When Average Isn't Good Enough: Identifying Meaningful Subgroups in Clinical Data.

ABSTRACT:

Background

Clinical data are usually analyzed with the assumption that knowledge gathered from group averages applies to the individual. Doing so potentially obscures patients with meaningfully different trajectories of therapeutic change. Needed are "idionomic" methods that first examine idiographic patterns before nomothetic generalizations are made. The objective of this paper is to test whether such an idionomic method leads to different clinical conclusions.

Methods

51 patients completed weekly process measures and symptom severity over a period of eight weeks. Change trajectories were analyzed using a nomothetic approach and an idiographic approach with bottom-up clustering of similar individuals. The outcome was patients' well-being at post-treatment.

Results

I

SUBMITTER: Gloster AT 

PROVIDER: S-EPMC11341641 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature