# Empowering Psychotherapy with Large Language Models: Cognitive Distortion Detection through Diagnosis of Thought Prompting

arXiv: https://arxiv.org/abs/2310.07146 · HTML: https://mlsanity.com/paper/2310.07146/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning.
- Builds on 14 of its 37 references that are in the map.
- First posted on arXiv 11 Oct 2023.

## Placed in

- LLM reasoning / [Clinical and biomedical applications](https://mlsanity.com/lr/clinical-and-biomedical-applications/)

## Builds on (most cited first, 14 of 14)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Large Language Models are Zero-Shot Reasoners](https://mlsanity.com/paper/2205.11916/) (2022)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://mlsanity.com/paper/2302.04023/) (2023)
- [A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support](https://mlsanity.com/paper/2009.08441/) (2020)
- [Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models](https://mlsanity.com/paper/2305.14763/) (2023)
- [MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare](https://mlsanity.com/paper/2110.15621/) (2021)
- [Large Language Models are few(1)-shot Table Reasoners](https://mlsanity.com/paper/2210.06710/) (2022)
- [SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions](https://mlsanity.com/paper/1806.05258/) (2018)
- [Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts](https://mlsanity.com/paper/2307.02768/) (2023)
- [Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes](https://mlsanity.com/paper/1907.00326/) (2019)
- [Helping the Helper: Supporting Peer Counselors via AI-Empowered Practice and Feedback](https://mlsanity.com/paper/2305.08982/) (2023)
- [RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses](https://mlsanity.com/paper/1806.07916/) (2018)
- [EmoMent: An Emotion Annotated Mental Health Corpus from two South Asian Countries](https://mlsanity.com/paper/2208.08486/) (2022)

## Built on by (most cited first, 30 of 31)

- [HealMe: Harnessing Cognitive Reframing in Large Language Models for Psychotherapy](https://mlsanity.com/paper/2403.05574/) (2024)
- [Large Language Models in Mental Health Care: a Scoping Review](https://mlsanity.com/paper/2401.02984/) (2024)
- [PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents](https://mlsanity.com/paper/2402.12326/) (2024)
- [Data-Centric Foundation Models in Computational Healthcare: A Survey](https://mlsanity.com/paper/2401.02458/) (2024)
- [PATIENT-Psi: Using Large Language Models to Simulate Patients for Training Mental Health Professionals](https://mlsanity.com/paper/2405.19660/) (2024)
- [Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts](https://mlsanity.com/paper/2403.13786/) (2024)
- [Detecting Conversational Mental Manipulation with Intent-Aware Prompting](https://mlsanity.com/paper/2412.08414/) (2024)
- [MAGI: Multi-Agent Guided Interview for Psychiatric Assessment](https://mlsanity.com/paper/2504.18260/) (2025)
- [CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy](https://mlsanity.com/paper/2410.13218/) (2024)
- [A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions](https://mlsanity.com/paper/2502.11095/) (2025)
- [Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis](https://mlsanity.com/paper/2403.16303/) (2024)
- [Preference Learning Unlocks LLMs' Psycho-Counseling Skills](https://mlsanity.com/paper/2502.19731/) (2025)
- [Socratic Reasoning Improves Positive Text Rewriting](https://mlsanity.com/paper/2403.03029/) (2024)
- [Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain](https://mlsanity.com/paper/2403.20288/) (2024)
- [The Pursuit of Empathy: Evaluating Small Language Models for PTSD Dialogue Support](https://mlsanity.com/paper/2505.15065/) (2025)
- [KoACD: The First Korean Adolescent Dataset for Cognitive Distortion Analysis via Role-Switching Multi-LLM Negotiation](https://mlsanity.com/paper/2505.00367/) (2025)
- [Exploratory Study into Relations between Cognitive Distortions and Emotional Appraisals](https://mlsanity.com/paper/2503.15979/) (2025)
- [A Survey of Cognitive Distortion Detection and Classification in NLP](https://mlsanity.com/paper/2508.09878/) (2025)
- [Enhancing Depression-Diagnosis-Oriented Chat with Psychological State Tracking](https://mlsanity.com/paper/2403.09717/) (2024)
- [A Generic Review of Integrating Artificial Intelligence in Cognitive Behavioral Therapy](https://mlsanity.com/paper/2407.19422/) (2024)
- [Does "Reasoning" with Large Language Models Improve Recognizing, Generating, and Reframing Unhelpful Thoughts?](https://mlsanity.com/paper/2504.00163/) (2025)
- [Responsible Evaluation of AI for Mental Health](https://mlsanity.com/paper/2602.00065/) (2026)
- [Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortion Detection](https://mlsanity.com/paper/2509.17292/) (2025)
- [Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation](https://mlsanity.com/paper/2511.01482/) (2025)
- [IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being](https://mlsanity.com/paper/2406.13791/) (2024)
- [CALLM: Understanding Cancer Survivors' Emotions and Intervention Opportunities via Mobile Diaries and Context-Aware Language Models](https://mlsanity.com/paper/2503.10707/) (2025)
- [When LLM Therapists Become Salespeople: Evaluating Large Language Models for Ethical Motivational Interviewing](https://mlsanity.com/paper/2503.23566/) (2025)
- [Signs of Struggle: Spotting Cognitive Distortions across Language and Register](https://mlsanity.com/paper/2508.20771/) (2025)
- [Assessing the Effectiveness of LLMs in Delivering Cognitive Behavioral Therapy](https://mlsanity.com/paper/2603.03862/) (2026)
- [Exploring Profiles of Cognitive Distortions Associated with Mental Health Disorders](https://mlsanity.com/paper/2605.24996/) (2026)

## Abstract (arXiv)

Mental illness remains one of the most critical public health issues of our time, due to the severe scarcity and accessibility limit of professionals. Psychotherapy requires high-level expertise to conduct deep, complex reasoning and analysis on the cognition modeling of the patients. In the era of Large Language Models, we believe it is the right time to develop AI assistance for computational psychotherapy. We study the task of cognitive distortion detection and propose the Diagnosis of Thought (DoT) prompting. DoT performs diagnosis on the patient's speech via three stages: subjectivity assessment to separate the facts and the thoughts; contrastive reasoning to elicit the reasoning processes supporting and contradicting the thoughts; and schema analysis to summarize the cognition schemas. The generated diagnosis rationales through the three stages are essential for assisting the professionals. Experiments demonstrate that DoT obtains significant improvements over ChatGPT for cognitive distortion detection, while generating high-quality rationales approved by human experts.