Key Takeaways
- Definition: The Hawthorne effect refers to the increase in the performance of individuals who are noticed, watched, and paid attention to by researchers or supervisors.
- Origin of the Term: In 1958, sociologist Henry A. Landsberger popularised the term ‘Hawthorne effect’ while re-evaluating studies at Western Electric’s Hawthorne Works near Chicago. Researcher John R. P. French had originally coined the term in 1953.
- Alternative Explanations: The novelty effect, demand characteristics and feedback on performance may explain what is widely perceived as the Hawthorne effect.
- Modern Critique: Although the Hawthorne effect’s possible implications remain relevant in many contexts, recent research challenges many of its original conclusions.
The Hawthorne effect refers to the tendency to alter behavior when aware of being observed (Fox et al., 2008).
This phenomenon means people may act differently once they know they are subjects in an experiment. Simply receiving attention from experimenters can be enough to change their behavior.
Hawthorne Studies
The Hawthorne effect is named after a set of studies conducted at Western Electric’s Hawthorne Plant in Cicero during the 1920s. The scientists on this research team were Elton Mayo (Psychologist), Roethlisberger and Whitehead (Sociologists), and William Dickson (company representative).
There are 4 separate experiments in Hawthorne Studies:
- Illumination Experiments (1924-1927)
- Relay Assembly Test Room Experiments (1927-1932)
- Experiments in Interviewing Workers (1928- 1930)
- Bank Wiring Room Experiments (1931-1932)
The Hawthorne Experiments, conducted at Western Electric’s Hawthorne plant in the 1920s and 30s, fundamentally influenced management theories.
They highlighted the importance of psychological and social factors in workplace productivity, such as employee attention and group dynamics. This led to a more human-centric approach in management practices.
Illumination Experiment
The first and most influential of these studies is known as the “Illumination Experiment”, conducted between 1924 and 1927 (sponsored by the National Research Council).
The company wanted to find out whether productivity was related to the work environment, such as the level of lighting in a factory.
During the first study, a group of workers who made electrical relays experienced several changes in lighting. Their performance was observed in response to even the smallest changes in lighting.
The original researchers found that any change in a variable, such as lighting levels, led to an improvement in productivity. This was true even when the change was negative, such as a return to poor lighting.
These gains in productivity, however, disappeared once the attention faded (Roethlisberger & Dickson, 1939). The outcome implied that the increase in productivity resulted from a motivational effect on the workers. It was not a response to the physical conditions themselves.
Their awareness of being observed, not the lighting itself, appeared to explain their increased output.
Hawthorne Experiment by Elton Mayo
Relay Assembly Test Room Experiment
Spurred by these initial findings, a series of experiments were conducted at the plant over the next eight years. From 1928 to 1932, Elton Mayo (1880–1949) and his colleagues began a set of studies on a group of five women. The studies examined changes in work structure, such as rest periods, the length of the working day, and other physical conditions.
The results of the Elton Mayo studies reinforced the initial findings of the illumination experiment. Freedman (1981, p. 49) summarizes the results of the next round of experiments as follows:
“Regardless of the conditions, whether there were more or fewer rest periods, longer or shorter workdays…the women worked harder and more efficiently.”
Analysis of the findings by Landsberger (1958) led to the term the Hawthorne effect. It describes the increase in the performance of individuals who are noticed, watched, and paid attention to by researchers or supervisors.
Further Hawthorne Studies
A Second Relay Study
In a separate study conducted between 1927 and 1932, six women working together to assemble telephone relays were observed (Harvard Business School, Historical Collections).
Following the secret measuring of their output for two weeks, the women were moved to a special experiment room. The experiment room, which they would occupy for the rest of the study, had a supervisor who discussed various changes to their work.
The subsequent alterations the women experienced included variations in the length and regularity of breaks. Other changes included the provision, or non-provision, of food, and changes to the length of the workday.
Most changes to these variables, including returns to the original state, were accompanied by an increase in productivity.
The researchers concluded that the women’s awareness of being monitored improved their productivity. So did the team spirit created by the close environment (Mayo, 1945).
Bank Wiring Observation Room Study
Subsequently, a related study was conducted by W. Lloyd Warner and Elton Mayo, anthropologists from Harvard (Henslin, 2008).
They carried out their experiment on 14 men who assembled telephone switching equipment. The men were placed in a room along with a full-time observer who would record everything that happened. The workers were to be paid for their individual productivity.
The surprising outcome, however, was a decrease in productivity. The researchers discovered that the men had become suspicious of rising productivity. They feared it would lead the company to lower their base rate, or find grounds to fire some workers.
Additional observation unveiled the existence of smaller cliques within the main group. Moreover, these cliques seemed to have their own rules for conduct and distinct means to enforce them.
The results of the study seemed to indicate that workers were likely to be influenced more by the social force of their peer groups. This mattered more than the incentives offered by their superiors.
This outcome was seen not as challenging the previous findings, but as accounting for the potentially stronger social effect of peer groups.
