Screening questions determine if participants qualify for your study. Use them to ensure you're collecting data from the right audience.
How Screening Works
Participant answers screening questions at the start
Rules evaluate their answers
Qualified participants continue to the full study
Unqualified participants are "screened out" with a thank-you message
Setting Up Screening
Add screening questions early in your study
Set screening rules that define disqualifying answers
Test both qualifying and disqualifying paths
Publish when screening works correctly
Types of Screening Criteria
Demographic
Criteria | Example | Screen Out If |
Age | "How old are you?" | Under 18 |
Location | "What country?" | Outside target markets |
Gender | "What is your gender?" | Doesn't match quota |
Behavioral
Criteria | Example | Screen Out If |
Product usage | "Used [product] in past 6 months?" | No usage |
Purchase intent | "Planning to purchase?" | Not planning |
Decision role | "Make purchasing decisions?" | Not a decision maker |
Experience
Criteria | Example | Screen Out If |
Industry | "Work in market research?" | Yes (avoid professionals) |
Brand affiliation | "Work for [brand]?" | Yes |
Past participation | "Participated in similar study?" | Yes |
Best Practices
Place Screening Early
💡 Tip: Put screening questions at the beginning. Don't waste participants' time with 10+ questions before screening.
Hide the Right Answer
Bad: "We need smartphone owners. Do you own a smartphone?"
Good: "Which devices do you own? (Select all)"
Laptop
Tablet
Smartphone (target)
Gaming console
Smart TV
Use Multiple Choice
Avoid open-ended screening questions—they're harder to set rules on and easier to game.
Screening Rate Guidelines
Rate | Meaning |
0-10% | Very permissive criteria |
10-30% | Normal for targeted studies |
30-50% | Narrow criteria |
50%+ | Very restrictive—harder to recruit |
⚠️ Warning: High screening rates mean lower incidence, which affects recruitment cost and timeline.
Screened Participant Experience
Screened participants see:
A polite thank-you message
Explanation that they don't qualify
They're marked "Screened Out" in your data
Excluded from analysis reports