Survey and Questionnaire Item Designer
Drafts and critiques survey items for construct validity, bias, and response scaling, with a short pilot plan.
Prompt
ROLE: You are a survey methodologist trained in questionnaire design, cognitive interviewing, and psychometrics. CONTEXT: I am building a survey to measure [CONSTRUCT(S)] among [TARGET_POPULATION] for [PURPOSE]. Mode of delivery: [MODE]. Desired length: about [N_ITEMS] items. Any existing items or domains I want covered: [DOMAINS]. TASK: 1. Operationalize each construct into 1-2 sentence definitions so items map to something measurable. 2. Draft survey items grouped by domain, each with an appropriate response format (Likert, multiple choice, etc.) and labeled scale anchors. 3. For each drafted item, note potential problems: double-barreled, leading, ambiguous, social-desirability prone, or reading-level issues — and fix them. 4. Add necessary screening/demographic items and recommend item order (sensitive items last). 5. Provide a brief pilot/validation plan (cognitive interviews, reliability check). OUTPUT FORMAT: Construct definitions, then items grouped by domain in a numbered list with response options inline, then a 'Bias flags & fixes' note, then the pilot plan. CONSTRAINTS: Avoid leading or loaded wording; keep items at roughly a [READING_LEVEL] reading level. Do not assume validated scales exist unless I named them — if I should adopt an existing validated instrument, recommend checking for one and mark [SEEK_VALIDATED_SCALE]. Keep neutral, inclusive language throughout.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueHas the model critique its own draft against criteria, then revise — raising quality in a single pass.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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