RESEARCH STARTER

Observer expectancy effect

The observer expectancy effect refers to a psychological phenomenon where the expectations and biases of an observer or experimenter influence the outcomes of an experiment, survey, or activity. This effect can manifest in subtle forms, such as body language or facial expressions, or through more explicit actions like the way questions are framed. It often occurs without the observer's conscious awareness, shaped by their personal experiences and beliefs. This cognitive bias can have significant implications, not only in scientific research but also in everyday interactions, such as education and workplace dynamics.

In scientific contexts, the observer expectancy effect can lead to skewed results if, for instance, an experimenter inadvertently signals desired outcomes to participants. Notably, techniques like double-blind studies are employed to mitigate these biases by ensuring that neither the participants nor the experimenters know who is receiving the treatment versus a control. Real-world examples illustrate how expectations can create self-fulfilling prophecies, such as when teachers or parents adjust their behaviors based on preconceived notions about a child's abilities. Recognizing and addressing the observer expectancy effect is crucial for obtaining accurate results in both experimental and everyday situations.

Full Article

Observer expectancy effect is a term used to describe when the results of an activity such as an experiment or survey are altered by what the person conducting the activity expects to happen. It is an example of a psychological bias. Observer expectancy effect is sometimes referred to as the experimenter expectancy effect. It is also known as experimenter effect or expectancy bias.

In the observer expectancy effect, the attitudes and preconceived notions of the person conducting the activity alter the situation in some way. This can be subtle, such as a facial expression or gesture, or more overt, such as the type of questions used in a survey or the way an experiment is set up. These influences often occur subconsciously and are based on the observer or experimenter’s personal experiences, knowledge, and opinions. Everyone has biases and opinions, and a person’s experiences and previous knowledge are an inevitable part of how they approach an activity. However, finding ways to minimize the impact of opinions and expectations and avoiding the observer expectancy effect is vital to obtaining accurate results when conducting scientific and educational activities.

Though it is most often thought of in the context of scientific experimentation, the observer expectancy effect has implications in everyday life as well. For example, teachers who think children from certain social or economic backgrounds are less capable of learning may stunt the children’s education by providing less challenging opportunities. They may also subtly convey to the student that they are less capable, causing the student to have lower expectations of their own abilities.

Background

The observer expectancy effect is an example of a cognitive bias. A cognitive bias is a fundamental error in the thought process that affects a person’s expectations, decisions, and judgments. It results from the brain’s efforts to streamline the complicated thinking and decision-making processes it continuously controls.

This can be necessary and beneficial. For example, if the brain of a driver proceeding through an intersection had to stop to analyze what kind of vehicle was speeding towards their car, the brain might not have time to react and send signals that direct the driver to turn and accelerate to safety. Instead, the brain generalizes to “speeding car coming” and triggers a reaction.

These same types of generalizations can also lead to faulty decisions. If a person once purchased a generic shampoo and had an allergic reaction to it, that person may make the generalization that all generic shampoos are going to cause allergic reactions and refuse to try them again. In reality, the shampoo ingredient that caused the allergic reaction may only be in one brand’s product. In this case, the person’s bias towards generics is unsubstantiated and does little except cost them more money.

One form of cognitive bias closely associated with the observer expectancy effect is confirmation bias. Confirmation bias occurs when a person chooses data and information that supports a preconceived expectation about a situation. For example, a person who thinks hockey referees are biased against their favorite team is likely to notice all the times when the referee’s actions negatively affect their team. They may also discount times when the referee’s actions favor their team.

Confirmation bias is particularly problematic when it comes to scientific experiments because it can drastically affect the outcome and findings from the experiment. One famous case of confirmation bias was an experiment conducted in the 1960s by English psychologist Cyril Burt. Burt was conducting experiments to determine if intelligence was hereditary. He believed that people from the working class were less intelligent than those from the upper class. He devised an experiment to test the intelligence of schoolchildren, which confirmed his expectation that working-class children scored lower than those from higher social classes. Burt’s research had a significant impact on British schools. It led to a multi-tiered education system that was thought to accommodate the intelligence and ability of the respective classes. It provided better educational experiences for children of the middle and upper classes and less demanding schools for children of the working class. However, subsequent investigations identified serious irregularities in his later data and methods, and many scholars concluded that at least some of the data had been manipulated or fabricated. His experiment’s design and the way it was conducted were later found to have been affected by his expectations, and his findings were later widely questioned.

Overview

The observer expectancy effect occurs when an observer or experimenter allows their personal opinions or biases to affect an experiment, test, survey, or other situation. This often occurs without the experimenter or observer being aware of the impact they are having. The experimenter may structure the experiment in a way that encourages the results they expect. They may also directly affect the outcome by giving signals as to what they think should or will happen, thereby altering the behavior of the participants in the situation.

