Abstract Background: The GRADE framework is widely used to assess the certainty of evidence in systematic reviews and guideline development. Its four categories (high, moderate, low, very low) represent structured judgments regarding how likely the probability that the true effect lies within a specified range around the estimate. However, the construct labeled as “certainty” is operationalized as a graded probabilistic judgment, raising questions about potential conceptual ambiguity. Objective: To examine whether the terminology “certainty of evidence” aligns with its operational definition within GRADE and to explore whether terminological clarification could enhance interpretive precision without altering methodological structure. Methods: We conducted a conceptual analysis of key GRADE publications from 2004 to 2025, including GRADE Guidance papers, examining the evolution of terminology and its alignment with principles of construct validity in measurement theory. Results: Early GRADE publications framed judgments primarily in terms of “confidence in estimates.” Subsequent guidance consolidated the terminology “certainty of evidence,” while retaining probabilistic and graded operational criteria. From a construct validity perspective, the operational definition corresponds to graded confidence rather than categorical epistemic certainty. Although this does not undermine the methodological integrity of GRADE, it may introduce interpretive ambiguity, particularly in interdisciplinary or high-stakes contexts. Conclusions: Reframing “certainty of evidence” as “confidence in evidence” would preserve the analytic structure of GRADE while improving semantic alignment between construct label and operational function. Terminological refinement represents an incremental clarification consistent with GRADE’s tradition of methodological development.

Background: The Cochrane Handbook’s I 2 categorization system (0-25% ”low”, 25-75% ”moderate”, ≥50% ”high” heterogeneity) serves as the international standard for interpreting heterogeneity in meta-analysis, influencing thousands of systematic reviews annually. Despite its ubiquitous adoption, neither the logical coherence nor the intended analytical function of this system has been systematically examined. Objective: To examine whether the Cochrane Handbook’s I 2 categorization system contains overlapping category definitions that violate fundamental principles of logical classification, and to propose context-specific analytical frameworks that preserve I 2’s function as a decision tool for heterogeneity exploration. Methods: We conducted systematic examination of the Cochrane Handbook’s I 2 categorical definitions to identify logical inconsistencies, specifically analyzing whether individual I 2 values can simultaneously satisfy multiple contradictory category criteria. We performed logical analysis of the I 2 categorization system using principles from formal logic, philosophy of science, and statistical theory. We examined genealogical origins through comprehensive literature review from the original I 2 statistic development through current Cochrane guidance. Context-specific analytical frameworks were developed based on patient-important outcome categories. Results: Our systematic examination confirmed that the I 2 categorization system exhibits overlapping category definitions where identical values simultaneously satisfy multiple contradictory categorical criteria (e.g., I 2=50% meets both ”moderate” 25-75% and ”high” ≥50% definitions). The I 2 categorization system exhibits fundamental interpretive inconsistencies: (1) Individual values (e.g., I 2=50%) simultaneously satisfy multiple contradictory categorical definitions; (2) The system violates Leibniz’s principle of identity and non-contradiction; (3) No theoretical or empirical justification exists in primary literature for chosen thresholds; (4) Current approach misuses I 2 as interpretation endpoint rather than analytical decision tool for meta-regression in studies with ≥10 trials. These violations compromise the clinical utility of evidence synthesis by obscuring the context-dependent nature of heterogeneity assessment. Conclusions: The current I 2 categorization system may lead to interpretive ambiguity and inconsistent analytical decisions across outcome contexts.. Rather than abandoning I 2, evidence synthesis requires context-specific analytical frameworks where I 2=20% in all-cause mortality triggers different analytical decisions than I 2=20% in quality-of-life outcomes. We propose the Patient-Important Outcome Heterogeneity Assessment (PIOHA) framework to align heterogeneity analysis with clinical relevance while preserving I 2’s valuable function as an analytical decision tool. Clinical Relevance: Systematic reviews inform clinical guidelines and patient care decisions. Context-specific heterogeneity assessment frameworks enable appropriate analytical decisions that reflect the clinical importance and expected variability patterns of different patient-important outcomes.