UCLA

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.