CLINICAL UNCERTAINTY IN DENTISTRY: NAVIGATING DIAGNOSTIC AND THERAPEUTIC GRAY ZONES

Abstract

Background: Clinical uncertainty, caused by biological variability, imperfect diagnostic tools, and incomplete or conflicting evidence ,is a feature of dental practice and a major driver of variability in diagnosis, treatment planning, and clinician stress.

Aim: This narrative review synthesizes the possible reasons uncertainty arises across dental diagnosis and treatment planning, it’s influence on clinical decision-making, and examines educational & practice strategies can help clinicians navigate diagnostic and therapeutic gray zones more safely and transparently.

Methods: A search of dentistry focused uncertainty and clinical decision making literature, including scoping review evidence, studies on interpretive variability, guideline/evidence limitations, and emerging work on artificial intelligence (AI) in oral diagnosis and education was performed using PUBMED,SCOPUS, and WEB OF SCIENCE including 43 studies.

Results: Uncertainty is sustained by heterogeneous disease natures and borderline clinical findings, further complicated by interclinician variability and gaps in high quality evidence; thus increasing reliance on experience, and risk tolerance, contributing to inconsistent recommendations. Educational approaches that explicitly teach uncertainty management such as case-based learning, reflective practice, mentorship, and bias-awareness, support more resilient clinical reasoning. AI may reduce some diagnostic uncertainty, but also introduce new concerns about transparency, calibration, and safe deployment.

Conclusion: Instead of being disregarded, uncertainty should be anticipated, communicated, and managed. Structured educational frameworks, standardized diagnostic calibration, shared decision-making, and cautiou integration of validated AI tools can improve consistency, safety, and clinician confidence.