ObjectiveTo systematically investigate the application status of the minimal clinically important difference (MCID) and minimal important change (MIC) in intragroup and intergroup analyses of functional constipation symptom scales from 2000 to 2025, and provide a reference for the standardized formulation of clinical efficacy evaluation criteria for functional constipation in China. MethodsRandomized controlled trials (RCTs) and meta-analyses on functional constipation were retrieved from WanFang Data, CNKI, PubMed, Embase, and CENTRAL databases between January 1, 2000, and January 7, 2025. Three reviewers independently screened the literature, extracted information on the characteristics of MIC/MCID reported in the studies, and conducted descriptive analyses. ResultsA total of 337 studies were evaluated for readability, with 291 studies meeting the inclusion criteria. Among eligible studies, 6 used MIC/MCID thresholds, and 38 reported responder definitions, including 5 using MIC and 1 using MIC and MCID. Discrepancies were observed between the expected and actual values of MIC/MCID. Six included studies provided explicit citation support for their selected MIC/MCID thresholds. ConclusionThe application and interpretation of MIC and MCID thresholds face fundamental challenges. Using functional constipation research as an example, researchers often derive MIC-like thresholds through intergroup comparisons of individual change proportions and mistakenly equate them with MCID. This conceptual confusion may lead to clinical interpretation bias due to neglecting the essential differences between the two thresholds. Additionally, issues include lack of methodological justification for responder analysis, broad threshold ranges, and near-absence of blinded evaluations. It is recommended that researchers clarify the definitions and analytical pathways of the two thresholds during RCT design, avoid misusing intergroup statistics as individual efficacy criteria, and strengthen the methodological rigor of blinded design and threshold validation.
