observational research psychology definition

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Non-Experimental Research

32 Observational Research

Learning objectives.

• List the various types of observational research methods and distinguish between each.
• Describe the strengths and weakness of each observational research method. 

What Is Observational Research?

The term observational research is used to refer to several different types of non-experimental studies in which behavior is systematically observed and recorded. The goal of observational research is to describe a variable or set of variables. More generally, the goal is to obtain a snapshot of specific characteristics of an individual, group, or setting. As described previously, observational research is non-experimental because nothing is manipulated or controlled, and as such we cannot arrive at causal conclusions using this approach. The data that are collected in observational research studies are often qualitative in nature but they may also be quantitative or both (mixed-methods). There are several different types of observational methods that will be described below.

Naturalistic Observation

Naturalistic observation  is an observational method that involves observing people’s behavior in the environment in which it typically occurs. Thus naturalistic observation is a type of field research (as opposed to a type of laboratory research). Jane Goodall’s famous research on chimpanzees is a classic example of naturalistic observation. Dr.  Goodall spent three decades observing chimpanzees in their natural environment in East Africa. She examined such things as chimpanzee’s social structure, mating patterns, gender roles, family structure, and care of offspring by observing them in the wild. However, naturalistic observation  could more simply involve observing shoppers in a grocery store, children on a school playground, or psychiatric inpatients in their wards. Researchers engaged in naturalistic observation usually make their observations as unobtrusively as possible so that participants are not aware that they are being studied. Such an approach is called disguised naturalistic observation .  Ethically, this method is considered to be acceptable if the participants remain anonymous and the behavior occurs in a public setting where people would not normally have an expectation of privacy. Grocery shoppers putting items into their shopping carts, for example, are engaged in public behavior that is easily observable by store employees and other shoppers. For this reason, most researchers would consider it ethically acceptable to observe them for a study. On the other hand, one of the arguments against the ethicality of the naturalistic observation of “bathroom behavior” discussed earlier in the book is that people have a reasonable expectation of privacy even in a public restroom and that this expectation was violated. 

In cases where it is not ethical or practical to conduct disguised naturalistic observation, researchers can conduct  undisguised naturalistic observation where the participants are made aware of the researcher presence and monitoring of their behavior. However, one concern with undisguised naturalistic observation is  reactivity. Reactivity refers to when a measure changes participants’ behavior. In the case of undisguised naturalistic observation, the concern with reactivity is that when people know they are being observed and studied, they may act differently than they normally would. This type of reactivity is known as the Hawthorne effect . For instance, you may act much differently in a bar if you know that someone is observing you and recording your behaviors and this would invalidate the study. So disguised observation is less reactive and therefore can have higher validity because people are not aware that their behaviors are being observed and recorded. However, we now know that people often become used to being observed and with time they begin to behave naturally in the researcher’s presence. In other words, over time people habituate to being observed. Think about reality shows like Big Brother or Survivor where people are constantly being observed and recorded. While they may be on their best behavior at first, in a fairly short amount of time they are flirting, having sex, wearing next to nothing, screaming at each other, and occasionally behaving in ways that are embarrassing.

Participant Observation

Another approach to data collection in observational research is participant observation. In  participant observation , researchers become active participants in the group or situation they are studying. Participant observation is very similar to naturalistic observation in that it involves observing people’s behavior in the environment in which it typically occurs. As with naturalistic observation, the data that are collected can include interviews (usually unstructured), notes based on their observations and interactions, documents, photographs, and other artifacts. The only difference between naturalistic observation and participant observation is that researchers engaged in participant observation become active members of the group or situations they are studying. The basic rationale for participant observation is that there may be important information that is only accessible to, or can be interpreted only by, someone who is an active participant in the group or situation. Like naturalistic observation, participant observation can be either disguised or undisguised. In disguised participant observation , the researchers pretend to be members of the social group they are observing and conceal their true identity as researchers.

In a famous example of disguised participant observation, Leon Festinger and his colleagues infiltrated a doomsday cult known as the Seekers, whose members believed that the apocalypse would occur on December 21, 1954. Interested in studying how members of the group would cope psychologically when the prophecy inevitably failed, they carefully recorded the events and reactions of the cult members in the days before and after the supposed end of the world. Unsurprisingly, the cult members did not give up their belief but instead convinced themselves that it was their faith and efforts that saved the world from destruction. Festinger and his colleagues later published a book about this experience, which they used to illustrate the theory of cognitive dissonance (Festinger, Riecken, & Schachter, 1956) [1] .

In contrast with undisguised participant observation ,  the researchers become a part of the group they are studying and they disclose their true identity as researchers to the group under investigation. Once again there are important ethical issues to consider with disguised participant observation.  First no informed consent can be obtained and second deception is being used. The researcher is deceiving the participants by intentionally withholding information about their motivations for being a part of the social group they are studying. But sometimes disguised participation is the only way to access a protective group (like a cult). Further, disguised participant observation is less prone to reactivity than undisguised participant observation. 

Rosenhan’s study (1973) [2]   of the experience of people in a psychiatric ward would be considered disguised participant observation because Rosenhan and his pseudopatients were admitted into psychiatric hospitals on the pretense of being patients so that they could observe the way that psychiatric patients are treated by staff. The staff and other patients were unaware of their true identities as researchers.

Another example of participant observation comes from a study by sociologist Amy Wilkins on a university-based religious organization that emphasized how happy its members were (Wilkins, 2008) [3] . Wilkins spent 12 months attending and participating in the group’s meetings and social events, and she interviewed several group members. In her study, Wilkins identified several ways in which the group “enforced” happiness—for example, by continually talking about happiness, discouraging the expression of negative emotions, and using happiness as a way to distinguish themselves from other groups.

One of the primary benefits of participant observation is that the researchers are in a much better position to understand the viewpoint and experiences of the people they are studying when they are a part of the social group. The primary limitation with this approach is that the mere presence of the observer could affect the behavior of the people being observed. While this is also a concern with naturalistic observation, additional concerns arise when researchers become active members of the social group they are studying because that they may change the social dynamics and/or influence the behavior of the people they are studying. Similarly, if the researcher acts as a participant observer there can be concerns with biases resulting from developing relationships with the participants. Concretely, the researcher may become less objective resulting in more experimenter bias.

Structured Observation

Another observational method is structured observation . Here the investigator makes careful observations of one or more specific behaviors in a particular setting that is more structured than the settings used in naturalistic or participant observation. Often the setting in which the observations are made is not the natural setting. Instead, the researcher may observe people in the laboratory environment. Alternatively, the researcher may observe people in a natural setting (like a classroom setting) that they have structured some way, for instance by introducing some specific task participants are to engage in or by introducing a specific social situation or manipulation.

Structured observation is very similar to naturalistic observation and participant observation in that in all three cases researchers are observing naturally occurring behavior; however, the emphasis in structured observation is on gathering quantitative rather than qualitative data. Researchers using this approach are interested in a limited set of behaviors. This allows them to quantify the behaviors they are observing. In other words, structured observation is less global than naturalistic or participant observation because the researcher engaged in structured observations is interested in a small number of specific behaviors. Therefore, rather than recording everything that happens, the researcher only focuses on very specific behaviors of interest.

Researchers Robert Levine and Ara Norenzayan used structured observation to study differences in the “pace of life” across countries (Levine & Norenzayan, 1999) [4] . One of their measures involved observing pedestrians in a large city to see how long it took them to walk 60 feet. They found that people in some countries walked reliably faster than people in other countries. For example, people in Canada and Sweden covered 60 feet in just under 13 seconds on average, while people in Brazil and Romania took close to 17 seconds. When structured observation  takes place in the complex and even chaotic “real world,” the questions of when, where, and under what conditions the observations will be made, and who exactly will be observed are important to consider. Levine and Norenzayan described their sampling process as follows:

“Male and female walking speed over a distance of 60 feet was measured in at least two locations in main downtown areas in each city. Measurements were taken during main business hours on clear summer days. All locations were flat, unobstructed, had broad sidewalks, and were sufficiently uncrowded to allow pedestrians to move at potentially maximum speeds. To control for the effects of socializing, only pedestrians walking alone were used. Children, individuals with obvious physical handicaps, and window-shoppers were not timed. Thirty-five men and 35 women were timed in most cities.” (p. 186).

