ArticlePloS one2015
"Rate My Therapist": Automated Detection of Empathy in Drug and Alcohol Counseling via Speech and Language Processing.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
53 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Natural language processing for mental health interventions: a systematic review and research framework.Translational psychiatry · 2023Pooled it
- A multivariate meta-analysis of motivational interviewing process and outcome.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2017Pooled it
- Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.Prevention science : the official journal of the Society for Prevention Research · 2026Trial
- Capitalizing on natural language processing (NLP) to automate the evaluation of coach implementation fidelity in guided digital cognitive-behavioral therapy (GdCBT).Psychological medicine · 2025Trial
- Use of common and unique techniques in the early treatment phase for cognitive-behavioral, interpersonal/emotional, and supportive listening interventions for generalized anxiety disorder.Psychotherapy (Chicago, Ill.) · 2020Trial
- An individually tailored family-centered intervention for pediatric obesity in primary care: study protocol of a randomized type II hybrid effectiveness-implementation trial (Raising Healthy Children study).Implementation science : IS · 2018Trial
- Applying Artificial Intelligence to Expand the Measurement Tool Kit in Clinical-Psychological Science: Moving Beyond Self-Reports.Clinical psychological science : a journal of the Association for Psychological Science · 2026Article
- It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety.JMIR mental health · 2026Article
- Automating the assessment of multicultural orientation through machine learning and natural language processing.Psychotherapy (Chicago, Ill.) · 2025Article
- Investigating psychotherapists' attitudes towards artificial intelligence in psychotherapy.BMC psychology · 2025Article
- Development and validation of a cognitive behavioral therapy for psychosis online training with automated feedback.Psychotherapy (Chicago, Ill.) · 2025Article
- Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.Journal of consulting and clinical psychology · 2025Article
- Employing large language models for emotion detection in psychotherapy transcripts.Frontiers in psychiatry · 2025Article
- Developing an Implementation Model for ADHD Intervention in Community Clinics: Leveraging Artificial Intelligence and Digital Technology.Cognitive and behavioral practice · 2024Article
- Machine Learning-Based Evaluation of Suicide Risk Assessment in Crisis Counseling Calls.Psychiatric services (Washington, D.C.) · 2024Article
- Machine-Learning-Based Prediction of Client Distress From Session Recordings.Clinical psychological science : a journal of the Association for Psychological Science · 2024Article
- A scoping review of empathy recognition in text using natural language processing.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Improving the quality of counseling and clinical supervision in opioid treatment programs: how can technology help?Addiction science & clinical practice · 2024Article
- Mental Health Counseling From Conversational Content With Transformer-Based Machine Learning.JAMA network open · 2024Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The technology for evaluating patient-provider interactions in psychotherapy-observational coding-has not changed in 70 years. It is labor-intensive, error prone, and expensive, limiting its use in evaluating psychotherapy in the real world. Engineering solutions from speech and language processing provide new methods for the automatic evaluation of provider ratings from session recordings. The primary data are 200 Motivational Interviewing (MI) sessions from a study on MI training methods with observer ratings of counselor empathy. Automatic Speech Recognition (ASR) was used to transcribe sessions, and the resulting words were used in a text-based predictive model of empathy. Two supporting datasets trained the speech processing tasks including ASR (1200 transcripts from heterogeneous psychotherapy sessions and 153 transcripts and session recordings from 5 MI clinical trials). The accuracy of computationally-derived empathy ratings were evaluated against human ratings for each provider. Computationally-derived empathy scores and classifications (high vs. low) were highly accurate against human-based codes and classifications, with a correlation of 0.65 and F-score (a weighted average of sensitivity and specificity) of 0.86, respectively. Empathy prediction using human transcription as input (as opposed to ASR) resulted in a slight increase in prediction accuracies, suggesting that the fully automatic system with ASR is relatively robust. Using speech and language processing methods, it is possible to generate accurate predictions of provider performance in psychotherapy from audio recordings alone. This technology can support large-scale evaluation of psychotherapy for dissemination and process studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.