The observer expectancy effect arises due to demand characteristics, which are subtle cues given by the researcher to the participant about the nature of the study, as well as confirmation bias, which is when the researcher collects and interprets data in a way that confirms their hypothesis and ignores information that contradicts it.
Demand characteristics are a form of response bias that may give rise to the observer expectancy effect. Typically seen in psychological research, demand characteristics are subtle cues from the experimenter that may give the participants some idea of what the study is about. While some information about the study must be divulged to the participants for ethical reasons, it is ideal for participants to know as little as possible about the nature of the research being done. The more participants know, the more likely it is that they will try to “help” the researcher by behaving in the way they think the researcher wants them to. Unfortunately, when this happens, the data collected is inaccurate and therefore not very informative.
Many things can act as demand characteristics. Any verbal or non-verbal communication between the participant and the experimenter, the appearance of the room where the study is being held, and any knowledge the participant might have of the kind of work the lab does could all suggest certain behaviors to the participants. Naturally, demand characteristics cannot be eliminated completely, but their effects can be minimized.
Participants may provide biased responses in studies due to social desirability – wanting to give a good impression of themselves. However, it has been shown that, when participants have some knowledge of the researcher’s hypothesis, they are more likely to respond in a way that they think will benefit the researcher, whether or not it makes them look good. They do not want to provide “bad” information that would ruin the study or disprove the researcher’s hypothesis.1
Despite the good intentions of many participants, demand characteristics give rise to the observer expectancy effect, which compromises the accuracy of the study. Accurate data that yield no significant results are more informative and more valuable than inaccurate data that yield significant results.
Another factor that contributes to the observer expectancy effect is confirmation bias. Researchers are highly motivated to find evidence in support of their hypothesis, particularly now, when it is so difficult to get papers published in reputable journals. The intense motivation to collect data in support of a hypothesis can cause researchers to selectively notice and remember information that aligns with their hypothesis. This biased interpretation of data is referred to as confirmation bias.
The motivated search for information that confirms their hypothesis can lead experimenters to interpret participants’ behavior in a way that confirms their hypothesis. However, confirmation bias not only affects how we interpret data; it influences how we collect the data in the first place. As such, researchers may ask participants leading questions, which prompt a specific response, or even treat participants in a way that elicits the desired behavior. Of course, the data collected under such conditions is not accurate and therefore not helpful in the progression of knowledge.