Precise specification of the sampling process in this way makes data collection manageable for the observers, and it also provides some control over important extraneous variables. For example, by making their observations on clear summer days in all countries, Levine and Norenzayan controlled for effects of the weather on people’s walking speeds.  In Levine and Norenzayan’s study, measurement was relatively straightforward. They simply measured out a 60-foot distance along a city sidewalk and then used a stopwatch to time participants as they walked over that distance.

As another example, researchers Robert Kraut and Robert Johnston wanted to study bowlers’ reactions to their shots, both when they were facing the pins and then when they turned toward their companions (Kraut & Johnston, 1979) [5] . But what “reactions” should they observe? Based on previous research and their own pilot testing, Kraut and Johnston created a list of reactions that included “closed smile,” “open smile,” “laugh,” “neutral face,” “look down,” “look away,” and “face cover” (covering one’s face with one’s hands). The observers committed this list to memory and then practiced by coding the reactions of bowlers who had been videotaped. During the actual study, the observers spoke into an audio recorder, describing the reactions they observed. Among the most interesting results of this study was that bowlers rarely smiled while they still faced the pins. They were much more likely to smile after they turned toward their companions, suggesting that smiling is not purely an expression of happiness but also a form of social communication.

In yet another example (this one in a laboratory environment), Dov Cohen and his colleagues had observers rate the emotional reactions of participants who had just been deliberately bumped and insulted by a confederate after they dropped off a completed questionnaire at the end of a hallway. The confederate was posing as someone who worked in the same building and who was frustrated by having to close a file drawer twice in order to permit the participants to walk past them (first to drop off the questionnaire at the end of the hallway and once again on their way back to the room where they believed the study they signed up for was taking place). The two observers were positioned at different ends of the hallway so that they could read the participants’ body language and hear anything they might say. Interestingly, the researchers hypothesized that participants from the southern United States, which is one of several places in the world that has a “culture of honor,” would react with more aggression than participants from the northern United States, a prediction that was in fact supported by the observational data (Cohen, Nisbett, Bowdle, & Schwarz, 1996) [6] .

When the observations require a judgment on the part of the observers—as in the studies by Kraut and Johnston and Cohen and his colleagues—a process referred to as   coding is typically required . Coding generally requires clearly defining a set of target behaviors. The observers then categorize participants individually in terms of which behavior they have engaged in and the number of times they engaged in each behavior. The observers might even record the duration of each behavior. The target behaviors must be defined in such a way that guides different observers to code them in the same way. This difficulty with coding illustrates the issue of interrater reliability, as mentioned in Chapter 4. Researchers are expected to demonstrate the interrater reliability of their coding procedure by having multiple raters code the same behaviors independently and then showing that the different observers are in close agreement. Kraut and Johnston, for example, video recorded a subset of their participants’ reactions and had two observers independently code them. The two observers showed that they agreed on the reactions that were exhibited 97% of the time, indicating good interrater reliability.

One of the primary benefits of structured observation is that it is far more efficient than naturalistic and participant observation. Since the researchers are focused on specific behaviors this reduces time and expense. Also, often times the environment is structured to encourage the behaviors of interest which again means that researchers do not have to invest as much time in waiting for the behaviors of interest to naturally occur. Finally, researchers using this approach can clearly exert greater control over the environment. However, when researchers exert more control over the environment it may make the environment less natural which decreases external validity. It is less clear for instance whether structured observations made in a laboratory environment will generalize to a real world environment. Furthermore, since researchers engaged in structured observation are often not disguised there may be more concerns with reactivity.

Case Studies

A  case study   is an in-depth examination of an individual. Sometimes case studies are also completed on social units (e.g., a cult) and events (e.g., a natural disaster). Most commonly in psychology, however, case studies provide a detailed description and analysis of an individual. Often the individual has a rare or unusual condition or disorder or has damage to a specific region of the brain.

Like many observational research methods, case studies tend to be more qualitative in nature. Case study methods involve an in-depth, and often a longitudinal examination of an individual. Depending on the focus of the case study, individuals may or may not be observed in their natural setting. If the natural setting is not what is of interest, then the individual may be brought into a therapist’s office or a researcher’s lab for study. Also, the bulk of the case study report will focus on in-depth descriptions of the person rather than on statistical analyses. With that said some quantitative data may also be included in the write-up of a case study. For instance, an individual’s depression score may be compared to normative scores or their score before and after treatment may be compared. As with other qualitative methods, a variety of different methods and tools can be used to collect information on the case. For instance, interviews, naturalistic observation, structured observation, psychological testing (e.g., IQ test), and/or physiological measurements (e.g., brain scans) may be used to collect information on the individual.

HM is one of the most notorious case studies in psychology. HM suffered from intractable and very severe epilepsy. A surgeon localized HM’s epilepsy to his medial temporal lobe and in 1953 he removed large sections of his hippocampus in an attempt to stop the seizures. The treatment was a success, in that it resolved his epilepsy and his IQ and personality were unaffected. However, the doctors soon realized that HM exhibited a strange form of amnesia, called anterograde amnesia. HM was able to carry out a conversation and he could remember short strings of letters, digits, and words. Basically, his short term memory was preserved. However, HM could not commit new events to memory. He lost the ability to transfer information from his short-term memory to his long term memory, something memory researchers call consolidation. So while he could carry on a conversation with someone, he would completely forget the conversation after it ended. This was an extremely important case study for memory researchers because it suggested that there’s a dissociation between short-term memory and long-term memory, it suggested that these were two different abilities sub-served by different areas of the brain. It also suggested that the temporal lobes are particularly important for consolidating new information (i.e., for transferring information from short-term memory to long-term memory).

The history of psychology is filled with influential cases studies, such as Sigmund Freud’s description of “Anna O.” (see Note 6.1 “The Case of “Anna O.””) and John Watson and Rosalie Rayner’s description of Little Albert (Watson & Rayner, 1920) [7] , who allegedly learned to fear a white rat—along with other furry objects—when the researchers repeatedly made a loud noise every time the rat approached him.

The Case of “Anna O.”

Sigmund Freud used the case of a young woman he called “Anna O.” to illustrate many principles of his theory of psychoanalysis (Freud, 1961) [8] . (Her real name was Bertha Pappenheim, and she was an early feminist who went on to make important contributions to the field of social work.) Anna had come to Freud’s colleague Josef Breuer around 1880 with a variety of odd physical and psychological symptoms. One of them was that for several weeks she was unable to drink any fluids. According to Freud,

She would take up the glass of water that she longed for, but as soon as it touched her lips she would push it away like someone suffering from hydrophobia.…She lived only on fruit, such as melons, etc., so as to lessen her tormenting thirst. (p. 9)

But according to Freud, a breakthrough came one day while Anna was under hypnosis.

[S]he grumbled about her English “lady-companion,” whom she did not care for, and went on to describe, with every sign of disgust, how she had once gone into this lady’s room and how her little dog—horrid creature!—had drunk out of a glass there. The patient had said nothing, as she had wanted to be polite. After giving further energetic expression to the anger she had held back, she asked for something to drink, drank a large quantity of water without any difficulty, and awoke from her hypnosis with the glass at her lips; and thereupon the disturbance vanished, never to return. (p.9)

Freud’s interpretation was that Anna had repressed the memory of this incident along with the emotion that it triggered and that this was what had caused her inability to drink. Furthermore, he believed that her recollection of the incident, along with her expression of the emotion she had repressed, caused the symptom to go away.

As an illustration of Freud’s theory, the case study of Anna O. is quite effective. As evidence for the theory, however, it is essentially worthless. The description provides no way of knowing whether Anna had really repressed the memory of the dog drinking from the glass, whether this repression had caused her inability to drink, or whether recalling this “trauma” relieved the symptom. It is also unclear from this case study how typical or atypical Anna’s experience was.

