Patty B Kuo, Maitrey Mehta, Halleh Hashtpari, Vivek Srikumar, Michael J Tanana, Karen W Tao, Joanna M Drinane, Jake Van-Epps, Zac E Imel
{"title":"Identification of cultural conversations in therapy using natural language processing models.","authors":"Patty B Kuo, Maitrey Mehta, Halleh Hashtpari, Vivek Srikumar, Michael J Tanana, Karen W Tao, Joanna M Drinane, Jake Van-Epps, Zac E Imel","doi":"10.1037/pst0000542","DOIUrl":null,"url":null,"abstract":"<p><p>Researchers have historically focused on understanding therapist multicultural competency and orientation through client self-report measures and behavioral coding. While client perceptions of therapist cultural competency and multicultural orientation and behavioral coding are important, reliance on these methods limits therapists receiving systematic, scalable feedback on cultural opportunities within sessions. Prior research demonstrating the feasibility of automatically identifying topics of conversation in psychotherapy suggests that natural language processing (NLP) models could be trained to automatically identify when clients and therapists are talking about cultural concerns and could inform training and provision of rapid feedback to therapists. Utilizing 103,170 labeled talk turns from 188 psychotherapy sessions, we developed NLP models that recognized the discussion of cultural topics in psychotherapy (<i>F</i>-1 = 70.0; Spearman's ρ = 0.78, <i>p</i> < .001). We discuss implications for research and practice and applications for future NLP-based feedback tools. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":20910,"journal":{"name":"Psychotherapy","volume":" ","pages":"259-268"},"PeriodicalIF":2.6000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychotherapy","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/pst0000542","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/14 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Researchers have historically focused on understanding therapist multicultural competency and orientation through client self-report measures and behavioral coding. While client perceptions of therapist cultural competency and multicultural orientation and behavioral coding are important, reliance on these methods limits therapists receiving systematic, scalable feedback on cultural opportunities within sessions. Prior research demonstrating the feasibility of automatically identifying topics of conversation in psychotherapy suggests that natural language processing (NLP) models could be trained to automatically identify when clients and therapists are talking about cultural concerns and could inform training and provision of rapid feedback to therapists. Utilizing 103,170 labeled talk turns from 188 psychotherapy sessions, we developed NLP models that recognized the discussion of cultural topics in psychotherapy (F-1 = 70.0; Spearman's ρ = 0.78, p < .001). We discuss implications for research and practice and applications for future NLP-based feedback tools. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍:
Psychotherapy Theory, Research, Practice, Training publishes a wide variety of articles relevant to the field of psychotherapy. The journal strives to foster interactions among individuals involved with training, practice theory, and research since all areas are essential to psychotherapy. This journal is an invaluable resource for practicing clinical and counseling psychologists, social workers, and mental health professionals.