Including quality control questions when designing your survey questionnaire is an important step to ensure the reliability, validity, and integrity of the data you collect. Incorporating these checks into survey design not only helps maintain data quality but also enhances the efficiency of data analysis by filtering out unreliable responses early in the process.
The result is cleaner data that reduces the need for extensive data cleansing, allowing researchers to focus on analysis and get insights faster. In this article, we’ll cover five types of quality control questions you can employ to enhance the reliability of your surveys.
Quality control questions, such as attention check, authentication, or trap questions, are included when surveys are programmed to ensure respondents are paying attention and providing accurate responses. These questions are designed to catch fraudulent respondents, as well as real respondents who may be responding randomly, speeding through the survey, or not fully engaging with the questions.
When a respondent fails a quality control question, they are then flagged for further review. A general rule of thumb is that if a respondent fails any three quality checks, they should automatically be removed.
In addition to programmatic checks such as speeder or straightlining flags, you can include several quality control questions in your questionnaire.
These are questions interspersed throughout a survey that can identify whether or not a respondent is authentically providing answers that align with their personal experience. Researchers can insert a combination of opposite statements or unrealistic actions to deduce whether they’re consistently responding to very similar questions the same way.
To determine whether a respondent is paying attention, researchers can use an attention check by inserting a prompt such as “Please select the number 3 for quality purposes.” If these particular exercises are incorrectly answered, researchers can rightfully suspect that the respondent is speed-clicking through the survey without regard to the content of the questions.
It’s critical to check if a respondent is who they say they are, which can be determined with a question they should be able to answer. If the target audience is IT-related, for example, researchers could include a computer-related knowledge check that a respondent cannot quickly look up online and that the target respondent should know.
To boost their odds of qualifying for online surveys, clever respondents often exaggerate their qualifications. A seeking check is a multi-select question in a survey screener that asks about a variety of experiences or interests and includes highly uncommon activities, like helicopter shopping. Respondents who select the distractor option or an above-average number of options may immediately be disqualified or flagged as potential seekers for further review. Alternatively, researchers may present a list of known uncommon activities–buying a new car, flying to Mauritania, buying an insurance policy against bed bugs, passing your driving license exam–and set a maximum threshold that respondents must not pass.
This type of check is used to implicitly verify respondent consistency. For example, researchers can present a list of known frequent activities–drinking water, shopping for food, watching TV, using a bank account, driving–and set a minimum threshold that respondents must pass.
Effective quality control questions require careful alignment with your study’s goals and objectives. The aim is for them to be subtle yet effective without disrupting the survey flow.
Some factors to consider:
Relevance: Always align your questions with the survey’s main objectives. Irrelevant or tangential questions may confuse respondents and compromise data quality.
Placement: Integrate quality control questions throughout the questionnaire. Distributing them throughout the sections helps maintain engagement and prevents predictability.
Flow: Quality control questions should be embedded seamlessly in the overall questionnaire structure. Avoid abrupt transitions or interruptions that could disrupt the respondents’ focus.
Complexity: Keep questions clear and concise so they are easy to understand. Complex or ambiguous wording can confuse respondents and lead to inaccurate responses.
Frequency: Balance the frequency of quality control questions to maintain data integrity without overwhelming respondents. Too many questions may increase cognitive load and decrease survey completion rates, while too few may compromise the ability to detect inaccuracies effectively.
Investing in a high-quality questionnaire and well-written screener is paramount to the success of any survey project. Adding quality control questions will help ensure your final data set is of the highest possible standard.
IntelliSurvey carefully reviews all questionnaires and provides thoughtful feedback for every project engagement. The combined strategy of using quality control questions and IntelliSurvey's propriety CheatSweep™ data cleansing algorithm makes us well-positioned to support the most challenging of fielding efforts. For more information on how we can partner to perfect your questionnaire and support your survey fielding, please get in touch.