Case studies are useful because they provide a level of detailed analysis not found in many other research methods and greater insights may be gained from this more detailed analysis. As a result of the case study, the researcher may gain a sharpened understanding of what might become important to look at more extensively in future more controlled research. Case studies are also often the only way to study rare conditions because it may be impossible to find a large enough sample of individuals with the condition to use quantitative methods. Although at first glance a case study of a rare individual might seem to tell us little about ourselves, they often do provide insights into normal behavior. The case of HM provided important insights into the role of the hippocampus in memory consolidation.

However, it is important to note that while case studies can provide insights into certain areas and variables to study, and can be useful in helping develop theories, they should never be used as evidence for theories. In other words, case studies can be used as inspiration to formulate theories and hypotheses, but those hypotheses and theories then need to be formally tested using more rigorous quantitative methods. The reason case studies shouldn’t be used to provide support for theories is that they suffer from problems with both internal and external validity. Case studies lack the proper controls that true experiments contain. As such, they suffer from problems with internal validity, so they cannot be used to determine causation. For instance, during HM’s surgery, the surgeon may have accidentally lesioned another area of HM’s brain (a possibility suggested by the dissection of HM’s brain following his death) and that lesion may have contributed to his inability to consolidate new information. The fact is, with case studies we cannot rule out these sorts of alternative explanations. So, as with all observational methods, case studies do not permit determination of causation. In addition, because case studies are often of a single individual, and typically an abnormal individual, researchers cannot generalize their conclusions to other individuals. Recall that with most research designs there is a trade-off between internal and external validity. With case studies, however, there are problems with both internal validity and external validity. So there are limits both to the ability to determine causation and to generalize the results. A final limitation of case studies is that ample opportunity exists for the theoretical biases of the researcher to color or bias the case description. Indeed, there have been accusations that the woman who studied HM destroyed a lot of her data that were not published and she has been called into question for destroying contradictory data that didn’t support her theory about how memories are consolidated. There is a fascinating New York Times article that describes some of the controversies that ensued after HM’s death and analysis of his brain that can be found at: https://www.nytimes.com/2016/08/07/magazine/the-brain-that-couldnt-remember.html?_r=0

Archival Research

Another approach that is often considered observational research involves analyzing archival data that have already been collected for some other purpose. An example is a study by Brett Pelham and his colleagues on “implicit egotism”—the tendency for people to prefer people, places, and things that are similar to themselves (Pelham, Carvallo, & Jones, 2005) [9] . In one study, they examined Social Security records to show that women with the names Virginia, Georgia, Louise, and Florence were especially likely to have moved to the states of Virginia, Georgia, Louisiana, and Florida, respectively.

As with naturalistic observation, measurement can be more or less straightforward when working with archival data. For example, counting the number of people named Virginia who live in various states based on Social Security records is relatively straightforward. But consider a study by Christopher Peterson and his colleagues on the relationship between optimism and health using data that had been collected many years before for a study on adult development (Peterson, Seligman, & Vaillant, 1988) [10] . In the 1940s, healthy male college students had completed an open-ended questionnaire about difficult wartime experiences. In the late 1980s, Peterson and his colleagues reviewed the men’s questionnaire responses to obtain a measure of explanatory style—their habitual ways of explaining bad events that happen to them. More pessimistic people tend to blame themselves and expect long-term negative consequences that affect many aspects of their lives, while more optimistic people tend to blame outside forces and expect limited negative consequences. To obtain a measure of explanatory style for each participant, the researchers used a procedure in which all negative events mentioned in the questionnaire responses, and any causal explanations for them were identified and written on index cards. These were given to a separate group of raters who rated each explanation in terms of three separate dimensions of optimism-pessimism. These ratings were then averaged to produce an explanatory style score for each participant. The researchers then assessed the statistical relationship between the men’s explanatory style as undergraduate students and archival measures of their health at approximately 60 years of age. The primary result was that the more optimistic the men were as undergraduate students, the healthier they were as older men. Pearson’s  r  was +.25.

This method is an example of  content analysis —a family of systematic approaches to measurement using complex archival data. Just as structured observation requires specifying the behaviors of interest and then noting them as they occur, content analysis requires specifying keywords, phrases, or ideas and then finding all occurrences of them in the data. These occurrences can then be counted, timed (e.g., the amount of time devoted to entertainment topics on the nightly news show), or analyzed in a variety of other ways.

Media Attributions

• What happens when you remove the hippocampus? – Sam Kean by TED-Ed licensed under a standard YouTube License
• Pappenheim 1882  by unknown is in the  Public Domain .
• Festinger, L., Riecken, H., & Schachter, S. (1956). When prophecy fails: A social and psychological study of a modern group that predicted the destruction of the world. University of Minnesota Press. ↵
• Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵
• Wilkins, A. (2008). “Happier than Non-Christians”: Collective emotions and symbolic boundaries among evangelical Christians. Social Psychology Quarterly, 71 , 281–301. ↵
• Levine, R. V., & Norenzayan, A. (1999). The pace of life in 31 countries. Journal of Cross-Cultural Psychology, 30 , 178–205. ↵
• Kraut, R. E., & Johnston, R. E. (1979). Social and emotional messages of smiling: An ethological approach. Journal of Personality and Social Psychology, 37 , 1539–1553. ↵
• Cohen, D., Nisbett, R. E., Bowdle, B. F., & Schwarz, N. (1996). Insult, aggression, and the southern culture of honor: An "experimental ethnography." Journal of Personality and Social Psychology, 70 (5), 945-960. ↵
• Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions. Journal of Experimental Psychology, 3 , 1–14. ↵
• Freud, S. (1961).  Five lectures on psycho-analysis . New York, NY: Norton. ↵
• Pelham, B. W., Carvallo, M., & Jones, J. T. (2005). Implicit egotism. Current Directions in Psychological Science, 14 , 106–110. ↵
• Peterson, C., Seligman, M. E. P., & Vaillant, G. E. (1988). Pessimistic explanatory style is a risk factor for physical illness: A thirty-five year longitudinal study. Journal of Personality and Social Psychology, 55 , 23–27. ↵

Research that is non-experimental because it focuses on recording systemic observations of behavior in a natural or laboratory setting without manipulating anything.

An observational method that involves observing people’s behavior in the environment in which it typically occurs.

When researchers engage in naturalistic observation by making their observations as unobtrusively as possible so that participants are not aware that they are being studied.

Where the participants are made aware of the researcher presence and monitoring of their behavior.

Refers to when a measure changes participants’ behavior.

In the case of undisguised naturalistic observation, it is a type of reactivity when people know they are being observed and studied, they may act differently than they normally would.

Researchers become active participants in the group or situation they are studying.

Researchers pretend to be members of the social group they are observing and conceal their true identity as researchers.

Researchers become a part of the group they are studying and they disclose their true identity as researchers to the group under investigation.

When a researcher makes careful observations of one or more specific behaviors in a particular setting that is more structured than the settings used in naturalistic or participant observation.

A part of structured observation whereby the observers use a clearly defined set of guidelines to "code" behaviors—assigning specific behaviors they are observing to a category—and count the number of times or the duration that the behavior occurs.

An in-depth examination of an individual.

A family of systematic approaches to measurement using qualitative methods to analyze complex archival data.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Effective Guidelines for Conducting Observation Research

Table of Contents

Have you ever wondered how psychologists gather authentic data about human behavior without influencing it? One key method they use is observation , a foundational approach that can yield deep insights when done correctly. In this post, we’ll walk through the essential guidelines for conducting effective observation research, ensuring that you can confidently plan, execute, and interpret your studies.

Understanding the Types of Observation

Before diving into data collection, it’s crucial to understand the different types of observation methods available. Each type serves a unique purpose and can affect the outcome of your study.

Structured vs. Unstructured Observation

Structured observation involves specific criteria and a systematic approach to recording behavior, while unstructured observation is more open-ended, allowing the observer to record all that occurs without a predetermined scheme.

Participant vs. Non-participant Observation

In participant observation, the researcher becomes a part of the group being observed, which can provide an inside view of the group’s dynamics. Non\-participant observation , on the other hand, requires the observer to remain detached from the group.

Covert vs. Overt Observation

When observers do not reveal their research intentions to the subjects, it is known as covert observation. This can help in capturing unaltered behavior but poses ethical questions. Overt observation is where the subjects are aware they are being observed, which can influence their behavior but is ethically transparent.

