Survey example: Clinical Trial Participants survey about adverse events reporting

Create conversational survey example by chatting with AI.

This is an example of an AI survey for Clinical Trial Participants about adverse events reporting. If you want to understand how conversational surveys can streamline your adverse events reporting, see and try the example.

Designing effective surveys for adverse events reporting is tough—unclear responses and follow-up emails slow everything down and data quality suffers.

Specific is built for this: every tool you see here, including this survey example, comes from our platform, combining expert logic and smart AI to set the bar for conversational research.

What is a conversational survey and why AI makes it better for clinical trial participants

Let’s face it; adverse events reporting is often riddled with gaps, confusion, and incomplete feedback. In clinical research, surveys are crucial, but traditional forms make it hard for participants to provide clear, insightful, and actionable feedback.

Statistics back this up: a systematic review found that 59% of phase III cancer trials didn’t compare adverse event (AE) rates between groups, and 15.6% only recorded severe AEs. That’s a staggering amount of uncollected or unrefined feedback that could make a big difference in drug development and patient safety [1].

So, how does an AI survey generator change the game for clinical trial participants?

  • AI surveys ask questions in a natural, conversational flow, much like chatting with a smart, attentive researcher.

  • They automatically adapt to respondent’s previous answers, providing targeted follow-ups that clarify and deepen understanding.

  • With an AI survey builder, you build or edit your survey with easy natural language prompts—no more wrestling with complicated forms or endless drag-and-drop builders.

Here’s a quick comparison:

Manual survey creation

AI-generated conversational survey

Rigid forms, static questions

Dynamic, adaptive flow—questions tailor themselves

Manual follow-ups required (often by email later)

Automatic follow-ups in real time, based on replies

Editing and reworking takes time

Rapid edits—just describe your change and it's done

Flat, uninspired UX—often low engagement

Sleek, engaging chat interface keeps people responding

Why use AI for clinical trial participants surveys?

  • Stop settling for generic forms. AI surveys clarify ambiguous feedback, so you never wonder what your participant meant in their answer.

  • Boost engagement and accuracy. By simulating a two-way conversation, you collect richer, more reliable AE data for compliance and research integrity.

  • Specific offers a best-in-class user experience in conversational surveys, making the feedback process smooth, accessible, and pleasant for both clinical teams and participants.

If you want to see how the right questions improve AE data, check out our guide to the best questions for clinical trial adverse events surveys.

Automatic follow-up questions based on previous reply

Specific’s standout feature is its real-time AI follow-up questions. The AI reads the participant’s latest reply and, like an expert interviewer, instantly asks smart, clarifying questions. This context-driven probing uncovers detail that static forms or manual emails miss.

Why does it matter? Consider the real-world impact:

  • Participant: “I felt dizzy during week two.”

  • AI follow-up: “Can you describe how severe the dizziness was? Did it affect your daily activities or require you to stop the medication?”

If you don’t ask follow-ups, it’s easy to end up with half-baked data you can’t use. You’ll either waste time trying to interpret unclear input, or find yourself stuck sending individual clarifying emails.

You can see more about how these automatic AI follow-up questions work. They’re a new way to collect richer responses without extra burden. Try generating a survey to experience the difference.

It’s these follow-ups that transform a basic survey into a real conversational survey—making every respondent feel heard, and every answer actionable.

Easy editing, like magic

Changing your survey on Specific is just as easy as building it. You simply describe what you want—like “add a clarifying follow-up after the dizziness question” or “focus more on mild but frequent symptoms”—and the AI survey editor does all the tedious work for you, instantly.

What might take hours in traditional survey tools now takes seconds—and you get the benefit of AI’s research acumen in every tweak. If you ever want to start fresh, you can always use the AI survey builder for any survey idea you have.

Share your AE survey: landing page or in-product

You need your adverse events reporting survey to actually reach clinical trial participants—so we give you two seamless delivery options:

  • Sharable landing page surveys: Generate a unique survey link you can email, post to participant portals, or embed in your study dashboard. Especially ideal for multi-site or geographically distributed trials, where direct in-app access isn’t possible.

  • In-product surveys: For digital trials with participant-facing apps, embed your survey as a lightweight widget. Trigger AE surveys right after treatment milestones, logins, or when symptoms are reported—increasing both participation and reporting accuracy.

For clinical trial participants and adverse events reporting, landing pages make widespread outreach and longitudinal follow-up easier, while in-product surveys unlock targeting triggers based on actual study activity.

AI-powered analysis: instant, actionable insights

Once responses roll in, Specific handles the most time-consuming part—analysis. AI-powered survey analysis instantly summarizes responses, detects key themes, and transforms open-ended feedback into structured findings, all without spreadsheets. You can chat with the AI to dig into specifics or see automatic topic detections in action. Read our guide on how to analyze clinical trial participants adverse events reporting survey responses with AI for step-by-step detail or see the full capabilities on our survey response analysis page.

This approach delivers automated survey insights that help research and medical monitors surface safety issues, compliance gaps, or unexpected side effects—without slogging through raw qualitative data.

See this adverse events reporting survey example now

Try the AI-powered conversational survey for adverse events reporting and experience how smart follow-ups and instant analysis can transform participant feedback into real research advantage.

Try it out. It's fun!

Sources

  1. NIH/National Library of Medicine. Systematic review of adverse event reporting in cancer clinical trials.

  2. PubMed. Geographical variation in adverse event reporting rates across clinical trials.

  3. BMC Medical Research Methodology. Discrepancies in adverse event reporting between ClinicalTrials.gov and publications.

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Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.