Background: MSQOL-54 is a multidimensional, widely-used, health-related quality of life (HRQOL) instrument specifc for multiple sclerosis (MS). Findings from the validation study suggested that the two MSQOL-54 composite scores are correlated. Given this correlation, it could be assumed that a unique total score of HRQOL may be calculated, with the advantage to provide key stakeholders with a single overall HRQOL score. We aimed to assess how well the bifactor model could account for the MSQOL-54 structure, in order to verify whether a total HRQOL score can be calculated. Methods: A large international database (3669 MS patients) was used. By means of confrmatory factor analysis, we estimated a bifactor model in which every item loads onto both a general factor and a group factor. Fit of the bifactor model was compared to that of single and two second-order factor models by means of Akaike information and Bayesian information criteria reduction. Reliability of the total and subscale scores was evaluated with Mc Donald’s coefcients (omega, and omega hierarchical). Results: The bifactor model outperformed the two second-order factor models in all the statistics. All items loaded satisfactorily (≥0.40) on the general HRQOL factor, except the sexual function items. Omega coefcients for total score were very satisfactory (0.98 and 0.87). Omega hierarchical for subscales ranged between 0.22 to 0.57, except for the sexual function (0.70). Conclusions: The bifactor model is particularly useful when it is intended to acknowledge multidimensionality and at the same time take account of a single general construct, as the HRQOL related to MS. The total raw score can be used as an estimate of the general HRQOL latent score.
Viability of a MSQOL-54 general health-related quality of life score using bifactor model
Testa S;
2021-01-01
Abstract
Background: MSQOL-54 is a multidimensional, widely-used, health-related quality of life (HRQOL) instrument specifc for multiple sclerosis (MS). Findings from the validation study suggested that the two MSQOL-54 composite scores are correlated. Given this correlation, it could be assumed that a unique total score of HRQOL may be calculated, with the advantage to provide key stakeholders with a single overall HRQOL score. We aimed to assess how well the bifactor model could account for the MSQOL-54 structure, in order to verify whether a total HRQOL score can be calculated. Methods: A large international database (3669 MS patients) was used. By means of confrmatory factor analysis, we estimated a bifactor model in which every item loads onto both a general factor and a group factor. Fit of the bifactor model was compared to that of single and two second-order factor models by means of Akaike information and Bayesian information criteria reduction. Reliability of the total and subscale scores was evaluated with Mc Donald’s coefcients (omega, and omega hierarchical). Results: The bifactor model outperformed the two second-order factor models in all the statistics. All items loaded satisfactorily (≥0.40) on the general HRQOL factor, except the sexual function items. Omega coefcients for total score were very satisfactory (0.98 and 0.87). Omega hierarchical for subscales ranged between 0.22 to 0.57, except for the sexual function (0.70). Conclusions: The bifactor model is particularly useful when it is intended to acknowledge multidimensionality and at the same time take account of a single general construct, as the HRQOL related to MS. The total raw score can be used as an estimate of the general HRQOL latent score.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.