AI HeartBot to Increase Women's Awareness and Knowledge of Heart Attack: A Pilot Study (Preprint)

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Heart disease remains a leading cause of death for women in the United States, yet awareness and knowledge are declining. Artificial intelligence (AI) chatbots have great potential to educate women. Objective: To evaluate the potential efficacy of HeartBot to increase women’s awareness and knowledge of heart attack symptoms and care-seeking behavior. Methods: In this pilot, quasi-experimental study, 92 women aged 25 years or older without history of heart disease completed the HeartBot interaction via Short Message Service. The study was remotely conducted from October 2023 to January 2024. HeartBot, a fully automated AI chatbot, covered 15 topics of heart attack awareness, knowledge, symptoms, and care-seeking in a single session. The mean (SD) length of the HeartBot interaction was 13.0 (7.80) minutes. The primary outcomes consist of 4 questions on (1) recognizing signs and symptoms of a heart attack, (2) telling the difference between the signs and symptoms of a heart attack, (3) calling an ambulance or dialing 911 when experiencing heart attack symptoms, and (4) getting to an emergency room within 60 minutes after the onset of symptoms of a heart attack. Women were asked to answer the 4 questions before and after the HeartBot interaction on a scale of 1-4, with higher score indicating higher levels of awareness and knowledge of heart attack risks and symptoms. Results: The sample mean (SD) age was 45.9 (11.9) years. 55 (59.8%) of the sample represented racial/ethnic minorities. The mean (SD) length of the HeartBot interaction was 13.0 (7.80) minutes. In ordinal logistic regression models, women significantly increased in the 4 self-reported outcomes (i.e., heart attack symptoms, calling 911) even after controlling for potential confounding factors (adjusted odds ratio (AOR) = 7.10, 95% CI: 3.52-13.16 for outcome 1; AOR=5.47, 95% CI: 2.77-10.78 for outcome 2; AOR=5.75, 95% CI: 2.86-11.59 for outcome 3; AOR=2.85, 95% CI: 1.54-5.25 for outcome 4; p < 0.001 for all 4 outcomes). Conclusions: HeartBot led to a significant increase in awareness and knowledge of heart attack risks and symptoms in women. These findings suggest that HeartBot is a promising approach to improve heart health education. A randomized controlled trial of HeartBot is warranted to establish its efficacy and safety for the clinical setting.

This publication has 34 references indexed in Scilit: