4.5 Article

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

Journal

QUALITY OF LIFE RESEARCH
Volume 22, Issue 9, Pages 2549-2559

Publisher

SPRINGER
DOI: 10.1007/s11136-013-0388-7

Keywords

Quality of life; Confirmatory factor analysis; Exploratory factor analysis; Method effect; Psychometrics; Older people

Funding

  1. Health Research Board in Ireland [PHD/2007/16]
  2. Government of Ireland through the Office of the Minister for Health and Children
  3. Atlantic Philanthropies
  4. Irish Life

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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 (chi(2) 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.

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