Ensuring your respondents are fully engaged and paying attention to your survey questions is always a concern before launching a survey. In a perfect world, you want to ensure respondents are not distracted and take the time to read through and answer each question. However, many factors can cause participants to disengage and provide low-quality answers that introduce noise to your data.
Attention checks are an effective way to ensure that respondents read your questions and answer them to the best of their ability. This market research guide will explain what attention check questions are, how to employ them effectively, and common errors to avoid when implementing them into your surveys.
Attention check questions are survey questions that help researchers determine which respondents are focused and which are disengaged. If a respondent is inattentive during a survey, researchers can omit their responses when reviewing the final data.
Attention check questions are typically straightforward, but they often feature a specific instruction that tells researchers if a respondent is paying full attention to the survey questions. Many surveys incorporate one or two attention checks to help them discern usable data points from questionable ones.
While creating engaging survey questions is a surefire way to keep participants on task, attention checks are a critical tool in a researcher's data quality arsenal. Because modern research practices focus on interviewing a small group as a proxy for a larger population, non-representative responses can skew conclusions and fuel poor business decisions.
Attention checks become even more important as the length of the survey increases. Over time, even well-meaning participants will suffer from survey fatigue. In most cases, longer surveys require more attention checks. Attention checks can also be viewed in aggregate as a measure of survey engagement and usability.
Attention check questions help researchers identify which respondents provide high-quality and low-quality responses. Some other things to look out for when isolating low-quality responses include measuring inconsistencies in responses, how fast it takes a respondent to complete a survey, and spotting open-ended questions with nonsensical answers.
Many survey authors use the following four question types when crafting attention checks for respondents:
Trap questions help catch respondents who are not reading questions or breezing through a survey. This attention check question is typical for scale-based surveys and can be a standalone question or placed in the middle of a long table. Trap questions interrupt the flow of the survey by asking the respondent for a specific answer.
These questions should have a correct answer that’s easy to identify if users are reading through them rather than just breezing through them. In longer surveys, some researchers may implement multiple trap questions to ensure that respondents remain engaged.
Example:
Attention filter questions are typically lengthier questions with specific instructions located somewhere in the middle of the text. This attention check question ensures that respondents thoroughly read each question before responding.
In these questions, participants usually find directions instructing them to answer in a way that does not correspond with how they would typically respond. Participants who read the additional instructions and answer the questions appropriately show researchers that they are paying close attention to each question on the survey.
Example:
In surveys with scale-based questions, questions with reverse wording ask the same thing twice but in a different voice. For example, if the original question is in a positive voice, then the question with reverse wording will be the negative inverse.
If readers pay attention to each question, they will provide the same answer for the inverse of the question. In other words, how you word a question should not change the respondent’s feelings on the topic.
If you do not have the same answer twice, your respondent was likely not paying attention to the question.
Example:
Commitment check questions are usually the first question in a survey. Commitment checks explain to respondents the importance of data integrity and ask them to provide thoughtful answers to each question after reading them thoroughly.
For these questions, a respondent answers “Yes,” or agrees to the commitment to pass the attention check.
Attention checks only need to perform one task: ensure the respondent is paying attention. Ineffective attention check questions usually come in the form of questions that attempt to do more than measure attention. Some common mistakes include asking memory-based questions, questions that require industry-specific knowledge, and questions that do not have one clear answer.
Attention checks should only measure attention. Many survey authors make the mistake of asking questions that require memorization or industry-specific knowledge. Memory-based questions can lead to omitting useful information from high-quality respondents. For example, asking a respondent to remember an irrelevant detail in a previous question does not necessarily confirm that they were not paying attention.
In attention check questions, it is imperative that researchers only use questions that check for comprehension after presenting material with critical information.
It is crucial to ensure that each attention check question only has one correct answer. If a question is too ambiguous, it can lead to a wrongfully failed attention check. Attention check questions should not ask for an opinion or provide another possible correct answer.
For example, if you ask a respondent to “agree” to a specific statement to show they are paying attention, do not give them the option to select “strongly agree.” The respondent will have no idea if choosing anything but “agree” disqualifies them from the survey, meaning the presence of both answer choices can lead to further confusion.
Quality attention check questions do not require respondents to ignore straightforward questions. Attention checks should emphasize that the instructions are critical to pay attention to by ensuring that the expected answer is clear to the respondent. Avoid creating attention checks based on intuition, as these questions often lack validity and can wind up disqualifying attentive respondents.
Attention checks can effectively ensure that survey respondents are fully engaged and paying attention to the questions. They help researchers identify who is providing high-quality responses and those who are disengaged, allowing them to omit low-quality answers when reviewing the final data.
Attention check questions can come in various forms, such as trap questions, attention filter questions, and questions with reverse wording. By implementing attention checks in surveys, researchers can improve data quality and make more informed decisions based on the results. Remember that the importance of attention checks increases as survey length increases, so longer surveys require multiple attention checks.
If you need a professional and reliable solution to ensure that your survey respondents are fully engaged and providing high-quality responses, consider enlisting the help of IntelliSurvey. Our team of experienced programmers and samplers work together to assist with attention checks and other data quality measures throughout your project.
Our proprietary technology, CheatSweep™, allows us to analyze survey data and identify potential cheating, speeding, or poor data input. By choosing IntelliSurvey, you can rest assured that your research data will be accurate and usable. Please do not hesitate to contact us to learn more about our products and services and how we can help improve the quality of your survey data.