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      Betriebliche Gesundheitspolitik : Der Weg zur gesunden Organisation 

      Kernkompetenzen im Betrieblichen Gesundheitsmanagement

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      Springer Berlin Heidelberg

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          Psychological Contracts in Organizations: Understanding Written and Unwritten Agreements

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            A meta-analysis of observational studies identifies predictors of sickness absence.

            About one in every three employees seen by their occupational physician is absent from work because of psychosocial health complaints. To implement preventive measures, it is necessary to identify predictors for this type of sickness absence. A meta-analysis was carried out to quantify the association between predictive factors and psychosocial sickness absence and to assess clinical outcomes and heterogeneity. Eligible for inclusion were prospective studies that examined this association and provided sufficient information to estimate summary odds ratios (SORs). Twenty prospective studies were included. Significant SORs for sick leave >3 days were found for being unmarried, 1.37 (95% confidence interval [CI]=1.15-1.64), experiencing psychosomatic complaints, 1.79 (95% CI=1.54-2.07), using medication, 3.13 (95% CI=1.71-5.72), having a burnout, 2.34 (95% CI=1.59-3.45), suffering from psychological problems, 1.97 (95% CI=1.37-2.85), having low job control, 1.28 (95% CI=1.23-1.33), having low decision latitude, 1.33 (95% CI=1.16-1.56), and experiencing no fairness at work, 1.30 (95% CI=1.18-1.45). This study shows that predictors of sickness absence can be identified in a homogeneous manner. The results provide leads to public health interventions to successfully improve psychosocial health and to reduce sickness absence.
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              Sickness absence as a measure of health status and functioning: from the UK Whitehall II study.

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                Author and book information

                Book Chapter
                2010
                January 20 2010
                : 204-335
                10.1007/978-3-642-04337-6_8
                fe01f191-ed8c-4e7b-8b8b-68c9351d993c
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