Geometric Melasma Area Patterns (Gmaps) Can be Used for Teledermatology Practice Without Inter - Observer Variation: A Comparative Non- Interventional Validation Study by Assessing Residents on A Self-Directed Learning (Sdl) Platform

Background: A novel method, geometric melasma area patterns (GMAPs), categorizes melasma into six distinct geometric configurations and quantifies the extent of affected areas. Aims/Objectives: This study evaluates GMAPs by comparing teledermatology assessments with in-person evaluations and analyzing inter-observer variability among dermatology residents. Methodology: The principal investigator (PI) conducted in-person GMAP assessments for 100 patients. Digital images were presented via a PowerPoint display, and 10 residents, trained using a standardized self-directed learning protocol, identified the patterns. Results: Kappa coefficients comparing the PI’s assessments with those of the 10 residents were highly significant ( P < 0.001). Half of the residents achieved strong agreement, while the others showed moderate agreement, with an overall agreement rate of 65.93%. Fleiss kappa values for individual GMAPs (horizontal straight line, upper triangle, lower triangle, quadrilateral, pentagon, and hexagon) were 0.905, 0.388, 0.364, 0.465, 0.798, and 0.843, respectively. Higher agreement was noted for horizontal straight line, pentagon, and hexagon, with lower agreement for upper triangle, lower triangle, and quadrilateral. Conclusion: This study confirms the effectiveness of image-based GMAP analysis in teledermatology, demonstrating minimal inter-observer variability.