0184 Considering giving up gainful employment as predictor for early exit from the labour force. (21st August 2017)

• Record Type: Journal Article
• Authors: Rose, Uwe; Burr, Hermann; Kersten, Norbert
• Is Part Of: Occupational and environmental medicine. Volume 74(2017)Supplement 1
• Page Start: A56
• Page End: A56
• Publication Date: 2017-08-21
• Subjects: Medicine, Industrial -- Periodicals; Environmental health -- Periodicals; 616.980305
• DOI: 10.1136/oemed-2017-104636.149
• Languages: English
• ISSNs: 1351-0711

Abstract

Abstract : Introduction: I ll health, socio-economic status and working conditions are important determinants for labour market participation. But this perspective neglects the subjective view of individuals and the role of cognitive processes. The aim of the present study is to investigate the contribution of these considerations for the prediction of subsequent exit from the labour force. Method: The sampling frame is defined by all German employees being subject to social security contributions and born between 1951 and 1980. The sample consists of 4511 survey participants of whom 4182 employees are with full- or part-time employ­ment. At the time of the first interview they were asked how often they have thought about giving up gainful employment within the last year. The analysis focusses on the prediction of employment status five years later. Results: At baseline 8% of female and of 7.2% male employees reported having "sometimes thoughts within the last year" and 4.4% of the female and 3.7% of the male employees reported a frequency up to "every day". The follow-up interviews are currently underway and are expected to end May 2017. Results on associations between considerations at baseline and status of employment at follow-up and will be presented at the conference. Discussion: Research on the association between cognitive processes and subsequent behaviour is very limited. We assume that the inclusion of these aspects will improve the prediction of labour force participation. However, there are strong limitations by the sample size and the number of observations at the second wave of assessment.