Research is always complex, with many factors and characteristics to consider thoroughly. Even one variable thrown off can mess up the entire experiment. This is particularly true when human participants are involved, because in order for the research to be wholly accurate, the information must be completely honest and unbiased. However, human behavior is not always predictable.

The importance of neutrality and lack of bias in a study is one of the most critical pieces for a researcher to focus on. Any perceived bias, either explicit or implicit, could reduce the legitimacy of the entire experiment. To prevent this from happening, researchers have to be aware of the psychology behind human behavior to watch for irregularities and inconsistencies, like the Hawthorne Effect. This psychological phenomenon is frequently seen in human participants, and in order for a scholar to analyze their data accurately and optimally, they have to know what to look for.

What is the Hawthorne Effect?

When it comes to human behavior in research studies, the Hawthorne Effect is one of the most commonly discussed psychological aspects. This term is used to describe the frequently seen tendency of individuals to change their behavior when they know they are participating in research. Typically, people will work harder, boosting performance levels because they are involved in a study. It sounds like a good problem, but it muddies the water and makes it more difficult for a scholar to narrow down whether the independent variable they are studying is responsible for the change or not.

This phenomenon was initially described academically in the 1950s by Henry A. Landsberger. He was evaluating experiments that had occurred in the ‘20s and ‘30s, taking place at Western Electric’s Hawthorne Works electric company in Illinois. Even back then, business owners were concerned about improving the productivity of their workers, and the company had requested research to see how the work environment played a role in productivity. But when the variables were analyzed, the results showed that it really didn’t matter what change in the environment was discussed. They all led to an increase in productivity from the workers, whether the variable was a good or bad change.

This led to Landsberger’s groundbreaking realization that once people know they’re part of a study, they will perform better.

How Does the Hawthorne Effect Impact Research?

Knowing that your human participants are likely to behave outside of their normal parameters when they know they’re being observed helps you to watch for tells. This “honeymoon period” probably isn’t going to last the whole time. Once they feel comfortable with their role, and with you or whoever they are working with during the study, they will begin to act naturally.

Because of this tendency, it’s often suggested that clinical trials be extended longer than would be necessary otherwise. This way, you can observe the participants longer, check for change from the initial time period when the Hawthorne Effect is most likely to be in play, and then separate the variables to determine if what you’re experimenting with is actually working.

Other Psychological Factors to Watch For

The Hawthorne Effect isn’t the only psychological factor that researchers must be aware of in their human participation studies. Other variables can account for increased productivity, too, such as:

●      Researcher bias cues, in which the researcher gives subtle hints that give away what they are looking for from the participant. Since people typically want to please the other person, they may change their responses or behaviors to meet the biased cue given by the academic expert, who might not even realize they’re displaying it.

●      Feedback, in which the experimenter gives the worker attention that they were looking for, offering performance feedback that results in improved productivity but wasn’t directly due to the variable being observed.

●      Novelty, which is anything different from the normal daily routine. When an individual knows they are being observed, the newness of the situation alone could result in increased productivity until it wears off.

Between these factors and the Hawthorne Effect itself, scholars need to be cautious of accepting data during this initial “honeymoon period.”