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

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.