Questionnaire
Reviewed byMallik Gaddam
Definition
A questionnaire is a structured set of questions designed to collect standardized data from respondents in survey research. Questionnaires can include closed ended items (with predefined response options such as multiple choice or Likert scales), open ended items (allowing free text responses), or a combination.[1] They are used across disciplines to measure attitudes, behaviors, knowledge, health status, and a wide range of other constructs.
Explore the concept
From draft items to 2,790 answers
Page through a vaccine hesitancy questionnaire from first draft to fielding, and see what careful wording, cognitive interviews and psychometric testing each catch.
Step 1 of 5: Draft the items
Items drafted
25
COVID 19 vaccine hesitancy
Sources
2
literature review, expert consultation
Wording traps
Start from the construct
The big idea: A questionnaire is a measuring instrument, not just a list of questions: items are drafted against a defined construct and worded to avoid double barreled, leading and ambiguous questions, then pilot tested and checked for reliability and validity before it is fielded. Use a validated questionnaire when one exists.
Figures are the article's example: 25 items, cognitive interviews with 12 nurses (3 items revised), a field test with 150 respondents (alpha 0.88, two week test retest ICC 0.82, three subscales), and 2,790 completed of 4,500 invited online (62%). The double barreled item is the article's own example; the leading and ambiguous examples are illustrative. Formats, ordering and length advice follow the article.
Why it matters
Questionnaires are among the most commonly used data collection instruments in social science, health research, and education. When well designed, they produce reliable, valid, and comparable data across large samples at relatively low cost. The design of a questionnaire directly affects data quality: poorly worded questions, biased response options, inappropriate scales, and confusing layouts can introduce measurement error, reduce response rates, and compromise the interpretability of results.[1] Researchers investing in questionnaire development and validation contribute tools that may be used across hundreds of subsequent studies, magnifying the impact of good or poor design decisions.
How it works
Questionnaire development typically follows a structured process. The researcher begins by defining the constructs to be measured, informed by the research question and existing literature. Items are drafted to capture each construct, with attention to clarity, specificity, and the avoidance of double barreled questions (which ask about two things at once), leading questions (which suggest a preferred answer), and ambiguous language.[1][2]
Response formats are selected based on the measurement goals. Likert scales (typically five or seven points) measure the intensity of agreement, frequency, or satisfaction.[2] Visual analogue scales allow respondents to mark a continuous scale. Dichotomous items (yes or no) are efficient but sacrifice precision. For factual questions (age, education level), categorical or numerical response options are appropriate.
The questionnaire undergoes pilot testing with a small sample to identify problems with comprehension, flow, and response patterns. Cognitive interviewing, in which respondents think aloud while answering, or answer follow up probes about how they understood each question and arrived at their answer, can reveal misinterpretations that would not be detected through quantitative pilot testing alone.[3] After revision, the questionnaire is administered to a larger sample for psychometric evaluation, including assessment of reliability (internal consistency via Cronbach's alpha, test retest reliability) and validity (construct validity, criterion validity); content validity is judged earlier, when experts review the draft items against the definition of the construct.[2]
Question order affects responses. Sensitive questions are generally placed later in the questionnaire, after rapport has been established. The overall length affects completion rates, with shorter questionnaires generally producing higher response rates. Mode of administration (online, paper, telephone, in person) also influences response patterns, and researchers should consider mode effects when interpreting results or comparing across studies.[1]
When to use it
Use questionnaires when the goal is to collect standardized self report data from a sample of respondents. They are appropriate for surveys, epidemiological studies, clinical trials (for patient reported outcomes), and any study requiring structured measurement of subjective or factual information. Use validated questionnaires whenever possible, as developing and validating a new instrument is time consuming and reduces comparability with prior research. If no validated instrument exists for the construct of interest, invest in rigorous development and validation before using the new instrument in a study.
Key takeaways
- Questionnaires are among the most commonly used data collection instruments in social science, health research, and education.
- The researcher begins by defining the constructs to be measured, informed by the research question and existing literature.
- Use questionnaires when the goal is to collect standardized self report data from a sample of respondents.
- A common error is using an unvalidated questionnaire, assuming that face validity (the items "look right") is sufficient evidence of measurement quality.
Common mistakes
- A common error is using an unvalidated questionnaire, assuming that face validity (the items "look right") is sufficient evidence of measurement quality.[2]
- Another mistake is writing double barreled questions that confound two constructs (for example, "How satisfied are you with the quality and timeliness of care?"), making responses uninterpretable.
- Researchers sometimes use too many items, leading to respondent fatigue and reduced data quality in later sections.
- Ignoring mode effects when switching from paper to online administration, or vice versa, can introduce systematic differences.[1]
- Finally, failing to pilot test the questionnaire before full deployment often results in discovering problems too late to correct.[1][3]
Example
A public health team develops a 25 item questionnaire to assess COVID 19 vaccine hesitancy among healthcare workers. Items are drafted based on a literature review and expert consultation. Cognitive interviews with 12 nurses reveal that three items are consistently misunderstood, and these are revised. A field test with 150 respondents yields a Cronbach's alpha of 0.88 for the full scale and a two week test retest intraclass correlation coefficient (ICC) of 0.82. Exploratory factor analysis identifies three subscales: safety concerns, efficacy doubts, and institutional distrust, so internal consistency is also reported for each subscale, because a high alpha across all 25 items does not show that they measure one construct. The final questionnaire is administered online to 4,500 healthcare workers, achieving a 62% response rate (2,790 completed questionnaires from 4,500 invited).
Test your understanding
5 questions that adapt as you go: answer two in a row correctly and they get harder.
Question 1 of 5
Scenario:
An item reads: "Given the proven benefits of exercise, how often do you exercise?"
Question:
What kind of wording problem is this?
Hardness: Interpret
Sources
- [1]Dillman DA, Smyth JD, Christian LM. Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method. 4th ed. Wiley, 2014. ISBN 9781118456149
- [2]DeVellis RF, Thorpe CT. Scale Development: Theory and Applications. 5th ed. SAGE Publications, 2022. ISBN 9781544379340
- [3]Willis GB. Cognitive Interviewing: A Tool for Improving Questionnaire Design. Thousand Oaks, CA: Sage Publications; 2005. ISBN 9780761928041
Cite this term
Paperguide. (2026, October 15). Questionnaire. In Paperguide Research Glossary. https://paperguide.ai/research-glossary/questionnaire/(Paperguide, 2026)