Participants And You? How Participants Participate in Research

Your hypothesis is formulated, your study is outlined, you are ready to go ahead with testing your research thesis. Now all that’s left is to find participants who will provide their thoughts on the topic or choose between the red and blue pill. For a minute, let’s put aside where you’ll find the right folks to fit your particular parameters.

How do you make sure your subjects are not just telling you what they think you want to hear when they fill out your 30-page questionnaire or when they pick between Coke and Pepsi? Each participant is different, but each comes with their own set of preconceptions and biases.

Research has identified three types of subjects in the lab:

  1. The negativistic subject who wants to disprove the experimenter’s hypothesis. The subject may be upset at having to give up their time for the study, or that they are not in control, but whatever the reason the subject wants to disconfirm the experimenter. Think about the forced volunteers of Psychology 101 who have to toil for 20 hours of “volunteer” participant studies—no one said they had to be honest.
  2. On the other hand the good subject wants to benefit science or the experimenter and they consciously or subconsciously tell the experimenter what the subject thinks the experimenter wants to hear. Participants may subconsciously look for and answer with the “right answer” instead of giving their true opinion.
  3. Third is the apprehensive subject who wants to “look good” in the eyes of the experimenter. When asked a question that has a response which might make the subject look bad, the subject may lie to look good. For example, if you were to ask a subject whether they would help a stranger in dire trouble, they would of course tell you they would… however, the real answer may be quite different.

Even participants who think they are telling the truth may be subconsciously telling you what they think of themselves, vs. what they actually do or choose. This is a general phenomenon referred to as “self-enhancement” — overestimating that one would engage in a positive action, but being remarkably accurate predicting the action of strangers. For example, subjects overestimated the amount of money they would give to charity while being spot on estimating the donations of others. In general, people think of themselves as above average — a statistical impossibility. Just ask anyone: they do above average work, drive above average, participate in civics more than your average voter.

And remember, researchers have biases too that they may subconsciously impress on the participant. A researcher may subconsciously, through body language or verbal tone, convey to the participant “the right answer” for the task or question, which the participant then selects or does over the other options.

Knowing the environment of your study and the possible participant biases, conscious and subconscious, is the first step in properly structuring your experiment. Think through which interactions the participants will have with the researcher and how to best normalize those interactions so that participant biases do not enter the equation. Are double blind studies possible? Can you anonymize your interactions with the participants? How carefully are you screening your participants ahead of time to ensure that only participants with your specific demographic requirement are showing up to your study?

For this reason, Research And Me connects researchers and participants in an anonymous Internet medium, using detailed screening questionnaires that researchers build ahead of the participant selection. At the end of the day (or at the beginning of your study) understanding your own and your research team’s biases is instrumental — they all play heavily into getting truthful and accurate responses.


Research And Me is a study recruitment service that applies the scientific method to ensure that research recruitment is efficient, quick, and simple.

Participants And You? How Participants Participate in Research

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