The objective of this paper is to display how the exposure to psychosocial risk factors impact on workers’ well-being as much as the physical risk factors, in particular showing the strength of the effect of exposure to selected risk factors existing in the workplace on workers’ well-being. Following the framework proposed by EU-OSHA (2013) and applying statistical procedures to the European Working Conditions Survey data, we analysed how and to what extent physical risk factors and psychosocial risk factors impact on health and well-being of workers in European workplaces. More in particular, we carried out Ordered Probit models to measure the effect of specific items operationalising the physical and the psychosocial risk factors and subsequently run a Principal Component Analysis (PCA) to identify two separate synthetic indicators of physical risk factors and psychosocial risk factors respectively, to analyse their impact on health and well-being.
Deriving a Composite Indicator to Measure Well-being at Work in European Union Countries / Capecchi, S; Cappelli, C.; Curtarelli, M.; Di Iorio, F.. - (2019). (Intervento presentato al convegno 6th Regulating for Decent Work Conference, Work and well-being in the 21st century tenutosi a ILO Geneve, Switzerland nel 8-10 July 2019).
Deriving a Composite Indicator to Measure Well-being at Work in European Union Countries
Capecchi, S
;Cappelli, C.;Di Iorio, F.
2019
Abstract
The objective of this paper is to display how the exposure to psychosocial risk factors impact on workers’ well-being as much as the physical risk factors, in particular showing the strength of the effect of exposure to selected risk factors existing in the workplace on workers’ well-being. Following the framework proposed by EU-OSHA (2013) and applying statistical procedures to the European Working Conditions Survey data, we analysed how and to what extent physical risk factors and psychosocial risk factors impact on health and well-being of workers in European workplaces. More in particular, we carried out Ordered Probit models to measure the effect of specific items operationalising the physical and the psychosocial risk factors and subsequently run a Principal Component Analysis (PCA) to identify two separate synthetic indicators of physical risk factors and psychosocial risk factors respectively, to analyse their impact on health and well-being.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.