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Psychometric evaluation of the CASP-19 quality of life scale in an older Irish cohort

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Abstract

Purpose

This study aims to evaluate the validity of current measurement models for the control, autonomy, self-realisation, and pleasure (CASP) measure of quality of life (QoL)—a second-order four-factor CASP-19 model and a second-order three-factor CASP-12 version—in a recent population survey. A previous large sample study did not report good fit for these measurement models. The study also aims to re-develop the model and propose a well-fitting alternative.

Methods

To evaluate the current measurement models, confirmatory factor analysis (CFA) was used. A cross-sectional sample (n = 6,823) representative of the Irish community-dwelling population aged 50 and over was obtained from the Irish Longitudinal Study of Ageing (TILDA). Model revision was based on descriptive statistics, exploratory factor analysis and examination of fit diagnostic statistics. Revised models were tested using CFA.

Results

The results of the CFA did not support the validity of the established measurement models. A reformulated 12-item, two-factor model comprising control/autonomy and self-realisation/pleasure, with residual covariances for negatively worded items, had excellent fit to the data (χ2 161.90, df = 44, p < 0.001; RMSEA = 0.03, 90 % CI 0.02–0.03), and a clearer conceptual rationale. The same model with one overall QoL factor had similar excellent fit.

Conclusions

We recommend the use of the single-factor model (CASP-R12) when assessing overall quality of life. The dimensions of control/autonomy and self-realisation/pleasure can be examined separately by researchers interested in those constructs. Researchers using structural equation modelling can use the well-fitting measurement model outlined here including adjustment for residual covariances.

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References

  1. Hickey, A., Barker, M., McGee, H., & O’Boyle, C. (2005). Measuring health-related quality of life in older patient populations: A review of current approaches. PharmacoEconomics, 23(10), 971–993.

    Article  PubMed  Google Scholar 

  2. Moons, P., Budts, W., & De Geest, S. (2006). Critique on the conceptualisation of quality of life: A review and evaluation of different conceptual approaches. International Journal of Nursing Studies, 43(7), 891–901.

    Article  PubMed  Google Scholar 

  3. Higgs, P., Hyde, M., Wiggins, R., & Blane, D. (2003). Researching quality of life in early old age: The importance of the sociological dimension. Social Policy & Administration, 37(3), 239–252.

    Article  Google Scholar 

  4. Hyde, M., Wiggins, R. D., Higgs, P., & Blane, D. B. (2003). A measure of quality of life in early old age : The theory, development and properties of a needs satisfaction model (CASP-19). Ageing and Mental Health, 7(3), 186–194.

    Article  CAS  Google Scholar 

  5. Maslow, A. H. (1968). Toward a psychology of being (2nd ed.). Princeton, NJ: Van Nostrand.

    Google Scholar 

  6. Doyal, L., & Gough, I. (1991). A theory of human need. Basingstoke, Hampshire: Macmillan Education Ltd.

    Google Scholar 

  7. Laslett, P. (1991). A fresh map of life: The emergence of the third age (2nd ed.). Basingstoke, Hampshire: Macmillan Press Ltd.

    Google Scholar 

  8. Giddens, A. (1990). The consequences of modernity. Cambridge: Polity Press.

    Google Scholar 

  9. Wiggins, R. D., Netuveli, G., Hyde, M., Higgs, P., & Blane, D. (2008). The evaluation of a self-enumerated scale of quality of life (CASP-19) in the context of research on ageing: A combination of exploratory and confirmatory approaches. Social Indicators Research, 89(1), 61–77.

    Article  Google Scholar 

  10. Sim, J., Bartlam, B., & Bernard, M. (2011). The CASP-19 as a measure of quality of life in old age: Evaluation of its use in a retirement community. Quality of Life Research, 20(7), 997–1004.

    Article  PubMed  Google Scholar 

  11. Llewellyn, D. J., Lang, I., Langa, K. M., & Huppert, F. A. (2008). Cognitive function and psychological well-being: Findings from a population-based cohort. Age and Ageing, 37(6), 685–689.

    Article  PubMed  Google Scholar 

  12. Netuveli, G., Wiggins, R. D., Hildon, Z., Montgomery, S. M., & Blane, D. (2006). Quality of life at older ages: Evidence from the English longitudinal study of aging (wave 1). Journal of Epidemiology and Community Health, 60(4), 357–363.

    Article  PubMed  Google Scholar 

  13. Wikman, A., Wardle, J., & Steptoe, A. (2011). Quality of life and affective well-being in middle-aged and older people with chronic medical illnesses: A cross-sectional population based study. PLoS ONE, 6(4), e18952. doi:10.1371/journal.pone.0018952.

    Article  PubMed  CAS  Google Scholar 

  14. Blane, D., Netuveli, G., & Montgomery, S. M. (2008). Quality of life, health and physiological status and change at older ages. Social Science and Medicine, 66(7), 1579–1587.

    Article  PubMed  Google Scholar 

  15. Webb, E., Blane, D., McMunn, A., & Netuveli, G. (2011). Proximal predictors of change in quality of life at older ages. Journal of Epidemiology and Community Health, 65(6), 542–547.

