Development and validation of a latent, multidimensional, self-report periodontal disease measure.

Abstract

Self-report measures of periodontal disease have utility for screening, but have not capitalized on a latent variable approach based on psychometric theory to validate such measures. This study aimed to develop a psychometrically valid self-report measure of periodontal disease using latent variable factor analysis and other evidence-based psychometric analyses. Likert-type items reflecting periodontal disease were administered to a sample of adults (n=828) in the United States via an online survey. Items were adapted from prior self-report measures or were newly developed based on psychometric item development theory and theoretical knowledge of periodontal disease. Psychometric analyses included exploratory and confirmatory factor analysis, parallel analysis, and a calculation of internal consistency. Exploratory factor analysis (EFA) was indicative of the goodness-of-fit with two factors (root mean square error of approximation (RMSEA)=0.08; comparative fit index (CFI)=0.97; Tucker Lewis index (TLI)=0.96; standardized root mean squared residual=0.06); five of the 22 original survey questions were eliminated based on the results of this EFA. Parallel analysis supported a two-factor model to represent the similarities across items-one factor reflecting physiologic components and another reflecting functional components of periodontal disease. Confirmatory Factor Analysis also indicated adequate model fit (RMSEA=0.07; CFI=0.98; TLI=0.98; and weighted root mean square residual=1.20). Psychometric analyses of a new 17-item periodontal disease self-report measure provided initial evidence of construct/factor validity. This approach to developing self-report periodontal disease measures may facilitate useful and cost-effective estimates of periodontal disease and provide a testable scale. Future work should include clinical validation.