Barbaranelli, C., Lee, C. S, Vellone, E. & Riegel, B. (2014). Dimensionality and reliability of the self-care of heart failure index scales: Further evidence from confirmatory factor analysis. Research in Nursing and Health,37(6), 524-537. United States: John Wiley and Sons Inc.. Retrieved from https://doi.org/10.1002/nur.21623
The Self-Care of Heart Failure Index (SCHFI) is used widely, but issues with reliability have been evident. Cronbach alpha coefficient is usually used to assess reliability, but this approach assumes a unidimensional scale. The purpose of this article is to address the dimensionality and internal consistency reliability of the SCHFI. This was a secondary analysis of data from 629 adults with heart failure enrolled in three separate studies conducted in the northeastern and northwestern United States. Following testing for scale dimensionality using confirmatory factor analysis, reliability was tested using coefficient alpha and alternative options. Confirmatory factor analysis demonstrated that: (a) the Self-Care Maintenance Scale has a multidimensional four-factor structure; (b) the Self-Care Management Scale has a two-factor structure, but the primary factors loaded on a common higher-order factor; and (c) the Self-Care Confidence Scale is unidimensional. Reliability estimates for the three scales, obtained with methods compatible with each scale's dimensionality, were adequate or high. The results of the analysis demonstrate that issues of dimensionality and reliability cannot be separated. Appropriate estimates of reliability that are consistent with the dimensionality of the scale must be used. In the case of the SCHFI, coefficient alpha should not be used to assess reliability of the self-care maintenance and the self-care management scales, due to their multidimensionality. When performing psychometric evaluations, we recommend testing dimensionality before assessing reliability, as well using multiple indices of reliability, such as model-based internal consistency, composite reliability, and omega and maximal reliability coefficients
Mary MacKillop Institute for Health Research
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