is hypothesized to be reciprocal, but few longitudinal studies have examined changes in both health and working hour patterns over time. We examined combined trajectories of self-related health and two working hour patterns (working <35 h/week and working night shifts) and the extent to which these trajectories were predicted by employees' lifestyle and mental health. Methods: Participants of this cohort study with a 8-year follow-up were 5,947 health care shift workers. We linked self-reports of health from three repeated surveys with objective pay-roll based data on working hours. Using group-based multi-trajectory analysis we identified concurrent trajectories for self-rated health and working hour patterns. We examined their associations with baseline lifestyle-related factors (smoking, at-risk alcohol use, obesity, and physical inactivity) and mental health (sleep problems and psychological distress) using multinomial regression analysis. Results: Three combined trajectories of self-rated health and working <35 h/week and four combined trajectories of self-rated health and night work were identified. Unhealthy lifestyle and poor mental health were associated with trajectories of moderate and declining health. Sleep problems were linked with working <35 h/week. Younger age and good mental health were associated with a combined trajectory of good health and continued night shift work. Conclusion: Trajectories of suboptimal and declining health are associated with trajectories of reducing working hours and leaving night work, and are more common in employees with unhealthy lifestyle, sleep problems, and psychological distress.