Minimal changes in health status questionnaires: Distinction between minimally detectable change and minimally important change

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.

Original languageEnglish
Article number54
JournalHealth and Quality of Life Outcomes
Volume4
DOIs
Publication statusPublished - 22 Aug 2006

Cite this

@article{906f9f0926fd48debc160cab70524c4e,
title = "Minimal changes in health status questionnaires: Distinction between minimally detectable change and minimally important change",
abstract = "Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.",
author = "{de Vet}, {Henrica C.} and Terwee, {Caroline B.} and Ostelo, {Raymond W.} and Heleen Beckerman and Knol, {Dirk L.} and Bouter, {Lex M.}",
year = "2006",
month = "8",
day = "22",
doi = "10.1186/1477-7525-4-54",
language = "English",
volume = "4",
journal = "Health and Quality of Life Outcomes",
issn = "1477-7525",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Minimal changes in health status questionnaires

T2 - Distinction between minimally detectable change and minimally important change

AU - de Vet, Henrica C.

AU - Terwee, Caroline B.

AU - Ostelo, Raymond W.

AU - Beckerman, Heleen

AU - Knol, Dirk L.

AU - Bouter, Lex M.

PY - 2006/8/22

Y1 - 2006/8/22

N2 - Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.

AB - Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.

UR - http://www.scopus.com/inward/record.url?scp=33749390540&partnerID=8YFLogxK

U2 - 10.1186/1477-7525-4-54

DO - 10.1186/1477-7525-4-54

M3 - Article

VL - 4

JO - Health and Quality of Life Outcomes

JF - Health and Quality of Life Outcomes

SN - 1477-7525

M1 - 54

ER -