What Are Loaded Questions?
The way you ask questions can influence the sorts of answers you receive and the quality of those responses.
Consequently, if you ask for information in a neutral and straightforward way, you’re more likely to receive honest, thoughtful and valuable feedback. In contrast, if you implant an opinion or assumption into your question, you’re more likely to get a biased response, that provides little or no use to you moving forward.
The trouble with bias, however, is that it can sneak up on you in the most unexpected ways. Everyone has their own preferences and opinions, and however much we might not want them to, these biases can leak into our professional lives. Poorly constructed survey questions are an example of how personal or professional bias can flow into our work, which can sometimes impact the outcome of a survey or questionnaire, leading to inaccurate results.
Subsequently, if you’re to remove or minimise the likelihood of biased questions creeping into your survey, you need to have some idea of what they can look like.
That’s why we’ve put together this blog piece on loaded questions to help you.
Loaded question example
A good illustration of a loaded question could be one that is targeted at an individual’s political viewpoint. In such a scenario, a biased question may be worded as follows.
Do you really intend to vote for this controversial prime ministerial candidate?
In this question, the survey creator is outrageously assuming:
- An individual’s voting choice is potentially corrupt
- The person likes supporting controversial candidates running for office
- That there is something implicitly bad about another person’s voting choice
In terms of their use, loaded questions can be asked about many different things in society, from a product to a person, or a business. For instance, if we take the example of products, the use of loaded questions here will assume your respondent loves whatever product you’re asking them about.
Now this may be great if all you’re looking for is positive answers, but if you want honest and transparent feedback that you can do something useful with, each question must be phrased without preconceived ideas.
Leading question example
The following question offers a good illustration, of the sort of bias that can arise when a respondent is asked a leading question.
Which is a better use of end-of-year profits for the employees: extra paid time off, or a holiday bonus?
In this example, the survey recipient is constrained to two options disguised as an open-ended question. If they had been given the ability to answer honestly, the respondent may have suggested a completely different priority, such as a charity donation or a company party. Instead, they’re forced to choose between two options that may have little interest to them.
A better and more bias free way of asking this question would be.
How would you like to see extra profits at the end of the year being used to reward the employees for their hard work?
The difference between loaded and leading questions
Hopefully, having read our outline of loaded and leading questions, you should now be aware of the main differences between the two.
While loaded questions aim to push recipients towards making a particular response, based on assumptions they make about that respondent, leading questions look to get people to answer a question in a specific way, by the way they’ve phrased that question.
However, while the differences between the two are slight, the key thing to remember about loaded and leading questions is that they both end up confusing, misleading, or influencing users into making a particular selection.
Often, they’re created unintentionally and sometimes deliberately. Yet, in nearly all cases, it’s possible to modify both loaded and leading questions to present better options to respondents and gain more accurate results as a consequence.
How to avoid biased questions in surveys
From words that are overcharged with strongly negative or positive emotions to phrasing within a question that implies bias towards a specific answer. Whenever you’re creating a survey or questionnaire, it can be so easy to inadvertently bring bias into it.
Consequently, it can be helpful to have some tips to hand offering advice about what you can do to minimise the potential of question bias slipping into your survey.
Review your questions and ask yourself if there’s a particular way you want a question to be answered or a certain type of response you’re expecting. Then reword your questions to focus on all options. Don’t just ask readers to confirm something you believe to be true.
Next, examine the words you’re using. Are you describing something in a biased way?
Remove any biased language and describe options using clear and precise phrasing. Be careful not to imply that any response is better than another.
Next, check if any of the questions you’re looking to ask will require users to give an answer that may not completely represent their response.
If you’re in any doubt about whether you have covered off all the options your respondent expects to see, make sure you include an ‘other’ option to cater for this.
We hope you have found this blog helpful and will be able to put some of the advice to use in your next survey to help reduce bias.
The key thing to remember is that the goal of any survey is to identify what’s working, what isn’t, and where there is any room for improvement.
If a survey contains loaded and leading questions that influence respondents to answer in a particular way, the organisation running that survey will miss out on honest feedback that could have otherwise provided them with unexpected insights and benefits. That alone makes checking for and removing any bias from your survey, a very worthwhile task for you to undertake.