For many patients, the process of exploring clinical trials begins with searching for information online. This early-stage content—study description, eligibility criteria, and study plan details—is often the first meaningful interaction a patient has with a study.
At this point, patients are not deciding whether to enroll. They are trying to answer a simpler question: Is this relevant to me?
However, the information they encounter is often difficult to interpret. Study descriptions are written in technical language, eligibility criteria are structured in complex formats, and key details are not always easy to identify. Research shows that nearly two-thirds of the words used in ClinicalTrials.gov trial descriptions fall outside basic medical vocabulary. Drop-off can begin here, long before screening or consent. This is the gap TrialX is working to address.
To explore this challenge further, we recently conducted a webinar titled “From Jargon to Plain Language: Designing Effective AI Prompts for Patient-Friendly Clinical Trial Listings.” In this session, we discussed how AI can help simplify complex trial content and make it more accessible for patients, along with practical examples teams can apply in real-world workflows.
Why Clinical Trial Information Is Hard to Understand
Clinical trial information isn’t meant to be difficult, but it’s written for research documentation, not patient readability.
One major barrier is language complexity. A large-scale analysis of over 165,000 trials found that ClinicalTrials.gov descriptions typically require about 18 years of education, roughly a postgraduate level, to fully understand. This level of complexity stands out even within healthcare. Trial descriptions have been shown to be more difficult to read than clinician notes, which are typically written for communication between healthcare professionals—not patients.
Structure adds to the challenge. Eligibility criteria, study objectives, and interventions are presented in protocol-driven formats that prioritize accuracy but not ease of understanding. Key details are often present, but not easy to find. For patients, this results in uncertainty. Many struggle to interpret whether they qualify or if a study is relevant. Dense language makes it harder to identify key information and decide what to do next.
Ultimately, the issue isn’t just detail—it’s that trial information assumes familiarity with medical and research terminology that many patients don’t have.
Making Clinical Trial Information Easy to Understand With TrialX AI-Powered Simplification Tools
If the challenge is that clinical trial information is difficult to interpret, the next step is not to reduce detail, but to present that detail more clearly.
This is where language simplification becomes relevant. TrialX applies this approach to publicly available clinical trial listings. Using AI-powered simplification, complex medical language is translated into plain, structured text, typically aligned with a 5th or 8th-grade reading level.
Through this:
- Technical terms are clarified or simplified
- Long, dense sections are broken into clearer formats
- Eligibility criteria are organized in a way that is easier to scan
This allows patients to more quickly answer practical questions:
Does this trial apply to me? What would participation involve? Should I learn more?
In this way, language simplification addresses a specific but important gap: helping patients better understand trial information at the moment they first encounter it.
Want to explore more about our AI-simplification feature? Click here to learn more.
