ArticleJournal of medical Internet research2021
Patient Interactions With an Automated Conversational Agent Delivering Pretest Genetics Education: Descriptive Study.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 25 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.
Population Health Management Approaches to Increase Lung Cancer Screening in Community Health Centers - UG3 Pilot Clinical Trial
SAFE.AI: Developing and Testing an AI-based Hybrid Chatbot for Financial Empowerment in Rural Cancer Care
Who cites it
25 citing papers in PubMed.
- Importance of Prior Patient Interactions With the Healthcare System to Engaging With Pretest Cancer Genetic Services via Digital Health Tools Among Unaffected Primary Care Patients: Findings From the BRIDGE Trial.Health services research · 2026Trial
- Effectiveness of Al-Assisted Patient Health Education Using Voice Cloning and ChatGPT: Prospective Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Bridging Technology and Pretest Genetic Services: Quantitative Study of Chatbot Interaction Patterns, User Characteristics, and Genetic Testing Decisions.Journal of medical Internet research · 2025Trial
- Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility.BMC cancer · 2025Trial
- Uptake of Cancer Genetic Services for Chatbot vs Standard-of-Care Delivery Models: The BRIDGE Randomized Clinical Trial.JAMA network open · 2024Trial
- The Usability and Experience of Artificial Intelligence-Based Conversational Agents in Health Education for Cancer Patients: A Scoping Review.Journal of clinical nursing · 2026Article
- Metrics Used for the Evaluation of Chatbots Providing Cancer Genetic Risk Assessment and Education: Systematic Review.JMIR AI · 2026Review
- Engagement with a Chatbot-based Intervention for the delivery of mailed at-home COVID-19 Testing: a Descriptive Log Analysis Study from the SCALE-UP II Trial.medRxiv : the preprint server for health sciences · 2026Article
- A Chatbot to Meet Parents' Information Needs for Sickle Cell Trait Newborn Screening Results: Multiple Methods Formative Study.Journal of medical Internet research · 2026Article
- Genetic analysis of neurodegenerative diseases.The Journal of clinical investigation · 2026Review
- Cascade Chatbot: A Scalable Approach to Family-Based Genetic Testing for Hereditary Cancer Syndromes.JCO clinical cancer informatics · 2026Article
- Views on a Chatbot for Cancer Family History Collection among Leaders of Hispanic and Pacific Islander Communities in Utah.Public health genomics · 2026Article
- Implementation of AI in oncology: a systematic review of educational and clinical integration in global contexts.Frontiers in digital health · 2026Review
- Rethinking agency for genetic testing intention among Latinos: Determining predictors of intention for carrier screening and cancer predisposition testing.Genetics in medicine : official journal of the American College of Medical Genetics · 2025Article
- Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project.JMIR cancer · 2025Article
- User Engagement with A Multimodal Conversational Agent for Self-Care and Chronic Disease Management: A Retrospective Analysis.Journal of medical systems · 2025Article
- The ENGAGE study: evaluation of a conversational virtual agent that provides tailored pre-test genetic education to cancer patients.Journal of cancer survivorship : research and practice · 2025Article
- Strategies for Effective Public Health Communication in a Complex Information Environment.Annual review of public health · 2025Review
- Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study.Journal of medical Internet research · 2023Article
- Intentions of Patients With Cancer and Their Relatives to Use a Live Chat on Familial Cancer Risk: Results From a Cross-Sectional Web-Based Survey.Journal of medical Internet research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
Abstract
backgroundCancer genetic testing to assess an individual's cancer risk and to enable genomics-informed cancer treatment has grown exponentially in the past decade. Because of this continued growth and a shortage of health care workers, there is a need for automated strategies that provide high-quality genetics services to patients to reduce the clinical demand for genetics providers. Conversational agents have shown promise in managing mental health, pain, and other chronic conditions and are increasingly being used in cancer genetic services. However, research on how patients interact with these agents to satisfy their information needs is limited.
objectiveOur primary aim is to assess user interactions with a conversational agent for pretest genetics education.
methodsWe conducted a feasibility study of user interactions with a conversational agent who delivers pretest genetics education to primary care patients without cancer who are eligible for cancer genetic evaluation. The conversational agent provided scripted content similar to that delivered in a pretest genetic counseling visit for cancer genetic testing. Outside of a core set of information delivered to all patients, users were able to navigate within the chat to request additional content in their areas of interest. An artificial intelligence-based preprogrammed library was also established to allow users to ask open-ended questions to the conversational agent. Transcripts of the interactions were recorded. Here, we describe the information selected, time spent to complete the chat, and use of the open-ended question feature. Descriptive statistics were used for quantitative measures, and thematic analyses were used for qualitative responses.
resultsWe invited 103 patients to participate, of which 88.3% (91/103) were offered access to the conversational agent, 39% (36/91) started the chat, and 32% (30/91) completed the chat. Most users who completed the chat indicated that they wanted to continue with genetic testing (21/30, 70%), few were unsure (9/30, 30%), and no patient declined to move forward with testing. Those who decided to test spent an average of 10 (SD 2.57) minutes on the chat, selected an average of 1.87 (SD 1.2) additional pieces of information, and generally did not ask open-ended questions. Those who were unsure spent 4 more minutes on average (mean 14.1, SD 7.41; P=.03) on the chat, selected an average of 3.67 (SD 2.9) additional pieces of information, and asked at least one open-ended question.
conclusionsThe pretest chat provided enough information for most patients to decide on cancer genetic testing, as indicated by the small number of open-ended questions. A subset of participants were still unsure about receiving genetic testing and may require additional education or interpersonal support before making a testing decision. Conversational agents have the potential to become a scalable alternative for pretest genetics education, reducing the clinical demand on genetics providers.
Indexed as
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.