For example, if an experimenter testing the effectiveness of a new medication tells the participants in the study that they are testing a new drug designed to cure their condition, the experiment’s outcome could be affected in several ways. One is the placebo effect, where people experience a positive response to a medication or procedure simply because they are told that they will. This can happen even if the person is given a pill with no medication in it at all.

The participants in the study can also actively or subconsciously absorb the expectations of the experimenter or observer from clues such as the person’s body language, questions, or other forms of interaction. Similar to how Burt’s intelligence experiments produced the results he expected based on his preconceived expectations, an observer can influence the behavior of the participants and direct the experiment’s outcome.

In addition, the mere presence of an observer has been found to have the potential to alter the results in a study or experiment. In one well-known example from the 1920s and 1930s, researchers studying worker productivity, later analyzed by Henry A. Landsberger, worked at a Western Electric facility in the Hawthorne Works in Cicero, Illinois. After researchers found productivity improved no matter what changes were made, Landsberger later suggested that the presence of the researchers affected the way supervisors treated workers, which may have influenced productivity along with other factors. This became known as the Hawthorne Effect. Later studies have suggested that changes in productivity may result from several factors, including attention, group dynamics, and changes in working conditions.

The effects of observer or experimenter influence are not limited to human participants. In the late 1800s, a German man named Wilhelm von Osten conducted experiments to test the intelligence of animals. By 1904, he believed he had taught his horse, Clever Hans, to count and do simple math problems, which he answered with taps of his hoof. The animal was tested by numerous experts and seldom failed to come up with the correct answer. He was even able to respond correctly when someone other than Von Osten asked the questions. However, it was later determined that rather than learning math, Hans had learned how to interpret the body language of Von Osten or anyone else who questioned him. The person’s reaction to Hans’ tapping the correct answer told the horse when to stop tapping. This was proven when he failed to get the correct answer when he could not see the person asking the question or when the questioner did not know the correct answer. In those cases, Hans did not have the clues necessary to know when to stop tapping.

Since the expectations or biases of the observer or experimenter are at the root of this effect, eliminating or masking those expectations and biases is crucial to preserving the integrity of the scientific findings. One way to do this is the double-blind study. In this form of experimentation, neither the participants nor the person conducting the study or experiment knows which participants are actual test subjects and which are controls. Controls are people who are similar to the test subjects but are present simply to provide a basis for comparison. Early forms of double-blind studies were developed in the early twentieth century to reduce bias in experiments. Since then, double-blind studies have become a standard in experimentation to help overcome various forms of biases, including the observer expectancy effect. Researchers also use methods such as preregistering hypotheses, using registered reports, and analyzing data without knowing expected outcomes to further reduce bias. Concerns about bias in research have also led to stronger standards for sharing data, repeating studies, and clearly reporting methods. Some studies also use automated tools to collect and analyze data, which can reduce the influence of human expectations.

The observer expectancy effect is not just limited to experimental and academic settings. It is also considered in areas such as user experience research, behavioral economics, and clinical studies, where expectations can affect how people respond. It is a factor in personal interactions and other situations as well. For example, an employee who is told a new boss is harsh and hard to work with will likely be apprehensive, standoffish, and possibly nervous when interacting with the new boss. This can lead the boss to form a negative impression of the employee, leading to a self-fulfilling prophecy of the boss being hard to work with. Similarly, parents who are told a child has been born with cognitive delays may lower their expectations for the child and provide fewer opportunities, limiting the child’s potential. Other self-fulfilling prophecy situations may also be influenced by the observer expectancy effect.

In the 2020s, the observer expectancy effect remains an important issue not only in psychology but also in clinical trials, education research, user experience studies, behavioral economics, and human–artificial intelligence (AI) decision-making. A 2025 meta-epidemiological study in the Journal of Clinical Epidemiology found that in randomized clinical trials with subjective outcomes, non-blinded assessors exaggerated effect estimates by about 29 percent on average. Research continues to increasingly combine traditional safeguards such as blinding with open-science practices, independent verification, transparent reporting, and careful oversight of algorithmic tools.


Bibliography

Azarova, Mayya. “The Hawthorne Effect or Observer Bias in User Research.” Nielsen Norman Group, 21 May 2023, www.nngroup.com/articles/hawthorne-effect-observer-bias-user-research/. Accessed 13 Apr. 2026.

