Do you remember being in school and having your teacher look over your shoulder as you completed an exam or a worksheet? Or perhaps you’ve had a boss who is a bit of a micromanager, scrutinizing your every move. Maybe growing up, you experienced helicopter parenting from a parent or babysitter following you around, watching to see exactly where you’re going and what you’re doing. In these situations, you may have noticed your productivity change—perhaps working more carefully or trying harder—simply because you knew someone was watching.

The Hawthorne effect describes how people tend to change their behavior when they’re aware of being observed, often resulting in short-term boosts in performance. This phenomenon is frequently seen in social and clinical research. Although most participants are well-intentioned, answering questions or contributing to an experiment in a research environment might shift people’s natural behavior and responses, whether consciously or unconsciously.

Participating in a study can be exciting and often rewarding—especially when there’s a financial incentive involved—but when participants are eager to help the researchers, they may unwittingly work to confirm the researchers’ hypothesis or bias the data in other ways, a related phenomenon known as demand effects. The Hawthorne effect reveals one way that experimental environments influence subjects beyond the introduction of particular variables, and it continues to shape how we conduct and interpret research in social science.

Observer-Expectancy Effect: How the perceived expectations of an observer can influence the actions of the people being observed. This term is usually used in a research context to describe how the presence of a researcher can influence the behavior of participants in their study.

Social Facilitation: The tendency of individuals to improve their performance on a task due to the real or perceived perception of others.

Productivity: The measure of efficiency in performance or output, a dependent variable analyzed in the Hawthorne studies to determine the effects of workplace changes on employees.¹

Experimenter Bias: A type of bias introduced when researchers’ expectations or beliefs influence the outcome of a study, whether through the observer-expectancy effect or by other means. 

Workplace Dynamics: The social and psychological interactions among employees that can influence behavior and performance.

Psychological Engagement: The level of mental and emotional involvement individuals have in their tasks, believed to have been heightened during the Hawthorne experiments due to the attention they received.¹

Performance Metrics: Quantitative measures used to assess productivity or output, which were central to evaluating the results of the Hawthorne studies.¹

Experimental Design: A structured process used to plan and conduct experiments. It involves defining and manipulating variables, such as lighting and work schedules in the Hawthorne experiments, to assess their impact on dependent variables such as participant behavior.

The Hawthorne effect gets its name from the original Hawthorne studies, a series of experiments conducted at the Western Electric Hawthorne Works factory in Cicero, Illinois, from 1924 to 1932, led by the Australian psychologist Elton Mayo. Mayo worked with American sociologist W. Lloyd Warner to run the experiments, which were originally aimed at understanding how physical working conditions such as lighting levels affected worker productivity—but the researchers soon began to take note of surprising results, leading to unexpected takeaways.^2,3,4

The setup of one of the experiments involved tracking workers’ productivity levels across two different rooms: the control room, where workers performed their daily tasks under the lighting levels they were already accustomed to, and the experiment room, where they worked under varying light levels. The scientists hypothesized that as the amount of light increased in the experiment room, the workers would become more productive. 

Instead, the researchers found that as they increased the brightness in the experiment room, the workers’ productivity improved in both rooms. Even more confusingly, when the researchers dimmed the lights, productivity also increased. It was clear to the researchers that a confounding variable was at play, and that the changes in lighting levels were likely not impacting productivity (unless, of course, the lighting was completely reduced and the factory workers were forced to perform in the dark).^2,3,4

Around the same time, in 1927, the same researchers conducted another study, looking at productivity among telephone relay workers. In this case, they chose two female workers as test subjects and asked them to select four other women to join their test group. To establish the baseline productivity level, the women were studied for two weeks before they were moved to the experiment room. The women weren’t aware that the study had begun, but researchers measured their pre-intervention output, and eventually the pre-selected team was moved to a separate room, and their productivity was studied for the next year.⁵ 

Throughout the course of these studies, a number of variables were introduced, including varying the length of breaks, providing lunches and coffee for workers, and eliminating the Saturday workday. Every change seemed to increase workers’ productivity—no matter what it was. The researchers proposed multiple possible explanations: for one, the women chose their own coworkers and formed a distinct team, separated in a room apart from the rest of the factory’s workers. Elton Mayo’s original observations from the Hawthorne studies contributed to the explanation that "the six individuals became a team and the team gave itself wholeheartedly and spontaneously to cooperation in the experiment."⁵

Since several variables could have contributed to this positive outcome, including team selection, separation from other workers, and changes in working conditions, the methodological limitations were clear. However, when the researchers attempted to isolate the psychological factor associated with being observed, they found that compared to the control conditions, the employees worked harder when they were aware that they were being monitored individually—which was later recognized as the Hawthorne effect. The participants’ performance also likely improved because, by virtue of taking part in the experiment, they were given special treatment, both by their supervisor and by getting to work in a separate room. Thus, although it was difficult to isolate the precise nature of the impact, the researchers discovered that social and psychological factors can have a much greater influence on worker productivity than the physical environment alone.

