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Dellve, Lotta; Hallberg, Lillemor R.-M. (2010)
Publisher: Co-Action Publishing
Journal: International Journal of Qualitative Studies on Health and Well-being
Languages: English
Types: Article
Epidemiological research has so far failed to explain the high incidence of occupational disorders among home care workers (HCWs) and the great differences in organizational incidence rate. A qualitative approach may contribute to a deeper understanding of work group reasoning and handling in a more contextual manner. The aim of this grounded theory study was to gain a deeper understanding of the main concern in the processes of recognizing, communicating and reporting occupational disorders among HCWs. Focus group interviews were conducted with 40 HCWs in 9 focus groups. The selected municipalities represented variations in municipality type and incidence rate of occupational disorders. Making it work in the frontline was identified as the core category explaining that the perceived work situation in home care work was the main concern but interacted with work-group socialising processes as well as with the communicability and derivability of the occupational disorder when defining and reporting occupational disorders. Complex problems could be reformulated and agreed within the workgroup to increase communicability. Described significances for reporting/non-reporting were related to financial compensation, to a part of organizational political game or to an existential uncertainty, i.e. questioning if it belonged to their chosen work and life. Our conclusion is that working situation and work group attitudes have importance for reporting of occupational disorders. To support work-related health for HCWs, integrating communication should be developed about work-related challenges in work situation, as well as about attitudes, culture and efficiency within work-group. Key words: Work injury, social environment, home care, social support, collective coping, focus group, grounded theory
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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