Brown, Erik. “Clever Hans—The Horse that Could Count.” Medium, 12 Apr. 2019, medium.com/lessons-from-history/clever-hans-the-horse-that-could-count-561cdd5a1eab. Accessed 13 Apr. 2026.

Cherry, Kendra. “Double-Blind Studies in Research.” VeryWell Mind, 9 Jan. 2026, www.verywellmind.com/what-is-a-double-blind-study-2795103. Accessed 15 Apr. 2026.

Cherry, Kendra. “How Cognitive Biases Influence the Way You Think and Act.” VeryWell Mind, 16 Oct. 2025, www.verywellmind.com/what-is-a-cognitive-bias-2794963. Accessed 15 Apr. 2026.

Cherry, Kendra. “How the Hawthorne Effect Works.” VeryWell Mind, 3 Dec. 2025, www.verywellmind.com/what-is-the-hawthorne-effect-2795234. Accessed 15 Apr. 2026.

Ching, Teo Choong. “Types of Cognitive Biases You Need to Be Aware of as a Researcher.” UX Collective, 27 Sept. 2016, uxdesign.cc/cognitive-biases-you-need-to-be-familiar-with-as-a-researcher-c482c9ee1d49. Accessed 13 Apr. 2026.

“Expectancy Effect.” Psychology, psychology.iresearchnet.com/social-psychology/social-cognition/expectancy-effect/. Accessed 13 Apr. 2026.

Farnsworth, Bryn. “The iMotions Lab Screen-Based Eye Tracking Module [Explained].” IMotions, 9 Apr. 2026, imotions.com/blog/researcher-bias/. Accessed 13 Apr. 2026.

Hacking, Ian. Representing and Intervening. Cambridge UP, 1983.

Jordan, Katy, and Rebecca Eynon. “Open, Reproducible, and Automated Research.” Nature Human Behaviour, 2018.

Joynson, Robert B. The Burt Affair. Routledge, 1989.

Nosek, Brian A., et al. “Promoting an Open Research Culture.” Science, vol. 348, no. 6242, 2015, pp. 1422–25, doi:10.1126/science.aab2374. Accessed 13 Apr. 2026.

Salazar, Josefina, et al. “Empirical Evidence of Observer Bias in Randomized Clinical Trials: Updated and Expanded Analysis of Trials with Both Blinded and Non-Blinded Outcome Assessors.” Journal of Clinical Epidemiology, vol. 183, July 2025, p. 111787, doi:10.1016/j.jclinepi.2025.111787. Accessed 15 Apr. 2026.

“Why Do We Change Our Behavior When We’re Being Watched?” The Decision Lab, thedecisionlab.com/biases/observer-expectancy-effect/. Accessed 13 Apr. 2026.

Zhong, Yiping. “Experimenter Effect.” The ECPH Encyclopedia of Psychology, 24 Apr. 2024, doi:10.1007/978-981-99-6000-2_755-1. Accessed 13 Apr. 2026.

Full Article

Observer expectancy effect is a term used to describe when the results of an activity such as an experiment or survey are altered by what the person conducting the activity expects to happen. It is an example of a psychological bias. Observer expectancy effect is sometimes referred to as the experimenter expectancy effect. It is also known as experimenter effect or expectancy bias.

In the observer expectancy effect, the attitudes and preconceived notions of the person conducting the activity alter the situation in some way. This can be subtle, such as a facial expression or gesture, or more overt, such as the type of questions used in a survey or the way an experiment is set up. These influences often occur subconsciously and are based on the observer or experimenter’s personal experiences, knowledge, and opinions. Everyone has biases and opinions, and a person’s experiences and previous knowledge are an inevitable part of how they approach an activity. However, finding ways to minimize the impact of opinions and expectations and avoiding the observer expectancy effect is vital to obtaining accurate results when conducting scientific and educational activities.

Though it is most often thought of in the context of scientific experimentation, the observer expectancy effect has implications in everyday life as well. For example, teachers who think children from certain social or economic backgrounds are less capable of learning may stunt the children’s education by providing less challenging opportunities. They may also subtly convey to the student that they are less capable, causing the student to have lower expectations of their own abilities.

Background

The observer expectancy effect is an example of a cognitive bias. A cognitive bias is a fundamental error in the thought process that affects a person’s expectations, decisions, and judgments. It results from the brain’s efforts to streamline the complicated thinking and decision-making processes it continuously controls.

This can be necessary and beneficial. For example, if the brain of a driver proceeding through an intersection had to stop to analyze what kind of vehicle was speeding towards their car, the brain might not have time to react and send signals that direct the driver to turn and accelerate to safety. Instead, the brain generalizes to “speeding car coming” and triggers a reaction.

