Participant bias: Types, Reasons, & Measures


Participant bias: Types, Reasons, & Measures Participant bias
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Researchers rely on their survey participants for reliable data. Any data collecting method, be it online, phone surveys, interviews, focus groups, and more, are dependent on what the respondents feed into them. This data then goes further for analysis and derives relevant insights from it. 

Since the entire business decisions are based on such participant data, it is important to pay attention to errors that might happen from their side. This error is called participant bias. 

Here, we will discuss what is participant bias.

What is participant bias?

When participants react in specific ways, they want to match what they think the researchers are searching for, known as participant bias. 

While not acting in their usual manner, the person is reacting how they believe they should. This can be harmful since it may appear as though an independent variable was impacting the result when the participant acted in a way that suggested it was. 

Utilizing blind studies and lowering demand characteristics are two ways to prevent participant bias.

Participants could change their behavior because they are aware that they are a part of a study, which can result in a lack of validity. The behavior they display is influenced by how they perceive the research project, the researcher, and the researcher’s behavior toward them.

Now that we have established what is participant bias, we will dive into what causes the bias. 

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What causes participant bias?

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As we know, participant bias occurs when the participants answer the survey in a way that is not personal to them but is generalized and framed to be accepted by the researcher. Although the reason behind it is simple from a researcher’s perspective, what makes the participants create this bias? 

Well, let us discuss some of them:

1. Participant fatigue 

Participants who are worn out from the survey work. The participant’s perception of the data quality will begin to deteriorate. This will result in the participants’ attention waning, especially during the survey’s final sections. Fatigued participants may continue to respond with “don’t know” or select a “straight-line” response. 

2. Question framing: 

How the survey’s questions are phrased contributes to participant bias. How the participants see the researcher affects how they will react. Hence, it is always advised to focus more on survey questions and shouldn’t be leading in any way.

3. Desired image

The desire to be good experimental subjects may occasionally be present in the volunteers. They might respond in a way that is seen as acceptable by society as a result. This happens mostly in surveys that are not anonymous, and the responses are mapped to respective participants. 

How can you detect participant bias?

Most of the time, participant bias in research goes unnoticed at a glance. But they do come up and affect the integrity of the data when it is time to analyze it. 

The prevention and redress of biases can be more challenging. The researcher should ensure that all of the studies have a high-reliability level. The researcher should also ensure they know all the details on the individuals.

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What are the different types of participant bias?

In this section of the article, we will look at various types of participant biases and some closely related to it.

1. Acquiescence bias

Acquiescence bias, commonly known as “yea-saying,” is a type of participant bias in which survey participants tend to agree with all the items in a measure. 

Because the participant immediately supports all statements, even though the results are conflicting responses, this bias may indicate a sort of dishonest reporting.

For instance, if a participant agrees with the statement, “I like to spend time with people,” and later again agrees with the statement, “I prefer to spend time alone,” the data would be unreliable.

2. Confirmation bias 

This type of participant bias results from the tendency of people to seek out information that supports their own opinions while rejecting information that contradicts them. 

The researcher may disregard all contradicting information and rely solely on participant data to validate their hypothesis, thus resulting in skewed results. 

Imagine, for instance, that someone thinks left-handed people are more imaginative than right-handed people.

3. Demand Characteristics Bias 

Any research can fall victim to demand characteristics bias. It happens when respondents try to understand the goal and adjust their behavior or response to be “right.” 

Here are some of the biased characteristics;

  1. Rumor: There is news about the company in the market every other day. If respondents know about any of the information, whether fake or real, they start to believe it and follow.
    For example, they might have heard that if you fill out a brand recognition survey with positive answers, you would be given a free 1-year subscription to the brand’s service.
  1. Setting: The brand or the company that conducts a survey, is influenced by the area in which a survey is set or performed. 
  2. Communication: Communication plays a vital role in influencing the response. Any kind of verbal or non-verbal communication between the respondent and the survey conductor can influence the response to the survey. 