    Article  PubMed  Google Scholar 

  16. Kearney, P. M., Cronin, H., O’Regan, C., Kamiya, Y., Savva, G. M., Whelan, B., et al. (2011). Cohort profile: The Irish longitudinal study on ageing. International Journal of Epidemiology, 40(4), 877–884.

    Article  PubMed  Google Scholar 

  17. Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press.

    Google Scholar 

  18. Muthen, L. K. & Muthen, B. O. (1998–2010). MPlus user’s guide. (6th ed.). Los Angeles, CA: Muthen & Muthen.

  19. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: The Guilford Press.

    Google Scholar 

  20. Yu, C.-Y. (2002). Evaluating Cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. Dissertation. University of California, Los Angeles. http://www.statmodel.com/download/Yudissertation.pdf. Accessed 4th July 2012.

  21. Marsh, H. W., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting Cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11(3), 320–341.

    Article  Google Scholar 

  22. Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141–151.

    Article  Google Scholar 

  23. Kaplan, D. (2009). Structural equation modelling: Foundations and extensions (2nd ed.). Thousand Oaks, California: Sage Publications.

    Google Scholar 

  24. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81–105.

    Article  PubMed  CAS  Google Scholar 

  25. Marsh, H. W. (1996). Positive and negative global self-esteem: A substantively meaningful distinction or artifactors? Journal of Personality and Social Psychology, 70(4), 810–819.

    Article  PubMed  CAS  Google Scholar 

  26. Kenny, D. A., & Kashy, D. A. (1992). Analysis of the multitrait-multimethod matrix by confirmatory factor analysis. Psychological Bulletin, 112, 165–172.

    Article  Google Scholar 

  27. Kenny, D. A., Kashy, D. A., & Bolger, N. (1998). Data analysis in social psychology. In D. T. Gilbert & S. T. Fiske (Eds.), The handbook of social psychology (pp. 233–265). New York: McGraw-Hill.

    Google Scholar 

  28. Ryff, C. D., & Singer, B. H. (2006). Know thyself and become what you are: A eudaimonic approach to psychological well-being. Journal of Happiness Studies, 9(1), 13–39.

    Article  Google Scholar 

  29. Saris, W. E., Satorra, A., & van der Veld, W. M. (2009). Testing structural equation models or detection of misspecifications? Structural Equation Modeling: A Multidisciplinary Journal, 16(4), 561–582.

    Article  Google Scholar 

  30. Abbott, R. A., Ploubidis, G. B., Huppert, F. A., Kuh, D., Wadsworth, M. E. J., & Croudace, T. J. (2006). Psychometric evaluation and predictive validity of Ryff’s psychological well-being items in a UK birth cohort sample of women. Health and Quality of Life Outcomes, 4(1), 76.

    Article  PubMed  Google Scholar 

  31. Wood, A. M., Taylor, P. J., & Joseph, S. (2010). Does the CES-D measure a continuum from depression to happiness? Comparing substantive and artifactual models. Psychiatry Research, 177(1–2), 120–123.

    Article  PubMed  Google Scholar 

  32. Barnette, J. J. (2000). Effect of stem and likert response option reversals on survey internal consistency: If you feel the need, there is a better alternative to using negatively worded stems. Educational and Psychological Measurement, 60(3), 361–370.

    Article  Google Scholar 

  33. Dolnicar, S., & Grün, B. (2009). Does one size fit all? The suitability of answer formats for different constructs measured. Australasian Marketing Journal (AMJ), 17(1), 58–64.

    Article  Google Scholar 

  34. Dolnicar, S., & Grün, B. (2007). How constrained a response : A comparison of binary, ordinal and metric answer formats. Journal of Retailing and Consumer Services, 4(2), 108–122.

    Article  Google Scholar 

  35. Dolnicar, S., Grün, B., Leisch, F. & Rossiter, J. (2000). Three good reasons NOT to use five and seven point Likert items. In: CAUTHE 2011: 21st CAUTHE National Conference. Adelaide, Australia.

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Acknowledgments

This work was funded by the Health Research Board in Ireland under Grant No. PHD/2007/16. TILDA data have been co-funded by the Government of Ireland through the Office of the Minister for Health and Children, by Atlantic Philanthropies, and by Irish Life; the data for this study have been collected under the Statistics Act, 1993, of the Central Statistics Office. The project has been designed and implemented by the TILDA Study Team. © Department of Health and Children.

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Authors and Affiliations

  1. Royal College of Surgeons in Ireland, Beaux Lane House, Lwr Mercer St, Dublin 2, Ireland

    Eithne Sexton, Ronan M. Conroy & Anne Hickey

  2. TILDA Project, Department of Medical Gerontology, Trinity College, Dublin, Ireland

    Bellinda L. King-Kallimanis

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  1. Eithne Sexton
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  2. Bellinda L. King-Kallimanis
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  3. Ronan M. Conroy
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  4. Anne Hickey
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Correspondence to Eithne Sexton.

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Sexton, E., King-Kallimanis, B.L., Conroy, R.M. et al. Psychometric evaluation of the CASP-19 quality of life scale in an older Irish cohort. Qual Life Res 22, 2549–2559 (2013). https://doi.org/10.1007/s11136-013-0388-7

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