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

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

Inter-physician agreement on the readiness of sick-listed employees to return to work

Purpose: To determine the agreement between occupational physician (OP) ratings of an employee's readiness to return to work (RRTW). Method: Anonymized written vignettes of 132 employees, sick-listed for at least 3 weeks, were reviewed by 5 OPs. The OPs intuitively rated RRTW as the ability (knowledge and skills) and willingness (motivation and confidence) of sick-listed employees to resume work. Inter-OP percentages of agreement were calculated and Cohen's kappas (kappa) were determined to correct for agreement by chance. Results: The percentage of agreement between OPs was 57% (range 39-89%) on the ability and 63% (range 48-87%) on the willingness of sick-listed employees to resume work. The mean. was 0.14 (range from -0.21 to 0.79) for ability and 0.25 (range from -0.11 to 0.74) for willingness. The OP-rating of RRTW of employees sick-listed with mental disorders did not differ from the OP-rating of RRTW of employees with musculoskeletal disorders. Conclusion: The inter-OP agreement on intuitively rated RRTW showed a wide variability, which accentuates the need for instruments to establish an employee's RRTW and for training in giving well founded return to work recommendations

Risk reclassification analysis investigating the added value of fatigue to sickness absence predictions

Prognostic models including age, self-rated health and prior sickness absence (SA) have been found to predict high (a parts per thousand yen30) SA days and high (a parts per thousand yen3) SA episodes during 1-year follow-up. More predictors of high SA are needed to improve these SA prognostic models. The purpose of this study was to investigate fatigue as new predictor in SA prognostic models by using risk reclassification methods and measures. This was a prospective cohort study with 1-year follow-up of 1,137 office workers. Fatigue was measured at baseline with the 20-item checklist individual strength and added to the existing SA prognostic models. SA days and episodes during 1-year follow-up were retrieved from an occupational health service register. The added value of fatigue was investigated with Net Reclassification Index (NRI) and integrated discrimination improvement (IDI) measures. In total, 579 (51 %) office workers had complete data for analysis. Fatigue was prospectively associated with both high SA days and episodes. The NRI revealed that adding fatigue to the SA days model correctly reclassified workers with high SA days, but incorrectly reclassified workers without high SA days. The IDI indicated no improvement in risk discrimination by the SA days model. Both NRI and IDI showed that the prognostic model predicting high SA episodes did not improve when fatigue was added as predictor variable. In the present study, fatigue increased false-positive rates which may reduce the cost-effectiveness of interventions for preventing SA

Effect of an eHealth Intervention to Reduce Sickness Absence Frequency Among Employees With Frequent Sickness Absence:Randomized Controlled Trial

BACKGROUND: Frequent sickness absence-that is, 3 or more episodes of sickness absence in 1 year-is a problem for employers and employees. Many employees who have had frequent sickness absence in a prior year also have frequent sickness absence in subsequent years: 39% in the first follow-up year and 61% within 4 years. Moreover, 19% have long-term sickness absence (≥6 weeks) in the first follow-up year and 50% within 4 years. We developed an electronic health (eHealth) intervention, consisting of fully automated feedback and advice, to use either as a stand-alone tool (eHealth intervention-only) or combined with consultation with an occupational physician (eHealth intervention-occupational physician)

Sickness absence frequency among women working in hospital care

Background Frequent short sickness absences result in understaffing and interfere with work processes. We need more knowledge about factors associated with this type of absence. Aims To investigate associations between the frequency of previous sickness absence and self-reported perceptions of health and work. Methods Cross-sectional study of female hospital care workers in which health, work characteristics and coping styles were assessed by questionnaire and linked to the number of sickness absence episodes recorded in the preceding 5 years using negative binomial regression analysis for counts distinguishing between short (1-7 days) and long (>7 days) episodes of absence after adjusting for age and duration of employment in December 2007 and hours worked between 2003 and 2007. Results Of 350 women employed for at least 5 years, 237 (68%) answered the questionnaire. The hours worked over the 5 year period [rate ratio (RR) = 1.2] and problem solving coping style score (RR = 1.1) were positively associated with the number of short sickness absence episodes. Age (RR = 0.8) and good general health (RR = 0.7) were inversely related to the number of both short and long episodes. Self-reported mental health and work characteristics were not shown to be related to the frequency of sickness absence. Conclusions Hours worked, problem-solving coping style, age and general health showed associations with the frequency of previous sickness absence among women who had worked at least 5 years in health care. Future prospective studies on the frequency of sickness absence should consider the impact of these factors further

