Psychometric evaluation of the CASP-19 quality of life scale in an older Irish cohort
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.
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.
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.
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.
KeywordsQuality of life Confirmatory factor analysis Exploratory factor analysis Method effect Psychometrics Older people
- 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.CrossRefGoogle 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.Google Scholar
- 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.CrossRefGoogle Scholar
- 23.Kaplan, D. (2009). Structural equation modelling: Foundations and extensions (2nd ed.). Thousand Oaks, California: Sage Publications.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
- 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.PubMedCrossRefGoogle 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.Google Scholar