TY - JOUR
T1 - Empirically and clinically useful decision making in psychotherapy
T2 - Differential predictions with treatment response models
AU - Lutz, Wolfgang
AU - Saunders, Stephen M.
AU - Leon, Scott C.
AU - Martinovich, Zoran
AU - Kosfelder, Joachim
AU - Schulte, Dietmar
AU - Grawe, Klaus
AU - Tholen, Sven
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2006/6
Y1 - 2006/6
N2 - In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research networks. This article presents a strategy to disaggregate patients into homogeneous subgroups to generate optimal expected treatment response profiles, which can be used to predict and track the progress of patients in different treatment modalities. The study was based on data from 618 diagnostically diverse patients treated with either a cognitive-behavioral treatment protocol (n = 262) or an integrative cognitive-behavioral and interpersonal treatment protocol (n = 356). The validity of expected treatment response models to predict treatment in those 2 protocols for individual patients was evaluated. The ways such a procedure might be used in outpatient centers to learn more about patients, predict treatment response, and improve clinical practice are discussed.
AB - In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research networks. This article presents a strategy to disaggregate patients into homogeneous subgroups to generate optimal expected treatment response profiles, which can be used to predict and track the progress of patients in different treatment modalities. The study was based on data from 618 diagnostically diverse patients treated with either a cognitive-behavioral treatment protocol (n = 262) or an integrative cognitive-behavioral and interpersonal treatment protocol (n = 356). The validity of expected treatment response models to predict treatment in those 2 protocols for individual patients was evaluated. The ways such a procedure might be used in outpatient centers to learn more about patients, predict treatment response, and improve clinical practice are discussed.
KW - Adaptive decision making
KW - Differential predictions
KW - Expected treatment response
KW - Outcomes management
KW - Patient-focused research
UR - http://www.scopus.com/inward/record.url?scp=33746271566&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33746271566&partnerID=8YFLogxK
U2 - 10.1037/1040-3590.18.2.133
DO - 10.1037/1040-3590.18.2.133
M3 - Article
C2 - 16768589
AN - SCOPUS:33746271566
SN - 1040-3590
VL - 18
SP - 133
EP - 141
JO - Psychological assessment
JF - Psychological assessment
IS - 2
ER -