These same types of generalizations can also lead to faulty decisions. If a person once purchased a generic shampoo and had an allergic reaction to it, that person may make the generalization that all generic shampoos are going to cause allergic reactions and refuse to try them again. In reality, the shampoo ingredient that caused the allergic reaction may only be in one brand’s product. In this case, the person’s bias towards generics is unsubstantiated and does little except cost them more money.

One form of cognitive bias closely associated with the observer expectancy effect is confirmation bias. Confirmation bias occurs when a person chooses data and information that supports a preconceived expectation about a situation. For example, a person who thinks hockey referees are biased against their favorite team is likely to notice all the times when the referee’s actions negatively affect their team. They may also discount times when the referee’s actions favor their team.

Confirmation bias is particularly problematic when it comes to scientific experiments because it can drastically affect the outcome and findings from the experiment. One famous case of confirmation bias was an experiment conducted in the 1960s by English psychologist Cyril Burt. Burt was conducting experiments to determine if intelligence was hereditary. He believed that people from the working class were less intelligent than those from the upper class. He devised an experiment to test the intelligence of schoolchildren, which confirmed his expectation that working-class children scored lower than those from higher social classes. Burt’s research had a significant impact on British schools. It led to a multi-tiered education system that was thought to accommodate the intelligence and ability of the respective classes. It provided better educational experiences for children of the middle and upper classes and less demanding schools for children of the working class. However, subsequent investigations identified serious irregularities in his later data and methods, and many scholars concluded that at least some of the data had been manipulated or fabricated. His experiment’s design and the way it was conducted were later found to have been affected by his expectations, and his findings were later widely questioned.

Overview

The observer expectancy effect occurs when an observer or experimenter allows their personal opinions or biases to affect an experiment, test, survey, or other situation. This often occurs without the experimenter or observer being aware of the impact they are having. The experimenter may structure the experiment in a way that encourages the results they expect. They may also directly affect the outcome by giving signals as to what they think should or will happen, thereby altering the behavior of the participants in the situation.

For example, if an experimenter testing the effectiveness of a new medication tells the participants in the study that they are testing a new drug designed to cure their condition, the experiment’s outcome could be affected in several ways. One is the placebo effect, where people experience a positive response to a medication or procedure simply because they are told that they will. This can happen even if the person is given a pill with no medication in it at all.

The participants in the study can also actively or subconsciously absorb the expectations of the experimenter or observer from clues such as the person’s body language, questions, or other forms of interaction. Similar to how Burt’s intelligence experiments produced the results he expected based on his preconceived expectations, an observer can influence the behavior of the participants and direct the experiment’s outcome.

In addition, the mere presence of an observer has been found to have the potential to alter the results in a study or experiment. In one well-known example from the 1920s and 1930s, researchers studying worker productivity, later analyzed by Henry A. Landsberger, worked at a Western Electric facility in the Hawthorne Works in Cicero, Illinois. After researchers found productivity improved no matter what changes were made, Landsberger later suggested that the presence of the researchers affected the way supervisors treated workers, which may have influenced productivity along with other factors. This became known as the Hawthorne Effect. Later studies have suggested that changes in productivity may result from several factors, including attention, group dynamics, and changes in working conditions.

The effects of observer or experimenter influence are not limited to human participants. In the late 1800s, a German man named Wilhelm von Osten conducted experiments to test the intelligence of animals. By 1904, he believed he had taught his horse, Clever Hans, to count and do simple math problems, which he answered with taps of his hoof. The animal was tested by numerous experts and seldom failed to come up with the correct answer. He was even able to respond correctly when someone other than Von Osten asked the questions. However, it was later determined that rather than learning math, Hans had learned how to interpret the body language of Von Osten or anyone else who questioned him. The person’s reaction to Hans’ tapping the correct answer told the horse when to stop tapping. This was proven when he failed to get the correct answer when he could not see the person asking the question or when the questioner did not know the correct answer. In those cases, Hans did not have the clues necessary to know when to stop tapping.

Since the expectations or biases of the observer or experimenter are at the root of this effect, eliminating or masking those expectations and biases is crucial to preserving the integrity of the scientific findings. One way to do this is the double-blind study. In this form of experimentation, neither the participants nor the person conducting the study or experiment knows which participants are actual test subjects and which are controls. Controls are people who are similar to the test subjects but are present simply to provide a basis for comparison. Early forms of double-blind studies were developed in the early twentieth century to reduce bias in experiments. Since then, double-blind studies have become a standard in experimentation to help overcome various forms of biases, including the observer expectancy effect. Researchers also use methods such as preregistering hypotheses, using registered reports, and analyzing data without knowing expected outcomes to further reduce bias. Concerns about bias in research have also led to stronger standards for sharing data, repeating studies, and clearly reporting methods. Some studies also use automated tools to collect and analyze data, which can reduce the influence of human expectations.

