Psychosocial determinants predicting long-term sickness absence: a register-based cohort study. Issue 11 (13th July 2020)

• Record Type: Journal Article
• Authors: Goorts, Kaat; Boets, Isabelle; Decuman, Saskia; Du Bois, Marc; Rusu, Dorina; Godderis, Lode
• Is Part Of: Journal of epidemiology and community health. Volume 74:Issue 11(2020)
• Page Start: 913
• Page End: 918
• Publication Date: 2020-07-13
• Subjects: Disability -- epidemiology -- public health -- health services; Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech-2020-214181
• Languages: English
• ISSNs: 0143-005X

Abstract

Abstract : Background: This study assessed the psychosocial determinants as explanatory variables for the length of the work disability period. The aim was to estimate the predictive value of a selected set of psychosocial determinants from the Quickscan questionnaire for the length of the sick leave period. A comparison was also made with the most common biomedical determinant: diagnosis. Methods: In a cohort study of 4 981 insured Belgian patients, the length of the sick leave was calculated using Kaplan–Meier. Predictive psychosocial determinants were selected using backward conditional selection in Cox regression and using concordance index values (C-index) we compared the predictive value of the biomedical to the psychosocial model in a sample subset. Results: Fourteen psychosocial determinants were significantly (p<0.10) related to the length of the sick leave: health perception of the patient, physical workload, social support management, social support colleagues, work–health interference, psychological distress, fear of colleagues' expectations, stressful life-events, autonomy, learning and development opportunities, job satisfaction, workload, work expectations and expectation to return to work. The C-index of this biopsychosocial model including gender, age and labour status was 0.80 (CI: 0.78; 0.81) (n=4 981). In the subset of 2 868 respondents with diagnostic information, the C-index for the same model was .73 (CI: 0.71; 0.76) compared with 0.63 (CI: 0.61; 0.65) for the biomedical model. Conclusions: A set of 14 psychosocial determinants showed good predictive capacity (C-index: 0.80). Also, in a subset of the sample, the selected determinants performed better compared with diagnostic information to predict long-term sick leave (>6 months).