ArticleJMIR medical informatics2021
A User-Centered Chatbot (Wakamola) to Collect Linked Data in Population Networks to Support Studies of Overweight and Obesity Causes: Design and Pilot Study.
Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A community-based programme to reduce non-communicable disease risk among persons living in disadvantaged neighbourhoods in three European countries: protocol for a controlled trial.BMC public health · 2026Article
- The Intersection of ChatGPT, Clinical Medicine, and Medical Education.JMIR medical education · 2023Article
- An Overview of Chatbot-Based Mobile Mental Health Apps: Insights From App Description and User Reviews.JMIR mHealth and uHealth · 2023Article
- iCHECK-DH: Guidelines and Checklist for the Reporting on Digital Health Implementations.Journal of medical Internet research · 2023Article
- Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.Frontiers in artificial intelligence · 2023Review
- The Use of Artificial Intelligence-Based Conversational Agents (Chatbots) for Weight Loss: Scoping Review and Practical Recommendations.JMIR medical informatics · 2022Article
- SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management: System Design and Finding.Frontiers in nutrition · 2022Article
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Authors and funding
12 authors.
Funding
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Abstract
backgroundObesity and overweight are a serious health problem worldwide with multiple and connected causes. Simultaneously, chatbots are becoming increasingly popular as a way to interact with users in mobile health apps.
objectiveThis study reports the user-centered design and feasibility study of a chatbot to collect linked data to support the study of individual and social overweight and obesity causes in populations.
methodsWe first studied the users' needs and gathered users' graphical preferences through an open survey on 52 wireframes designed by 150 design students; it also included questions about sociodemographics, diet and activity habits, the need for overweight and obesity apps, and desired functionality. We also interviewed an expert panel. We then designed and developed a chatbot. Finally, we conducted a pilot study to test feasibility.
resultsWe collected 452 answers to the survey and interviewed 4 specialists. Based on this research, we developed a Telegram chatbot named Wakamola structured in six sections: personal, diet, physical activity, social network, user's status score, and project information. We defined a user's status score as a normalized sum (0-100) of scores about diet (frequency of eating 50 foods), physical activity, BMI, and social network. We performed a pilot to evaluate the chatbot implementation among 85 healthy volunteers. Of 74 participants who completed all sections, we found 8 underweight people (11%), 5 overweight people (7%), and no obesity cases. The mean BMI was 21.4 kg/m
conclusionsThe Telegram chatbot Wakamola is a feasible tool to collect data from a population about sociodemographics, diet patterns, physical activity, BMI, and specific diseases. Besides, the chatbot allows the connection of users in a social network to study overweight and obesity causes from both individual and social perspectives.
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