We can now consider some principles of writing questionnaire items that minimize unintended context effects and maximize the reliability and validity of participants’ responses. A rough guideline for writing questionnaire items is provided by the BRUSO model (Peterson, 2000). 1 An acronym, BRUSO stands for “brief,” “relevant,” “unambiguous,” “specific,” and “objective.” Effective questionnaire items are brief and to the point. They avoid long, overly technical, or unnecessary words. This makes them easier for respondents to understand and faster for them to complete. Effective questionnaire items are also relevant to the research question. If a respondent’s sexual orientation, marital status, or income is not relevant, then items on them should probably not be included. Again, this makes the questionnaire faster to complete, but it also avoids annoying respondents with what they will rightly perceive as irrelevant or even “nosy” questions. Effective questionnaire items are also unambiguous; they can be interpreted in only one way. Part of the problem with the alcohol item presented earlier in this section is that different respondents might have different ideas about what constitutes “an alcoholic drink” or “a typical day.” Effective questionnaire items are also specific,so that it is clear to respondents what their response should be about and clear to researchers what it is about. A common problem here is closed- ended items that are “double barreled.” They ask about two conceptually separate issues but allow only one response. For example, “Please rate the extent to which you have been feeling anxious and depressed.” This item should probably be split into two separate items—one about anxiety and one about depression. Finally, effective questionnaire items are objective in the sense that they do not reveal the researcher’s own opinions or lead participants to answer in a particular way. Table 9.2 shows some examples of poor and effective questionnaire items based on the BRUSO criteria.
|
Criterion |
Poor |
Effective |
|
B—Brief |
“Are you now or have you ever been the possessor of a firearm?” |
“Have you ever owned a gun?” |
|
R—Relevant |
“What is your sexual orientation?” |
Do not include this item unless it is clearly relevant to the research. |
|
U— Unambiguous |
“Are you a gun person?” |
“Do you currently own a gun?” |
|
S—Specific |
“How much have you read about the new gun control measure and sales tax?” |
“How much have you read about the new gun control measure?” “How much have you read about the new sales tax?” |
|
O—Objective |
“How much do you support the new gun control measure?” |
“What is your view of the new gun control measure?” |
For closed-ended items, it is also important to create an appropriate response scale. For categorical variables, the categories presented should generally be mutually exclusive and exhaustive. Mutually exclusive categories do not overlap. For a religion item, for example, the categories of Christian and Catholicare not mutually exclusive but Protestant and Catholi care. Exhaustive categories cover all possible responses. Although Protestant and Catholi care mutually exclusive, they are not exhaustive because there are many other religious categories that a respondent might select: Jewish, Hindu, Buddhist, and so on. In many cases, it is not feasible to include every possible category, in which case an Other category, with a space for the respondent to fill in a more specific response, is a good solution. If respondents could belong to more than one category (e.g., race), they should be instructed to choose all categories that apply.
For rating scales, five or seven response options generally allow about as much precision as respondents are capable of. However, numerical scales with more options can sometimes be appropriate. For dimensions such as attractiveness, pain, and likelihood, a 0-to-10 scale will be familiar to many respondents and easy for them to use. Regardless of the number of response options, the most extreme ones should generally be “balanced” around a neutral or modal midpoint. An example of an unbalanced rating scale measuring perceived likelihood might look like this:
Unlikely \ Somewhat Likely \ Likely \ Very Likely \ Extremely Likely
A balanced version might look like this:
Extremely Unlikely \ Somewhat Unlikely \ As Likely as Not \ Somewhat Likely \ Extremely Likely
Note, however, that a middle or neutral response option does not have to be included. Researchers sometimes choose to leave it out because they want to encourage respondents to think more deeply about their response and not simply choose the middle option by default.
Numerical rating scales often begin at 1 and go up to 5 or 7. However, they can also begin at 0 if the lowest response option means the complete absence of something (e.g., no pain). They can also have 0 as their midpoint, but it is important to think about how this might change people’s interpretation of the response options. For example, when asked to rate how successful in life they have been on a 0-to-10 scale, many people use numbers in the lower half of the scale because they interpret this to mean that they have been only somewhat successful in life. But when asked to rate how successful they have been in life on a −5 to +5 scale, very few people use numbers in the lower half of the scale because they interpret this to mean they have actually been unsuccessfulin life (Schwarz, 1999). 2
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