ArticlePLOS mental health2025
When ELIZA meets therapists: A Turing test for the heart and mind.
Article in PLOS mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Possible Role and Function of AI Conversational Agents in Dialectical Behavior Therapy for Borderline Personality Disorder: Qualitative Interview Study.JMIR mental health · 2026Article
- Breaking Barriers in Student Mental Health Care With AI-Enhanced Group Cognitive Behavioral Therapy: Pilot Feasibility Study.JMIR formative research · 2026Article
- Prevalence of AI-Supported Sexual Activities Among Adults in Germany: Results from a National Online Survey.Archives of sexual behavior · 2026Article
- Are Psychiatry Faculty Prepared to Guide AI Use? A National Survey.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
- PsychiatryBench: a multi-task benchmark for LLMs in psychiatry.NPJ digital medicine · 2026Article
- Large language models for psychosocial risk assessment: A multi-method evaluation across suicide, intimate partner violence, and substance misuse.PLOS digital health · 2026Article
- Toward clinical integration of generative AI in mental health: personalization, multimodality and inter-entity experience.Frontiers in public health · 2026Article
- AI and the coming mental health zombie apocalypse.Molecular psychiatry · 2025Article
- Anti-AI Bias Toward Couple Images and Couple Counseling: Findings from Two Experiments.Archives of sexual behavior · 2025Article
- Charting the evolution of artificial intelligence mental health chatbots from rule-based systems to large language models: a systematic review.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2025Article
- Placebo, Nocebo, and Machine Learning: How Generative AI Could Shape Patient Perception in Mental Health Care.JMIR mental health · 2025Article
- Generative Artificial Intelligence in Primary Care: Qualitative Study of UK General Practitioners' Views.Journal of medical Internet research · 2025Article
- Conversational AI in Pediatric Mental Health: A Narrative Review.Children (Basel, Switzerland) · 2025Review
- Artificial intelligence and psychoanalysis: is it time for psychoanalyst.AI?Frontiers in psychiatry · 2025Article
- Correction: When ELIZA meets therapists: A Turing test for the heart and mind.PLOS mental health · 2025Article
- ChatGPT as a mental health advisory service: Comparing evaluations from youth and health professionals.Digital healthArticle
Corrections and comments
- Erratum issued
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
"Can machines be therapists?" is a question receiving increased attention given the relative ease of working with generative artificial intelligence. Although recent (and decades-old) research has found that humans struggle to tell the difference between responses from machines and humans, recent findings suggest that artificial intelligence can write empathically and the generated content is rated highly by therapists and outperforms professionals. It is uncertain whether, in a preregistered competition where therapists and ChatGPT respond to therapeutic vignettes about couple therapy, a) a panel of participants can tell which responses are ChatGPT-generated and which are written by therapists (N = 13), b) the generated responses or the therapist-written responses fall more in line with key therapy principles, and c) linguistic differences between conditions are present. In a large sample (N = 830), we showed that a) participants could rarely tell the difference between responses written by ChatGPT and responses written by a therapist, b) the responses written by ChatGPT were generally rated higher in key psychotherapy principles, and c) the language patterns between ChatGPT and therapists were different. Using different measures, we then confirmed that responses written by ChatGPT were rated higher than the therapist's responses suggesting these differences may be explained by part-of-speech and response sentiment. This may be an early indication that ChatGPT has the potential to improve psychotherapeutic processes. We anticipate that this work may lead to the development of different methods of testing and creating psychotherapeutic interventions. Further, we discuss limitations (including the lack of the therapeutic context), and how continued research in this area may lead to improved efficacy of psychotherapeutic interventions allowing such interventions to be placed in the hands of individuals who need them the most.
Identifiers
What OpenQuestion holds
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.