{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T19:35:10Z","timestamp":1786563310357,"version":"build-2736575974"},"reference-count":38,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Res Protoc"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Heart disease remains a leading cause of death for women in the United States. Despite this burden, awareness that heart disease is the leading cause of death among women declined from 65% in 2009 to 44% in 2019, with the largest declines observed among Hispanic, Black, and younger women. Thus, innovative, scalable, and cost-effective educational strategies are needed to improve women\u2019s awareness of heart attack symptoms and appropriate care-seeking behaviors.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to evaluate the short-term efficacy of the artificial intelligence (AI) HeartBot II, a chatbot-based educational intervention, in improving women\u2019s awareness and knowledge of heart attack symptoms and care-seeking behavior compared with a waitlist control group.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This randomized controlled clinical trial (RCT) with a waitlist control will enroll 200 women aged 25 or older, who will be randomized using a 1:1 allocation ratio. The intervention group will download the AI HeartBot II app and complete the 4 modules (including information on heart attack symptoms, risk factors, and calling 911) over 12 weeks. The waitlist control group will start receiving an identical intervention at 12 weeks. The primary outcomes will be change from baseline to 12 weeks in a 4-item heart attack response preparedness score, calculated as the mean of 4 self-reported items assessing confidence in recognizing signs and symptoms of a heart attack, distinguishing heart attack symptoms from other medical problems, calling 911 or an ambulance if a heart attack is suspected, and reaching an emergency room within 60 minutes of symptom onset. The primary analysis will estimate the intervention effect using constrained longitudinal data analysis implemented with linear mixed models, including fixed effects for time and time-by-treatment group interaction. Sensitivity analyses for the individual ordinal items will use ordinal logistic mixed-effects models.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n We received approval from the University of California, San Francisco, Institutional Review Board (No. 25\u201044825) on January 9, 2026, and this trial was registered on ClinicalTrials.gov (NCT07416734) on February 11, 2026, prior to enrollment of the first participant. Recruitment began in April 2026. As of manuscript submission, 86 participants were enrolled. Enrollment is expected to be completed by September 2026, and all follow-up assessments are anticipated to be completed by March 2027. Data analysis is expected to begin in spring 2027, with study results anticipated for publication later in 2027.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n To the best of our knowledge, this is the first RCT to rigorously evaluate the efficacy of the AI HeartBot II intervention. If effective, AI HeartBot II could provide a scalable, accessible, and cost-effective public health communication strategy to improve women\u2019s awareness of heart attack symptoms and promote timely care-seeking behaviors in the United States.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/103597","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T19:12:51Z","timestamp":1786561971000},"page":"e103597-e103597","source":"Crossref","is-referenced-by-count":0,"title":["Short-Term Efficacy of the Artificial Intelligence HeartBot II in Increasing Awareness and Knowledge of Heart Attack in Women: Protocol for a Randomized Controlled Trial With a Waitlist 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