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Deeper Understanding of Appearance in Orofacial Clefts: A Structural Equation Model of the CLEFT-Q Appearance Scales
BACKGROUND: The CLEFT-Q is a patient-reported outcome measure with seven scales measuring elements of facial appearance in cleft lip and/or palate. We built on the validated CLEFT-Q structural model to describe conceptual relationships between these scales, and tested our hypothesis through structur...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447998/ https://www.ncbi.nlm.nih.gov/pubmed/34549001 http://dx.doi.org/10.1097/GOX.0000000000003806 |
Sumario: | BACKGROUND: The CLEFT-Q is a patient-reported outcome measure with seven scales measuring elements of facial appearance in cleft lip and/or palate. We built on the validated CLEFT-Q structural model to describe conceptual relationships between these scales, and tested our hypothesis through structural equation modeling (SEM). In our hypothesized model, the appearance of the nose, nostrils, teeth, jaw, lips, and cleft lip scar all contribute to overall facial appearance. METHODS: We included 640 participants from the international CLEFT-Q field test. Model fit was assessed using weighted least squares mean and variance adjusted regression. The model was then refined through modification indices. The fit of the hypothesized model was confirmed in an independent sample of 452 participants. RESULTS: The refined model demonstrated excellent fit to the data (comparative fit index 0.999, Tucker-Lewis index 0.999, root mean square error of approximation 0.036 and standardized root mean square residual 0.036). The confirmatory analysis also demonstrated excellent model fit. CONCLUSION: Our structural model, based on a clinical understanding of appearance in orofacial clefting, aligns with CLEFT-Q field test data. This supports the instrument’s use and the exploration of a wider range of applications, such as multidimensional computerized adaptive testing. |
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