Testing Set-Point Theory in a Swiss National Sample: Reaction and Adaptation to Major Life Events
- 740 Downloads
Set-point theory posits that individuals react to the experience of major life events, but quickly adapt back to pre-event baseline levels of subjective well-being in the years following the event. A large, nationally representative panel study of Swiss households was used to examine set-point theory by investigating the extent of adaptation following the experience of marriage, childbirth, widowhood, unemployment, and disability. Our results demonstrate that major life events are associated with marked changes in life satisfaction and, for some events (e.g., marriage, disability), these changes are relatively long lasting even when accounting for normative, age related changes.
KeywordsHappiness Subjective well-being Life events Adaptation Swiss Household Panel
The data used in this article were made available to us by the Swiss Foundation for Research in Social Sciences (FORS). The Swiss Household Panel is financed by the Swiss National Science Foundation and based at FORS in Lausanne, Switzerland. Neither the original collectors of the data nor the data archive bear any responsibility for the analyses or interpretations presented here. This research was supported in part by Doctoral Fellowships from the Social Sciences and Humanities Research Council of Canada awarded to Ivana Anusic and Stevie Yap, and NIA grants AG032001 and AG040715 awarded to Richard Lucas.
- Bates, D., & Maechler, M. (2010). lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-35. http://cran.r-project.org/web/packages/lme4/lme4.pdf.
- Budowski, M., Tillmann, R., Zimmermann, E., Wernli, B., Scherpenzeel, A., & Gabadinho, A. (2001). The Swiss Household Panel 1999–2003: Data for research on micro-social change. ZUMA-Nachrichten, 49, 100–125.Google Scholar
- Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life. New York: Russell Sage Foundation.Google Scholar
- Fredrick, S., & Loewenstein, G. (1999). Hedonic adaptation. In D. Kahneman, E. Diener, & N. Schwartz (Eds.), Well-being: The foundations of hedonic psychology (pp. 302–329). New York: Sage.Google Scholar
- Frey, B. S., & Stutzer, A. (2004). Happiness and economics: How the economy and institutions affect human well-being. Princeton, NJ: Princeton University Press.Google Scholar
- Gelman, A., & Hill, J. (2009). Data analysis using regression and multilevel/hierarchical models. New York: Cambridge University Press.Google Scholar
- Gelman, A., Su, Y., Yajima, J., Hill, J., Pittau, M. G., Kerman, J., & Zheng, T. (2011). Arm: Data analysis using regression and multilevel hierarchical models. R package version 1.4-14. http://cran.r-project.org/web/packages/arm/arm.pdf.
- Kobau, R., Sniezek, J., Zack, M. M., Lucas, R. E., & Burns, A. (2010). Well-being assessment: An evaluation of well-being scales for public health and population estimates of well-being among US adults. Applied Psychology: Health and Well-Being, 2, 272–297.Google Scholar
- R Development Core Team. (2010). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar