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Background: The Multiple Sclerosis Quality of Life-54 (MSQOL-54) is one of the most commonly-used MS-specific health-related quality of life (HRQOL) measures. It is a multidimensional, MS-specific HRQOL inventory, which includes the generic SF-36 core items, supplemented with 18 MS-targeted items. Availability of an adaptive short version providing immediate item scoring may improve instrument usability and validity. However, multidimensional computerized adaptive testing (MCAT) has not been previously applied to MSQOL-54 items. We thus aimed to apply MCAT to the MSQOL-54 and assess its performance. Methods: Responses from a large international sample of 3669 MS patients were assessed. We calibrated 52 (of the 54) items using bifactor graded response model (10 group factors and one general HRQOL factor). Then, eight simulations were run with different termination criteria: standard errors (SE) for the general factor and group factors set to different values, and change in factor estimates from one item to the next set at < 0.01 for both the general and the group factors. Performance of the MCAT was assessed by the number of administered items, root mean square difference (RMSD), and correlation. Results: Eight items were removed due to local dependency. The simulation with SE set to 0.32 (general factor), and no SE thresholds (group factors) provided satisfactory performance: the median number of administered items was 24, RMSD was 0.32, and correlation was 0.94. Conclusions: Compared to the full-length MSQOL-54, the simulated MCAT required fewer items without losing precision for the general HRQOL factor. Further work is needed to add/integrate/revise MSQOL-54 items in order to make the calibration and MCAT performance efficient also on group factors, so that the MCAT version may be used in clinical practice and research. [ABSTRACT FROM AUTHOR]

Background: MSQOL-54 is a multidimensional, widely-used, health-related quality of life (HRQOL) instrument specific 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 confirmatory 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 coefficients (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 coefficients 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. [ABSTRACT FROM AUTHOR]