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

Background 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. Methods 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. Results 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). Conclusions 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.