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 Fox.Jean@bls.gov

202-691-7370

Scott S. Fricker Fricker.Scott@bls.gov

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.