OBJECTIVE: 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. STUDY DESIGN AND SETTING: 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). RESULTS: 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). CONCLUSION: 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.
OBJECTIVE: 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. STUDY DESIGN AND SETTING: 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). RESULTS: 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). CONCLUSION: 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.
Authors: Adriane Mesquita de Medeiros; Ada Ávila Assunção; Sandhi Maria Barreto Journal: Int Arch Occup Environ Health Date: 2011-12-23 Impact factor: 3.015
Authors: Angel Carlos Matía Cubillo; José Cordero Guevara; José Javier Mediavilla Bravo; Maria José Pereda Riguera; Maria Luisa González Castro; Ana González Sanz Journal: Aten Primaria Date: 2012-05-17 Impact factor: 1.137
Authors: Swenne G van den Heuvel; Goedele A Geuskens; Wendela E Hooftman; Lando L J Koppes; Seth N J van den Bossche Journal: J Occup Rehabil Date: 2010-09
Authors: Jesper Pihl-Thingvad; Ask Elklit; Lars Peter Andreas Brandt; Lars Louis Andersen Journal: Int Arch Occup Environ Health Date: 2019-03-25 Impact factor: 3.015
Authors: Desta Fekedulegn; Cecil M Burchfiel; Tara A Hartley; Michael E Andrew; Luenda E Charles; Cathy A Tinney-Zara; John M Violanti Journal: Chronobiol Int Date: 2013-06-28 Impact factor: 2.877
Authors: Heribert Limm; Peter Angerer; Mechthild Heinmueller; Birgitt Marten-Mittag; Urs M Nater; Harald Guendel Journal: BMC Public Health Date: 2010-05-14 Impact factor: 3.295
Authors: Petra C Koopmans; Corné Am Roelen; Ute Bültmann; Rob Hoedeman; Jac Jl van der Klink; Johan W Groothoff Journal: BMC Public Health Date: 2010-07-20 Impact factor: 3.295