Abstract

Artificial intelligence generally and machine learning specifically have become deeply woven into the lives and technologies of modern life. Machine learning is dramatically changing scientific research and industry and may also hold promise for addressing limitations encountered in mental health care and psychotherapy. The current paper introduces machine learning and natural language processing as related methodologies that may prove valuable for automating the assessment of meaningful aspects of treatment. Prediction of therapeutic alliance from session recordings is used as a case in point. Recordings from 1,235 sessions of 386 clients seen by 40 therapists at a university counseling center were processed using automatic speech recognition software. Machine learning algorithms learned associations between client ratings of therapeutic alliance exclusively from session linguistic content. Using a …

Date

2020

Authors

Simon B Goldberg, Nikolaos Flemotomos, Victor R Martinez, Michael J Tanana, Patty B Kuo, Brian T Pace, Jennifer L Villatte, Panayiotis G Georgiou, Jake Van Epps, Zac E Imel, Shrikanth S Narayanan, David C Atkins

Journal

Journal of counseling psychology

Volume

67

Issue

4

Pages

438

Publisher

American Psychological Association