Empowering Psychotherapy with Large Language Models: Cognitive Distortion Detection through Diagnosis of Thought Prompting (2023)

Abstract: 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.

## introduction about one in eight people worldwide suffer from mental disorders @xcite . however, such mental health conditions are severely underserved, due to a number of reasons including the scarcity of mental health professionals, poor quality of services, unaffordable cost, and social stigma @xcite . treatment coverage for mental health service use ranges from 33% in highincome locations to only 8% in low-and lower middle-income countries @xcite . a recent study from the american psychological association (apa) 1 found that six in ten psychologists "no longer have openings for new patients." to mitigate such situations, there have been consistent efforts on developing automated systems for mental health support, such as sentiment analysis @xcite and empathetic chatbots @xcite @xcite . however, existing works mostly take shallow attempts in a heuristic manner, e.g., analyzing emotions and generating comforting responses. there is still a significant gap for such systems to contribute to real professional psychotherapy, which requires deep studies of the patient's thinking patterns, the establishment of cognition models, and the methods to reconstruct the cognition models. these procedures constitute the core pillars in common classic therapy paradigms like cognitive-behavior therapy (cbt) @xcite @xcite and acceptance and commitment therapy (act) @xcite . most data sources recording the interactions between the patients and licensed professionals are confidential, making it even more challenging to build professional assistance for psychotherapy. recent progress in large language model (llm) development uncovers its astonishing ability in various textual reasoning tasks in zero-shot setting @xcite @xcite . for the psychology domain, chat-gpt and gpt-4 present very promising performance in the classic sally-anne test @xcite , evaluating the basic theory of mind capabilities to attribute mental states such as beliefs, emotions, desires, etc. we believe it is promising to further exploit such ability to complex mental reasoning and analysis. it is the right time to start developing professional, targeted, and systematic ai assistance for psychotherapy. in this paper, we take the first step by studying the task of cognitive distortion detection, the first core procedure in cognitive behavior therapy (cbt) @xcite . inspired by how psychother- cognitive distortion type interpretation example distorted speech personalization personalizing or taking up the blame for a situation, that in reality involved many factors and was out of the person's control. my son is pretty quiet today. i wonder what i did to upset him. mind reading suspecting what others are thinking or what are the motivations behind their actions. my house was dirty when my friends came over, they must think i'm a slob! all-or-nothing thinking looking at a situation as either black or white or thinking that there are only two possible outcomes to a situation. if i cannot get my ph.d., then i am a total failure. ## cognitive distortion detection cognitive behavior therapy (cbt) is a wellestablished therapy paradigm primarily on depression and anxiety disorders @xcite . in cbt, given the patients' speech or written content, we establish the cognitive model by building the interactions among the situations, thoughts, and emotions. patients with mental disorders, such as depression or anxiety, tend to form negative thoughts very rapidly and unconsciously, leading to negative emotions which further strengthen their overall negative views and beliefs about the world. to break this vicious circle, in a typical cbt process, the first core step is to identify those mal-adaptive negative thoughts and summarize their underlying schemas, formally known as cognitive distortions. there are generally 10-20 common, wellstudied types of cognitive distortions. we present a few types with examples in in the real psychotherapy process, there's a significant amount of textual information including therapeutic conversations and diaries, etc. such information is often long, highly fragmented, and disorganized, containing multiple types of distortions beyond the toy examples in ## the diagnosis of thought prompting on discussing with psychotherapy professionals, we identify the following key stages to diagnose the patient's speech to detect cognitive distortions. subjectivity assessment. the patient's speech consists of a mixture of reality (objective facts) and interpretations/opinions (subjective thoughts). in order to perform deep analysis of distorted thinking, we first need to find out which parts of the speech are objective facts and which parts are subjective thoughts. after such an assessment, we summa-patient speech: … my advisor was quiet in our meeting today, i must have done something wrong… objective facts: the advisor was quiet in the meeting with the speaker today. ## related work due to the verbal and textual nature of psychotherapy procedures, there have been consistent efforts to employ nlp techniques to assist the mental health domain @xcite @xcite . however, with the knowledge gap between the two communities, most existing works take shallow attempts without deep investigation of the professional psychotherapy knowledge. a majority of the previous studies targets identification of common mental health issues, such as depression and anxiety, from textual contents @xcite @xcite @xcite . another major category of works study therapeutic conversations with a focus on emotional/empathetic supports @xcite @xcite , and discourse structures @xcite . a few more recent works have started to investigate deeper professional psychotherapy knowledge, e.g., cognitive distortion detection in cbt @xcite @xcite , identifying and reframing unhelpful thoughts @xcite . early famous system eliza foot_5 took the initial attempts to emulate a rogerian psychotherapist. due to its rule-based nature, the responses are often reflections or rephrasings of the user's statements. if users deviate too much from expected inputs or probe its capabilities, the program may produce irrelevant or nonsensical responses. recent progress in large language model reveals that chatgpt and gpt-4 present very promising performance in the classic sally-anne test @xcite , evaluating the basic theory of mind capabilities to attribute mental states such as beliefs, emotions, desires, etc. however, latter works also point out the robustness issue of such ability @xcite . in our work, we are inspired by such enhanced ability and investigate the application of diagnosing patients' thoughts in psychotherapy. our experiments on the real dataset, not anecdotal examples, show very promising performance both in auto-matic and human expert evaluation. we believe it is a very important future research direction to investigate the general cognitive abilities of llm and make connections to the field of psychology and cognitive science. theory-wise, we are eager to explore to what extent the llm can simulate the human cognitive functions, so as to determine the role that language plays in the overall human cognition. application-wise, a straightforward and encouraging direction should be the integration for assisting mental health treatment, as the motivation and goal of this work. ## conclusion and future work this work delved into the integration of large language models (llms) within the realm of psychotherapy. we introduced the diagnosis of thought (dot) framework, which strategically prompts the llm to produce diagnosis rationales pertinent to the detection of cognitive distortions. we believe that there exists substantial potential for leveraging llms within numerous facets of mental health support that are currently under-explored. our findings, thus, not only illuminate a path towards more efficient therapy methods but also open doors for future investigations to push the boundaries of ai's role in mental health treatment. in the domain of ai-enhanced psychotherapy, particularly when harnessing the power of llms, there are paramount challenges surrounding safety, robustness, and ethical responsibilities. llm is known to generate hallucinations and biases. while one potential usage of our system is to serve as a self-diagnosing/assisting tool for patients, e.g., to help the patients to recognize their own thinking patterns and learn how the cognitive distortions developed, such tools should not be deployed for direct patient use without the supervision of professionals. as we navigate the potential of llm in psychotherapy, our foremost priority should remain in building systems that are safe and responsible. concurrently, the formulation of robust ethical guidelines tailored to this new era becomes indispensable.