Hawthorne Effect Examples
Managers in the Workplace
The studies discussed above reveal much about the dynamic relationship between productivity and observation.
On the one hand, letting employees know they are being observed may create a sense of accountability. Such accountability may, in turn, improve performance.
But what if employees perceive ulterior motives behind the observation? A different set of outcomes may then ensue. If employees reason that increased productivity could harm their fellow workers, they may not be motivated to improve their performance. The same applies if they fear it could eventually reduce their own earnings.
This suggests that while observation in the workplace may bring real benefits, it must still account for other factors. These include the camaraderie among workers, the existing relationship between management and employees, and the compensation system.
Education
A study investigated whether pupils’ awareness of experimentation, based on direct and indirect cues, affected their performance (Bauernfeind & Olson, 1973). Among children in grades 3 to 9, the researchers found little evidence of a Hawthorne effect. Either the effect was absent, the intended cues failed to evoke it, or it was too weak to alter the results.
What if the Hawthorne effect were present in other educational contexts, such as older students or teachers being observed? The implications could be important.
For instance, teachers might alter their approach if they know they are being observed and evaluated. This could be via camera or an observer sitting in the class.
Likewise, if older students were informed that their classroom participation would be observed, they might have more incentives to pay diligent attention to the lessons.
Medicine and Clinical Trials
The Hawthorne effect is a recognised problem in clinical research, which is one reason trials rely on control groups, placebo conditions, and blinding.
McCarney and colleagues (2007) ran a randomised controlled trial designed specifically to test for the effect. They found that older people in a dementia study changed their behavior once they knew they were being more closely observed.
The effect is especially troublesome for behavioral measures of treatment adherence. An electronic pill-bottle cap that timestamps every opening can itself change behavior. Patients may take their medication more reliably simply because they know it is being tracked. The measurement then acts as an unintended intervention, rather than an accurate record of normal adherence.
Alternative Explanations
Despite the possibility of the Hawthorne effect and its seeming impact on performance, alternative accounts cannot be discounted.
The Novelty Effect
The Novelty Effect describes how human performance improves in response to new stimuli in the environment (Clark & Sugrue, 1988).
Such improvements result not from any advances in learning or growth, but from a heightened interest in the new stimuli.
Demand Characteristics
Demand characteristics describe the phenomenon in which the subjects of an experiment draw conclusions about the experiment’s objectives. They then alter their behavior, consciously or subconsciously, as a result (Orne, 2009).
The participant’s intentions would play a vital role here. These may range from striving to support the experimenter’s implicit agenda, to attempting to undermine the credibility of the study entirely.
Feedback on Performance
Regular evaluations by experimenters can function as a scoreboard that boosts productivity. Simply being more aware of their own performance may motivate workers to increase their output.
Criticism
Despite the seeming implications of the Hawthorne effect in a variety of contexts, recent reviews of the initial studies seem to challenge the original conclusions.
For instance, the data from the first experiment were long thought to have been destroyed. Rice (1982) notes that “the original [illumination] research data somehow disappeared.”
Gale (2004, p. 439) states that “these particular experiments were never written up, the original study reports were lost, and the only contemporary account of them derives from a few paragraphs in a trade journal.”
Yet Steven Levitt and John List of the University of Chicago were able to uncover and evaluate these data (Levitt & List, 2011). They found that the supposedly notable patterns were entirely fictional despite the possible manifestations of the Hawthorne effect.
As an alternative test for the Hawthorne effect, they proposed comparing responses to experimenter-induced changes against naturally occurring ones.
Another study sought to determine whether the Hawthorne effect actually exists (McCambridge, Witton & Elbourne, 2014). If so, the researchers asked under what conditions it occurs, and how large it could be.
Following a systematic review of the available evidence, the researchers concluded that research participation can indeed impact the behaviors being investigated. However, discovering more about its operation, magnitude, and mechanisms requires further investigation.
Toward ‘Research Participation Effects’
Rather than debating whether ‘the’ Hawthorne effect exists, most researchers now measure research-participation effects directly and design studies around them.
McCambridge and colleagues (2014) argue for replacing the single, catch-all ‘Hawthorne effect’ label with more precise concepts tailored to each study. The issue is increasingly relevant to digital research too. In large-scale A/B testing, participants who realise they are part of a study may behave differently. Researchers therefore rely on unobtrusive logging and identically treated control groups, to stop observation itself from confounding the results.
How to Reduce the Hawthorne Effect
The credibility of experiments is essential to advances in any scientific discipline. Testing hypotheses becomes exceedingly difficult, though, when results are significantly influenced by the mere fact that subjects were observed.
Several strategies can help reduce the Hawthorne Effect.
Discarding the Initial Observations:
- Participants in studies often take time to get used to their new environments.
- During this period, the alterations in performance may stem more from a temporary discomfort with the new environment than from an actual variable.
- Greater familiarity with the environment, however, would decrease this transition effect over time. It would also reveal the raw effects of the variables the experimenters are observing.
