KR-20260064468-A - METHOD AND SYSTEM FOR PROVIDING COGNITIVE BEHAVIORAL THERAPY PROGRAM BASED ON LARGE LANGUAGE MODEL

KR20260064468AKR 20260064468 AKR20260064468 AKR 20260064468AKR-20260064468-A

Abstract

A method for providing a cognitive behavioral therapy program based on a large language model according to the present invention may include the steps of: providing at least one survey related to cognitive behavioral therapy to a user terminal; generating a prompt to be input into a large language model using response data for the survey received from the user terminal; inputting the prompt into the large language model and generating feedback related to a treatment program for cognitive behavioral therapy based on natural language response data included in the response data; updating the prompt based on the generated feedback and inputting it into the large language model, and updating the treatment program through the large language model; and providing the updated treatment program to the user terminal.

Inventors

최치현
윤찬

Assignees

에버엑스 주식회사

Dates

Publication Date: 20260507
Application Date: 20250612
Priority Date: 20241030

Claims (12)

A step of providing at least one questionnaire related to cognitive behavioral therapy to a user terminal; A step of generating a prompt to be input into a large language model using response data to the survey received from the user terminal; A step of inputting the above prompt into the above large language model to generate feedback related to the treatment program for cognitive behavioral therapy based on natural language response data included in the above response data; A step of updating the prompt based on the generated feedback, inputting it into the large language model, and updating the treatment program through the large language model; and A method for providing a large language model-based cognitive behavioral therapy program characterized by including the step of providing the updated treatment program to the user terminal.
In paragraph 1, The step of generating the above prompt is, A step of extracting multiple natural language response data from the response data for the above survey; A step of analyzing the emotion type corresponding to each of the plurality of natural language response data and grouping the natural language response data corresponding to the same emotion type among the plurality of natural language response data; and A method for providing a large language model-based cognitive behavioral therapy program, characterized by including the step of generating multiple different prompts to be input into the large language model based on each of a multiple natural language response data group corresponding to different emotion types.
In paragraph 2, The above plurality of natural language response data groups are, A first type natural language response data group comprising at least one natural language response data corresponding to a first sentiment type among the plurality of natural language response data above, and A method for providing a large language model-based cognitive behavioral therapy program characterized by including at least one of at least one group of second type natural language response data, which includes at least one natural language response data corresponding to a second emotion type among the plurality of natural language response data.
In paragraph 3, The step of generating the above-mentioned multiple different prompts is, Generate multiple prompts corresponding to each of the multiple natural language response data groups corresponding to the above different emotion types, and The above plurality of prompts are, A method for providing a large language model-based cognitive behavioral therapy program characterized by including at least one of a first type prompt associated with the first type natural language response data group and a second type prompt associated with the second type natural language response data group.
In paragraph 4, Multiple treatment programs corresponding to different topics are matched and stored in the database, and In the above user terminal, According to the treatment week set in a specific treatment program related to the user's cognitive behavioral therapy among the plurality of treatment programs mentioned above, a plurality of treatment contents constituting the specific treatment program are provided sequentially, and The step of generating the above feedback is, A method for providing a large language model-based cognitive behavioral therapy program characterized by inputting at least one of the first type prompt and the second type prompt into the large language model to generate feedback for the specific therapy program through the large language model.
In paragraph 5, The above feedback is, It includes at least one of a first type feedback corresponding to the first type prompt and a second type feedback corresponding to the second type prompt. Each of the above-mentioned first type feedback and the above-mentioned second type feedback is, A method for providing a large language model-based cognitive behavioral therapy program characterized by including different types of update information for the specific therapy program mentioned above.
In paragraph 6, The step of updating the above treatment program is, A method for providing a large language model-based cognitive behavioral therapy program, characterized by updating information related to at least one of the treatment weeks in which each of the plurality of treatment contents is provided, based on the different types of update information for the specific treatment program.
In paragraph 1, The above at least one survey is, A multiple-choice questionnaire consisting of at least one multiple-choice question item related to the above-mentioned cognitive behavioral therapy and a plurality of selection items corresponding to the above-mentioned multiple-choice question item, and A method for providing a large language model-based cognitive behavioral therapy program, characterized by including at least one open-ended questionnaire capable of receiving natural language input for at least one open-ended question item from the user terminal in relation to the above cognitive behavioral therapy.
In paragraph 8, The above response data is, It includes at least one of the objective survey response data for the above objective survey and the subjective survey response data for the above subjective survey, and The above multiple-choice survey response data is, It includes the natural language response data corresponding to a specific selection item selected by user input among the plurality of selection items above, and The above open-ended survey response data is, The above natural language input and for the above subjective query items A method for providing a large language model-based cognitive behavioral therapy program, characterized by processing the above natural language input as an input to the large language model and including the above natural language response data corresponding to at least one of the natural language answers obtained through the large language model.
In paragraph 1, A step of predicting the emotional patterns of a user subject to cognitive behavioral therapy using the above-mentioned large language model, and The method further includes the step of providing notification information to the user terminal that includes prediction information corresponding to the emotion pattern according to the predicted emotion pattern. The step of predicting the emotional pattern of the user mentioned above is, A step of generating a prediction prompt for predicting the emotion pattern using at least one of the response data to the above survey, the above feedback, and user information collected from the database; and A method for providing a large language model-based cognitive behavioral therapy program, characterized by including the step of processing the above prediction prompt as input to the large language model and generating the above prediction information of a type corresponding to the above emotion pattern through the large language model.
It includes a communication unit that provides at least one survey related to cognitive behavioral therapy to a user terminal, and a control unit that generates a prompt to be input into a large language model using response data for the survey received from the user terminal. The above control unit is, Input the above prompt into the above large language model to generate feedback related to the treatment program for cognitive behavioral therapy based on the natural language response data included in the above response data, and Based on the generated feedback, the prompt is updated and input into the large language model, and the treatment program is updated through the large language model, and A large language model-based cognitive behavioral therapy program providing system characterized by providing the updated treatment program to the user terminal.
It is executed by one or more processes on an electronic device and can be read by a computer. As a program stored on an existing recording medium, The above program is, A step of providing at least one questionnaire related to cognitive behavioral therapy to a user terminal; A step of generating a prompt to be input into a large language model using response data to the survey received from the user terminal; A step of inputting the above prompt into the above large language model to generate feedback related to the treatment program for cognitive behavioral therapy based on natural language response data included in the above response data; A step of updating the prompt based on the generated feedback, inputting it into the large language model, and updating the treatment program through the large language model; and A program stored on a computer-readable recording medium characterized by including instructions that perform the step of providing the updated treatment program to the user terminal.

