Survey example: Patient survey about smoking cessation support
Create conversational survey example by chatting with AI.
This is an example of an AI survey for Patients about Smoking Cessation Support—see and try the example to experience how it works.
Creating effective patient surveys about smoking cessation support can be difficult: traditional forms are tedious for patients and rarely capture nuanced feedback.
At Specific, we’ve mastered the art of conversational surveys. Every tool on this page is powered by our platform—designed for depth, context, and actionable insight.
What is a conversational survey and why AI makes it better for patients
Building a patient survey about smoking cessation support is always tricky. Too often, static survey forms drive low completion rates and lack the personal touch that motivates honest patient feedback. Patients abandon rigid surveys quickly, or give short answers that leave you with more questions than insights. Enter the AI survey generator: a smarter way to get to the heart of what patients need, using natural conversation and real-time intelligence.
AI survey generators completely change the game. They use advanced language models to converse with respondents, adapting questions as needed—no more guessing which follow-up matters most. Instead of filling out a static form, the patient interacts in a familiar chat format. This personalized experience keeps them engaged and surfaces deeper insights.
In fact, AI-powered surveys achieve completion rates between 70–90%, compared to the 10–30% typical of traditional methods. This leap is possible because AI adapts dynamically to each respondent, keeping them engaged and minimizing drop-off. [1]
Manual Survey | AI-Generated Survey | |
---|---|---|
Setup Time | Slow, manual editing | Automated, chat-based |
Question Logic | Static, often generic | Personalized and dynamic |
Engagement | Low completion rate | High engagement, up to 90% |
Insights | Surface-level | Rich, contextual, actionable |
Why use AI for patient surveys?
Higher engagement: Conversational AI feels more like a real interaction—so patients complete surveys and provide richer feedback.
Smarter follow-ups: The AI asks relevant, context-aware questions you might not have thought of, even in real time.
Depth over breadth: Get beyond superficial yes/no answers. Capture detailed stories and motivation behind each patient’s experience.
Easy and accessible: Conversational surveys work on any device and mimic the natural feel of chat we’re all used to.
With Specific, every conversational survey offers a best-in-class experience for both creator and respondent. Patients don’t just fill forms—they have a genuine, guided conversation built for actionable insights.
If you want to learn more about best questions and tips, check out the best questions for patient surveys on smoking cessation support or see how to create a patient survey from scratch.
Automatic follow-up questions based on previous reply
The standout feature of Specific’s conversational surveys is our AI-driven follow-up questions. As patients answer, the AI listens and asks smarter, deeper questions—like a skilled interviewer—right in the moment. This leads to much richer insights, as you get the full story the first time, without chasing down patients via email later.
Say a patient gives a vague response. Without automatic follow-ups, you end up in the dark:
Patient: “Sometimes the support wasn’t helpful.”
AI follow-up: “Could you share an example of a time when the support didn’t meet your needs?”
Small, tailored follow-ups like these help clarify intent and uncover the specifics that matter.
Try generating a survey and see how these real-time, context-aware follow-ups turn a generic questionnaire into a meaningful conversation. For more on how this works, visit automatic AI follow-up questions.
These follow-ups make patient surveys truly conversational—delivering better experiences and far more useful results.
Easy editing, like magic
Editing your patient smoking cessation support survey with Specific is effortless. You just tell the AI—using plain language—what you want to change, and it updates your survey instantly with expert-level professionalism. No more tedious form builders or manual logic trees; the AI handles it all in seconds, freeing you to focus on what matters. Experience this in action with the AI survey editor.
Deliver surveys where patients respond
You can deliver your AI survey through two seamless methods, each tailored for specific use cases:
Sharable landing page surveys: Ideal for patient recruitment, public health outreach, or follow-up programs. Just send the link via email, SMS, QR code, or embed in patient portals so anyone can participate at their convenience.
In-product surveys: Perfect for clinics, digital health platforms, or telemedicine portals. Trigger the survey while the patient is logged in—gather contextual feedback right after smoking cessation counseling or support interventions.
Select the method that reaches your patients best—and get better data in return.
AI-powered analysis: insights in seconds
Analyzing survey responses with AI unlocks actionable insights instantly. With Specific, the AI summarizes feedback, pinpoints key themes, and answers questions about patient needs—all without manual coding or spreadsheets. Features like automatic topic detection and the ability to chat directly with the AI about your results empower you to move fast from data to action.
If you want a walkthrough of the process, see how to analyze patient smoking cessation support survey responses with AI for real-world examples.
This is true AI survey analysis—making automated survey insights accessible and genuinely helpful to every team.
See this Smoking Cessation Support survey example now
Take a look for yourself—see a real conversational AI survey for patient smoking cessation support in action, and discover how follow-up questions, intuitive editing, and smart analytics make your survey process effortless.
Related resources
Sources
SuperAGI. AI vs Traditional Surveys: A Comparative Analysis of Automation, Accuracy, and User Engagement in 2025
NIH PubMed. Patient engagement and receipt of smoking cessation support during medical encounters
Substance Abuse Treatment, Prevention, and Policy. Effectiveness of face-to-face interventions for smoking cessation support