Preparing for Data Collection

Preparation is key to successful observation research. There are several steps you need to take before you begin collecting data.

Choosing the Right Setting and Subjects

Select a setting that is natural for the subjects and conducive to observing the behaviors of interest. The subjects should also be representative of the population you’re studying.

Developing the Observation Guide

Create an observation guide that details what behaviors or events are to be observed and recorded. This will ensure consistency and reliability in your data collection.

Training Observers

Ensure that all observers are thoroughly trained to use the observation guide and understand the nuances of the research. This reduces the risk of observer bias .

Executing the Observation Study

With preparation out of the way, it’s time to begin the actual observation. This phase is critical, as it’s where the data you’ll be analyzing is collected.

Recording Observations

Meticulous note-taking is a must. Use audio or video recording if possible, to capture details that might be missed in real-time.

Staying Unobtrusive

Whether you’re participating or not, staying unobtrusive helps in maintaining the integrity of the observed behaviors.

Being Ethical

Always adhere to ethical guidelines . If the observation is covert, ensure that it doesn’t intrude on privacy and is justified by the study’s potential benefits.

Analyzing and Interpreting Observational Data

Once you’ve gathered your data, the next step is to make sense of it. This phase is as important as the data collection itself.

Coding and Organizing Data

Develop a coding system to categorize the behaviors observed. This helps in organizing the data for analysis.

Identifying Patterns and Themes

Look for recurring behaviors or events that signify underlying patterns or themes in your data.

Maintaining Objectivity

It’s essential to remain objective during analysis. Avoid imposing your biases or expectations on the data.

Reporting Your Findings

Reporting your findings with clarity and honesty is the final step in the research process. Your report should be detailed enough to allow others to replicate the study if they wish.

Describing the Methodology

Detail the observation method used, the setting, and the subjects, so the context of the study is clear.

Presenting the Data

Present your data in a way that is both accessible and comprehensible, using visuals like charts or graphs where appropriate.

Discussing the Implications

Discuss what your findings mean in the broader context of the research question, and suggest areas for further study.

Observation research is a powerful method in psychology, allowing researchers to gather data in natural settings and gain insights that might otherwise be inaccessible. By following these guidelines, from choosing the right type of observation to effectively analyzing and reporting data, you can enhance the validity and reliability of your observational studies. It’s a meticulous process, but with careful planning and execution, your observations can lead to significant contributions in the field of psychology.

What do you think? How might the presence of an observer alter the behavior of the subjects, and how can this impact be minimized? Are there ethical considerations that might limit the use of observation research, and how should they be addressed? Share your thoughts and let’s delve into the complexities of observation research together.

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Research Methods in Psychology

1 Introduction to Psychological Research – Objectives and Goals, Problems, Hypothesis and Variables

• Nature of Psychological Research
• The Context of Discovery
• Context of Justification
• Characteristics of Psychological Research
• Goals and Objectives of Psychological Research

2 Introduction to Psychological Experiments and Tests

• Independent and Dependent Variables
• Extraneous Variables
• Experimental and Control Groups
• Introduction of Test
• Types of Psychological Test
• Uses of Psychological Tests

3 Steps in Research

• Research Process
• Identification of the Problem
• Review of Literature
• Formulating a Hypothesis
• Identifying Manipulating and Controlling Variables
• Formulating a Research Design
• Constructing Devices for Observation and Measurement
• Sample Selection and Data Collection
• Data Analysis and Interpretation
• Hypothesis Testing
• Drawing Conclusion

4 Types of Research and Methods of Research

• Historical Research
• Descriptive Research
• Correlational Research
• Qualitative Research
• Ex-Post Facto Research
• True Experimental Research
• Quasi-Experimental Research

5 Definition and Description Research Design, Quality of Research Design

• Research Design
• Purpose of Research Design
• Design Selection
• Criteria of Research Design
• Qualities of Research Design

6 Experimental Design (Control Group Design and Two Factor Design)

• Experimental Design
• Control Group Design
• Two Factor Design

7 Survey Design

• Survey Research Designs
• Steps in Survey Design
• Structuring and Designing the Questionnaire
• Interviewing Methodology
• Data Analysis
• Final Report

8 Single Subject Design

• Single Subject Design: Definition and Meaning
• Phases Within Single Subject Design
• Requirements of Single Subject Design
• Characteristics of Single Subject Design
• Types of Single Subject Design
• Advantages of Single Subject Design
• Disadvantages of Single Subject Design

9 Observation Method

• Definition and Meaning of Observation
• Characteristics of Observation
• Types of Observation
• Advantages and Disadvantages of Observation
• Guides for Observation Method

10 Interview and Interviewing

• Definition of Interview
• Types of Interview
• Aspects of Qualitative Research Interviews
• Interview Questions
• Convergent Interviewing as Action Research
• Research Team

11 Questionnaire Method

• Definition and Description of Questionnaires
• Types of Questionnaires
• Purpose of Questionnaire Studies
• Designing Research Questionnaires
• The Methods to Make a Questionnaire Efficient
• The Types of Questionnaire to be Included in the Questionnaire
• Advantages and Disadvantages of Questionnaire
• When to Use a Questionnaire?

12 Case Study

• Definition and Description of Case Study Method
• Historical Account of Case Study Method
• Designing Case Study
• Requirements for Case Studies
• Guideline to Follow in Case Study Method
• Other Important Measures in Case Study Method
• Case Reports

13 Report Writing

• Purpose of a Report
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14 Review of Literature

• Purposes of Review of Literature
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• Types of Literature
• Writing Process of the Review of Literature
• Preparation of Index Card for Reviewing and Abstracting

15 Methodology

• Definition and Purpose of Methodology
• Participants (Sample)
• Apparatus and Materials

16 Result, Analysis and Discussion of the Data

• Definition and Description of Results
• Statistical Presentation
• Tables and Figures

17 Summary and Conclusion

• Summary Definition and Description
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• Writing the Summary and Choosing Words
• A Process for Paraphrasing and Summarising
• Summary of a Report
• Writing Conclusions

18 References in Research Report

• Reference List (the Format)
• References (Process of Writing)
• Reference List and Print Sources
• Electronic Sources
• Book on CD Tape and Movie
• Reference Specifications
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Observational Method

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• Wang Jisheng 2 &
• Zhang Kan 2  

Observational method is the basic research method of psychology that determines the psychological characteristics of an observed person by purposefully and systematically observing and recording his or her speech and behavior. Observational method has long been adopted by people. Confucius said, “It used to be that with people, when I heard what they said I trusted their conduct would match; now I listen to what they say and observe their conduct.” (The Analects of Confucius · Gongye Chang). It is referring to the use of observational method to know people. After psychology became an independent discipline, the observational method has also developed greatly.

The greatest feature of the observational method is the direct observation and recording of the mental and behavioral activities of the observed person in natural or simulated situations. The raw data collected by observational method need to be classified, coded, frequency statistics counted, and qualitative statistics analyzed...

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Kantowitz BH, Roediger HL, Elmes DG (2015) Experimental psychology, 10th edn. Cengage Learning, Boston

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Zhang X-M (2014) Shu Hua. Beijing Normal University Publishing Group, Experimental Psychology. Beijing

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Jisheng, W., Kan, Z. (2024). Observational Method. In: The ECPH Encyclopedia of Psychology. Springer, Singapore. https://doi.org/10.1007/978-981-99-6000-2_476-1

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Home » Observational Research – Methods and Guide

Observational Research – Methods and Guide

Table of Contents

Observational Research

Definition:

Observational research is a type of research method where the researcher observes and records the behavior of individuals or groups in their natural environment. In other words, the researcher does not intervene or manipulate any variables but simply observes and describes what is happening.

Observation

Observation is the process of collecting and recording data by observing and noting events, behaviors, or phenomena in a systematic and objective manner. It is a fundamental method used in research, scientific inquiry, and everyday life to gain an understanding of the world around us.

Types of Observational Research

Observational research can be categorized into different types based on the level of control and the degree of involvement of the researcher in the study. Some of the common types of observational research are:

Naturalistic Observation

In naturalistic observation, the researcher observes and records the behavior of individuals or groups in their natural environment without any interference or manipulation of variables.

