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Confirmatory factor analysis of the Oral Health Impact Profile
Author(s) -
John M. T.,
Feuerstahler L.,
Waller N.,
Baba K.,
Larsson P.,
Čelebić A.,
Kende D.,
RenerSitar K.,
Reissmann D. R.
Publication year - 2014
Publication title -
journal of oral rehabilitation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.991
H-Index - 93
eISSN - 1365-2842
pISSN - 0305-182X
DOI - 10.1111/joor.12191
Subject(s) - confirmatory factor analysis , interpretability , structural equation modeling , exploratory factor analysis , psychosocial , population , psychology , oral health , goodness of fit , clinical psychology , factor analysis , sample (material) , medicine , statistics , psychometrics , dentistry , mathematics , psychiatry , artificial intelligence , computer science , environmental health , chemistry , chromatography
Summary Previous exploratory analyses suggest that the Oral Health Impact Profile ( OHIP ) consists of four correlated dimensions and that individual differences in OHIP total scores reflect an underlying higher‐order factor. The aim of this report is to corroborate these findings in the Dimensions of Oral Health‐Related Quality of Life ( DOQ ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Validation Sample ( n = 5022), we conducted confirmatory factor analyses in a sample of 4993 subjects with sufficiently complete data. In particular, we compared the psychometric performance of three models: a unidimensional model, a four‐factor model and a bifactor model that included one general factor and four group factors. Using model‐fit criteria and factor interpretability as guides, the four‐factor model was deemed best in terms of strong item loadings, model fit ( RMSEA = 0·05, CFI = 0·99) and interpretability. These results corroborate our previous findings that four highly correlated factors – which we have named Oral Function , Oro‐facial Pain , Oro‐facial Appearance and Psychosocial Impact – can be reliably extracted from the OHIP item pool. However, the good fit of the unidimensional model and the high interfactor correlations in the four‐factor solution suggest that OHRQ oL can also be sufficiently described with one score.