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Legitimising and rationalising in talk about satisfaction with formal healthcare among bereaved family members
Author(s) -
Funk Laura M.,
Stajduhar Kelli I.,
Robin Cohen S.,
Heyland Daren K.,
Williams Allison
Publication year - 2012
Publication title -
sociology of health and illness
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.146
H-Index - 97
eISSN - 1467-9566
pISSN - 0141-9889
DOI - 10.1111/j.1467-9566.2011.01457.x
Subject(s) - acknowledgement , psychology , quality (philosophy) , health care , process (computing) , social psychology , relation (database) , nursing , public relations , medicine , political science , law , computer science , epistemology , philosophy , computer security , operating system , database
While there is a fair amount of knowledge regarding substantive features of end of life care that family members desire and appreciate, we lack full understanding of the process whereby family members formulate care evaluations. In this article we draw on an analysis of interview data from 24 bereaved family members to explicate how they interpret their experiences and formulate evaluations of end of life care services. Most participants wove between expressing and legitimising dissatisfaction, and qualifying or diffusing it. This occurred through processes of comparisons against prior care experiences and expectations, personalising (drawing on personal situations and knowledge), collectivising (drawing on conversations with and observations of others) and attempting to understand causes for their negative care experiences and to attribute responsibility. The findings suggest that dissatisfaction might be diffused even where care is experienced negatively, primarily through the acknowledgement of mitigating circumstances. To a lesser extent, some participants attributed responsibility to the ‘system’ (policy and decision‐makers) and individual staff members. The findings are discussed in relation to the theoretical understanding of satisfaction and evaluation processes and how satisfaction data might inform improvements to care quality.

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