Identification of cultural conversations in therapy using natural language processing models.

Journal: Psychotherapy (Chicago, Ill.)
PMID:

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 (-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).

Authors

  • Patty B Kuo
    University of Utah.
  • Maitrey Mehta
    Kahlert School of Computing, University of Utah.
  • Halleh Hashtpari
    Department of Psychology, Hawai'i Pacific University.
  • Vivek Srikumar
    University of Utah, School of Computing, 50S. Central Campus Drive Room 3190, Salt Lake City, UT, United States. Electronic address: svivek@cs.utah.edu.
  • Michael J Tanana
    University of Utah.
  • Karen W Tao
    Department of Educational Psychology, University of Utah.
  • Joanna M Drinane
    Department of Educational Psychology, University of Utah.
  • Jake Van-Epps
    Resiliency Center, School of Medicine, University of Utah.
  • Zac E Imel
    University of Utah.