Steps to Design a Better Survey (Jean Fox & Scott Fricker)
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Transcript of Steps to Design a Better Survey (Jean Fox & Scott Fricker)
Steps to Design a Better Survey
Jean E. Fox Scott S. Fricker
Office of Survey Methods Research Bureau of Labor Statistics
October 19, 2012
Introduction
Our backgrounds
Usability
Survey Methodology
Goal of the presentation
Combine what we know from our fields to improve usability surveys
Types of Usability Surveys
Usability Tests
Post-task
Post-test (e.g., SUS)
Ethnographic work
Learn how people do their work
Solicit input from users
Administered
Self-administered (online, paper)
By interviewer (oral)
Introduction
Three steps we‟ll discuss
1. Decide what you really need to know
2. Write the questions following best practices
3. Test the survey
Step 1
Decide what you really need to know
Decide What You Really Need to Know
Are you asking for data you really need?
Will you really use it?
Can you get the data somewhere else?
Decide What You Really Need to Know
Are you asking questions respondents can answer?
Can you include “screeners”?
– Questions to allow respondents skip irrelevant questions
Do you need separate surveys?
Decide What You Really Need to Know
Are you asking for data in a format you can analyze?
Open-ended vs multiple choice
Are you really going to analyze it?
Step 2
Write the questions following best practices
Best Practices
Rating scales
Rankings
Double-barreled questions
Agree/Disagree items
Satisficing
Types of Scales
Likert-type item
Semantic Differential
Types of Scales
Bi-polar
Previous examples
Uni-polar
Rating Scales
How many response options do you usually use in a rating scale?
3…5…7…10… or something else?
Number of options
Generally, scales with 5-7 options are the most reliable.
The optimum size depends on the issue being rated (Alwin, 1997; Garner, 1960)
– More options for bi-polar scales
Scales
Do you usually have a neutral midpoint?
Odd or Even number of options
Without a midpoint, respondents tend to choose randomly between two middle options.
For usability, generally include a mid-point.
Rating Scales
Do you label the endpoints, a few options, or all of them?
Labels
Use text labels for each option
Avoid numbers, unless they are meaningful
– Especially avoid using negative numbers. Respondents do not like to select negative options.
Rating Scales
Be sure the scale is balanced.
This scale has 3 “satisfied” options, but only one “dissatisfied” option.
Ranking
Definitions
Rating: Select a value for individual items from a scale
Ranking: Select an order for the items, comparing each against all the others.
Ranking
Consider other options before using ranking
Ranking is difficult and less enjoyable than other evaluation methods (Elig and Frieze, 1979).
You don‟t get any interval level data
Ranking
Recommendations
Use ratings instead if you can.
– Determine ranks from average ratings.
Use rankings if you need respondents to prioritize options.
Question Wording
Double-Barreled Questions
Avoid double-barreled questions
They force respondents to make a single response to multiple questions
They assume that respondents logically group the topics together, which may or may not be true
Recommendations
– Watch for the use of “and” in questions.
– Eliminate all double-barreled questions.
– Divide them into multiple questions.
Agree / Disagree Items
Who uses agree / disagree items? Why?
They are fairly easy to write
You can cover lots of topics with one scale
It‟s a fairly standard scale
It‟s familiar to respondents
Agree / Disagree Items
Unfortunately, they can be problematic
They are prone to acquiescence bias
– The tendency to agree with a statement
They require an additional level of processing for the respondent
– Respondents need to translate their response to the agree/disagree scale.
Agree / Disagree Items
Recommendation
Avoid agree / disagree items if possible
Use “construct specific” responses
Other Issues
Be sure the responses match the question.
Speak the respondent‟s language
Avoid jargon unless appropriate
Remember that responses can be impacted by
Question order
The size of the text field
Graphics, even seemingly innocuous ones
Broader Issue - Satisficing
Responding to surveys often requires considerable effort
Rather than finding the „optimal‟ answer, people may take shortcuts, choose the first minimally acceptable answer
“Satisficing” (Krosnick, 1991) – depends on:
Task difficulty, respondent ability and motivation
Satisficing – Remedies
Minimize task difficulty
Minimize number of words in questions
Avoid double-barreled questions
Decompose questions when needed
– Instead of asking how much someone spent on clothing, ask about different types of clothing separately
Use ratings not rankings
Label response options
Satisficing – Remedies, cont.
Maximize motivation
Describe purpose and value of study
Provide instructions to think carefully
Include random probes (“why do you say that?”)
Keep surveys short
Put important questions early
Satisficing – Remedies, cont.
Minimize “response effects”
Avoid blocks of ratings on the same scale (prevents „straight-lining‟)
Do not offer „no opinion‟ response options
Avoid agree/disagree, yes/no, true/false questions
Step 3
Test the survey
Testing Surveys
Be sure your questions work
Consider an expert review
Need an expert
For usability testing, be sure to include the survey in your pilot test.
A common technique for evaluating surveys is Cognitive Interviewing (see Willis, 2005)
Cognitive Interviewing
Cognitive interviewing basics
Have participant complete the survey
Afterwards, ask participants questions, such as
– In your own words, what was the question asking?
– What did you consider in determining your response?
– Was there anything difficult about this question?
Cognitive Interviewing
Cognitive interviewing basics (con‟t)
Review the qualitative data you get to identify potential problems and solutions
Like usability testing, there are different approaches (e.g., think aloud)
Summary
Decide what you really need to know
Write the questions following best practices
Test the survey
Contact Information
Jean E. Fox [email protected]
202-691-7370
Scott S. Fricker [email protected]
202-691-7390
References
Alwin, D.F. (1997). Feeling Thermometers Versus 7-Point Scales: Which Are Better? Sociological Methods and Research, 25(3), pp 318 – 340
Elig, T. W., & Frieze, I.H. (1979). Measuring causal attributions for success and failure. Journal of Personality and Social Psychology, 37(4), 621-634.
Garner, W.R. (1960). Rating scales, discriminability, and information transmission. The Psychological Review, 67 (6), 343-352.
Krosnick, J.A. (1991). Response strategies for coping with the cognitive demands of attitude strength in surveys. In J.M. Tanur (ed.) Questions About Questions: Inquiries into the Cognitive Bases of Surveys. New York: Russell Sage Foundation, pp. 177 – 203.
Krosnick, J.A. and Presser, S. (2010). Question and questionnaire design. In Handbook of Survey Research, 2nd Edition, Peter V. Marsden and James D. Wright (Eds). Bingley, UK: Emerald Group Publishing Ltd.
Willis, G. (2005). Cognitive Interviewing: A Tool for Improving Questionnaire Design, Thousand Oaks, CA: Sage Publications, Inc.