Skip to main content

Advertisement

SpringerLink
Log in

Age-Related Differences in the Factor Structure of Multiple Wellbeing Indicators in a Large Multinational European Survey

  • Research Paper
  • Published:
Journal of Happiness Studies Aims and scope Submit manuscript

Abstract

There is increasing evidence that uni-dimensional wellbeing models often report comparable and sometimes better fit to multi-dimensional and hierarchical models. Recent proliferation in Bi-Factor modelling supports a general factor reflecting substantial commonality in wellbeing indicators. The current study examines age-related differences in the factor structure of wellbeing across the lifespan. Participants (n = 42,038) were from the European Social Survey (ESS), a large multi-national study who completed the ESS wellbeing module. Confirmatory Factor (CFA) and Bi-factor analyses revealed a uni-dimensional model reported best fit. Age differences in the magnitude and rank order of factor loadings was supported by a formal invariance test of the factor loadings although these differences did not substantially impact on factor scores. In line with a growing body of CFA and Bi-Factor findings, ESS wellbeing indicators reflect one general wellbeing factor. Despite age differences in the factor loadings, these differences had little adverse impact on overall wellbeing score. Overall, a uni-dimensional factor structure was consistent over the lifespan.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin,107, 238–246.

    Google Scholar 

  • Bonsang, E., & van Soest, A. (2012). Satisfaction with job and income among older individuals across European Countries. Social Indicators Research,105, 227–254.

    Google Scholar 

  • Browne, M. W., & Cudeck, R. (1989). Single sample cross-validation indices for covariance structures. Oct 1989 1989. Multivariate Behavioral Research,24, 445–455.

    Google Scholar 

  • Burns, R. A., Anstey, K. J., & Windsor, T. D. (2011). Subjective well-being mediates the effects of resilience and mastery on depression and anxiety in a large community sample of young and middle-aged adults. Australian and New Zealand Journal of Psychiatry,45, 240–248.

    Google Scholar 

  • Burns, R. A., & Ma, J. (2015). Examining the association between psychological wellbeing with daily and intra-individual variation in subjective wellbeing. Personality and Individual Differences,82, 34–39.

    Google Scholar 

  • Burns, R. A., & Machin, M. A. (2009). Investigating the structural validity of Ryff’s psychological well-being scales across two samples. Social Indicators Research,93, 359–375.

    Google Scholar 

  • Burns, R. A., & Machin, M. A. (2010). Identifying gender differences in the independent effects of personality and psychological well-being on two broad affect components of subjective well-being. Personality and Individual Differences,48, 22–27.

    Google Scholar 

  • Burns, R. A., Mitchell, P., Shaw, J., & Anstey, K. (2014). Trajectories of terminal decline in the wellbeing of older women: The DYNOPTA project. Psychology and Aging,29, 44–56.

    Google Scholar 

  • Butterworth, P., & Crosier, T. (2004). The validity of the SF-36 in an Australian National Household Survey: Demonstrating the applicability of the Household Income and Labour Dynamics in Australia (HILDA) Survey to examination of health inequalities. Bmc Public Health,4, 44.

    Google Scholar 

  • Charles, S. T., Reynolds, C. A., & Gatz, M. (2001). Age-related differences and change in positive and negative affect over 23 years. Journal of Personality,80, 136–151.

    Google Scholar 

  • Chen, F. F., Jing, Y., Hayes, A., & Lee, J. M. (2013). Two concepts or two approaches? A bifactor analysis of psychological and subjective well-being. Journal of Happiness Studies,14, 1033–1068.

    Google Scholar 

  • Clark, L. A., Watson, D., & Mineka, S. (1994). Temperament, personality, and the mood and anxiety disorders. Journal of Abnormal Psychology,103, 103–116.

    Google Scholar 

  • Compton, W. C., Smith, M. L., Cornish, K. A., & Qualls, D. L. (1996). Factor structure of mental health measures. Journal of Personality and Social Psychology,71, 406–413.

    Google Scholar 

  • ESS Round 3: European Social Survey Round 3 Data. (2006). Data file edition 3.7. NSD - Norwegian Centre for Research Data, Norway – Data Archive and distributor of ESS data for ESS ERIC.

