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Race Matching in Predicting Relational Therapy Outcome: a Machine Learning Approach.
- Source :
- International Journal of Systemic Therapy; Apr-Jun2023, Vol. 34 Issue 2, p83-94, 12p, 1 Diagram, 4 Charts
- Publication Year :
- 2023
-
Abstract
- This study explores the relationship between therapist-client race/ethnicity matching on client treatment outcomes and whether other demographic factors contribute to treatment outcomes in a training clinic. An ANCOVA was conducted to examine the differences between race match and mismatch groups. A random forest algorithm was used to determine how racial matching conditions and other factors, such as gender, predict treatment outcomes. We found significant relationships between therapist-client race/ethnicity matching conditions and treatment outcomes for clients who received at least 10 sessions of therapy. However, results of the random forest algorithm indicated that race/ethnicity matching is one of the weakest predictors of treatment outcomes. Clinical implications and the limitations of the study are discussed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2692398X
- Volume :
- 34
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- International Journal of Systemic Therapy
- Publication Type :
- Academic Journal
- Accession number :
- 163248785
- Full Text :
- https://doi.org/10.1080/2692398X.2023.2169028