Roles: UX Design, UX Research, Product Management
Tools: Figma
Timeframe: 26 hours
In the past year, 77% of health-related information was found from search engines like Google, Bing, or Yahoo. Of this group, only 13% of online health seekers visited specialized health information sites, and even less consulted sources with data validation or peer review. This poses a significant risk, as seen during the pandemic, where misinformation can have destructive consequences, impacting health, fostering political turmoil, and misrepresenting social movements. In a time marked by polarizing news and opinion-based content, the critical importance of relying on data-driven, peer-reviewed insights cannot be emphasized enough.
Varro is designed to tackle information reliability concerns by delivering expert-backed content in a user-friendly format. It functions as an AI-powered search engine, offering insights into relevant articles, bias, readability, and credibility based on the provided text.
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How do you typically search for health information online, and what influences your choice of sources?
What aspects of an article make you more likely or more interested in reading the text... length, complexity, author?
Can you share any frustrations or challenges you've faced in terms of reliability when searching for information online?
How do you feel about the integration of artificial intelligence in health research, and would you be more inclined to use such AI-powered tools for learning about health information?
Can you describe any pain points or challenges you've encountered when searching for health information online?
At the DubHacks hackathon, I conducted 6 usability tests with potential users from various backgrounds and experiences. When talking with the participants, I successfully pinpointed user needs regarding advancements in Varro's future, ultimately countering gaps in design, friction points, and bugs.
Our next steps involve implementing personalized user profiles, allowing for saving searches and bookmarking articles. This feature will assist future search results to align with user preferences in readability and citation/reference quantity. In addition, we plan to introduce metrics gauging article credibility, considering factors like the impact of the journal or the publication history of the author. These enhancements aim to provide users with a more personalized and informed research experience.