AI Article Synopsis

  • Obesity is a global health issue with various interconnected causes, prompting the need for innovative solutions like chatbots to gather relevant data.
  • A user-centered design approach involving 52 wireframes and expert input led to the development of a Telegram chatbot, Wakamola, aimed at understanding obesity's personal and social factors.
  • A pilot study involving 85 volunteers revealed insights on participants' diet, physical activity, and social networks, indicating a mostly healthy population with no obesity cases found.

Article Abstract

Background: Obesity 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.

Objective: This 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.

Methods: We 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.

Results: We 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 (normal weight). The most consumed foods were olive oil, milk and derivatives, cereals, vegetables, and fruits. People walked 10 minutes on 5.8 days per week, slept 7.02 hours per day, and were sitting 30.57 hours per week. Moreover, we were able to create a social network with 74 users, 178 relations, and 12 communities.

Conclusions: The 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087340PMC
http://dx.doi.org/10.2196/17503DOI Listing

Publication Analysis

Top Keywords

overweight obesity
16
social network
16
physical activity
12
chatbot wakamola
8
collect linked
8
linked data
8
data population
8
pilot study
8
individual social
8
sociodemographics diet
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!