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Predicting quality of life outcomes as a guide for decision-making: the challenge of hitting a moving target

Published online by Cambridge University Press:  11 January 2023

FD McMillan
FD McMillan*
Affiliation:
VCA Miller Animal Hospital, 8807 Melrose Avenue, Los Angeles CA 90069, USA
*
Correspondence: [email protected]
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Abstract

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In animal care, when current decisions are made to maximise long-term quality of life (QoL), a key necessity is being able to make accurate predictions about how current choices will affect the animal's future QoL. However, in the procession of any individual's life, many factors that influence QoL change — some are foreseeable, many are not. Moreover, QoL has no fixed anchor points; it is dynamic, mutable, with a shifting frame of reference over time. In addition to actual changes in QoL over time, numerous factors have been identified that influence one's ability to adopt the mindset of the individual at a later point in time — for one's self as well as that of others. It has been shown that in people, across a wide range of health conditions, individuals with illness or disability typically report greater happiness and QoL than do healthy people envisioning themselves in similar circumstances (‘the disability paradox‘). Difficulties in QoL outcome prediction fall into two categories: (1) predictions made with the wrong mindset, in which there is a mismatch between the mindset of the assessor/predictor and that of the assessee/experiencer; and (2) predictions made on the basis of unforeseen or incorrectly estimated psychological changes in the assessee/experiencer.

Keywords

adaptationanimal welfaredisability paradoxhappiness set-pointquality of lifescale recalibration
Type
Research Article
Information
Animal Welfare , Volume 16 , Issue S1: Quality of Life: the heart of the matter: Proceedings of the UFAW/BVA Ethics Committee International Symposium, The Royal Society, London, 13-14 September 2006. , May 2007 , pp. 135 - 142
Copyright
© 2007 Universities Federation for Animal Welfare

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