Controlled Observation

In controlled observation, the researcher controls the environment in which the observation is taking place. This type of observation is often used in laboratory settings.

Participant Observation

In participant observation, the researcher becomes an active participant in the group or situation being observed. The researcher may interact with the individuals being observed and gather data on their behavior, attitudes, and experiences.

Structured Observation

In structured observation, the researcher defines a set of behaviors or events to be observed and records their occurrence.

Unstructured Observation

In unstructured observation, the researcher observes and records any behaviors or events that occur without predetermined categories.

Cross-Sectional Observation

In cross-sectional observation, the researcher observes and records the behavior of different individuals or groups at a single point in time.

Longitudinal Observation

In longitudinal observation, the researcher observes and records the behavior of the same individuals or groups over an extended period of time.

Data Collection Methods

Observational research uses various data collection methods to gather information about the behaviors and experiences of individuals or groups being observed. Some common data collection methods used in observational research include:

Field Notes

This method involves recording detailed notes of the observed behavior, events, and interactions. These notes are usually written in real-time during the observation process.

Audio and Video Recordings

Audio and video recordings can be used to capture the observed behavior and interactions. These recordings can be later analyzed to extract relevant information.

Surveys and Questionnaires

Surveys and questionnaires can be used to gather additional information from the individuals or groups being observed. This method can be used to validate or supplement the observational data.

Time Sampling

This method involves taking a snapshot of the observed behavior at pre-determined time intervals. This method helps to identify the frequency and duration of the observed behavior.

Event Sampling

This method involves recording specific events or behaviors that are of interest to the researcher. This method helps to provide detailed information about specific behaviors or events.

Checklists and Rating Scales

Checklists and rating scales can be used to record the occurrence and frequency of specific behaviors or events. This method helps to simplify and standardize the data collection process.

Observational Data Analysis Methods

Observational Data Analysis Methods are:

Descriptive Statistics

This method involves using statistical techniques such as frequency distributions, means, and standard deviations to summarize the observed behaviors, events, or interactions.

Qualitative Analysis

Qualitative analysis involves identifying patterns and themes in the observed behaviors or interactions. This analysis can be done manually or with the help of software tools.

Content Analysis

Content analysis involves categorizing and counting the occurrences of specific behaviors or events. This analysis can be done manually or with the help of software tools.

Time-series Analysis

Time-series analysis involves analyzing the changes in behavior or interactions over time. This analysis can help identify trends and patterns in the observed data.

Inter-observer Reliability Analysis

Inter-observer reliability analysis involves comparing the observations made by multiple observers to ensure the consistency and reliability of the data.

Multivariate Analysis

Multivariate analysis involves analyzing multiple variables simultaneously to identify the relationships between the observed behaviors, events, or interactions.

Event Coding

This method involves coding observed behaviors or events into specific categories and then analyzing the frequency and duration of each category.

Cluster Analysis

Cluster analysis involves grouping similar behaviors or events into clusters based on their characteristics or patterns.

Latent Class Analysis

Latent class analysis involves identifying subgroups of individuals or groups based on their observed behaviors or interactions.

Social network Analysis

Social network analysis involves mapping the social relationships and interactions between individuals or groups based on their observed behaviors.

The choice of data analysis method depends on the research question, the type of data collected, and the available resources. Researchers should choose the appropriate method that best fits their research question and objectives. It is also important to ensure the validity and reliability of the data analysis by using appropriate statistical tests and measures.

Applications of Observational Research

Observational research is a versatile research method that can be used in a variety of fields to explore and understand human behavior, attitudes, and preferences. Here are some common applications of observational research:

• Psychology : Observational research is commonly used in psychology to study human behavior in natural settings. This can include observing children at play to understand their social development or observing people’s reactions to stress to better understand how stress affects behavior.
• Marketing : Observational research is used in marketing to understand consumer behavior and preferences. This can include observing shoppers in stores to understand how they make purchase decisions or observing how people interact with advertisements to determine their effectiveness.
• Education : Observational research is used in education to study teaching and learning in natural settings. This can include observing classrooms to understand how teachers interact with students or observing students to understand how they learn.
• Anthropology : Observational research is commonly used in anthropology to understand cultural practices and beliefs. This can include observing people’s daily routines to understand their culture or observing rituals and ceremonies to better understand their significance.
• Healthcare : Observational research is used in healthcare to understand patient behavior and preferences. This can include observing patients in hospitals to understand how they interact with healthcare professionals or observing patients with chronic illnesses to better understand their daily routines and needs.
• Sociology : Observational research is used in sociology to understand social interactions and relationships. This can include observing people in public spaces to understand how they interact with others or observing groups to understand how they function.
• Ecology : Observational research is used in ecology to understand the behavior and interactions of animals and plants in their natural habitats. This can include observing animal behavior to understand their social structures or observing plant growth to understand their response to environmental factors.
• Criminology : Observational research is used in criminology to understand criminal behavior and the factors that contribute to it. This can include observing criminal activity in a particular area to identify patterns or observing the behavior of inmates to understand their experience in the criminal justice system.

Observational Research Examples

Here are some real-time observational research examples:

• A researcher observes and records the behaviors of a group of children on a playground to study their social interactions and play patterns.
• A researcher observes the buying behaviors of customers in a retail store to study the impact of store layout and product placement on purchase decisions.
• A researcher observes the behavior of drivers at a busy intersection to study the effectiveness of traffic signs and signals.
• A researcher observes the behavior of patients in a hospital to study the impact of staff communication and interaction on patient satisfaction and recovery.
• A researcher observes the behavior of employees in a workplace to study the impact of the work environment on productivity and job satisfaction.
• A researcher observes the behavior of shoppers in a mall to study the impact of music and lighting on consumer behavior.
• A researcher observes the behavior of animals in their natural habitat to study their social and feeding behaviors.
• A researcher observes the behavior of students in a classroom to study the effectiveness of teaching methods and student engagement.
• A researcher observes the behavior of pedestrians and cyclists on a city street to study the impact of infrastructure and traffic regulations on safety.

How to Conduct Observational Research

Here are some general steps for conducting Observational Research:

• Define the Research Question: Determine the research question and objectives to guide the observational research study. The research question should be specific, clear, and relevant to the area of study.
• Choose the appropriate observational method: Choose the appropriate observational method based on the research question, the type of data required, and the available resources.
• Plan the observation: Plan the observation by selecting the observation location, duration, and sampling technique. Identify the population or sample to be observed and the characteristics to be recorded.
• Train observers: Train the observers on the observational method, data collection tools, and techniques. Ensure that the observers understand the research question and objectives and can accurately record the observed behaviors or events.
• Conduct the observation : Conduct the observation by recording the observed behaviors or events using the data collection tools and techniques. Ensure that the observation is conducted in a consistent and unbiased manner.
• Analyze the data: Analyze the observed data using appropriate data analysis methods such as descriptive statistics, qualitative analysis, or content analysis. Validate the data by checking the inter-observer reliability and conducting statistical tests.
• Interpret the results: Interpret the results by answering the research question and objectives. Identify the patterns, trends, or relationships in the observed data and draw conclusions based on the analysis.
• Report the findings: Report the findings in a clear and concise manner, using appropriate visual aids and tables. Discuss the implications of the results and the limitations of the study.

When to use Observational Research

Here are some situations where observational research can be useful:

• Exploratory Research: Observational research can be used in exploratory studies to gain insights into new phenomena or areas of interest.
• Hypothesis Generation: Observational research can be used to generate hypotheses about the relationships between variables, which can be tested using experimental research.
• Naturalistic Settings: Observational research is useful in naturalistic settings where it is difficult or unethical to manipulate the environment or variables.
• Human Behavior: Observational research is useful in studying human behavior, such as social interactions, decision-making, and communication patterns.
• Animal Behavior: Observational research is useful in studying animal behavior in their natural habitats, such as social and feeding behaviors.
• Longitudinal Studies: Observational research can be used in longitudinal studies to observe changes in behavior over time.
• Ethical Considerations: Observational research can be used in situations where manipulating the environment or variables would be unethical or impractical.