Description

Method and System for Providing Cognitive Behavioral Therapy Program Based on a Large Language Model The present invention relates to a method and system for providing a Cognitive Behavioral Therapy (CBT) program based on a large language model. With the rapid advancement of artificial intelligence (AI) technology in recent years, generative AI models capable of natural conversation with humans (e.g., ChatGPT) have emerged. In particular, unlike existing chatbots, Large Language Models (LLMs) provide conversational quality similar to humans based on their ability to understand various contexts and generate natural language, and are being rapidly adopted in various industrial fields such as medical, education, and healthcare. In particular, along with the advancement of artificial intelligence (AI) technology, the utilization of AI in the medical industry is rapidly expanding. For example, there is growing interest in AI technology that uses large language models to provide customized cognitive behavioral therapy programs remotely to patients who require such therapy. Cognitive Behavioral Therapy (CBT) can be understood as a psychotherapy method based on the premise that a person's thoughts, emotions, and behaviors are closely interconnected. It involves patients recognizing their own emotions, identifying faulty thoughts, and changing problematic behaviors during the treatment process. Recently, as the effectiveness of cognitive behavioral therapy has been scientifically proven, the use of the therapy for mental health problems such as depression, anxiety, insomnia, and pain is gradually increasing, leading to active research on methods to provide the therapy to patients. However, since such cognitive behavioral therapy requires continuous treatment, the fact that patients must visit the hospital frequently poses a significant burden. Consequently, there is growing interest in artificial intelligence technology that provides customized cognitive behavioral therapy programs remotely to patients who require such therapy. In such non-face-to-face cognitive behavioral therapy, it is essential to provide a customized program that takes into account the user's current condition. If a treatment program is provided uniformly without considering the user's current state and medical history, it may hinder therapeutic effectiveness or even worsen symptoms. Furthermore, users may be unable to engage with content irrelevant to their condition and are more likely to drop out early, which can significantly lower treatment retention rates and overall satisfaction. There is a need to address these issues with non-face-to-face cognitive behavioral therapy and to provide user-customized cognitive behavioral therapy programs. FIG. 1 is a conceptual diagram illustrating a large language model-based cognitive behavioral therapy program providing system according to the present invention. FIG. 2 is a flowchart for explaining, in general, a method for providing a large language model-based cognitive behavioral therapy program according to the present invention. FIGS. 3a and FIGS. 3b are conceptual diagrams for specifically explaining a survey provided to a user terminal according to the present invention. FIG. 4a is a conceptual diagram illustrating the process of extracting natural language response data from response data to a survey according to the present invention. FIG. 4b is a conceptual diagram for explaining the process of generating a natural language response data group based on the sentiment type corresponding to the natural language response data according to the present invention. FIG. 4c is a conceptual diagram illustrating the process of generating a prompt to be input into a large language model using natural language response data and user information according to the present invention. FIG. 5a is a conceptual diagram illustrating a cognitive behavioral therapy program according to the present invention. FIG. 5b is a conceptual diagram illustrating the process of generating feedback related to cognitive behavioral therapy using a large language model according to the present invention. FIGS. 6a and 6b are conceptual diagrams illustrating the process of updating a cognitive behavioral therapy program based on feedback according to the present invention and providing the updated therapy program to a user terminal. FIG. 7 is a conceptual diagram illustrating the process of predicting a user's emotional pattern according to the present invention and providing notification information corresponding to the predicted emotional pattern to a user terminal. Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Identical or similar components are assigned the same reference number regardless of the drawing symbols, and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are as