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Measuring Stability and Change: Methodological Issues in Quality of Life studies

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  • Filomena Maggino

    (University of Florence)

  • Carolina Facioni

    (National Institute of Statistics – ISTAT)

Abstract

The aim of the paper is to show how the variety of approaches to study social change may result in a challenging complexity for the social scientist, starting from the difficulty of defining the concept of “change” itself and managing it through observed data. This is particularly true in presence of complex phenomena, such as those defining and composing the quality of life. What should be pointed out is that quality of life studies not only are focused on the present time but have also long term perspectives. This represents the link between studies on quality of life and forecasting. When applied to the field of quality of life, the typical logical approach to forecasts, based upon inferential statistics, could reveal its limits. Those limits are related to different aspects: e.g., the forms of relationships between different aspects of the phenomenon, which can be linear and non-linear; the dimensionality of phenomenon, which can turn out to be very complex; the causality, which could be direct or indirect; the entity of change, which implies the idea that also small change can have great impact; the perspective of observation, which can be internal or external and local or global. Consequently, the study of change related to quality of life needs, in addition to the traditional statistical tools as well as the tradition of social indicators, a different approach. Although the Futures Studies are not a proper science, nevertheless their approach to social research may ensure the requested accuracy of a scientific forecasting process.

Suggested Citation

  • Filomena Maggino & Carolina Facioni, 2017. "Measuring Stability and Change: Methodological Issues in Quality of Life studies," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(1), pages 161-187, January.
    • Handle: RePEc:spr:soinre:v:130:y:2017:i:1:d:10.1007_s11205-015-1129-9
    DOI: 10.1007/s11205-015-1129-9
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    References listed on IDEAS

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    1. David Rogosa & John Willett, 1985. "Understanding correlates of change by modeling individual differences in growth," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 203-228, June.
    2. Lindsey, J. K., 1999. "Models for Repeated Measurements," OUP Catalogue, Oxford University Press, edition 2, number 9780198505594, Decembrie.
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    Cited by:

    1. A. l. Moro-Egido & M. Navarro & A. Sánchez, 2022. "Changes in Subjective Well-Being Over Time: Economic and Social Resources do Matter," Journal of Happiness Studies, Springer, vol. 23(5), pages 2009-2038, June.
    2. Deniz Yucel & Wen Fan, 2023. "Workplace flexibility, work–family interface, and psychological distress: differences by family caregiving obligations and gender," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 18(4), pages 1825-1847, August.
    3. Ana I. Moro Egido & Maria Navarro & Ángeles Sánchez-Domínguez, 2017. "Changes in Subjective Well-Being Over Time in Germnay," ThE Papers 17/05, Department of Economic Theory and Economic History of the University of Granada..
    4. Waldemar W. Koczkodaj & Mirosław Mazurek & Dominik Strzałka & Alicja Wolny-Dominiak & Marc Woodbury-Smith, 2019. "Electronic Health Record Breaches as Social Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(2), pages 861-871, January.
    5. Daria Loginova & Stefan Mann, 2023. "Measuring stability and structural breaks: Applications in social sciences," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 302-320, April.

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