As research in this field continued, social scientists discovered that the relationships between workers and their supervisors, the role workers feel they have in major decision-making processes, and their sense of belonging and contribution to the group as a whole all play a crucial role in determining productivity and job satisfaction and are often more important than external features of their working environment.⁵

The work of Elton Mayo and the legacy of the Hawthorne Studies contributed to the development of management theory and fields like organizational psychology. Although the Hawthorne effect specifically highlighted the influence on behavior when people know they’re being observed, these studies also provided concrete evidence of the significance of human relationships in the workplace, and their results initiated an overhaul of the traditional supervisor training, with a new employee-centered focus on the impact of group dynamics.⁶

An understanding of the Hawthorne effect has helped many managers to quickly increase productivity, and the Hawthorne studies have influenced the work of social and organizational theorists like Keith Davis, Chris Argyris, and Fred Herzberg.⁷ In recent years, some researchers have gone back to the original Hawthorne studies to critique or modify the theory of the Hawthorne effect. For example, researchers like Douglas McGregor have suggested that Mayo’s initial theory is too simplistic and that the links between motivation, organizational design, and productivity are far more complex.⁸ However, the Hawthorne effect continues to be studied in diverse contexts, and its impact is observed across a variety of fields.⁶ 

Elton Mayo

An Australian-born American psychologist, industrial researcher, and organizational theorist, Mayo is well-known for his role in the original Hawthorne studies, the namesake and first documented cases of the Hawthorne effect. This research led him to develop human relations management theory, which is a key underlying component of teamwork in many modern organizations.⁹

W. Lloyd Warner

An American sociologist and anthropologist, Warner’s research mainly focused on class structure, although he also studied group dynamics and social interactions. He worked with Elton Mayo on the bank wiring experiments in the original Hawthorne Studies, wherein the men being studied formed cliques and were influenced greatly by social pressure.¹⁰ 

Keith Davis

A management and organizational behavior expert who contributed to understanding human relations in the workplace. His work emphasized the importance of group dynamics, communication, and leadership, aligning with the insights of the Hawthorne studies about the impact of social and psychological factors on employee behavior.⁷

Chris Argyris

A prominent organizational theorist who developed theories on organizational learning and the relationship between individuals and organizations. Argyris' concepts of interpersonal competence and the role of human needs in motivation expanded on the Hawthorne effect's emphasis on worker psychology and the impact of attention on performance.⁷

Fred Herzberg

Known for his two-factor theory of motivation, distinguishing between hygiene factors (e.g., working conditions) and motivators (e.g., recognition, achievement), Herzberg’s psychology work complements the Hawthorne findings by highlighting how factors beyond material conditions, such as recognition and attention, can drive productivity.⁷

Douglas McGregor

A management theorist famous for developing Theory X and Theory Y, his work describes different assumptions about worker motivation. McGregor's work ties into the Hawthorne effect by emphasizing the role of management's perception and treatment of employees in shaping their performance and behavior, echoing the studies' findings on the influence of observation and attention.^8,11

Steven Levitt

Levitt is an American economist best known for his book Freakonomics, which explores the intersection of economics, psychology, and behavioral science. His work on behavioral economics has been incredibly influential across the social and political sciences. Alongside John List, Levitt reexamined the Hawthorne effect, highlighting a number of methodological shortcomings in the initial illumination experiments. 

John List

List, like Steven Levitt, is an American researcher in the field of behavioral economics and has influenced a number of social science fields. His research has impacted policy across the United States, and he is one of the first economists to suggest that economic experiments should take place outside of the laboratory. Due to this special interest in fieldwork, List and Levitt revisited the original Hawthorne studies in their 2009 paper. 

Since the Hawthorne effect describes the impact of the mere knowledge of being studied on participants’ behavior, it’s likely that this effect plays a role in nearly every realm of human research we conduct. Let’s explore just a handful of situations where this may take place.

