"Comparative Evaluation Of Shade Matching Accuracy: Smartphone Application Vs. Conventional Visual Method"
DOI:
https://doi.org/10.64252/x2rctp33Abstract
Aim: To compare the shade-matching accuracy between a smartphone application (NAiBU) and the conventional visual method using the Vita Classic shade guide in dental shade selection.
Methods: A total of 76 subjects were selected. Shade matching was performed on natural, unrestored maxillary anterior teeth using both the Vita Classic shade guide (conventional method) and the NAiBU smartphone application in Google pixel 8a with 64 MP (upto 8x Digital Zoom) wide angle primary camera specifications. Standardized conditions were maintained throughout, including the use of cheek retractors and consistent natural lighting. Shade tabs were positioned at a distance of 25 cm against a neutral grey background for visual matching. The selected shades were recorded and tabulated. Data were subjected to statistical analysis using Cronbach’s alpha for interobserver reliability, intraclass correlation coefficient (ICC) for assessing consistency among observers, and Spearman’s rho test to evaluate intra-observer correlation between the two methods.
Results: Interobserver reliability was higher for the conventional technique (Cronbach’s alpha = 0.60) compared to the app technique (0.047), indicating greater consistency among observers. Intraclass correlation also favored the conventional method (0.59, p ≤ 0.001), while the app showed low agreement (0.04, p = 0.389). A statistically significant positive correlation was observed between the app and observer assessments (Spearman’s ρ = 0.39, p = 0.001).
Conclusion: Within the limitations of the study, it can be concluded that the NAiBU app demonstrates potential as a supplementary aid in tooth shade selection; however, it cannot yet replace the conventional visual method due to several inherent limitations. One of the primary challenges lies in the variability introduced by different mobile devices—each with distinct camera specifications, sensor quality, and color calibration.