  • de Bruin, G. P., & du Plessis, G. A. (2015). Bifactor analysis of the mental health continuum-short form (MHC-SF). Psychological Reports,116, 438–446.

    Google Scholar 

  • Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry,11, 227–268.

    Google Scholar 

  • DeNeve, K. M., & Cooper, H. (1998). The happy personality: A meta-analysis of 137 personality traits and subjective well-being. Psychological Bulletin,124, 197–229.

    Google Scholar 

  • Fayad, Y. I., & Kazarian, S. S. (2013). Subjective vitality of Lebanese adults in Lebanon: Validation of the Arabic version of the subjective vitality scale. Social Indicators Research, 114(2), 465–478.

    Google Scholar 

  • Gallagher, M. W., Lopez, S. J., & Preacher, K. J. (2009). The hierarchical structure of well-being. Journal of Personality,77, 1025–1050.

    Google Scholar 

  • Gatt, J. M., Burton, K. L. O., Schofield, P. R., Bryant, R. A., & Williams, L. M. (2014). The heritability of mental health and wellbeing defined using COMPAS-W, a new composite measure of wellbeing. Psychiatry Research,219, 204–213.

    Google Scholar 

  • Headey, B., Muffels, R., & Wagner, G. G. (2010). Long-running German panel survey shows that personal and economic choices, not just genes, matter for happiness. Proceedings of the National Academy of Sciences of the United States of America,107, 17922–17926.

    Google Scholar 

  • Hervás, G., & Vázquez, C. (2013). Construction and validation of a measure of integrative well-being in seven languages: The Pemberton Happiness Index. Health and Quality of Life Outcomes,11, 66.

    Google Scholar 

  • Hides, L., Quinn, C., Stoyanov, S., Cockshaw, W., Mitchell, T., & Kavanagh, D. J. (2016). Is the mental wellbeing of young Australians best represented by a single, multidimensional or bifactor model? Psychiatry Research,241, 1–7.

    Google Scholar 

  • Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling,6, 1–55.

    Google Scholar 

  • Huppert, F. A., Marks, N., Clark, A., Siegrist, J., Stutzer, A., Vittersø, J., et al. (2009). Measuring well-being across Europe: Description of the ESS well-being module and preliminary findings. Social Indicators Research,91, 301–315.

    Google Scholar 

  • Huppert, F. A., & So, T. T. C. (2013). Flourishing across Europe: Application of a new conceptual framework for defining well-being. Social Indicators Research,110, 837–861.

    Google Scholar 

  • Huppert, F. A., & Whittington, J. E. (2003). Evidence for the independence of positive and negative well-being: Implications for quality of life assessment. British Journal of Health Psychology,8, 107–122.

    Google Scholar 

  • Jovanović, V. (2015). A bifactor model of subjective well-being: A re-examination of the structure of subjective well-being. Personality and Individual Differences,87, 45–49.

    Google Scholar 

  • Jowell, R. (2007). Measuring attitudes cross-nationally: Lessons from the European Social Survey. Los Angeles: Sage.

    Google Scholar 

  • Keyes, C. L. M. (2007). Promoting and protecting mental health as flourishing - A complementary strategy for improving national mental health. American Psychologist,62, 95–108.

    Google Scholar 

  • Keyes, C. L., Shmotkin, D., & Ryff, C. D. (2002). Optimizing well-being: The empirical encounter of two traditions. Journal of Personality,82, 1007–1022.

    Google Scholar 

  • Kim, K., Lehning, A. J., & Sacco, P. (2016). Assessing the factor structure of well-being in older adults: Findings from the National Health and Aging Trends Study. Aging & Mental Health,20, 814–822.

    Google Scholar 

  • Kling, K. C., Ryff, C. D., Love, G., & Essex, M. (2003). Exploring the Influence of personality on depressive symptoms and self-esteem across a significant life transition. Journal of Personality and Social Psychology, 85(5), 922–932.

    Google Scholar 

  • Kunzmann, U., Little, T. D., & Smith, J. (2000). Is age-related stability of subjective well-being a paradox? Cross-sectional and longitudinal evidence from the Berlin Aging Study. Psychology and Aging,15, 511–526.

    Google Scholar 

  • Linley, P. A., Maltby, J., Wood, A. M., Osborne, G., & Hurling, R. (2009). Measuring happiness: The higher order factor structure of subjective and psychological well-being measures. Personality and Individual Differences,47, 878–884.

