ArticleClinical psychological science : a journal of the Association for Psychological Science2024
Machine-Learning-Based Prediction of Client Distress From Session Recordings.
Article in Clinical psychological science : a journal of the Association for Psychological Science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Role of Artificial Intelligence in Clinical Psychology: How AI and NLP Systems Are Reshaping Psychological Interventions. A Systematic Review.Clinical psychology & psychotherapyPooled 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
- 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
- The Digital Mirror: Clinical Potentials and Relational Risks of Generative AI in Mental Health Interventions.Current psychiatry reports · 2026Review
- Multimodal assessments of therapist characteristics are largely unrelated to patient outcomes: A preregistered analysis.Clinical psychological science : a journal of the Association for Psychological Science · 2026Article
- The effectiveness of digital interventions for enhancing empathy in adults: a meta-analysis of randomized controlled trials.Current psychology (New Brunswick, N.J.) · 2026Article
- A Framework for Automation in Psychotherapy.Current directions in psychological science · 2025Article
- Automating the assessment of multicultural orientation through machine learning and natural language processing.Psychotherapy (Chicago, Ill.) · 2025Article
- Development and validation of large language model rating scales for automatically transcribed psychological therapy sessions.Scientific reports · 2025Article
- Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.Journal of consulting and clinical psychology · 2025Article
- Measuring activation during behavioral activation therapy: a proof-of-concept study using smartphone sensors and LLM-derived ratings in adolescents with anhedonia.NPP - digital psychiatry and neuroscience · 2025Article
- Developing Therapists' Multicultural Orientation Using Web-Based Deliberate Practice: An Initial Feasibility, Usability, and Acceptability Study.Professional psychology, research and practice · 2024Article
- Examining a sentiment algorithm on session patient records in an eating disorder treatment setting: a preliminary study.Frontiers in psychiatry · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Natural language processing (NLP) is a subfield of machine learning that may facilitate the evaluation of therapist-client interactions and provide feedback to therapists on client outcomes on a large scale. However, there have been limited studies applying NLP models to client outcome prediction that have (a) used transcripts of therapist-client interactions as direct predictors of client symptom improvement, (b) accounted for contextual linguistic complexities, and (c) used best practices in classical training and test splits in model development. Using 2,630 session recordings from 795 clients and 56 therapists, we developed NLP models that directly predicted client symptoms of a given session based on session recordings of the previous session (Spearman's rho =0.32, p<.001). Our results highlight the potential for NLP models to be implemented in outcome monitoring systems to improve quality of care. We discuss implications for future research and applications.
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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.