Kuo Patty B, Mehta Maitrey, Hashtpari Halleh, Srikumar Vivek, Tanana Michael J, Tao Karen W, Drinane Joanna M, Van-Epps Jake, Imel Zac E
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania.
Kahlert School of Computing, University of Utah.
Psychotherapy (Chic). 2024 Dec;61(4):259-268. doi: 10.1037/pst0000542. Epub 2024 Oct 14.
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 (-1 = 70.0; Spearman's ρ = 0.78, < .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).
从历史上看,研究人员一直专注于通过客户自我报告测量和行为编码来理解治疗师的多元文化能力和取向。虽然客户对治疗师文化能力和多元文化取向的看法以及行为编码很重要,但依赖这些方法限制了治疗师在治疗过程中获得关于文化机会的系统、可扩展的反馈。先前的研究表明,在心理治疗中自动识别谈话主题是可行的,这表明可以训练自然语言处理(NLP)模型来自动识别客户和治疗师何时在谈论文化问题,并可以为治疗师的培训和快速反馈提供信息。利用来自188次心理治疗会话的103170个标记谈话轮次,我们开发了NLP模型,该模型能够识别心理治疗中文化主题的讨论(-1 = 70.0;斯皮尔曼ρ = 0.78, <.001)。我们讨论了对研究和实践的影响以及未来基于NLP的反馈工具的应用。(PsycInfo数据库记录(c)2024美国心理学会,保留所有权利)