ArticlePsychotherapy (Chicago, Ill.)2015
Computational psychotherapy research: scaling up the evaluation of patient-provider interactions.
Article in Psychotherapy (Chicago, Ill.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 3 of them syntheses that pooled it.
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Who cites it
48 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Natural language processing for mental health interventions: a systematic review and research framework.Translational psychiatry · 2023Pooled it
- Towards text mining therapeutic change: A systematic review of text-based methods for Therapeutic Change Process Research.PloS one · 2019Pooled 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
- Capitalizing on natural language processing (NLP) to automate the evaluation of coach implementation fidelity in guided digital cognitive-behavioral therapy (GdCBT).Psychological medicine · 2025Trial
- Speech-Derived Digital Markers of Treatment Response and Improvement Trajectories in Pediatric Anxiety.Research square · 2026Article
- Natural language processing of patient in-session speech to predict brief motivational interviewing alcohol intervention response: an exploratory study.Alcohol and alcoholism (Oxford, Oxfordshire) · 2026Article
- Scoping review on natural language processing applications in counselling and psychotherapy.British journal of psychology (London, England : 1953) · 2026Article
- [Therapist augmentation by generative AI: concept and implementation of the GAINED feedback system at Osnabrück University].Psychotherapie (Heidelberg, Germany) · 2026Article
- Individual-Specific Animated Profiles of Mental Health.Perspectives on psychological science : a journal of the Association for Psychological Science · 2025Article
- Evolution of Linguistic Markers of Agency, Centrality and Content During Metacognitive Therapy for Psychosis: A Pilot Exploratory Study.Early intervention in psychiatry · 2025Article
- Introduction to the Special Issue: Technological Applications in Mental Health and Mental Health Services Research.Administration and policy in mental health · 2024Article
- Measuring Alliance and Symptom Severity in Psychotherapy Transcripts Using Bert Topic Modeling.Administration and policy in mental health · 2024Article
- Leveraging Novel Technologies and Artificial Intelligence to Advance Practice-Oriented Research.Administration and policy in mental health · 2024Article
- Machine-Learning-Based Prediction of Client Distress From Session Recordings.Clinical psychological science : a journal of the Association for Psychological Science · 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
- The Adoption of AI in Mental Health Care-Perspectives From Mental Health Professionals: Qualitative Descriptive Study.JMIR formative research · 2023Article
- Opening the Black Box of Family-Based Treatments: An Artificial Intelligence Framework to Examine Therapeutic Alliance and Therapist Empathy.Clinical child and family psychology review · 2023Article
- You never know what you are going to get: Large-scale assessment of therapists' supportive counseling skill use.Psychotherapy (Chicago, Ill.) · 2023Article
- Public Attitudes Toward Anxiety Disorder on Sina Weibo: Content Analysis.Journal of medical Internet research · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In psychotherapy, the patient-provider interaction contains the treatment's active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required to "scale up" to larger evaluation tasks and "drill down" into the raw linguistic data of patient-therapist interactions. In the current article, we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, relational, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment-related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive-behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model-derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time. We conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice.
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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.