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Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Critical reflections on the blind sides of frailty in later life
Liesbeth De Donder1, An-Sofie Smetcoren1, Jos M G A Schols2
1Vrije Universiteit Brussel, Pleinlaan 2, Brussel 1050, Belgium.
Abstract:
Since the 1970's, frailty emerged as a major theme and has become one of the most researched topics in aging studies. However, throughout the years, the concept 'frailty' became susceptible to different interpretations and has been approached by different synonyms, which resulted in a confusing picture. Based on a narrative literature review, this theoretical paper not only attempts to describe these different views on frailty, but by criticizing the dominance of some of these views, it also aspires to move the research and policy agenda on frailty forward. This paper is part of the D-SCOPE project in Belgium, and critically reflects on the blind sides of the biomedical domination of frailty and discusses three main themes: 1) frailty as a multidimensional and multilevel concept; 2) positive perspectives on frailty in later life; and 3) the suggestion of moving from a merely deficit-based frailty approach towards the concept of frailty-balance. At the theoretical level, conceptualizing frailty is not simply an exercise in semantics, but altering the theoretical definition of frailty can have wide-ranging implications, not only for the way frailty prevalence is measured and handled, but also for public or personal opinions on frailty in older people, for care and support practices, and for the scope of legislation. Therefore, the final section of the paper presents three building blocks for future research and policy-making: 1) adopting a multidimensional, multilevel, dynamic and positive view on frailty; 2) moving from dependency to interdependency; and 3) giving voice to (the resilience of) frail older people.
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Critical Region, Critical Values and Significance Level
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...

