ArticleJournal of counseling psychology2020
Machine learning and natural language processing in psychotherapy research: Alliance as example use case.
Article in Journal of counseling psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 4 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.
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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
46 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Does the Digital Therapeutic Alliance Exist? Integrative Review.JMIR mental health · 2025Pooled it
- Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications.Psychological medicine · 2025Pooled it
- Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review.JMIR mental health · 2024Pooled it
- Natural language processing for mental health interventions: a systematic review and research framework.Translational psychiatry · 2023Pooled 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
- Automated Working Alliance Assessment in Psychological Counseling Using Gemini and XGBoost.Entropy (Basel, Switzerland) · 2026Article
- Developing Methods for Observing Awe Narration in Psilocybin-Assisted Therapy.Healthcare (Basel, Switzerland) · 2026Article
- 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
- Scoping review on natural language processing applications in counselling and psychotherapy.British journal of psychology (London, England : 1953) · 2026Article
- From free association to free parameters: machine-learning empowers artificial intelligence models to rate the affective-relational aspects of narratives like an expert psychologist.Frontiers in digital health · 2026Article
- Utilizing artificial intelligence to optimize psychological trauma intervention in social assistances.Frontiers in psychology · 2026Article
- From promise to practice: artificial intelligence in mental health care in the MENA region.Frontiers in psychiatry · 2026Review
- Preprocessing Large-Scale Conversational Datasets: A Framework and Its Application to Behavioral Health Transcripts.JMIR formative research · 2025Article
- Automating the assessment of multicultural orientation through machine learning and natural language processing.Psychotherapy (Chicago, Ill.) · 2025Article
- A Scoping Review of Arabic Natural Language Processing for Mental Health.Healthcare (Basel, Switzerland) · 2025Review
- Evolution of Linguistic Markers of Agency, Centrality and Content During Metacognitive Therapy for Psychosis: A Pilot Exploratory Study.Early intervention in psychiatry · 2025Article
- Machine learning judged neutral facial expressions as key factors for a "good therapist" within the first five minutes: An experiment to simulate online video counselling.PEC innovation · 2024Article
- Protocol for a randomized controlled trial: exercise-priming of CBT for depression (the CBT+ trial).Trials · 2024Article
- Machine learning in preclinical drug discovery.Nature chemical biology · 2024Review
Corrections and comments
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Authors and funding
12 authors.
Funding
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 portion of the data to train the model, machine learning algorithms modestly predicted alliance ratings from session content in an independent test set (Spearman's ρ = .15, p < .001). These results highlight the potential to harness natural language processing and machine learning to predict a key psychotherapy process variable that is relatively distal from linguistic content. Six practical suggestions for conducting psychotherapy research using machine learning are presented along with several directions for future research. Questions of dissemination and implementation may be particularly important to explore as machine learning improves in its ability to automate assessment of psychotherapy process and outcome. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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.