Document Type

Article

Language

eng

Format of Original

11 p.

Publication Date

6-2015

Publisher

American Psychological Association

Source Publication

Psychological Assessment

Source ISSN

1040-3590

Original Item ID

DOI: 10.1037/pas0000060

Abstract

Several different approaches have been applied to identify early positive change in response to psychotherapy so as to predict later treatment outcome and length as well as use this information for outcome monitoring and treatment planning. In this study, simple methods based on clinically significant change criteria and computationally demanding growth mixture modeling (GMM) are compared with regard to their overlap and uniqueness as well as their characteristics in terms of initial impairment, therapy outcome, and treatment length. The GMM approach identified a highly specific subgroup of early improving patients. These patients were characterized by higher average intake impairments and higher pre-to-post-treatment score differences. Although being more specific for the prediction of treatment success, GMM was much less sensitive than clinically significant and reliable change criteria. There were no differences between the groups with regard to treatment length. Because each of the approaches had specific advantages, results suggest a combination of both methods for practical use in routine outcome monitoring and treatment planning.

Comments

Accepted version. Psychological Assessment, Vol 27, No. 2 (June 2015): 478-488. DOI. © 2015 American Psychological Association. Used with permission.

This article may not exactly replicate the final version published in the APA journal. It is not the copy of record.

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