Distress, Work Satisfaction, and Work Ability are Mediators of the Relation Between Psychosocial Working Conditions and Mental Health-Related Long-Term Sickness Absence.

Purpose This study investigated the effects of psychosocial working conditions on mental health-related long-term sickness absence and whether distress, work satisfaction, burnout, engagement, and work ability mediated the associations between psychosocial working conditions and mental health-related long-term sickness absence. Methods This cohort study included 53,833 non-sick listed workers who participated in occupational health surveys between 2010 and 2013. The effects of the individual psychosocial working conditions on mental long-term sickness absence were analyzed using univariable and multivariable logistic regression analyses. Mediation analyses were performed to examine the mediating role of distress, burnout, work satisfaction, engagement, and work ability between psychosocial working conditions and mental long-term sickness absence. The mediation analyses were performed using structural equation modeling. Results Role clarity, cognitive demands, emotional demands, work variety, learning opportunities, and co-worker support were related to mental health-related long-term sickness absence after adjustment for other working conditions. The relationship between emotional demands and mental health-related long-term sickness absence was the strongest, OR 1.304 (p < 0.001, 95% CI 1.135 to 1.498). The relation between psychosocial working conditions and mental health-related long-term sickness absence was mediated by distress, burnout, work satisfaction, engagement, and work ability. Distress was the most important mediator between psychosocial working conditions and mental health-related long-term sickness absence. Conclusions Psychosocial working conditions are related to mental health-related long-term sickness absence. After correction for other working conditions, the association between emotional demands and mental health-related long-term sickness absence was the strongest. Psychosocial working conditions are indirectly related to mental health-related long-term sickness absence through mediation by distress, work satisfaction, and work ability.

External validation of a prediction model and decision tree for sickness absence due to mental disorders.

PURPOSE: A previously developed prediction model and decision tree were externally validated for their ability to identify occupational health survey participants at increased risk of long-term sickness absence (LTSA) due to mental disorders. METHODS: The study population consisted of N = 3415 employees in mobility services who were invited in 2016 for an occupational health survey, consisting of an online questionnaire measuring the health status and working conditions, followed by a preventive consultation with an occupational health provider (OHP). The survey variables of the previously developed prediction model and decision tree were used for predicting mental LTSA (no = 0, yes = 1) at 1-year follow-up. Discrimination between survey participants with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). RESULTS: A total of n = 1736 (51%) non-sick-listed employees participated in the survey and 51 (3%) of them had mental LTSA during follow-up. The prediction model discriminated (AUC = 0.700; 95% CI 0.628-0.773) between participants with and without mental LTSA during follow-up. Discrimination by the decision tree (AUC = 0.671; 95% CI 0.589-0.753) did not differ significantly (p = 0.62) from discrimination by the prediction model. CONCLUSION: At external validation, the prediction model and the decision tree both poorly identified occupational health survey participants at increased risk of mental LTSA. OHPs could use the decision tree to determine if mental LTSA risk factors should be explored in the preventive consultation which follows after completing the survey questionnaire.

Development of Prediction Models for Sickness Absence Due to Mental Disorders in the General Working Population.

Purpose This study investigated if and how occupational health survey variables can be used to identify workers at risk of long-term sickness absence (LTSA) due to mental disorders. Methods Cohort study including 53,833 non-sicklisted participants in occupational health surveys between 2010 and 2013. Twenty-seven survey variables were included in a backward stepwise logistic regression analysis with mental LTSA at 1-year follow-up as outcome variable. The same variables were also used for decision tree analysis. Discrimination between participants with and without mental LTSA during follow-up was investigated by using the area under the receiver operating characteristic curve (AUC); the AUC was internally validated in 100 bootstrap samples. Results 30,857 (57%) participants had complete data for analysis; 450 (1.5%) participants had mental LTSA during follow-up. Discrimination by an 11-predictor logistic regression model (gender, marital status, economic sector, years employed at the company, role clarity, cognitive demands, learning opportunities, co-worker support, social support from family/friends, work satisfaction, and distress) was AUC = 0.713 (95% CI 0.692-0.732). A 3-node decision tree (distress, gender, work satisfaction, and work pace) also discriminated between participants with and without mental LTSA at follow-up (AUC = 0.709; 95% CI 0.615-0.804). Conclusions An 11-predictor regression model and a 3-node decision tree equally well identified workers at risk of mental LTSA. The decision tree provides better insight into the mental LTSA risk groups and is easier to use in occupational health care practice.

