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Prediction of dose–response relations based on patient characteristics
Author(s) -
Lutz Wolfgang,
Lowry Jenny,
Kopta S. Mark,
Einstein Danielle A.,
Howard Kenneth I.
Publication year - 2001
Publication title -
journal of clinical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.124
H-Index - 119
eISSN - 1097-4679
pISSN - 0021-9762
DOI - 10.1002/jclp.1057
Subject(s) - psychology , multilevel model , psychotherapist , radiation treatment planning , clinical psychology , machine learning , computer science , medicine , radiation therapy
The recent discussion of evidence‐based, adaptive treatment planning highlights the need for models for the prediction of courses of treatment response. We combine a dose–response model with growth curve modeling to determine dose–response relations for well‐being, symptoms, and functioning. Hierarchical linear modeling was used to model each patient's expected course of improvement. The resulting predictions were cross‐validated on two samples of psychotherapy outpatients. The results give further empirical support for the dose–response model and the phase model of psychotherapy as well as for the usefulness of patient treatment response profiling for individual treatment management. © 2001 John Wiley & Sons, Inc. J Clin Psychol 57: 889–900, 2001.