Digital assessment of rest seat and guide plane preparations in removable partial denture education: A pilot study

This study evaluated the reliability, efficiency, and educational validity of digital model-based assessment in removable partial denture (RPD) training compared to conventional methods in terms of agreement, evaluation time, and assessment tendencies.

Thirty-seven dental students prepared the occlusal rest seats and distal guide planes on mandibular resin models. The preparations were scanned (TRIOS3^®, 3Shape) to generate digital models. Eleven dentists (three prosthodontic specialists [experts] and eight non-specialists) independently evaluated the jaw and digital models using a standardized rubric to assess the undercuts, surface roughness, sharp edges, and dimensional accuracy. Preparations that met all criteria were classified as PERFECT. Statistical analyses included agreement coefficients and exploratory comparisons of the categorical and continuous outcomes.

Digital assessments required longer evaluation times than conventional assessments. Variations in the evaluative tendencies were observed between the modalities, particularly for surface roughness. The intra-rater agreement suggested moderate levels for rest seat size and guide plane roughness/size (κ = 0.44-0.53), whereas lower agreement was observed for rest undercut, rough surface, and sharp edge. Agreement for the composite PERFECT criterion tended to be higher in digital models than in jaw models (κ = 0.34 vs. 0.12, respectively). The experts tended to assign fewer PERFECT scores to digital assessments.

Digital assessment showed advantages in standardization and agreement, but required more time and had limited reliability for tactile-dependent criteria. It may be more suitable for quantitative parameters and hybrid approaches may improve its application in RPD education.