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A quantitative dynamic systems model of health-related quality of life among older adults

Authors Roppolo M, Kunnen ES, van Geert P, Mulasso A, Rabaglietti E

Received 2 July 2015

Accepted for publication 27 August 2015

Published 29 October 2015 Volume 2015:10 Pages 1755—1770

DOI https://doi.org/10.2147/CIA.S91605

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Supriya Swarnkar

Peer reviewer comments 3

Editor who approved publication: Dr Richard Walker


Mattia Roppolo,1,2 E Saskia Kunnen,2 Paul L van Geert,2 Anna Mulasso,1 Emanuela Rabaglietti1

1Department of Psychology, University of Torino, Torino, Italy; 2Department of Developmental Psychology, Rijksuniversiteit of Groningen, Groningen, Netherlands

Abstract: Health-related quality of life (HRQOL) is a person-centered concept. The analysis of HRQOL is highly relevant in the aged population, which is generally suffering from health decline. Starting from a conceptual dynamic systems model that describes the development of HRQOL in individuals over time, this study aims to develop and test a quantitative dynamic systems model, in order to reveal the possible dynamic trends of HRQOL among older adults. The model is tested in different ways: first, with a calibration procedure to test whether the model produces theoretically plausible results, and second, with a preliminary validation procedure using empirical data of 194 older adults. This first validation tested the prediction that given a particular starting point (first empirical data point), the model will generate dynamic trajectories that lead to the observed endpoint (second empirical data point). The analyses reveal that the quantitative model produces theoretically plausible trajectories, thus providing support for the calibration procedure. Furthermore, the analyses of validation show a good fit between empirical and simulated data. In fact, no differences were found in the comparison between empirical and simulated final data for the same subgroup of participants, whereas the comparison between different subgroups of people resulted in significant differences. These data provide an initial basis of evidence for the dynamic nature of HRQOL during the aging process. Therefore, these data may give new theoretical and applied insights into the study of HRQOL and its development with time in the aging population.

Keywords: older adults, dynamic systems model, nonlinear equations, simulated trajectories, validation

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