    Google Scholar 

  • Longo, Y., Jovanovic, V., Sampaio de Carvalho, J. & Karas, D. (2017). The general factor of well-being: Multinational evidence using bifactor ESEM on the mental health continuum-short form. Assessment, 1073191117748394.

  • Luhmann, M., Hofmann, W., Eid, M., & Lucas, R. E. (2012). Subjective well-being and adaptation to life events: A meta-analysis on differences between cognitive and affective well-being. Journal of Personality and Social Psychology,102, 592–615.

    Google Scholar 

  • Mroczek, D. K., & Spiro, A. (2005). Change in life satisfaction during adulthood: Findings from the veterans affairs normative aging study. Journal of Personality and Social Psychology,88, 189–202.

    Google Scholar 

  • Mroczek, D. K., Spiro, A., & Almeida, D. M. (2003). Between- and within-person variation in affect and personality over days and years: How basic and applied approaches can inform one another. Ageing International,28, 260–278.

    Google Scholar 

  • Park, N., Peterson, C., & Ruch, W. (2009). Orientations to happiness and life satisfaction in twenty-seven nations. The Journal of Positive Psychology,4, 273–279.

    Google Scholar 

  • Peterson, C., Park, N., & Seligman, M. E. P. (2005). Orientations to happiness and life satisfaction: The full life versus the empty life. Journal of Happiness Studies,6, 25–41.

    Google Scholar 

  • Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual Review of Psychology,52, 141–166.

    Google Scholar 

  • Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology,57, 1069.

    Google Scholar 

  • Ryff, C. D. (2014). Psychological well-being revisited: Advances in the science and practice of eudaimonia. Psychotherapy and Psychosomatics,83, 10–28.

    Google Scholar 

  • Ryff, C. D., & Singer, B. H. (2008). Know thyself and become what you are: A eudaimonic approach to psychological well-being. Journal of Happiness Studies,9, 13–39.

    Google Scholar 

  • Schmutte, P. S., & Ryff, C. D. (1997). Personality and well-being: Reexamining methods and meanings. Journal of Personality and Social Psychology,73, 549.

    Google Scholar 

  • Springer, K. W., Pudrovska, T., & Hauser, R. M. (2011). Does psychological well-being change with age? Longitudinal tests of age variations and further exploration of the multidimensionality of Ryff’s model of psychological well-being. Social Science Research,40, 392–398.

    Google Scholar 

  • Steel, P., Schmidt, J., & Shultz, J. (2008). Refining the relationship between personality and subjective well-being. Psychological Bulletin,134, 138–161.

    Google Scholar 

  • Thomas, C., Benzeval, M., & Stansfeld, S. A. (2005). Employment transitions and mental health: An analysis from the British household panel survey. Journal of Epidemiology and Community Health,59, 243–249.

    Google Scholar 

  • Van Horn, J. E., Taris, T. W., Schaufeli, W. B., & Schreurs, P. J. G. (2004). The structure of occupational well-being: A study among Dutch teachers. Journal of Occupational and Organizational Psychology,77, 365–375.

    Google Scholar 

  • Vittersø, J., Biswas-Diener, R., & Diener, E. (2005). The divergent meanings of life satisfaction: Item response modeling of the satisfaction with life scale in greenland and Norway. Social Indicators Research,74, 327–348.

    Google Scholar 

  • Windsor, T. D., Burns, R. A., & Byles, J. E. (2013). Age, physical functioning, and affect in midlife and older adulthood. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences,68, 395–399.

    Google Scholar 

  • Yang, C. C. (2006). Evaluating latent class analysis models in qualitative phenotype identification. Computational Statistics & Data Analysis,50, 1090–1104.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Research on Ageing, Health and Wellbeing, The Research School of Population Health, The Australian National University, Canberra, ACT, 0200, Australia

    R. A. Burns

Authors
  1. R. A. Burns
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. A. Burns.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Burns, R.A. Age-Related Differences in the Factor Structure of Multiple Wellbeing Indicators in a Large Multinational European Survey. J Happiness Stud 21, 37–52 (2020). https://doi.org/10.1007/s10902-019-00077-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10902-019-00077-y

Keywords

Search

Navigation