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

PurposeThis 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.MethodsCohort 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.Results30,857 (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).ConclusionsAn 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

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

Mental health symptoms identify workers at risk of long-term sickness absence due to mental disorders: prospective cohort study with 2-year follow-up

Background: Mental health problems are a leading cause of long-term sickness absence (LTSA). Workers at risk of mental LTSA should preferably be identified before they report sick. The objective of this study was to examine mental health symptoms as predictors of future mental LTSA in non-sicklisted workers. Methods: Prospective cohort study of 4877 non-sicklisted postal workers. Mental health symptoms were measured at baseline in November 2010 with the Four-Dimensional Symptom Questionnaire (distress and depressed mood) and Maslach's Burnout Inventory (fatigue). Mental health symptom scores were analyzed against incident mental LTSA retrieved from an occupational health register in 2011 and 2012. The area under the receiver operating characteristic curve (AUC) represented the ability of mental health symptom scores to discriminate between workers with and without mental LTSA during 2-year follow-up. Results: Complete cases analysis included 2782 (57 %) postal workers of whom 73 had mental LTSA during 2-year follow-up. Distress fairly (AUC = 0.75; 95 % CI 0.67-0.82) and both depressed mood (AUC = 0.64; 95 % CI 0.57-0.72) and fatigue (AUC = 0.61; 95 % CI 0.53-0.69) poorly discriminated between workers with and without mental LTSA during 2-year follow-up. The discriminative ability of distress did not improve by adding depressed mood and fatigue. Conclusions: Measurement of distress sufficed to identify non-sicklisted postal workers at risk of future mental LTSA. The Four-Dimensional Symptom Questionnaire distress scale is a promising tool to screen working populations for of mental LTSA, which enables secondary preventive strategies

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

Psychological distress screener for risk of future mental sickness absence in non-sicklisted employees

Background: Recently, a three-item screener, derived from the 16-item distress scale of the Four-Dimensional Symptom Checklist (4DSQ), was used to measure psychological distress in sicklisted employees. The aim of the present study was to investigate the ability of the 16-item distress scale and three-item distress screener to identify non-sicklisted employees at risk of sickness absence (SA) due to mental disorders. Methods: Prospective cohort study including 4877 employees working in distribution and transport. The 4DSQ distress scale was distributed at baseline in November 2010. SA diagnosed within the International Classification of Diseases -10 chapter F was defined as mental SA and retrieved from an occupational health register during 2-year follow-up. The area under the receiver operating characteristic curve (AUC) was used to discriminate between workers with ('cases') and without ('non-cases') mental SA during follow-up. Results: A total of 2782 employees (57%) were included in complete cases analysis; 73 employees had mental SA during 2-year follow-up. Discrimination between cases and non-cases was similar for the 16-item distress scale (AUC = 0.721; 95% CI, 0.622-0.823) and the three-item screener (AUC = 0.715; 95% CI, 0.615-0.815). Conclusion: Healthcare providers could use the three-item distress screener to identify non-sicklisted employees at risk of future mental SA