How to Reduce Social Desirability Bias

Many of us can probably relate to the following situation. When we’re in new or unfamiliar social surroundings, we will often mask our true selves and present a version of our ourselves that we believe others will find more favourable.

This can happen online too, particularly on social media sites. For example, an influencer could promote healthy eating online, which contrasts with their offline lifestyle, living off coffee and convenience foods.

It could be argued that in both scenarios behaviour is adapted, so it’s more socially desirable to the respective audiences.

What is Social Desirability Bias?

Social desirability bias refers to our tendency to respond in ways that we feel are more appropriate or socially acceptable to others. Even if untruthful.

This can be an issue for some survey takers too, especially when the content is of a sensitive nature. This can result in people answering questions according to how they think their responses will be viewed by others, instead of answering truthfully. The answers they provide, can also be inflated to reflect “good behaviour” or under-inflated to hide “bad behaviour”.

For example, think about the following survey question: “How many alcoholic drinks do you consume in a day?”.

A respondent might answer 1 or 2, to appear more socially acceptable, hiding the 4 or 5 they really consume.

This may not pose a problem if just a few individuals answered in this way. However, if many people answered untruthfully, it could skew your results.

In fact, bias is a well-known issue that can easily creep into surveys, if researchers are not vigilant. Sampling bias is a good example. This happens when the methods used unwittingly favour certain outcomes over others, such as when participants are not accurately selected.

Social desirability bias in surveys can be exacerbated when they’re delivered to recipients face to face or over the phone. In such scenarios there is often a greater desire among respondents to be viewed more favourably by their interviewer. This can lead to them providing the answers they think their interviewer will want to hear.

It’s therefore prudent to consider ways to reduce social desirability bias in your survey.

How to avoid Social Desirability Bias

With more careful consideration during survey planning and survey design, you can reduce your chances of experiencing social desirability bias.

Here are some of our top tips:

• Use an online survey (no in-person contact)

One of the most effective ways to start is with an online survey. One of the key advantages of online surveys, is that they don’t require an interviewer to administer them. Not only does this help to reduce expense, but more importantly there’s no longer any third party involved who could unwittingly influence how a respondent answers your survey – significantly reducing your chances of social desirability bias.

• Use an anonymous survey (no identifying information)

Think about issuing an anonymous survey to your recipients. This allows respondents to answer your questions, without having to leave any identifying details, which also includes their IP address.

The great thing about anonymous surveys, is that when people are confident that they can answer all your questions without the risk of identification or potential reprisal, they will be more likely to answer truthfully. It’s why many employee surveys are anonymous, as employers can gather much more valuable information about how staff are feeling.

• Keep the purpose of your survey vague

Depending on the nature of your organisation or your survey’s overall aim, you may want to think about keeping your survey’s purpose relatively vague in order to elicit more honest responses.

For example, if your organisation was a supporter of animal rights and you wanted to survey people about their views related to this, but it was obvious from the outset who you were and what you supported, you might find people seriously underestimating or overestimating some of their answers. This could include anything from how much meat they eat, to the number of products they use which are free from animal testing.

• Take care over questions

Think too about the wording you use. Response bias can be an issue with some types of survey questions, such as open-ended ones, if the questions have been badly worded.

Poorly constructed questions that end up producing leading questions are a good example of this. They can unwittingly lead respondents down a particular route with their answers.

For example, “How amazing was your experience with our customer service team?”

By communicating to respondents that you think your customer service team is amazing, you’re already squeezing out the potential for them to provide another answer, which could provide more valuable insight.

Another challenge is to avoid wording questions in such a way that they force respondents into providing an absolute categorical response when they might not have one.

For example, “Do you always use product X for your cleaning needs”

The problem here is that the chances of someone using your product 100% of the time will be very slim. Given that the answer will be mostly no, the response to this question is likely to produce a poor result.

• Consider using a consumer panel

The final area to think about is using a consumer panel. A consumer panel is ideal when you need to find survey participant’s fast, or you don’t have a sufficient volume of the correct audience among your existing contacts.

Consumer panels typically offer instant access to millions of respondents around the world. This makes them one of the most effective ways of reaching the exact demographic or niche audience group you require, such as age group, income, occupation and more.

Other benefits include the careful vetting of audiences to ensure they’re right for your survey. This includes the use of disqualification questions. These eliminate respondents from completing your survey, if they are unable to answer these questions correctly at the beginning. This helps to maintain the quality of your survey data.