Framingham score and work-related variables for predicting cardiovascular disease in the working population.

BACKGROUND: The Framingham score is commonly used to estimate the risk of cardiovascular disease (CVD). This study investigated whether work-related variables improve Framingham score predictions of sickness absence due to CVD. METHODS: Eleven occupational health survey variables (descent, marital status, education, work type, work pace, cognitive demands, supervisor support, co-worker support, commitment to work, intrinsic work motivation and distress) and the Framingham Point Score (FPS) were combined into a multi-variable logistic regression model for CVD sickness absence during 1-year follow-up of 19 707 survey participants. The Net Reclassification Index (NRI) was used to investigate the added value of work-related variables to the FPS risk classification. Discrimination between participants with and without CVD sickness absence during follow-up was investigated by the area under the receiver operating characteristic curve (AUC). RESULTS: A total of 129 (0.7%) occupational health survey participants had CVD sickness absence during 1-year follow-up. Manual work and high cognitive demands, but not the other work-related variables contributed to the FPS predictions of CVD sickness absence. However, work type and cognitive demands did not improve the FPS classification for risk of CVD sickness absence [NRI = 2.3%; 95% confidence interval (CI) -2.7 to 9.5%; P = 0.629]. The FPS discriminated well between participants with and without CVD sickness absence (AUC = 0.759; 95% CI 0.724-0.794). CONCLUSION: Work-related variables did not improve predictions of CVD sickness absence by the FPS. The non-laboratory Framingham score can be used to identify health survey participants at risk of CVD sickness absence.

External Validation and Update of a Prediction Rule for the Duration of Sickness Absence Due to Common Mental Disorders.

Purpose The objective of the present study was to validate an existing prediction rule (including age, education, depressive/anxiety symptoms, and recovery expectations) for predictions of the duration of sickness absence due to common mental disorders (CMDs) and investigate the added value of work-related factors. Methods A prospective cohort study including 596 employees who reported sick with CMDs in the period from September 2013 to April 2014. Work-related factors were measured at baseline with the Questionnaire on the Experience and Evaluation of Work. During 1-year follow-up, sickness absence data were retrieved from an occupational health register. The outcome variables of the study were sickness absence (no = 0, yes = 1) at 3 and 6 months after reporting sick with CMDs. Discrimination between workers with and without sickness absence was investigated at 3 and 6 months with the area under the receiver operating characteristic curve (AUC). Results A total of 220 (37 %) employees agreed to participate and 211 (35 %) had complete data for analysis. Discrimination was poor with AUC = 0.69 and AUC = 0.55 at 3 and 6 months, respectively. When 'variety in work' was added as predictor variable, discrimination between employees with and without CMD sickness absence improved to AUC = 0.74 (at 3 months) and AUC = 0.62 (at 6 months). Conclusions The original prediction rule poorly predicted CMD sickness absence duration. After adding 'variety in work', the prediction rule discriminated between employees with and without CMD sickness absence 3 months after reporting sick. This new prediction rule remains to be validated in other populations.

Shift work and mental health sickness absence: a 10-year observational cohort study among male production workers.

