Can time heal all wounds? An empirical assessment of adaptation to functional limitations in an older population
Chronic diseases and functional limitations may have serious and persistent consequences for one's quality of life (QoL). Over time, however, their negative impact on QoL may diminish because of adaptation. Understanding how much people adapt helps to correctly separate the effects attributable to interventions from those arising from adaptation and thus facilitates a better estimation of the effects of disease and treatment on QoL. To date, however, there is little empirical evidence on adaptation in older populations. In particular, it is unclear to which extent dimensions of QoL like health and overall experience with life are influenced by adaptation. This paper studies adaptation to functional limitations in 5000 respondents of the Survey of Health, Ageing and Retirement in Europe (SHARE) who develop disabilities during the span of the 5 waves of data collection between 2004 and 2015. To examine the association between time since the onset of functional limitations and self-perceived health and life satisfaction, a fixed effects ordered logit model is used. We found evidence supporting adaptation in life satisfaction, corresponding to a return to pre-onset levels of life satisfaction. Also in the self-perceived health dimension, adaptation does occur, but it does not occur fast enough to offset the negative changes in underlying health. This means that observational studies that measure one of these two outcome measures should be aware that part or all of the effects found are due to adaptation.
|Keywords||Europe, Adaptation, Functional limitations, Self-perceived health, Life satisfaction, Fixed effects ordered logit|
|Persistent URL||dx.doi.org/10.1016/j.socscimed.2018.12.028, hdl.handle.net/1765/114834|
|Journal||Social Science & Medicine|
de Hond, A.A.H., Bakx, P.L.H, & Versteegh, M.M. (2019). Can time heal all wounds? An empirical assessment of adaptation to functional limitations in an older population. Social Science & Medicine, 222, 180–187. doi:10.1016/j.socscimed.2018.12.028