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0120 Predicting long-term sickness absence and supporting return-to work processes, a quantitative research

Goorts, Kaat ; Duchesnes, Christiane ; Vandenbroeck, Sofie ; Rusu, Dorina ; Bois, Marc Du ; Mairiaux, Philippe ; Godderis, Lode

Occupational and environmental medicine (London, England), 2017-08, Vol.74 (Suppl 1), p.A34 [Periódico revisado por pares]

London: BMJ Publishing Group LTD

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  • Título:
    0120 Predicting long-term sickness absence and supporting return-to work processes, a quantitative research
  • Autor: Goorts, Kaat ; Duchesnes, Christiane ; Vandenbroeck, Sofie ; Rusu, Dorina ; Bois, Marc Du ; Mairiaux, Philippe ; Godderis, Lode
  • Assuntos: Absenteeism ; Expectancy ; Literature reviews ; Mathematical models ; Medical personnel ; Physicians ; Quantitative research ; Questionnaires ; Risk groups ; Sick leave
  • É parte de: Occupational and environmental medicine (London, England), 2017-08, Vol.74 (Suppl 1), p.A34
  • Descrição: Long-term sickness absence is increasing in 27 European member states and Norway. Promoting good health and attendance, instead of penalising absence, has become a growing policy issue (Edwards & Greasley, 2010). As most employees will return to work spontaneously, resources for return to work projects should be focused on the high-risk group for long-term sickness absence.In this project a questionnaire was developed to predict the risk of long-term sickness absence.The development of the questionnaire started with a literature review of the predictive factors for long-term sickness absence, and with a review of existing questionnaires that question long-term sickness absence. The questionnaire will be validated in a pilot study of 10 000 participants. These data will be used to calculate its predictive value and to build a model to predict the risk of long-term sickness absence. The literature study revealed 16 predictors for long-term sickness absence. The most predictive factor is, according to existing research, the patient‘s expectancy regarding their return to work. As the other factors are not unambiguously strong predictors, the pilot study will explore the predictive value of the complete model and each separate parameter. A new questionnaire was developed based on both reviews and the 16 predictors they revealed. The questionnaire is not specific for a certain illness, nor for use in a specific country.The questionnaire developed in this research will support physicians to assess the risk of long-term sickness absence, and to guide more employees successfully and sustainably back to work.
  • Editor: London: BMJ Publishing Group LTD
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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