4. The Halo effect 

In an experiment, this bias also occurs because we tend to overlook the flaws of people we like and look for the best in them regardless. To gauge a person’s opinions, a researcher should anticipate that if a subject has a favorable opinion of something, they will feel the same way about items that are similar to what they enjoy. 

For instance, a player who enjoys football might also enjoy other ball-related sports, like basketball, handball, and volleyball.

5. Question Order Bias

While conducting a survey, it is important to look after the order of the question you ask them. Which question you put first and how you arrange them can influence a participant’s response. 

Contrast Effect: 

Sometimes, how and when you ask the questions leads to a difference in the answer. 

For example, if you survey customers before any service about their overall satisfaction with the banquet at your restaurant, the satisfaction level may be very low. However, when you ask about specific services such as reservation, food, staff behavior, hygiene, etc., the satisfaction can be higher than for specific events. 

Assimilation Effect: 

Grouping questions together can also lead to participant bias. Respondents often provide answers which are consistent with their previous answers. 

For example, let’s say you ask your participant if they like to party every weekend, and most of them respond “yes.” When you follow it up by asking what they like to do every weekend, the same participant will reply they like to party. 

6. Social desirability

When respondents select responses based on what they believe to be socially acceptable, this happens. Participants may respond in a way that results in a greater proportion of “preferred” answers or a smaller proportion of “undesirable” responses.

The survey questions most likely impacted by participants’ social prejudice are those dealing with health, wealth, politics, and religion. 

For instance, if a participant is asked, “How frequently do you drink alcohol?” they might respond, “Least frequently,” which may not be accurate. Most people would downplay driving after drinking because it would reflect negatively on them and elicit negative reactions from others.

7. Extreme response bias 

This participant bias arises when respondents come up with answers wildly out of line with their true opinions. Usually, it is the outcome of an underlying bias.

For instance, excessive response bias also occurs when a responder chooses the most “positive” responses in a customer satisfaction survey while under the influence of acquiescence bias. Extreme response bias can also result from habituation bias, as respondents may routinely select the lowest or highest option out of habit or exhaustion.

To lessen excessive response bias, researchers should ensure question variety, unsuggestive wording, and respondent anonymity.

8. Non-response bias 

When potential respondents choose not to participate or finish a survey, this is known as non-response bias. Numerous factors, including respondent tiredness, privacy concerns, a difficult survey design, awkward question wording, or a survey that is irrelevant to the respondent, might cause this.

For instance, if a survey has too many open-ended questions, respondents could feel overburdened and decide not to finish it. Researchers should keep surveys as short as possible, with precise wording and instructions, and seek respondents relevant to the survey issue to reduce non-response bias.

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How to deal with participant bias?

Let us see how we can reduce, avoid or deal with the participant bias we find in our surveys and data. 

  • Question framing

To lessen acquiescence bias, the researcher should make use of diverse question types to keep respondents engaged. Yes/No, True/False, and Agree/Disagree are also included in this leading response. Dual negative-positive scale answer formats help minimize this kind of bias. The outcomes are also more similar across boards as a result.

  • Participant anonymity

Researchers should ensure participant anonymity and make individuals anonymous to lessen social desirability bias. Additionally, the researcher should word the questions in a non-suggestive way.

  • Analyze with an open mind

If researchers approach the analysis of current hypotheses with an open mind and consider all the available evidence, confirmation bias effects can be reduced. The researcher should be aware that the analysis may disprove the hypothesis.

  • Keep participants engaged

The habituation bias can be avoided if the researcher uses diverse question wording and an engaging tone to keep the respondents engaged.

  • Avoiding influences

If the researcher refrains from influencing the participants’ experiences before the study material is given to the participants, the halo effect bias can be avoided. It is crucial that the researcher only gives the participant the necessary information for the job at hand.

[Related read: Eliminating the Risk of Response Bias]


Participant bias happens at the participant’s end and is inevitable. That being said, a researcher must be ready to face it and expect participant bias in his data. There need to be proper measures taken to deal with the bias and try to minimize it. 

When handled correctly, you can prevent participant bias from impacting survey results. 

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