Between-group minimally important change versus individual treatment responders

Ron D. Hays*, John Devin Peipert

*Corresponding author for this work

Research output: Contribution to journalComment/debatepeer-review

Abstract

Purpose: Estimates of the minimally important change (MIC) can be used to evaluate whether group-level differences are large enough to be important. But responders to treatment have been based upon group-level MIC thresholds, resulting in inaccurate classification of change over time. This article reviews options and provides suggestions about individual-level statistics to assess whether individuals have improved, stayed the same, or declined. Methods: Review of MIC estimation and an example of misapplication of MIC group-level estimates to assess individual change. Secondary data analysis to show how perceptions about meaningful change can be used along with significance of individual change. Results: MIC thresholds yield over-optimistic conclusions about responders to treatment because they classify those who have not changed as responders. Conclusions: Future studies need to evaluate the significance of individual change using appropriate individual-level statistics such as the reliable change index or the equivalent coefficient of repeatability. Supplementing individual statistical significance with retrospective assessments of change is desirable.

Original languageEnglish (US)
Pages (from-to)2765-2772
Number of pages8
JournalQuality of Life Research
Volume30
Issue number10
DOIs
StatePublished - Oct 2021

Keywords

  • Meaningful change
  • Minimally important difference
  • Reliable change index
  • Responder

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

Fingerprint

Dive into the research topics of 'Between-group minimally important change versus individual treatment responders'. Together they form a unique fingerprint.

Cite this