Using Control Groups:
- In an experiment, subjects experiencing the intervention and those in the control group are treated in the same manner. Under these conditions, the Hawthorne effect would likely influence both groups equally.
- Under such circumstances, the impact of the intervention can be more readily identified and analyzed.
Secrecy:
- Where ethically permissible, the concealment of information and covert data collection can be used to mitigate the Hawthorne effect.
- Observing the subjects without informing them, or conducting experiments covertly, often yields more reliable outcomes. The famous marshmallow experiment at Stanford University, which was conducted initially on 3 to 5-year-old children, is a striking example.
Frequently Asked Questions
What did the researchers, who identified the Hawthorne effect, see as evidence that employee performance was influenced by something other than the physical work conditions?
The clearest evidence came from the illumination experiments (1924-1927) at Western Electric’s Hawthorne plant. Researchers changed the lighting for workers assembling electrical relays, making it brighter or dimmer. Output rose after almost every change, even when the light was turned back down to a poor level.
From 1927 to 1932, Elton Mayo’s team studied five women assembling telephone relays in the Relay Assembly Test Room. They varied rest breaks, workday length and refreshments. Output rose almost regardless of the direction of each change, whether breaks were added or removed.
Most strikingly, the special conditions were later withdrawn and the women returned to a full 48-hour week with no rest pauses or refreshments. Output still climbed to its highest level yet recorded. Mayo’s team concluded that being observed, not the physical conditions, drove the change (Roethlisberger & Dickson, 1939).
What is the Hawthorne effect in simple terms?
In simple terms, the Hawthorne effect is people changing their behavior simply because they know someone is watching them. It is not a response to whatever the researcher actually changed. It is named after the Hawthorne Works, a Western Electric factory near Chicago where the effect was first documented.
The researcher John French (1953) coined the term, and the sociologist Henry Landsberger (1958) made it famous when he re-analyzed the original studies decades later. Landsberger used it to describe how workers’ output rose when researchers or supervisors noticed, watched and paid attention to them.
Psychologists today treat it as a warning sign for research design, not a guaranteed finding. If people know they are being studied, that awareness alone can distort the results. Good studies control for it with blinding or a control group treated the same way.
References
Bauernfeind, R. H., & Olson, C. J. (1973). Is the Hawthorne effect in educational experiments a chimera? The Phi Delta Kappan, 55 (4), 271-273.
Clark, R. E., & Sugrue, B. M. (1988). Research on instructional media 1978-88. In D. Ely (Ed.), Educational Media and Technology Yearbook, 1994. Volume 20. Libraries Unlimited, Inc., PO Box 6633, Englewood, CO 80155-6633.
Cox, E. (2001). Psychology for A-level. Oxford University Press.
Fox, N. S., Brennan, J. S., & Chasen, S. T. (2008). Clinical estimation of fetal weight and the Hawthorne effect. European Journal of Obstetrics & Gynecology and Reproductive Biology, 141 (2), 111-114.
Gale, E.A.M. (2004). The Hawthorne studies – a fable for our times? Quarterly Journal of
Medicine, (7),439-449.
Henslin, J. M., Possamai, A. M., Possamai-Inesedy, A. L., Marjoribanks, T., & Elder, K. (2015). Sociology: A down to earth approach. Pearson Higher Education AU.
Landsberger, H. A. (1958). Hawthorne Revisited: Management and the Worker, Its Critics, and Developments in Human Relations in Industry.
Levitt, S. D., & List, J. A. (2011). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. American Economic Journal: Applied Economics, 3 (1), 224-38.
Mayo, E. (1945). The human problems of an industrial civilization. New York: The Macmillan
Company.
McCambridge, J., Witton, J., & Elbourne, D. R. (2014). Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. Journal of Clinical Epidemiology, 67 (3), 267-277.
McCarney, R., Warner, J., Iliffe, S., Van Haselen, R., Griffin, M., & Fisher, P. (2007). The Hawthorne Effect: a randomised, controlled trial. BMC Medical Research Methodology, 7 (1), 1-8.
Rice, B. (1982). The Hawthorne defect: Persistence of a flawed theory. Psychology Today, 16 (2), 70-74.
Orne, M. T. (2009). Demand characteristics and the concept of quasi-controls. Artifacts in behavioral research: Robert Rosenthal and Ralph L. Rosnow’s classic books, 110, 110-137.
Further Information
- Wickström, G., & Bendix, T. (2000). The” Hawthorne effect”—what did the original Hawthorne studies actually show?. Scandinavian journal of work, environment & health, 363-367.
- Levitt, S. D., & List, J. A. (2011). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. American Economic Journal: Applied Economics, 3(1), 224-38.
- Oswald, D., Sherratt, F., & Smith, S. (2014). Handling the Hawthorne effect: The challenges surrounding a participant observer. Review of social studies, 1(1), 53-73.
- Bloombaum, M. (1983). The Hawthorne experiments: a critique and reanalysis of the first statistical interpretation by Franke and Kaul. Sociological Perspectives, 26(1), 71-88.