Trial Effect in Healthcare

Scientists who often incorporate placebo conditions into their medical research have studied the clinical trial effect—which is tangential to the Hawthorne effect but specific to clinical trials. Some of these researchers claim that the effects of the research environment on participants may go beyond just increased attention and observation, which, according to the Hawthorne effect, can have a major impact on participant results. Additional factors could be involved in shaping patient results, including slightly better care, better compliance or adherence to the treatment, and selection bias.¹²

Selection bias occurs when participant selection isn’t adequately randomized, and the subject selection process leads to systematically skewed results. This could happen in several ways. In some situations, physicians may tend to recruit patients who seem to have better adherence potential for their treatments or who seem less likely to drop out of the study or require intensive follow-up. Presumably, patients who choose to participate in the study in the first place are more invested in continuing their treatment, given that they sought out the opportunity to participate in the research. It’s also possible that the inclusion or exclusion criteria of trials could skew the patient participant group to a healthier subset of the population. Although inclusion and exclusion criteria can help prevent confounding variables, they may ultimately contribute to bias, potentially selecting patients who are willing or capable of stronger reactions to treatment conditions​​.¹² Ultimately, the knowledge of the Hawthorne effect and other related effects involving experimenter bias makes researchers more aware of how the context of the research environment and the presence of the researcher affect experimental outcomes, and may inspire them to go to greater lengths to reduce bias and restore accuracy.

Secondary Observer Effect

You may be familiar with the observer effect, which suggests that observing a situation or phenomenon changes its outcome. This effect has been discussed in numerous fields, including physics, psychology, sociology, linguistics, and computer science, and was popularized by the Hawthorne studies. Although some critics call into question the reliability of the observer effect itself, others believe its impact to be so strong that they propose a secondary observer effect; when researchers work with secondary data like surveys or experimental data, their observations may impact the results of their scientific research. While the Hawthorne effect focuses on the psychological effect on the participant being observed, the secondary observer effect focuses more on the impact from the standpoint of the observer. Essentially, the researchers’ presence may unknowingly influence the findings of a study, even at a distance from the experimentation.¹³

Whereas in the primary observer effect, the participants' behaviors are actually changed, in the secondary observer effect, the researchers may unconsciously code, analyze, and interpret the data in ways that systematically skew or alter the findings. For example, as the researchers conduct statistical analyses of their data, they may unwittingly choose different methods of analysis, alternate software settings, or perform steps differently, which could ultimately cause significantly different results. 

To illustrate, consider when researchers use publicly available data. Some researchers may choose to use different measures of the same variables or even varying levels of contemporaneity; if one research uses global population information from 2005 and another uses information from 2015, the researchers may have varying results, which can lead to different conclusions. To combat this, some researchers suggest crowdsourcing data analysts and secondary data to better understand where secondary observer effects occur and more effectively minimize them.¹⁴

Organizational Behavior

The Hawthorne studies have had a profound impact on the field of organizational behavior, as they underscored the impact of social factors like recognition, opportunities for participation, and a sense of belonging in workplace dynamics and productivity. Prior to the Hawthorne studies, many workplaces were focused on efficiency and productivity above workers’ rights or well-being. However, because the Hawthorne studies demonstrated that workers are motivated by much more than just monetary or physical rewards, optimal management techniques shifted away from strict regulation and the bare minimum physical conditions and toward creating more supportive working environments.5

The Hawthorne studies have influenced modern management and industrial psychology practices, along with how we understand human relations and organizational behavior. To this day, the studies’ impact continues to pioneer the development of practices that prioritize employee engagement, teamwork, a supportive work environment, job satisfaction, and overall well-being. They’re part of why we’ve seen increased regulation around so many aspects of the office that make employee lives easier: mandatory work breaks, smoother management techniques, and the introduction of employee well-being groups.⁵

The Hawthorne effect has been described as a “glorified anecdote,” as there has been limited replicability of the original experiments. Critics have suggested a number of alternative explanations for the results seen in the original studies as well as led more recent studies that highlight the abundance of confounding variables.

The Novelty Effect 

Although there is some disagreement about the exact definition of the Hawthorne effect, the term describes the phenomenon of participants changing their behavior in response to being observed. Of course, people may change their behavior for a variety of reasons, making it difficult to distinguish between the Hawthorne effect and the "novelty effect.”

The novelty effect refers to the temporary increase in performance or productivity that participants experience due to the newness of the experimental context. In this case, the novelty effect can be considered a key component of the Hawthorne effect itself, and many researchers argue that the novelty of taking part in an experiment could play an oversized role in explaining the influence of study participation on participant behavior. This influence refers to the temporary increase in performance or productivity that participants experience simply because they’re aware they’re being observed as part of a new study, essentially getting a boost from the excitement of the newness of the situation. One way to address this concern is to study how the Hawthorne effect changes over time, as the novelty of the situation decreases. This would mean that any performance increases attributed to the novelty effect should dwindle, and the Hawthorne effect’s impact can be more strongly attributed to the results.³

The Demand Effect 

Another likely explanation for the Hawthorne effect includes the demand effect. This effect typically refers to the bias that occurs when participants infer the purpose of an experiment and consciously or unconsciously shift their behavior or responses to help confirm the researcher's hypothesis. In experiments, this can also refer to the experimenter-induced cues and expectations, which may influence the behavior of participants.¹⁵ In this case, people may be motivated to please the experimenter by performing more productively, especially if the participants are given favorable treatment while participating in the experiment, as was the case for many of the workers in the Hawthorne studies. 