Purpose of Observational Research

Observational research is a method of collecting and analyzing data by observing individuals or phenomena in their natural settings, without manipulating them in any way. The purpose of observational research is to gain insights into human behavior, attitudes, and preferences, as well as to identify patterns, trends, and relationships that may exist between variables.

The primary purpose of observational research is to generate hypotheses that can be tested through more rigorous experimental methods. By observing behavior and identifying patterns, researchers can develop a better understanding of the factors that influence human behavior, and use this knowledge to design experiments that test specific hypotheses.

Observational research is also used to generate descriptive data about a population or phenomenon. For example, an observational study of shoppers in a grocery store might reveal that women are more likely than men to buy organic produce. This type of information can be useful for marketers or policy-makers who want to understand consumer preferences and behavior.

In addition, observational research can be used to monitor changes over time. By observing behavior at different points in time, researchers can identify trends and changes that may be indicative of broader social or cultural shifts.

Overall, the purpose of observational research is to provide insights into human behavior and to generate hypotheses that can be tested through further research.

Advantages of Observational Research

There are several advantages to using observational research in different fields, including:

• Naturalistic observation: Observational research allows researchers to observe behavior in a naturalistic setting, which means that people are observed in their natural environment without the constraints of a laboratory. This helps to ensure that the behavior observed is more representative of the real-world situation.
• Unobtrusive : Observational research is often unobtrusive, which means that the researcher does not interfere with the behavior being observed. This can reduce the likelihood of the research being affected by the observer’s presence or the Hawthorne effect, where people modify their behavior when they know they are being observed.
• Cost-effective : Observational research can be less expensive than other research methods, such as experiments or surveys. Researchers do not need to recruit participants or pay for expensive equipment, making it a more cost-effective research method.
• Flexibility: Observational research is a flexible research method that can be used in a variety of settings and for a range of research questions. Observational research can be used to generate hypotheses, to collect data on behavior, or to monitor changes over time.
• Rich data : Observational research provides rich data that can be analyzed to identify patterns and relationships between variables. It can also provide context for behaviors, helping to explain why people behave in a certain way.
• Validity : Observational research can provide high levels of validity, meaning that the results accurately reflect the behavior being studied. This is because the behavior is being observed in a natural setting without interference from the researcher.

Disadvantages of Observational Research

While observational research has many advantages, it also has some limitations and disadvantages. Here are some of the disadvantages of observational research:

• Observer bias: Observational research is prone to observer bias, which is when the observer’s own beliefs and assumptions affect the way they interpret and record behavior. This can lead to inaccurate or unreliable data.
• Limited generalizability: The behavior observed in a specific setting may not be representative of the behavior in other settings. This can limit the generalizability of the findings from observational research.
• Difficulty in establishing causality: Observational research is often correlational, which means that it identifies relationships between variables but does not establish causality. This can make it difficult to determine if a particular behavior is causing an outcome or if the relationship is due to other factors.
• Ethical concerns: Observational research can raise ethical concerns if the participants being observed are unaware that they are being observed or if the observations invade their privacy.
• Time-consuming: Observational research can be time-consuming, especially if the behavior being observed is infrequent or occurs over a long period of time. This can make it difficult to collect enough data to draw valid conclusions.
• Difficulty in measuring internal processes: Observational research may not be effective in measuring internal processes, such as thoughts, feelings, and attitudes. This can limit the ability to understand the reasons behind behavior.

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What Is Naturalistic Observation?

Illustration by Brianna Gilmartin, Verywell

• How Naturalistic Observation Works
• Pros and Cons
• Data Collection Methods

How Often Is Data Collected?

Naturalistic observation is a research method that involves observing subjects in their natural environment. This approach is often used by psychologists and other social scientists. It is a form of qualitative research , which focuses on collecting, evaluating, and describing non-numerical data.

It can be useful if conducting lab research would be unrealistic, cost-prohibitive, or would unduly affect the subject's behavior. The goal of naturalistic observation is to observe behavior as it occurs in a natural setting without interference or attempts to manipulate variables.

This article discusses how naturalistic observation works and the pros and cons of doing this type of research. It also covers how data is collected and examples of when this method might be used in psychology research.

How Does Naturalistic Observation Work?

People do not necessarily behave in a lab setting the way they would in a natural environment. Researchers sometimes want to observe their subject's behavior as it happens ("in the wild," so to speak). Psychologists can get a better idea of how and why people react the way that they do by watching how they respond to situations and stimuli in real life.

Naturalistic observation is different than structured observation because it involves looking at a subject's behavior as it occurs in a natural setting, with no attempts at intervention on the part of the researcher.

For example, a researcher interested in aspects of classroom behavior (such as the interactions between students or teacher-student dynamics) might use naturalistic observation as part of their research.

Performing these observations in a lab would be difficult because it would involve recreating a classroom environment. This would likely influence the behavior of the participants, making it difficult to generalize the observations made.

By observing the subjects in their natural setting (the classroom where they work and learn), the researchers can more fully observe the behavior they are interested in as it occurs in the real world.

Naturalistic Observation Pros and Cons 

Like other research methods, naturalistic observation has advantages and disadvantages.

More realistic

More affordable

Can detect patterns

Inability to manipulate or control variables

Cannot explain why behaviors happen

Risk of observer bias

An advantage of naturalistic observation is that it allows the investigators to directly observe the subject in a natural setting. The method gives scientists a first-hand look at social behavior and can help them notice things that they might never have encountered in a lab setting.

The observations can also serve as inspiration for further investigations. The information gleaned from naturalistic observation can lead to insights that can be used to help people overcome problems and lead to healthier, happier lives.

Other advantages of naturalistic observation include:

• Allows researchers to study behaviors or situations that cannot be manipulated in a lab due to ethical concerns . For example, it would be unethical to study the effects of imprisonment by actually confining subjects. But researchers can gather information by using naturalistic observation in actual prison settings.
• Can support the external validity of research . Researchers might believe that the findings of a lab study can be generalized to a larger population, but that does not mean they would actually observe those findings in a natural setting. They may conduct naturalistic observation to make that confirmation.

Naturalistic observation can be useful in many cases, but the method also has some downsides. Some of these include:

• Inability to draw cause-and-effect conclusions : The biggest disadvantage of naturalistic observation is that determining the exact cause of a subject's behavior can be difficult.
• Lack of control : Another downside is that the experimenter cannot control for outside variables .
• Lack of validity : While the goal of naturalistic observation is to get a better idea of how it occurs in the real world, experimental effects can still influence how people respond. The Hawthorne effect and other demand characteristics can play a role in people altering their behavior simply because they know they are being observed.
• Observer bias : The biases of the people observing the natural behaviors can influence the interpretations that experimenters make.

It is also important to note that naturalistic observation is a type of correlational research (others include surveys and archival research). A correlational study is a non-experimental approach that seeks to find statistical relationships between variables. Naturalistic observation is one method that can be used to collect data for correlational studies.

While such methods can look at the direction or strength of a relationship between two variables, they cannot determine if one causes the other. As the saying goes, correlation does not imply causation.

Data Collection Methods 

Researchers use different techniques to collect and record data from naturalistic observation. For example, they might write down how many times a certain behavior occurred in a specific period of time or take a video recording of subjects.

• Audio or video recordings : Depending on the type of behavior being observed, the researchers might also decide to make audio or videotaped recordings of each observation session. They can then later review the recordings.
• Observer narrative : The observer might take notes during the session that they can refer back to. They can collect data and discern behavior patterns from these notes.
• Tally counts : The observer writes down when and how many times certain behaviors occurred.

It is rarely practical—or even possible—to observe  every  moment of a subject's life. Therefore, researchers often use sampling to gather information through naturalistic observation.

The goal is to make sure that the sample of data is representative of the subject's overall behavior. A representative sample is a selection that accurately depicts the characteristics that are present in the total subject of interest. A  representative sample  can be obtained through:

• Time sampling : This involves taking samples at different intervals of time (random or systematic). For example, a researcher might observe a person in the workplace to notice how frequently they engage in certain behaviors and to determine if there are patterns or trends.
• Situation sampling : This type of sampling involves observing behavior in different situations and settings. An example of this would be observing a child in a classroom, home, and community setting to determine if certain behaviors only occur in certain settings.
• Event sampling : This approach involves observing and recording each time an event happens. This allows the researchers to better identify patterns that might be present. For example, a researcher might note every time a subject becomes agitated. By noting the event and what was occurring around the time of each event, researchers can draw inferences about what might be triggering those behaviors.

