A chatbot for hypertension self-management support: user-centered design, development, and usability testing

Author:

Griffin Ashley C12ORCID,Khairat Saif34ORCID,Bailey Stacy C5,Chung Arlene E6

Affiliation:

1. VA Palo Alto Health Care System , Palo Alto, CA 94025, United States

2. Department of Health Policy, Stanford University School of Medicine , Stanford, CA 94305, United States

3. Carolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC) , Chapel Hill, NC 27599, United States

4. School of Nursing, UNC , Chapel Hill, NC 27599, United States

5. Division of General Internal Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University , Chicago, IL 60611, United States

6. Department of Biostatistics & Bioinformatics, Duke School of Medicine , Durham, NC 27710, United States

Abstract

Abstract Objectives Health-related chatbots have demonstrated early promise for improving self-management behaviors but have seldomly been utilized for hypertension. This research focused on the design, development, and usability evaluation of a chatbot for hypertension self-management, called “Medicagent.” Materials and Methods A user-centered design process was used to iteratively design and develop a text-based chatbot using Google Cloud’s Dialogflow natural language understanding platform. Then, usability testing sessions were conducted among patients with hypertension. Each session was comprised of: (1) background questionnaires, (2) 10 representative tasks within Medicagent, (3) System Usability Scale (SUS) questionnaire, and (4) a brief semi-structured interview. Sessions were video and audio recorded using Zoom. Qualitative and quantitative analyses were used to assess effectiveness, efficiency, and satisfaction of the chatbot. Results Participants (n = 10) completed nearly all tasks (98%, 98/100) and spent an average of 18 min (SD = 10 min) interacting with Medicagent. Only 11 (8.6%) utterances were not successfully mapped to an intent. Medicagent achieved a mean SUS score of 78.8/100, which demonstrated acceptable usability. Several participants had difficulties navigating the conversational interface without menu and back buttons, felt additional information would be useful for redirection when utterances were not recognized, and desired a health professional persona within the chatbot. Discussion The text-based chatbot was viewed favorably for assisting with blood pressure and medication-related tasks and had good usability. Conclusion Flexibility of interaction styles, handling unrecognized utterances gracefully, and having a credible persona were highlighted as design components that may further enrich the user experience of chatbots for hypertension self-management.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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