Effect of an eHealth Intervention to Reduce Sickness Absence Frequency Among Employees With Frequent Sickness Absence:Randomized Controlled Trial

BACKGROUND: Frequent sickness absence-that is, 3 or more episodes of sickness absence in 1 year-is a problem for employers and employees. Many employees who have had frequent sickness absence in a prior year also have frequent sickness absence in subsequent years: 39% in the first follow-up year and 61% within 4 years. Moreover, 19% have long-term sickness absence (≥6 weeks) in the first follow-up year and 50% within 4 years. We developed an electronic health (eHealth) intervention, consisting of fully automated feedback and advice, to use either as a stand-alone tool (eHealth intervention-only) or combined with consultation with an occupational physician (eHealth intervention-occupational physician)

Focus Group Study Exploring Factors Related to Frequent Sickness Absence

INTRODUCTION:Research investigating frequent sickness absence (3 or more episodes per year) is scarce and qualitative research from the perspective of frequent absentees themselves is lacking. The aim of the current study is to explore awareness, determinants of and solutions to frequent sickness absence from the perspective of frequent absentees themselves. METHODS:We performed a qualitative study of 3 focus group discussions involving a total of 15 frequent absentees. Focus group discussions were audiotaped and transcribed verbatim. Results were analyzed with the Graneheim method using the Job Demands Resources (JD-R) model as theoretical framework. RESULTS:Many participants were not aware of their frequent sickness absence and the risk of future long-term sickness absence. As determinants, participants mentioned job demands, job resources, home demands, poor health, chronic illness, unhealthy lifestyles, and diminished feeling of responsibility to attend work in cases of low job resources. Managing these factors and improving communication (skills) were regarded as solutions to reduce frequent sickness absence. CONCLUSIONS:The JD-R model provided a framework for determinants of and solutions to frequent sickness absence. Additional determinants were poor health, chronic illness, unhealthy lifestyles, and diminished feeling of responsibility to attend work in cases of low job resources. Frequent sickness absence should be regarded as a signal that something is wrong. Managers, supervisors, and occupational health care providers should advise and support frequent absentees to accommodate job demands, increase both job and personal resources, and improve health rather than express disapproval of frequent sickness absence and apply pressure regarding work attendance

Coping styles relate to health and work environment of Norwegian and Dutch hospital nurses:A comparative study

Nurses exposed to high nursing stress report no health complaints as long as they have high coping abilities. The purpose of this study was to investigate coping styles in relation to the health status and work environment of Norwegian and Dutch hospital nurses. This comparative study included a random sample of 5400 Norwegian nurses and a convenience sample of 588 Dutch nurses. Coping, health, and work environment were assessed by questionnaire in both samples and associations were investigated bivariately and multi-variately. We found that active problem-solving coping was associated with the health and work environment of Norwegian nurses but not with the health and work environment of Dutch. Passive coping (avoiding problems or waiting to see what happens) was found to relate to poor general health, poor mental health, low job control, and low job support in both Norwegian and Dutch nurses. Improvements in the nursing work environment may not only result in better mental health, but may also reduce passive coping

Subjective health complaints in relation to sickness absence

Objective: The Dutch population is healthy in terms of living and working conditions, but the levels of subjective health complaints (SHC) and sickness absence are high in the Dutch workforce. Are SHC related to sickness absence? Participants: The study population included the personnel of four companies: a library (n = 185), an administrative office (n = 114), a cheese factory (n = 201) and a company producing metal constructions (n = 65). Methods: The employees received the Basic Occupational Health Questionnaire including 22 common SHC. For each employee, the number and type of SHC but not their intensity was linked to the number of sickness absence episodes between January 2003 and December 2004. Results: The questionnaires of 409 employees (72%) were suitable for statistical analysis. The prevalence of SHC in the study population was 78% between January and June 2003. Employees who reported >= 5 SHC had higher rates of both short (1-7 days) and medium (8-42 days) sickness absence episodes. Long (> 42 days) episodes were strongly related to SHC amounting to a rate ratio (RR) of 4.2 with a 95% confidence interval [CI] 1.7 to 10.4 in workers reporting multiple SHC relative to those without complaints. Fatigue was associated with medium duration sickness absence (RR = 1.6; 95% CI 1.1-2.2) and musculoskeletal complaints, particularly low back pain (RR = 1.8; 95% CI 1.2-2.8), with long episodes. Conclusions: The number of SHC was related to sickness absence. The 20% of participants reporting most SHC were responsible for about 40% of work days lost in the two-year period of study