This article will guide you on how to create a citizen survey about mental health support awareness. At Specific, we help you build such a survey in seconds—no hassle, just answers.
Steps to create a survey for citizens about mental health support awareness
If you want to save time, just click this link to generate a survey with Specific—it’s that simple.
Tell what survey you want.
Done.
You honestly don’t even need to read further. With AI survey generators like Specific, you describe your goal and the AI instantly creates an expert-quality, conversational survey for citizens about mental health support awareness. Respondents even get relevant follow-up questions to capture richer insights, all without you lifting a finger.
Why citizen surveys on mental health support awareness matter
Understanding public awareness and sentiment around mental health support isn’t just a public service—it’s essential for shaping effective policies and interventions. And the data speaks for itself.
Only 23% of U.S. adults are familiar with the 988 Suicide & Crisis Lifeline, despite 67% having heard of it. If citizens aren’t truly aware of resources, they’ll never access the help they need. [1]
One in every eight people globally lives with a mental disorder—that’s a major community health concern. [2]
Over three-fourths of people in lower-income countries receive no treatment for mental disorders. [2]
If you’re not running these surveys, you’re missing out on:
Spotting gaps in awareness that lead to underutilized resources
Identifying the bottlenecks citizens experience when seeking help
Understanding how citizens perceive mental health support and what stops them from using it
Proving to stakeholders and officials that further outreach or funding is needed—it’s hard to argue with your own population’s words.
The importance of citizen feedback around mental health support awareness can’t be overstated. Every insight you gather brings decision-makers one step closer to solving real, costly, human problems. Globally, mental health issues are expected to cost $6 trillion per year by 2030—surveys are a direct way to spot problems before they become even more expensive. [3]
What makes a good survey on mental health support awareness
Great surveys don’t happen by accident. Whether you’re using AI or building manually, here’s what makes for an effective, conversational citizen survey on mental health support:
Clear, unbiased questions. If a citizen can misinterpret a question or feel judged, they’ll either answer inaccurately or drop out.
Conversational tone. Surveys shouldn’t sound or feel like a government quiz—speak in plain language to get honest responses.
Follow-up questions. These are game-changers (more below) for teasing out why someone feels a certain way or what stops them from acting.
You know a survey is good when it gets:
High completion rate (lots of citizens respond)
Rich, actionable quality (people give real context and detail)
Bad practices | Good practices |
|---|---|
Vague or leading questions | Clear, direct questions |
Question types and examples for a citizen survey on mental health support awareness
Mixing question types lets you capture broad sentiment, statistics, and deeply personal context in your mental health support surveys. Here’s how to approach it:
Open-ended questions give citizens the freedom to share in their own words—perfect for qualitative insight, especially when exploring lived experiences or barriers. Use them when you want citizens to elaborate, not just pick a category. Examples:
What challenges have you or people you know faced when trying to get mental health support?
How do you think your community could better promote mental health awareness?
These questions encourage depth and stories, revealing “why” beyond mere numbers.
Single-select multiple-choice questions are your go-to for quick stats, making it easy for citizens to click and proceed without friction—best when you need to compare responses at scale. Here’s an example:
Which of the following best describes your current knowledge of local mental health support resources?
I know exactly what’s available and how to access it.
I’m aware of some resources, but unsure how to use them.
I’ve heard of resources, but don’t know where to start.
I have no knowledge of any support resources.
NPS (Net Promoter Score) question is powerful for measuring how likely citizens are to recommend local mental health services, revealing advocacy and trust levels. Want more? See how to generate a NPS survey for citizens on mental health support awareness. Example question:
On a scale from 0–10, how likely are you to recommend local mental health support resources to a friend or neighbor?
Followup questions to uncover "the why": Whenever someone gives a low rating, or when more context is needed, follow-ups dig deeper. This is the key to actionable survey data. For example:
What makes you feel hesitant about recommending our mental health resources?
Can you share a specific experience that influenced your decision?
Use followups judiciously—they’re best when used to clarify surprising answers, or to understand pain points in more detail.
If you’re looking to expand your survey or see more best questions for citizen mental health awareness surveys, we’ve got a curated list plus actionable tips for building questions that deliver real insight.
What is a conversational survey?
A conversational survey feels like a real chat, not a cold form. The survey adapts in real-time—respondents answer one question at a time, often with dynamic follow-up questions shaped by their responses.
Here’s how AI-generated surveys blow manual surveys out of the water:
Manual Surveys | AI-generated with Specific |
|---|---|
Hours crafting questions | Survey made in seconds by describing your goal |
Why use AI for citizen surveys? Because nothing is faster, easier, or more effective at unlocking honest, actionable feedback—especially in sensitive topics like mental health support awareness. An AI survey example (or conversational survey) feels human and adapts instantly, so you capture truths that old-school forms miss.
Specific is built for best-in-class user experience in conversational surveys, making it smooth and surprisingly engaging for both creators and respondents. If you want to learn more about building surveys efficiently, check out our complete guide on how to create a survey using AI.
The power of follow-up questions
Follow-up questions are where conversational surveys turn from "just a list of questions" to genuine insight-machines. This is the heart of what makes Specific unique—read more about our AI-powered automated follow-up questions.
Let’s say a respondent gives only a vague answer:
Citizen: “I heard about the mental health hotline but haven’t used it.”
AI follow-up: “Can you share what’s stopped you from reaching out or using the hotline so far?”
Without the follow-up, you’d have no clue if their hesitation was due to stigma, lack of trust, confusion about eligibility, or something else. That’s a missed opportunity.
How many followups to ask? In our experience, two or three well-placed follow-up questions hit the sweet spot—enough to surface rich detail, but not so many as to wear people out. We let you set a skip-rule as soon as you capture the info you need.
This makes it a conversational survey: The survey adapts, digs deeper, and feels personal, not robotic. That makes citizens much more likely to open up.
Survey analysis with AI, automated insights, open text responses: Don’t let open-ended answers scare you. With Specific’s AI, you can analyze all responses easily—the AI will synthesize themes, group similar answers, and let you explore data in seconds, no matter how much text you get back.
Automated follow-up questions are still new in survey land—try generating a survey and see how much more insightful your results become.
See this mental health support awareness survey example now
Create your own survey with expert logic and see how real conversational AI uncovers what citizens truly think about mental health support—unlocking faster, richer, and more impactful feedback than ever before.