Examples of Naturalistic Observation

Imagine that you want to study risk-taking behavior in teenagers. You might choose to observe behavior in different settings, such as a sledding hill, a rock-climbing wall, an ice-skating rink, and a bumper car ride. After you operationally define "risk-taking behavior," you would observe your teen subjects in these settings and record every incidence of what you have defined as risky behavior.

Famous examples of naturalistic observations include Charles Darwin's journey aboard the  HMS Beagle , which served as the basis for his theory of natural selection, and Jane Goodall's work studying the behavior of chimpanzees in their natural habitat.

Naturalistic observation can play an important role in the research process. It offers a number of advantages, including often being more affordable and less intrusive than other types of research.

In some cases, researchers may utilize naturalistic observation as a way to learn more about something that is happening in a certain population. Using this information, they can then formulate a hypothesis that can be tested further.

Mehl MR, Robbins ML, Deters FG. Naturalistic observation of health-relevant social processes: the electronically activated recorder methodology in psychosomatics . Psychosom Med. 2012;74(4):410-7. doi:10.1097/PSY.0b013e3182545470

U.S. National Library of Medicine. Rewriting the book of nature - Darwin and the Beagle voyage .

Angrosino MV. Naturalistic Observation . Left Coast Press.

DiMercurio A, Connell JP, Clark M, Corbetta D. A naturalistic observation of spontaneous touches to the body and environment in the first 2 months of life . Front Psychol . 2018;9:2613. doi:10.3389/fpsyg.2018.02613

Pierce K, Pepler D. A peek behind the fence: observational methods 25 years later . In: Smith PK, Norman JO, eds. The Wiley Blackwell Handbook of Bullying. 1st ed . Wiley; 2021:215-232. doi:10.1002/9781118482650.ch12

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Observational studies and their utility for practice

Julia fm gilmartin-thomas.

2 Research Department of Practice and Policy, University College London, School of Pharmacy, London

1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne

Ingrid Hopper

Randomised controlled clinical trials are the best source of evidence for assessing the efficacy of drugs. Observational studies provide critical descriptive data and information on long-term efficacy and safety that clinical trials cannot provide, at generally much less expense.

Observational studies include case reports and case series, ecological studies, cross-sectional studies, case-control studies and cohort studies. New and ongoing developments in data and analytical technology, such as data linkage and propensity score matching, offer a promising future for observational studies. However, no study design or statistical method can account for confounders and bias in the way that randomised controlled trials can.

Clinical registries are gaining importance as a method to monitor and improve the quality of care in Australia. Although registries are a form of cohort study, clinical trials can be incorporated into them to exploit the routine follow-up of patients to capture relevant outcomes.

Introduction

Observational studies involve the study of participants without any forced change to their circumstances, that is, without any intervention. 1 Although the participants’ behaviour may change under observation, the intent of observational studies is to investigate the ‘natural’ state of risk factors, diseases or outcomes. For drug therapy, a group of people taking the drug can be compared to people not taking the drug.

The main types of observational studies used in health research, their purpose and main strengths and limitations are shown in the Table . 2 - 8

Their purpose may be descriptive, analytical or both.

• Descriptive studies are primarily designed to describe the characteristics of a studied population.
• Analytical studies seek to address cause-and-effect questions.

Case reports and case series

Case reports and case series are strictly speaking not studies. However, they serve a useful role in describing new or notable events in detail. These events often warrant further formal investigation. Examples include reports of unexpected benefits or adverse events, such as a case report describing the use of high-dose quetiapine in treatment-resistant schizophrenia after intolerance to clozapine developed 9 and a case report of a medication error involving lookalike packaging. 10

Ecological studies

Ecological studies are based on analysis of aggregated data at group levels (for example populations), and do not involve data on individuals. These data can be analysed descriptively, but not definitively for causation. Typical examples include studies that examine patterns of drug use over time. One example is the comparison of the use of non-steroidal anti-inflammatory drugs and COX-2 inhibitors in Australia and Canada. 11 Sometimes ecological studies describe associations between drugs and outcomes, such as changes in the rates of upper gastrointestinal haemorrhage after the introduction of COX-2 inhibitors. 12 However, because individual-level data are not presented, causality is at best only implied in ecological studies. The 'ecological fallacy' refers to the error of assuming that associations observed in ecological studies are causal when they are not.

Cross-sectional studies

Cross-sectional studies collect data at a single point in time for each single individual, but the actual data collection may take place over a period of time or on more than one occasion. There is no longitudinal follow-up of individuals. Cross-sectional studies represent the archetypal descriptive study. 1 Typically, they provide a profile of a population of interest, which may be broad, like the Australian Health Survey undertaken intermittently by the Australian Bureau of Statistics, 13 or focused on specific populations, such as older Australians. 14

Case-control studies

Case-control studies focus on determining risk factors for an outcome of interest (such as a disease or a drug’s adverse effect) that has already occurred. 5

• those who already have the outcome (cases)
• those who do not have the outcome (controls), who are often matched to the cases to make them similar and reduce bias.

Second, data on previous exposure to selected risk factors are collected and compared to see if these risk factors are more (or less) common among cases versus controls. Case-control studies are useful for studying the risk factors of rare outcomes, as there is no need to wait for these to occur. Multiple risk factors can be studied, but each case-control study can involve only one outcome. 5 One example explored the relationship between the use of antiplatelet and anticoagulant drugs (risk factor) and the risk of hospitalisation for bleeding (outcome) in older people with a history of stroke. 15 Another case-control study explored the risk factors for the development of flucloxacillin-associated jaundice (outcome). 16

Cohort studies

Cohort studies compare outcomes between or among subgroups of participants defined on the basis of whether or not they are exposed to a particular risk or protective factor (defined as an exposure). They provide information on how these exposures are associated with changes in the risk of particular downstream outcomes. Compared to case-control studies, cohort studies take individuals with exposures and look for outcomes, rather than taking those with outcomes and looking for exposures. Cohort studies are longitudinal, that is they involve follow-up of a cohort of participants over time. This follow-up can be prospective or retrospective. Retrospective cohort studies are those for which follow-up has already occurred. They are typically used to estimate the incidence of outcomes of interest, including the adverse effects of drugs.

Cohort studies provide a higher level of evidence of causality than case-control studies because temporality (the explicit time relationship between exposures and outcomes) is preserved. They also have the advantage of not being limited to a single outcome of interest. Their main disadvantage, compared to case-control studies, has been that longitudinal data are more expensive and time-consuming to collect. However, with the availability of electronic data, it has become easier to collect longitudinal data.

One prospective cohort study explored the relationship between the continuous use of antipsychotic drugs (exposure) and mortality (outcome) and hospitalisation (outcome) in older people. 17 In another older cohort, a retrospective study was used to explore the relationship between long-term treatment adherence (exposure) and hospital readmission (outcome). 18

Observational studies versus randomised controlled trials

Compared to randomised controlled trials, observational studies are relatively quick, inexpensive and easy to undertake. Observational studies can be much larger than randomised controlled trials so they can explore a rare outcome. They can be undertaken when a randomised controlled trial would be unethical. However, observational studies cannot control for bias and confounding to the extent that clinical trials can. Randomisation in clinical trials remains the best way to control for confounding by ensuring that potential confounders (such as age, sex and comorbidities) are evenly matched between the groups being compared. In observational studies, adjustment for potential confounders can be undertaken, but only for a limited number of confounders, and only those that are known. Randomisation in clinical trials also minimises selection bias, while blinding (masking) controls for information bias. Hence, for questions regarding drug efficacy, randomised controlled trials provide the most robust evidence.

New and upcoming developments

New methods of analysis and advances in technology are changing the way observational studies are performed.