The observer expectancy effect is not just limited to experimental and academic settings. It is also considered in areas such as user experience research, behavioral economics, and clinical studies, where expectations can affect how people respond. It is a factor in personal interactions and other situations as well. For example, an employee who is told a new boss is harsh and hard to work with will likely be apprehensive, standoffish, and possibly nervous when interacting with the new boss. This can lead the boss to form a negative impression of the employee, leading to a self-fulfilling prophecy of the boss being hard to work with. Similarly, parents who are told a child has been born with cognitive delays may lower their expectations for the child and provide fewer opportunities, limiting the child’s potential. Other self-fulfilling prophecy situations may also be influenced by the observer expectancy effect.

In the 2020s, the observer expectancy effect remains an important issue not only in psychology but also in clinical trials, education research, user experience studies, behavioral economics, and human–artificial intelligence (AI) decision-making. A 2025 meta-epidemiological study in the Journal of Clinical Epidemiology found that in randomized clinical trials with subjective outcomes, non-blinded assessors exaggerated effect estimates by about 29 percent on average. Research continues to increasingly combine traditional safeguards such as blinding with open-science practices, independent verification, transparent reporting, and careful oversight of algorithmic tools.


Bibliography

Azarova, Mayya. “The Hawthorne Effect or Observer Bias in User Research.” Nielsen Norman Group, 21 May 2023, www.nngroup.com/articles/hawthorne-effect-observer-bias-user-research/. Accessed 13 Apr. 2026.

Brown, Erik. “Clever Hans—The Horse that Could Count.” Medium, 12 Apr. 2019, medium.com/lessons-from-history/clever-hans-the-horse-that-could-count-561cdd5a1eab. Accessed 13 Apr. 2026.

Cherry, Kendra. “Double-Blind Studies in Research.” VeryWell Mind, 9 Jan. 2026, www.verywellmind.com/what-is-a-double-blind-study-2795103. Accessed 15 Apr. 2026.

Cherry, Kendra. “How Cognitive Biases Influence the Way You Think and Act.” VeryWell Mind, 16 Oct. 2025, www.verywellmind.com/what-is-a-cognitive-bias-2794963. Accessed 15 Apr. 2026.

Cherry, Kendra. “How the Hawthorne Effect Works.” VeryWell Mind, 3 Dec. 2025, www.verywellmind.com/what-is-the-hawthorne-effect-2795234. Accessed 15 Apr. 2026.

Ching, Teo Choong. “Types of Cognitive Biases You Need to Be Aware of as a Researcher.” UX Collective, 27 Sept. 2016, uxdesign.cc/cognitive-biases-you-need-to-be-familiar-with-as-a-researcher-c482c9ee1d49. Accessed 13 Apr. 2026.

“Expectancy Effect.” Psychology, psychology.iresearchnet.com/social-psychology/social-cognition/expectancy-effect/. Accessed 13 Apr. 2026.

Farnsworth, Bryn. “The iMotions Lab Screen-Based Eye Tracking Module [Explained].” IMotions, 9 Apr. 2026, imotions.com/blog/researcher-bias/. Accessed 13 Apr. 2026.

Hacking, Ian. Representing and Intervening. Cambridge UP, 1983.

Jordan, Katy, and Rebecca Eynon. “Open, Reproducible, and Automated Research.” Nature Human Behaviour, 2018.

Joynson, Robert B. The Burt Affair. Routledge, 1989.

Nosek, Brian A., et al. “Promoting an Open Research Culture.” Science, vol. 348, no. 6242, 2015, pp. 1422–25, doi:10.1126/science.aab2374. Accessed 13 Apr. 2026.

Salazar, Josefina, et al. “Empirical Evidence of Observer Bias in Randomized Clinical Trials: Updated and Expanded Analysis of Trials with Both Blinded and Non-Blinded Outcome Assessors.” Journal of Clinical Epidemiology, vol. 183, July 2025, p. 111787, doi:10.1016/j.jclinepi.2025.111787. Accessed 15 Apr. 2026.

“Why Do We Change Our Behavior When We’re Being Watched?” The Decision Lab, thedecisionlab.com/biases/observer-expectancy-effect/. Accessed 13 Apr. 2026.

Zhong, Yiping. “Experimenter Effect.” The ECPH Encyclopedia of Psychology, 24 Apr. 2024, doi:10.1007/978-981-99-6000-2_755-1. Accessed 13 Apr. 2026.

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