Yi-Hsin Hung, Deanna Linville, Emily E. Janes, Simon Yee
{"title":"Race Matching in Predicting Relational Therapy Outcome: a Machine Learning Approach","authors":"Yi-Hsin Hung, Deanna Linville, Emily E. Janes, Simon Yee","doi":"10.1080/2692398X.2023.2169028","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":29822,"journal":{"name":"International Journal of Systemic Therapy","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Systemic Therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2692398X.2023.2169028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
引用次数: 0
Abstract
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.