Erschienen in:
01.03.2015 | Original Paper
The utility of estimating population-level trajectories of terminal wellbeing decline within a growth mixture modelling framework
verfasst von:
R. A. Burns, J. Byles, D. J. Magliano, P. Mitchell, K. J. Anstey
Erschienen in:
Social Psychiatry and Psychiatric Epidemiology
|
Ausgabe 3/2015
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Abstract
Purpose
Mortality-related decline has been identified across multiple domains of human functioning, including mental health and wellbeing. The current study utilised a growth mixture modelling framework to establish whether a single population-level trajectory best describes mortality-related changes in both wellbeing and mental health, or whether subpopulations report quite different mortality-related changes.
Methods
Participants were older-aged (M = 69.59 years; SD = 8.08 years) deceased females (N = 1,862) from the dynamic analyses to optimise ageing (DYNOPTA) project. Growth mixture models analysed participants’ responses on measures of mental health and wellbeing for up to 16 years from death.
Results
Multi-level models confirmed overall terminal decline and terminal drop in both mental health and wellbeing. However, modelling data from the same participants within a latent class growth mixture framework indicated that most participants reported stability in mental health (90.3 %) and wellbeing (89.0 %) in the years preceding death.
Conclusions
Whilst confirming other population-level analyses which support terminal decline and drop hypotheses in both mental health and wellbeing, we subsequently identified that most of this effect is driven by a small, but significant minority of the population. Instead, most individuals report stable levels of mental health and wellbeing in the years preceding death.