How can AI can make online health information easier to understand?
In the United States today, around 93% of adults have online access, and about 80% of those go online seeking health-related information. However, low health literacy in the U.S. means that even well-intentioned educational materials may remain opaque or overwhelming to users.
Anjana Susarla the Omura-Saxena Professor in Responsible AI in the Michigan State University Eli Broad College of Business, recently co-authored a study funded by the National Institutes of Health, or NIH, that developed an automated method to evaluate how understandable patient-education videos are for people seeking information on diabetes.
The findings expose gaps in user engagement and comprehension and point toward how health systems and content creators might adopt evidence-based digital health strategies to make information more accessible and behaviorally persuasive.
Below, Susarla shares details about the findings and how artificial intelligence can improve health communication and digital literacy for patients seeking care information online.
Why is health literacy such a critical issue today, and what role do online videos play in shaping people’s health decisions?
It is estimated that almost 80% of the U.S. adult population seeks online health information. YouTube, the largest video-sharing social media platform, hosts more than 100 million videos providing information on various medical conditions and has become a major source of health information in the U.S. and worldwide.
At the same time, only 12% of adults in the United States are considered proficient in their ability to meaningfully interpret health information. People searching for health information on digital media platforms do not always have the requisite health literacy to understand and interpret health information.
Our research aims to address that gap in developing AI-augmented methods to retrieve understandable and relevant video-based health education content.
What motivated you and your colleagues to focus on diabetes videos on YouTube as the test case for this study?
Diabetes is among the most prevalent chronic conditions in the United States and many other parts of the world. More than 100 million U.S. adults are now living with diabetes or prediabetes, according to the Centers for Disease Control and Prevention’s 2020 report. Diabetes is a contributing factor to many other serious health conditions, such as heart disease, stroke, nerve and kidney diseases, and vision loss.
Your study discusses a “human-in-the-loop” approach, where AI works alongside human experts rather than replacing them. Can you explain how this collaboration between AI and medical professionals works in practice and why it was essential for evaluating health video content?
Evaluating health information in online videos is a multifaceted problem where we needed to incorporate evidence-based guidelines from health literacy and patient education (which are designed for small group-based focus studies, etc.). However, there are thousands (or hundreds of thousands) of videos on each medical condition on online platforms.
So, any method used to automate the classification of videos also needs to be scalable. Using AI methods is a good way to achieve scale. At the same time, cutting-edge AI algorithms need vast amounts of training data. In our case, we needed expert input from patient education experts to label the video, so it became prohibitively expensive to create very large training datasets.
We overcame that problem by combining a human-in-the-loop approach, where we can incorporate domain experts’ assessment when the results from machine learning models were insufficient.
Your findings showed that more understandable videos receive more views, likes and comments. What does this tell us about how patients engage with health information?
Our results highlight that patients have different health information needs. With the vast amount of health information available in multimedia formats on social media platforms such as YouTube and Facebook, billions of people across the globe are accessing health care information via social media without any way to verify the accuracy, understandability or relevance of the content. Our study offers a path to curate online health information using multiple criteria to meet the health literacy needs of a diverse population.
How can health care providers or organizations use your research to create more effective educational materials for patients?
Our results can help health care organizations tailor education materials to enable patient education and empowerment and thereby increase adherence and self-care.
Looking ahead, how could your approach be expanded to other health conditions beyond diabetes?
Well-designed patient education videos can be part of a holistic system of care encompassing disease prevention and lifestyle changes, along with resources for emotional support, better patient-physician interactions, and providing current and scientifically valid medical information to patients. The methods and principles we developed could be adapted to other chronic, acute and infectious health conditions, such as cardiovascular disease and cancer, and to broader patient education contexts, such as medication adherence and patient safety.