December 20, 2022
Research practitioners have a lot on their hands when it comes to designing an effective survey instrument and ensuring quality is not affected during data collection. Another important point researchers have to consider is avoiding respondent bias. Biased responses lead to inaccurate data and can incorrectly prompt companies to make changes that they didn’t need to make while leaving the need for other course corrections unrecognized. Fortunately, there are ways that researchers can recognize and avoid response bias in their surveys.
What is Respondent Bias?
Respondent bias lies more with the questions in a survey, and not so much with the willingness (or not) on the part of the respondents to answer the questions. Respondents can give inaccurate answers to questions due to conscious and subconscious factors, so it’s important that questions are worded carefully in order to get the most accurate responses. Respondents might not even realize that they are giving untruthful or inaccurate answers, but it affects the outcome of the data collection just the same.
Never Lead the Witness
So how can researchers avoid respondent bias and get the highest quality survey answers? One crucial thing that researchers can do is ensure that their survey questions are not framed in a way that leads the respondent to answer a question in a certain way. For example, if a survey had a question that read “How awful are plant-based burgers?”, it could lead the respondent to think, “Yes plant-based burgers are awful.” A better, non-leading question would be “What do you think of plant-based burgers?”
Leading questions can also happen with scaled questions. For example, a question on a survey could ask a respondent if they were extremely dissatisfied, dissatisfied, or satisfied. Offering more options for dissatisfied answers is biased and leads survey respondents in that direction. It is also important to always offer the respondent the option not to answer a question. Providing a ‘Prefer not to answer” option in a survey, or even offering a way for survey respondents to opt out of participating is important to avoid bias. Researchers should also craft survey questions in a way that is dynamic– make sure to use language that is clear and transparent and that avoids negative terms, such as the word ‘not’.
Learn to Trade Places
Finally, an easy way for researchers to avoid respondent bias in surveys is to imagine themselves in the place of the survey participants. If they were taking the survey, what would constitute bias in the eyes of the respondent? It’s important for researchers to take a 360-degree view of their surveys in order to ensure the best possible outcome for quality data collection.
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