Conversations surrounding food neutrality and positivity have become important factors in body neutrality and positivity. We’ve done our research, and it is no surprise to see that virtual messaging and communication systems have become an integral part of this movement.

  • “Nutritional interventions for adolescents using information and communication technologies (ICTs): A systematic review” link
  • “Adolescents’ Perspectives on Using Technology for Health: Qualitative Study” link

As discussed in the links above, technology has played an important role in improving nutritional well-being, and therefore, body perception in adolescents; chat bots are no exception to this statement. But how, might you ask, a chat bot incorporate the edge of working with a professional while giving user’s the most of their experience? …Much like a human! The following sources target strategies the team studied throughout the design and development of the ultimate food/body neutrality/positivity chatbot: BalanceBot!

  • “The Meaning and Factors That Influence the Concept of Body Image: Systematic Review and Meta-Ethnography from the Perspectives of Adolescents” link
  • “Preventing Nutritional Disorders in Adolescents by Encouraging a Healthy Relationship With Food” link

What it does

BalanceBot is a chatbot made to promote food and body neutrality/positivity amongst adolescents.

How we built it

Metadata doesn’t always meet the bar; when it comes to taking care of ourselves, we want quality care solutions that make us feel heard. That’s where BalanceBot comes in.

Over the course of the weekend, the team qualitatively interviewed two healthcare professionals to receive feedback on how to best structure a chatbot that can foster healthy conversation surrounding food and the body. While the identities of candidates reviewed will remain anonymous, both candidates agreed to have their credentials documented: Psychologist with 13 years of experience working with patients; graduated with a PhD in Depth Psychotherapy and a Master’s in Clinical Psychology, and has had experience running chatlines. 6 months of experience working as a therapist; current PhD student in Political Science and current Master’s student in Counseling Psychology.

Due to limited datasets involving such topics, working with trained professionals gave the team a sufficient amount of data and a newfound understanding of how to provide support to users.

By translating information collected from qualitative interviews into quantitative results, the team extrapolated nearly 250 data points utilized for training a chat bot using the chatterbot, pandas, and tkinter libraries in Python. In doing so, the team provided a lightweight, fast technological solution to allow for user access to support and resources in times of need.

Challenges we ran into

NOT ENOUGH DATA? Don’t fear! Our solution? The team coordinated and conducted qualitative interviews with trained professionals within 24 hours to extrapolate nearly 250 data points for chat bot.

Accomplishments that we're proud of && What we Learned

  • First time designing and developing a chat bot!!
  • Conducting a literature review to give a better perspective toward creating something technological in this design space.
  • Developed project in areas with little available dataset, instead worked to interview and generate credible ideas.
  • Worked with healthcare professionals to discuss important factors in creating such technological solutions, and collected data crucial to training such a chat bot.
  • MOST IMPORTANTLY, through BalanceBot, fostering a safe and loving community for those who need support.


We would like to acknowledge and formally thank Cynthia Le for designing the UI/UX experience utilized in our project. Cynthia is also a 4th year student at UC Irvine majoring in psychology. Upon graduation, she intends to pursue a career in user research, product design, or UI/UX design. Her expertise is greatly appreciated, and several of her notes are additionally documented below.

“Based on descriptions provided by: Cool colors overall are more calming than warm. Pastels are gentler on the eyes, and the fact that they are lighter shades tends to evoke more happiness. Blue is often used in health-related settings. Based on the site associations regarding light blue, the promotion of health provided by the bot nicely aligns with them. As for the dark blue, it was meant to be related with the knowledge that the service will provide. Green is mostly attributed to growth and rejuvenation, which is what we hope users will feel after messaging the chatbot.”

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