Observer-expectancy effect

Observer-expectancy effect (also known as the experimenter-expectancy effect, expectancy bias, observer effect, or experimenter effect) is a form of Cognitive bias that occurs when a researcher's cognitive bias causes them to subconsciously influence the participants of an experiment. This effect is closely related to the Hawthorne effect and Confirmation bias, and is considered a significant threat to the validity of an experiment in social sciences, Psychology, and Medicine.

Overview

The observer-expectancy effect can lead to the alteration of measurement of the outcome of an experiment due to the researcher's cognitive bias. This can occur in any form of scientific research, including Psychology, Medicine, and Physics, but is most notable in fields involving human subjects. The effect was first described by Psychologist Robert Rosenthal in 1966.

Mechanism

The mechanism behind the observer-expectancy effect involves subtle cues or signals from the experimenter to the participants about the expected outcome of the experiment. These cues can be non-verbal, such as body language or tone of voice, or verbal, through the wording of questions or instructions. Participants may alter their behavior based on these cues, leading to data that confirms the experimenter's expectations rather than the true nature of the phenomenon being studied.

Examples

One classic example of the observer-expectancy effect is the Clever Hans (a horse) phenomenon, where a horse seemed to be able to perform arithmetic operations. The horse's owner was unknowingly giving cues to the horse about when to start and stop tapping its hoof to signal the answer to mathematical problems.

Mitigation

To mitigate the observer-expectancy effect, researchers can employ several strategies, including:

• Using Double-blind study designs, where neither the participants nor the experimenters know which participants belong to the control group and which to the test group.
• Training experimenters to remain as neutral as possible in their interactions with participants.
• Utilizing automated systems to record responses, thereby reducing human interaction and potential bias.

Impact

The observer-expectancy effect can have a profound impact on the validity of research findings. It can lead to false positives, where effects are observed when they do not actually exist, potentially leading to the publication of incorrect or misleading scientific information. This effect underscores the importance of rigorous experimental design and the need for replication of studies to confirm findings.

See also

• Placebo effect
• Pygmalion effect
• List of cognitive biases

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