Developing a short form of Oral Health Impact Profile (OHIP) for dental aesthetics: OHIP-aesthetic.
ABSTRACT To develop and evaluate shortened forms of the Oral Health Impact Profile (OHIP) for discriminating dental aesthetics problems and evaluating dental aesthetic outcomes.
Eighty-seven subjects self-completed the 49-item OHIP at baseline and 63 at follow up (8 weeks later), with the intervention of applying an array of tooth-whitening products. Expert-based approach and regression analysis (on baseline data) were undertaken to derive two subset questionnaires (OHIP-conceptual and OHIP-regression). Their discriminatory ability for dental aesthetics and their responsiveness to tooth whitening were compared with the original OHIP-49, Slade's OHIP-14 and a Chinese short-form version of OHIP.
The measures developed were strongly associated with self-rating of dental aesthetics (P < 0.001) unlike OHIP-49 (P = 0.03) or other OHIP short forms (P > 0.05). The measures were also reliable (Cronbach's alpha 0.86) and comparable with the other OHIP forms. In terms of effect size, OHIP-conceptual was more effective in measuring changes than the one based on the regression analysis, the original OHIP-49, OHIP-14 and the Chinese version of the short-form OHIP. It also exhibited a less susceptibility to floor effects than other OHIP forms.
A modified short form of the OHIP derived (OHIP-conceptual) was the most favorable in discriminating dental aesthetics, was reliable and most sensitive to the dental aesthetics intervention - tooth whitening.
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ABSTRACT: Although oral health-related quality of life (OHRQoL) as measured by the Oral Health Impact Profile (OHIP) is thought to be multidimensional, the nature of these dimensions is not known. The aim of this report was to explore the dimensionality of the OHIP using the Dimensions of OHRQoL (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Learning Sample (n = 5173), we conducted an exploratory factor analysis on the 46 OHIP items not specifically referring to dentures for 5146 subjects with sufficiently complete data. The first eigenvalue (27·0) of the polychoric correlation matrix was more than ten times larger than the second eigenvalue (2·6), suggesting the presence of a dominant, higher-order general factor. Follow-up analyses with Horn's parallel analysis revealed a viable second-order, four-factor solution. An oblique rotation of this solution revealed four highly correlated factors that we named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact. These four dimensions and the strong general factor are two viable hypotheses for the factor structure of the OHIP.Journal of Oral Rehabilitation 06/2014; · 2.34 Impact Factor
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ABSTRACT: 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 OHRQoL can also be sufficiently described with one score.Journal of Oral Rehabilitation 06/2014; · 2.34 Impact Factor
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ABSTRACT: PURPOSE: The objective was to determine the responsiveness properties of the Oral Health Impact Profile (OHIP) short-forms and 36-item Short-Form (SF-36) in complete denture treatment, and further to evaluate the association between patients' satisfaction and improvements in oral and general health-related quality of life (OHRQoL and HRQoL) after fitting of new, complete dentures. METHODS: Study data were obtained from the 'Dentures for the Elders through Public Funding' study conducted in Kaohsiung County. A total of 224 subjects received denture treatments with 6-month follow-up and pre-/post-treatment interviews by questionnaire. The OHIP and SF-36 were used to measure OHRQoL and HRQoL. In addition, specific questions investigating seven aspects of patients' satisfaction were used to measure the patients' perceptions of complete denture success. The responsiveness of all outcome measures and their dimensions were assessed by effect size (ES). Multivariable analysis was used to examine the association between patients' satisfaction and OHIP/SF-36 while adjusting for demographic characteristics. RESULTS: There were improvements with regard to the 'physical pain' (ES = 0.19) and 'psychological discomfort' (ES = 0.42) dimensions of the Taiwanese short-form OHIP (OHIP-14T) after new complete denture treatment, but only improvement in the 'general health' (ES = 0.17) dimension in the SF-36 measure. Patients satisfied with 'comfort' and 'ease of cleaning' of their new dentures were significantly associated with the improvement of the OHIP-49 and OHIP-14T. CONCLUSIONS: This study suggests that denture treatments are associated with improvements of OHRQoL, but not in HRQoL. Furthermore, patients' satisfaction was significantly associated with responsiveness of OHRQoL but less significantly associated with responsiveness of HRQoL.Quality of Life Research 11/2012; · 2.86 Impact Factor