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Migraine screen questionnaire: further psychometric evidence from categorical data methods

Article scientifique 2020 Anglais

Résumé

BACKGROUND: Psychometric investigations of tools used in the screening of migraine including the migraine screen questionnaire (MS-Q), using an adequate statistical approach is needed. We assessed the psychometric properties of the migraine screen questionnaire (MS-Q) using categorical data methods. MATERIAL AND METHODS: A total of 343 students at Mizan-Tepi University, Ethiopia, age range = 18-35 years were selected by a simple random sampling method to participate in a cross-sectional study. The respondents completed the MS-Q, a semi-structured socio-demographic questionnaire, and a visual analog scale for attention (VAS-A). RESULTS: The cumulative variance rule (> 40%), the Kaiser's criteria (Eigenvalue> 1), the Scree test and, the parallel analysis (minimum rank) identified a 1-factor model for the MS-Q with the factor loadings in the range of 0.78 to 0.84. Fit indices favored a 1-factor model of the MS-Q as indicated by comparative fit index (0.993), weighted root mean square residual (0.048), root mean square error of approximation (0.067), the goodness of fit index (1.00), and non-normed fit index (0.987). The values of the Factor Determinacy Index (0.953), marginal reliability (0.909), H-latent (0.909), H-observed (0.727), explained common variance (0.906) and the mean item residual absolute loadings (0.225) further complimented finding of the 1-Factor model. McDonald's Omega (0.903) suggested adequate internal consistency. Discriminative validity was supported by significantly higher scores for the total and all the MS-Q items except one among those with complaints of attention. CONCLUSION: The categorical methods support the psychometric validity of the MS-Q in the study population.

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Manzar, M. D., Hameed, U. A., Mohammed, S., Khan, M. Y., Nureye, D., Jifar, W. W., Alamri, M., Albougami, A., Pandi‐Perumal, S. R., & BaHammam, A. S. (2020). Migraine screen questionnaire: further psychometric evidence from categorical data methods. Health and Quality of Life Outcomes. https://doi.org/10.1186/s12955-020-01361-9

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