Literature DB >> 34346043

Automated evaluation of psychotherapy skills using speech and language technologies.

Nikolaos Flemotomos1, Victor R Martinez2, Zhuohao Chen3, Karan Singla2, Victor Ardulov2, Raghuveer Peri3, Derek D Caperton4, James Gibson5, Michael J Tanana6, Panayiotis Georgiou3, Jake Van Epps7, Sarah P Lord8, Tad Hirsch9, Zac E Imel4, David C Atkins8, Shrikanth Narayanan3,2,5.   

Abstract

With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and quality assurance of services. Traditionally, quality assessment is addressed by human raters who evaluate recorded sessions along specific dimensions, often codified through constructs relevant to the approach and domain. This is, however, a cost-prohibitive and time-consuming method that leads to poor feasibility and limited use in real-world settings. To facilitate this process, we have developed an automated competency rating tool able to process the raw recorded audio of a session, analyzing who spoke when, what they said, and how the health professional used language to provide therapy. Focusing on a use case of a specific type of psychotherapy called "motivational interviewing", our system gives comprehensive feedback to the therapist, including information about the dynamics of the session (e.g., therapist's vs. client's talking time), low-level psychological language descriptors (e.g., type of questions asked), as well as other high-level behavioral constructs (e.g., the extent to which the therapist understands the clients' perspective). We describe our platform and its performance using a dataset of more than 5000 recordings drawn from its deployment in a real-world clinical setting used to assist training of new therapists. Widespread use of automated psychotherapy rating tools may augment experts' capabilities by providing an avenue for more effective training and skill improvement, eventually leading to more positive clinical outcomes.
© 2021. The Psychonomic Society, Inc.

Entities:  

Keywords:  MISC; Machine learning; Motivational interviewing; Psychotherapy; Quality assessment; Speech processing

Mesh:

Year:  2021        PMID: 34346043      PMCID: PMC8810915          DOI: 10.3758/s13428-021-01623-4

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  28 in total

Review 1.  Prosody in the comprehension of spoken language: a literature review.

Authors:  A Cutler; D Dahan; W van Donselaar
Journal:  Lang Speech       Date:  1997 Apr-Jun       Impact factor: 1.500

2.  Semantics derived automatically from language corpora contain human-like biases.

Authors:  Aylin Caliskan; Joanna J Bryson; Arvind Narayanan
Journal:  Science       Date:  2017-04-14       Impact factor: 47.728

3.  Computational psychotherapy research: scaling up the evaluation of patient-provider interactions.

Authors:  Zac E Imel; Mark Steyvers; David C Atkins
Journal:  Psychotherapy (Chic)       Date:  2014-05-26

4.  Machine learning and natural language processing in psychotherapy research: Alliance as example use case.

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:  J Couns Psychol       Date:  2020-07

5.  Design feasibility of an automated, machine-learning based feedback system for motivational interviewing.

Authors:  Zac E Imel; Brian T Pace; Christina S Soma; Michael Tanana; Tad Hirsch; James Gibson; Panayiotis Georgiou; Shrikanth Narayanan; David C Atkins
Journal:  Psychotherapy (Chic)       Date:  2019-04-08

6.  Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial.

Authors:  Kevin A Hallgren
Journal:  Tutor Quant Methods Psychol       Date:  2012

7.  Counselor skill influences outcomes of brief motivational interventions.

Authors:  Jacques Gaume; Gerhard Gmel; Mohamed Faouzi; Jean-Bernard Daeppen
Journal:  J Subst Abuse Treat       Date:  2009-03-31

8.  Agency context and tailored training in technology transfer: a pilot evaluation of motivational interviewing training for community counselors.

Authors:  John S Baer; Elizabeth A Wells; David B Rosengren; Bryan Hartzler; Blair Beadnell; Chris Dunn
Journal:  J Subst Abuse Treat       Date:  2009-03-31

9.  How Does Therapy Harm? A Model of Adverse Process Using Task Analysis in the Meta-Synthesis of Service Users' Experience.

Authors:  Joe Curran; Glenys D Parry; Gillian E Hardy; Jennifer Darling; Ann-Marie Mason; Eleni Chambers
Journal:  Front Psychol       Date:  2019-03-13

Review 10.  Electronic health records to facilitate clinical research.

Authors:  Martin R Cowie; Juuso I Blomster; Lesley H Curtis; Sylvie Duclaux; Ian Ford; Fleur Fritz; Samantha Goldman; Salim Janmohamed; Jörg Kreuzer; Mark Leenay; Alexander Michel; Seleen Ong; Jill P Pell; Mary Ross Southworth; Wendy Gattis Stough; Martin Thoenes; Faiez Zannad; Andrew Zalewski
Journal:  Clin Res Cardiol       Date:  2016-08-24       Impact factor: 5.460

View more
  2 in total

1.  An Automated Quality Evaluation Framework of Psychotherapy Conversations with Local Quality Estimates.

Authors:  Zhuohao Chen; Nikolaos Flemotomos; Karan Singla; Torrey A Creed; David C Atkins; Shrikanth Narayanan
Journal:  Comput Speech Lang       Date:  2022-03-28       Impact factor: 3.252

2.  Enhancing the quality of cognitive behavioral therapy in community mental health through artificial intelligence generated fidelity feedback (Project AFFECT): a study protocol.

Authors:  Torrey A Creed; Leah Salama; Roisin Slevin; Michael Tanana; Zac Imel; Shrikanth Narayanan; David C Atkins
Journal:  BMC Health Serv Res       Date:  2022-09-20       Impact factor: 2.908

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.