OBJECTIVES: Epidemiological studies investigating mental-health-related sickness absence (SA) among shift workers are lacking. This 10-year observational study investigated the risk of mental health SA among shift compared with day workers. METHODS: The data of 5826 male production workers were used for analyses: 4288 (74%) shift and 1538 (26%) day workers. The risk of mental health SA was analyzed with Cox regression analysis. Hazard ratios (HR) and 95% confidence intervals (95% CI) were adjusted for age and occupational grade. RESULTS: During a 10-year follow-up, 351 shift workers and 126 day workers had incident mental health SA. The risk of mental health SA did not differ (HR 1.03, 95% CI 0.84-1.26) between shift and day workers. Among shift workers, the risk of SA due to mood disorders (HR 1.87, 95% CI 0.73-4.76) was non-significantly higher than among day workers. A total of 96 shift workers and 21 day workers had recurrent mental health SA. The risk of recurrent mental health SA did not differ (HR 1.04, 95% CI 0.62-1.74) between shift and day workers. CONCLUSION: The risk of incident and recurrent mental health SA did not differ between shift and day workers.

Recovery and recurrence of mental sickness absence among production and office workers in the industrial sector.

BACKGROUND: Manual workers in the public sector have previously been found to be at risk of mental sickness absence (SA). As the impact of mental illness differs across economic sectors, this study investigated mental SA in the industrial sector, differentiating between office and production workers. METHODS: Ten-year observational cohort study including 14 369 (8164 production and 6205 office) workers with a total of 101 118 person years. SA data were retrieved from an occupational health register. Mental SA episodes were medically certified as emotional disturbances [10th version of the International Classification of Diseases (ICD-10 R45)] or mental and behavioural disorders (ICD-10 F00-F99). The first mental SA episode since baseline was called index mental SA. Recurrences were defined as any mental SA episode occurring >28 days after recovery from index mental SA. RESULTS: The incidence of mental SA was higher in production workers than in office workers, but office workers needed longer time to recover from mental SA. Mental SA recurred as frequently in production workers as in office workers. The median time to recurrence was 15.9 months and tangibly shorter in office workers (14.9 months) than in production workers (16.7 months). Production and office workers aged >55 years were at increased risk of recurrent mental SA within 12 months of recovery from index mental SA. CONCLUSIONS: The incidence of mental SA was higher in production workers than in office workers, whereas recurrence rates did not differ between them. Occupational health providers should pay special attention to older workers as they are at increased risk of recurrent mental SA.

Predictors of recurrent sickness absence due to depressive disorders--a Delphi approach involving scientists and physicians.

BACKGROUND: Depression is a common and highly recurrent mental disorder that is accompanied by poor functioning at home and at work. Not all depressed employees report sick and little is known about variables associated with sickness absence (SA) due to depression. Recurrent SA due to depression tends to marginalize employees from the workforce and exclude them from social participation. Therefore, this study sought group consensus on factors predicting recurrent SA due to depression. METHODOLOGY/PRINCIPAL FINDINGS: 23 scientists in the field of work and mental health and 23 physicians with expertise in assessing work disability were invited for a Delphi study. Sixty-seven factors retrieved from the literature were scored for their impact on the recurrence of SA due to depression, range 1 (no impact) to 10 (very high impact) in two Delphi rounds. The third Delphi round addressed the assessability and modifiability of elected predictors. Group consensus was defined as 75% agreement. In the first round (response 78%), group consensus was reached on a high impact of 13 factors on recurrent SA due to depression. The second round (response 79%) added another 8 factors with high impact on recurrent SA due to depression. The panelists were of the opinion that stressful life and work events, age at first diagnosis, duration of the last depressive episode, anxiety, lifetime number of depressive episodes, and psychological work demands were readily assessable in consultation with patients. Furthermore, work factors, particularly decision latitude, psychological job demands, and commitment to work, were recognized as modifiable. CONCLUSIONS/SIGNIFICANCE: Although results have to be validated with further quantitative research, physicians may identify employees at risk of recurrent SA due to depression and may support them to adjust their work aimed at increasing commitment to work and preventing future SA due to depression.