Three ways to quantify uncertainty in individually applied “minimally important change” values

• Published in: Journal of clinical epidemiology Vol. 63; no. 1; pp. 37 - 45
• Main Authors: de Vet, Henrica C.W, Terluin, Berend, Knol, Dirk L, Roorda, Leo D, Mokkink, Lidwine B, Ostelo, Raymond W.J.G, Hendriks, Erik J.M, Bouter, Lex M, Terwee, Caroline B
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 2010; Elsevier; Elsevier Limited
• Subjects: Anchor-based methods; Attitude to Health; Back pain; Biological and medical sciences; Change scores; Clinical outcomes; Computerized, statistical medical data processing and models in biomedicine; Data Interpretation, Statistical; Epidemiology; Humans; Internal Medicine; Low Back Pain - therapy; Medical sciences; Medical statistics; Minimally important change; Mortality; Outcome assessment; Patient Satisfaction; Patient-reported outcomes; Patients; Psychometrics; Quality of Life; Questionnaires; ROC Curve; ROC method; Treatment Outcome; Uncertainty; Anchor-based methods; ROC method; Patient-reported outcomes; Minimally important change; Outcome assessment; Change scores; Human; Uncertainty; Prognosis; Disease; Methodology; Self evaluation; Patient; Change; Receiver operating characteristic curves; Minimal important difference

Abstract Objective Determining “minimally important change” (MIC) facilitates the interpretation of change scores on multi-item instruments. This article focuses on how MIC values should be interpreted when applied to individual patients. Study Design and Setting The MIC value of a hypothetical ques...