NCT06801925|Enrolling By Invitation
Evaluating the Effectiveness and Acceptability of a GPT-4o and RAG-Based Voice Chatbot for Depression Screening Using PHQ-9
GPT4-RAG-PHQ
Loading search results
GPT4-RAG-PHQ
Sponsor study identifier
Secondary identifiers
OTHER · UCL Research Ethics Committee
observational
100
1 country
1
Study Start
February 1, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Primary Completion
March 31, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Study Completion
May 31, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
This study aims to assess the feasibility and acceptability of a voice-based chatbot, powered by GPT-4o and Retrieval-Augmented Generation (RAG), for conducting depression screening using the Patient Health Questionnaire-9 (PHQ-9). The PHQ-9 is a validated self-report instrument widely used to screen, diagnose, and monitor the severity of depression. It consists of nine questions that correspond to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for major depressive disorder. Respondents rate the frequency of symptoms experienced over the past two weeks on a scale from 0 ("not at all") to 3 ("nearly every day"). The total score (ranging from 0 to 27) indicates the severity of depressive symptoms, categorized into minimal, mild, moderate, moderately severe, or severe depression. The PHQ-9 is also used to assess functional impairment and guide treatment decisions in clinical and research settings. The voice-based chatbot integrates GPT-4o, with RAG to enhance its ability to provide informed and contextualized responses during interactions. GPT-4o serves as the conversational engine, capable of generating human-like, empathetic, and contextually appropriate dialogue. RAG, on the other hand, enables the chatbot to retrieve and incorporate external, up-to-date knowledge from a curated database or knowledge repository, ensuring the accuracy and reliability of its responses.
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
May 31, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Click on a node to explore related trials.
Some registry-reported names shown below are not yet linked in this graph.
Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
January 24, 2025
Actual (reported)January 30, 2025
Actual (reported)February 1, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
March 31, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
May 31, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Feasibility and Acceptability of the GPT-4o and RAG Voice Chatbot
Participants' perceptions of the chatbot's feasibility, acceptability, and effectiveness are assessed through semi-structured interviews conducted after the interaction session. These interviews explore themes such as the chatbot's empathy, usability, and the overall user experience.
Interviews are conducted immediately following the chatbot interaction.
Accuracy of PHQ-9 Scoring by the Chatbot
Measured immediately after the interaction session, once the chatbot has generated PHQ-9 scores
This study involves the use of a voice-based chatbot powered by GPT-4o and Retrieval-Augmented Generation (RAG) to conduct depression screening using the Patient Health Questionnaire-9 (PHQ-9). The chatbot aims to evaluate the feasibility and acceptability of using AI-powered conversational tools for mental health screening. Participants interact with the chatbot in a single session, answering PHQ-9 questions and receiving responses generated using GPT-4o and RAG technologies.
Registry-reported names are shown in full. Names without a link have not yet been matched to a Syfrah profile.
The study population consists of healthy individuals aged 18 to 65 years who do not have severe mental illnesses. We welcome participants who have an interest in artificial intelligence technologies. Recruitment will be conducted both online and offline. Participants will engage with a sophisticated AI chatbot designed to simulate a consultation with a mental health professional. This interaction enables them to complete a psychometric evaluation, such as the PHQ-9 test, in a structured yet conversational manner. Unlike conventional online versions of the PHQ-9 test, the chatbot offers enhanced interactivity. For individuals who may experience difficulties in articulating or summarizing their responses, the chatbot provides clarifications and assistance using a comprehensive language model. After the assessment, participants will receive an interpretation of their test results along with tailored advice, delivered in accordance with established mental health guidelines.
UCL Institute of Health Informatics
London, NW1 2DA, United Kingdom
Guo Z, Lai A, Ive J, Petcu A, Wang Y, Qi L, Thygesen JH, Li K. Feasibility and user evaluation of HopeBot: An LLM-powered conversational chatbot for depression screening. PLOS Digit Health. 2026 Jun 25;5(6):e0001446. doi: 10.1371/journal.pdig.0001446. eCollection 2026 Jun.
Kezhi Li
University College, London
First Submitted
January 24, 2025
First Posted
January 30, 2025
Study Start
February 1, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Primary Completion
March 31, 2025
Estimated (date passed)PERSONAE - a Personalized Online Treatment of Depression
Contact the study team to confirm eligibility.
This estimate has passed. The registry has not confirmed an actual date for this milestone.
Study Completion
May 31, 2025
Estimated (date passed)This estimate has passed. The registry has not confirmed an actual date for this milestone.
Last Updated
January 30, 2025
Record last verified: 2025-01
IPD will not be shared to ensure participant confidentiality and comply with ethical guidelines related to mental health research. Additionally, participants did not provide explicit consent for data sharing with external researchers.
Download the complete ClinicalTrials.gov record imported by Syfrah, including fields not shown in this page. The registry may contain a newer revision.
Source: ClinicalTrials.gov.
JSON downloads include source attribution and retrieval details alongside the unchanged original record or the separately normalized values.
Source retrieved: