Strategy for finding occupational health survey participants at risk of long-term sickness absence

BACKGROUND: When resources are limited, occupational health survey participants are usually invited to consultations based on an occupational health provider's subjective considerations. This study aimed to find health survey participants at risk of long-term (i.e., ≥ 42 consecutive days) sickness absence (LTSA) for consultations with occupational health providers (OHPs). METHODS: The data of 64 011 non-sicklisted participants in occupational health surveys between 2010 and 2015 were used for the study. In a random sample of 40 000 participants, 27 survey variables were included in decision tree analysis (DTA) predicting LTSA at 1-year follow-up. The decision tree was transferred into a strategy to find participants for OHP consultations, which was then tested in the remaining 24 011 participants. RESULTS: In the development sample, 1358 (3.4%) participants had LTSA at 1-year follow-up. DTA produced a decision tree with work ability as first splitting variable; company size and sleep problems were the other splitting variables. A strategy differentiating by company size would find 75% of the LTSA cases in small (≤99 workers) companies and 43% of the LTSA cases in medium-sized (100-499 workers) companies. For large companies (≥500 workers), case-finding was only 25%. CONCLUSIONS: In small and medium-sized companies, work ability and sleep problems can be used to find occupational health survey participants for OHP consultations aimed at preventing LTSA. Research is needed to further develop a case-finding strategy for large companies

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

К численному решению задач о деформации анизотропных пластин с отверстием

Представлен подход к расчету напряженно-деформированного состояния пластин с отверстием, основанный на численной параметризации двусвязной области, сведении исходной нелинейной краевой задачи к последовательности линейных двухмерных и интегрировании последних устойчивым численным методом. Исследуется влияние формы и месторасположения отверстия на напряженно-деформированное состояние квадратной пластины.Представлено підхід до розрахунку напружено-деформованого стану пластин, що послаблені отвором. Підхід базується на числовій параметризації двозв’язної області, зведенні вихідної нелінійної задачі до послідовності лінійних двомірних та останніх до одномірних, інтегрування яких проводиться стійким числовим методом. Досліджується вплив форми та місцезнаходження отвору на напружено-деформований стан квадратної пластини.The study presents an approach to stressed-state analysis of plates with apertures which is based on the numerical parameterization of a doubly-connected area, reduction of the initial nonlinear boundary-value problem to a sequence of linear two-dimensional problems and integrating the latter by the stable numerical method. The effect of form and place of an aperture on stressed state of a square plate has been analyzed

Psychosocial work characteristics and long-term sickness absence due to mental disorders

Background: Psychosocial work characteristics are associated with all-cause long-term sickness absence (LTSA). Aims: This study investigated whether psychosocial work characteristics such as higher workload, faster pace of work, less variety in work, lack of performance feedback, and lack of supervisor support are prospectively associated with higher LTSA due to mental disorders. Methods: Cohort study including 4877 workers employed in the distribution and transport sector in The Netherlands. Psychosocial work characteristics were included in a logistic regression model estimating the odds ratios (OR) and 95% confidence intervals (CI) of mental LTSA during 2-year follow-up. The ability of the regression model to discriminate between workers with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). Results: Tow thousand seven hundred and eighty-two (57%) workers were included in the analysis; 73 (3%) had mental LTSA. Feedback about one’s performance (OR = 0.82; 95% CI 0.70–0.96) was associated with mental LTSA. A prediction model including psychosocial work characteristics poorly discriminated (AUC = 0.65; 95% CI 0.56–0.74) between workers with and without mental LTSA. Conclusions: Feedback about one’s performance is associated with lower rates of mental LTSA, but it is not useful to measure psychosocial work characteristics to identify workers at risk of mental LTSA

Polymorphism of Xeroderma Pigmentosum group G and the risk of lung cancer and squamous cell carcinomas of the oropharynx, larynx and esophagus

We investigated the effects of XPG His1104Asp polymorphism (rs17655) on the risk of lung cancer and squamous cell carcinomas of the oropharynx, larynx and esophagus (SCCOLE). This population‐based case‐control study involves 611 new cases of lung cancer, 601 new cases of oropharyngeal, laryngeal and esophageal cancers, and 1,040 cancer‐free controls. The XPG polymorphism was assayed by PCR‐RFLP method for 497 lung cancer cases, 443 cases of oropharyngeal, laryngeal and esophageal cancers and 912 controls. Binary and polytomous unconditional logistic regression models were fitted to assess the main effects and the effect modifications between the polymorphism and environmental exposures. With the adjustment for potential confounders, the XPG Asp1104Asp genotype was inversely associated with lung cancer (odds ratio [OR] = 0.62, 95% confidence limits [CL] = 0.38, 1.0) and SCCOLE (OR = 0.47, 95% CL = 0.27, 0.82), with the combined His1104His and His1104Asp genotypes as the referent. With subjects having genotype Asp1104Asp and no tobacco smoking exposure as the common referent, the ORs on lung cancer were 13 (95% CL = 4.4, 37) for heavy tobacco smoking (>20 pack‐years), 1.9 (95% CL = 0.78, 4.5) for having at least one copy of 1104His, and 23 (95% CL = 9.5, 56) for the joint effect, respectively. Compared to non‐smokers with the Asp1104Asp genotype, the adjusted OR on SCCOLE for heavy smokers (>20 pack‐years) having at least one copy of 1104His was 8.0 (95% CL = 2.7, 24). Similarly, compared to non‐drinkers with the Asp1104Asp genotype, the adjusted OR on SCCOLE for heavy drinkers (≥3 drinks/day) with at least one copy of 1104His was 10 (95% CL = 2.7, 38). In conclusion, our study suggests that the XPG Asp1104Asp genotype may be associated with decreased susceptibility to lung cancer and SCCOLE. © 2005 Wiley‐Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88003/1/21413_ftp.pd