Although the demand effect usually refers specifically to participants changing their behavior based on the specifics of the hypothesis, there is also the influence of feedback, as performance is likely to change as participants receive feedback on their skills and output. In situations where people are exposed to performance feedback for the first time, many simply incorporate this feedback and improve accordingly. Although this could look like participants are improving simply because they are being studied, if researchers aren’t careful to control for any direct or indirect feedback cues, participants may be exposed to more guidance for improvement than in their normal work environment. 

Analysis of the Illumination Experiment 

In 2009, economists Steven Levitt and John List analyzed the original illumination experiment from the Hawthorne studies and published a scathing critique.16 Levitt and List recovered and reassessed the original illumination experiment data, which was long thought to have been destroyed. Their analysis revealed a lack of consistent evidence from the original experiment that productivity rose directly in response to changes in the lighting levels. The original paper claimed that each time the lighting level was adjusted, the workers’ productivity increased because the lighting changes indicated to the participants that they were being observed. But Levitt and List found no such relationship, which ultimately undermines the study’s principal claim that any adjustment, brighter or dimmer, spurred increases in output. This suggests that the Hawthorne effect may have been much weaker than the original paper proposed. Instead, the data they found indicated subtler effects: productivity was modestly higher during periods of experimental manipulation and more responsive to changes in artificial lighting introduced by the experimenters compared to natural light variations. 

The economists argued that the Hawthorne effect, as it is usually described, is likely an oversimplification and that the effect is not a universal principle but highly dependent on economic, psychological, and contextual factors. Rather than continuing to rely on this construct, we should further research the complexity of how experimental conditions and participant perceptions interact. Although the effect has inspired both legitimate academic research and practical improvements to workplace management, we must be cautious about applying the concept more broadly. Their reanalysis of the primary data has underscored the importance of designing experiments that consider contextual variables, as the impact of observation may be less predictable than the original studies presumed.16

Isolating the Hawthorne Effect in Dementia Treatment 

As we’ve discussed, one major concern regarding the Hawthorne effect’s impact is its role in healthcare and clinical trials. A 2007 study aiming to isolate the effects of ginkgo biloba for treating mild to moderate dementia also focused on identifying the role of the Hawthorne effect in its clinical trials.⁴ Participants in the dementia trial were randomized to either an intensive follow-up or minimal follow-up condition and assessed based on their cognitive functioning and quality of life. Theoretically, if clinical trial participation had an effect on participants, it could be at least partially explained by the placebo effect and should equally affect both the control and ginkgo-treated groups. But, as the researchers pointed out, isolating the Hawthorne effect could give a more accurate assessment of the effect size of the treatment because although the placebo and treatment should both be skewed by a placebo effect, any treatment impacts would be misleadingly amplified. 

The researchers found that more intensive follow-up of individuals in the placebo-controlled clinical trial resulted in better cognitive outcomes and worse reported quality of life than the minimal follow-up condition. They concluded that the Hawthorne effect was possibly at play because more intensive contact might have led to better recognition of needs. This could be due to developing a stronger relationship with the caretaker over the course of frequent follow-up appointments and, thus, more “honest” reporting of one’s needs. Another possibility is that more intensive contact with study personnel led to greater awareness of the diagnosis and resultant disability, impairing perception of their quality of life. In either case, the study itself (including the patients’ awareness of being studied and their interactions with the researchers) impacted the results of the trial, calling attention to the need for further research on this effect, particularly in clinical conditions.⁴

Social Sciences  

The discovery of the Hawthorne effect has been highly influential in the field of social sciences, as it encompasses a wide range of disciplines and inspired further study of the interactions between individuals and groups within societies. Read here to learn more about social sciences and how this field is impacted by the Hawthorne effect. 

Using Behavioral Science to Improve Team Dynamics 

The Hawthorne effect was discovered during the Hawthorne studies, which explored worker productivity and were foundational for understanding the importance of team dynamics on employee well-being and motivation. Read here to learn more about how we can leverage behavioral science research to improve team dynamics in the workplace. 

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