| Summary: | Diet quality monitoring in Guatemala has evolved significantly since 2023, placing participants at the center and emphasizing their interaction with accessible digital tools. Within this process, MEMO, a chatbot developed for high-frequency data collection, has served as a key mechanism to facilitate participation, learning, and near–real-time data generation. Throughout its implementation, the monitoring system has integrated Human-Centered Design (HCD) principles to adapt the tool to users’ needs, capacities, and local contexts, strengthening trust, understanding, and sustained engagement.
The data collected are analyzed and processed using machine learning techniques, enabling the transformation of raw information into simplified and actionable insights that are returned to both participants and local partners. This feedback loop supports informed decision-making at community and institutional levels. Currently, the results are publicly available on the SINTET platform, managed by the local partner CUNORI, ensuring open access to information for anyone interested in diet quality and food security.
This progress represents an important milestone for Guatemala, demonstrating how the integrated use of digital tools, participatory approaches, and a strong network of local partners can lead to a scalable system that complements traditional food and nutrition security monitoring mechanisms in the country.
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