Clinical registries

Clinical registries are essentially cohort studies, and are gaining importance as a method to monitor and improve the quality of care. 19 These registries systematically collect a uniform longitudinal dataset to evaluate specific outcomes for a population that is identified by a specific disease, condition or exposure. This allows for the identification of variations in clinical practice 20 and benchmarking across practitioners or institutions. These data can then be used to develop initiatives to improve evidence-based care and patient outcomes. 21

An example of a clinical registry in Australia is the Australian Rheumatology Association Database, 22 which collects data on the biologic disease-modifying antirheumatic drugs used for inflammatory arthritis. Clinical data from treating specialists are combined with patient-reported quality of life data and linked to national databases such as Medicare and the National Death Index. This registry has provided insight into the safety and efficacy of drugs and their effect on quality of life. It was used by the Pharmaceutical Benefits Advisory Committee to assess cost-effectiveness of these drugs. 23

Another example is the Haemostasis Registry. It was used to determine the thromboembolic adverse effects of off-label use of recombinant factor VII. 24

Clinical registries can also be used to undertake clinical trials which are nested within the registry architecture. Patients within a registry are randomised to interventions and comparators of interest. Their outcome data are then collected as part of the routine operation of the registry. The key advantages are convenience, reduced costs and greater representativeness of registry populations as opposed to those of traditional clinical trials.

One of the first registry-based trials was nested within the SWEDEHEART registry. 25 This prospectively examined manual aspiration of thrombus at the time of percutaneous coronary intervention in over 7000 patients. 26 The primary endpoint of all-cause mortality was ascertained through linkage to another Swedish registry. The cost of the trial was estimated to be US$400 000, which was a fraction of the many millions that a randomised controlled trial would have cost.

Propensity score matching

Even without randomising people within cohorts, methods have emerged in recent years that allow for less biased comparisons of two or more subgroups. Propensity score matching is a way to assemble two or more groups for comparison so that they appear like they had been randomised to an intervention or a comparator. 27 In short, the method involves logistic regression analyses to determine the likelihood (propensity) of each person within a cohort being on the intervention, and then matching people who were on the intervention to those who were not on the basis of propensity scores. Outcomes are then compared between the groups. Propensity score analysis of a large cohort of patients with relapsing remitting multiple sclerosis found that natalizumab was superior to interferon beta and glatiramer acetate in terms of improved outcomes. 28

Data technology

Increasing sophistication in techniques for data collection will lead to ongoing improvements in the capacity to undertake observational studies (and also clinical trials). Data linkage already offers a convenient way to capture outcomes, including retrospectively. However, ethical considerations must be taken into account, such as the possibility that informed consent might be required before linking data. Machine learning will soon allow for easy analyses of unstructured text (such as free text entries in an electronic prescription). 29 Patient-reported outcome measures are important and in future will be greatly facilitated by standardised, secure hardware and software platforms that allow for their capture, processing and analyses.

While clinical trials remain the best source of evidence regarding the efficacy of drugs, observational studies provide critical descriptive data. Observational studies can also provide information on long-term efficacy and safety that is usually lacking in clinical trials. New and ongoing developments in data and analytical technology offer a promising future for observational studies in pharmaceutical research.

Conflict of interest: Julia Gilmartin-Thomas is a Dementia research development fellow with the National Health and Medical Research Council (NHMRC) - Australian Research Council (ARC). Ingrid Hopper is supported by an NHMRC Early Career Fellowship.

Naturalistic Observation: Definition, Examples, and Advantages

Categories Research Methods

Naturalistic observation is a psychological research method that involves observing and recording behavior in the natural environment. Unlike experiments, researchers do not manipulate variables. This research method is frequently used in psychology to help researchers investigate human behavior.

This article explores how naturalistic observation is used in psychology. It offers examples and the potential advantages and disadvantages of this type of research. 

Table of Contents

What Is Naturalistic Observation?

In naturalistic observation, the researcher observes the participants’ behavior in their natural setting, taking notes on their behavior and interactions. The researcher may use various tools, such as video or audio recordings, to help capture the behavior accurately. The researcher may also use coding systems or other quantitative measures to systematically record observed behavior.

Naturalistic observation can be used to investigate a wide range of psychological phenomena, such as social interaction patterns, parental behavior, or animal behavior. 

Types of Naturalistic Observation

Naturalistic observation can be:

Unstructured or Structured

The observer can either watch and record everything that happens, or they can have a checklist or form to guide their observations.

Participant or Non-Participant

The observer can be an active participant, or they can remain separate from the subject and view from the sidelines.

Overt or Covert

The observer can either openly watch and record the subjects’ behaviors, or they can keep their presence hidden from the individual or group.

The specific type of naturalistic observation that researchers use depends on the situation, what they are researching, and the resources available. No matter the type, the observation must occur in a natural setting rather than in an experimental lab.

How to Collect Data in Naturalistic Observation

There are a number of methods that researchers might utilize to record data about the behaviors and events they observe. Some of these include:

• Note-taking : Research may opt to take notes about what they witness. This approach tends to be unstructured, allowing the observers to determine what they think is relevant and to include insights that may be helpful.
• Tally counts : In other cases, research may take a more structured approach where they count the frequency of a behavior.
• Audiovisual recordings : In other cases, research may want recordings of participant behavior. This not only allows researchers to refer to the recordings later, it can also be useful for sharing with others.

How Data Is Sampled in Naturalistic Observation

While naturalistic observation is not an experimental design, researchers still want to ensure that the data they collect represents what is happening in the group. To do this, researchers must collect a representative sample. When a sample is representative, it means that it accurately reflects what is happening in a given population.

To do this, researchers may utilize three primary sampling approaches:

Event Sampling

Event sampling involves the researcher creating a set of predefined categories and behaviors they will observe. This method is useful when the researcher wants to collect data on specific behaviors or events, allowing for more precise data collection.

Using this approach, the research would note every occurrence of a specific behavior.

Situation Sampling

Situation sampling involves observing participants in more than one situation. This approach can give researchers more insight and allow them to determine if certain behaviors only occur in specific contexts or settings. 

Time Sampling

Time sampling is a type of systematic observation that involves the researcher observing and recording the subjects’ behavior at predetermined intervals. This method is useful when the researcher wants to collect data on the frequency and duration of specific behaviors.

Each method of data collection has its strengths and weaknesses, and the choice of method depends on the research question and the nature of the subjects being observed.

Examples of Naturalistic Observation

It can be helpful to look at a few different examples to learn more about how naturalistic observation can be used:

• Researchers might observe children in a classroom to learn more about their social interaction patterns. 
• Naturalistic observation can also be used to study animal behavior in their natural habitat, such as observing chimpanzees in the wild to understand their social behavior.

Researchers use this research method in various fields, including animal researchers and anthropologists. 

The work of zoologist Konrad Lorenz, for example, relied on the use of naturalistic observation. Lorenz observed the behavior of ducklings after they hatched and noted that they became attached to the first possible parent figure they saw, a phenomenon known as imprinting. Once imprinted on a parent figure, the duckling would follow and learn from their parent.

From his naturalistic observations, Lorenz hypothesized that there was a critical period immediately after hatching where ducklings needed to imprint on a parent. Based on his observations, Lorenz conducted further experiments that confirmed his hypothesis.

More Examples of Naturalistic Observation

Naturalistic observation is a research method commonly used in various areas of psychology. 

Social Psychology

Naturalistic observation can provide valuable insights into people’s behavior in different social situations. By observing people’s behavior in a crowded public place like a shopping mall or train station, researchers can better understand how social norms are established and maintained and how people interact in various social groups.

Consumer Research

Consumer research is another area where naturalistic observation can be used effectively. By observing shoppers in a grocery store or shopping mall, researchers can study how people make purchasing decisions in real-life situations.

Researchers can gain valuable insights into consumer behavior by analyzing what catches their attention, how they interact with different products, and how they decide what to buy.

Developmental Psychology

Observing children playing in a playground or a classroom can help researchers understand how children develop and learn new skills in natural settings.

Researchers can gain insights into the developmental process by observing children as they interact with each other and learn social skills or as they learn new concepts and skills in a classroom.

Cognitive Psychology

Naturalistic observation can be used to study how people think and process information in real-life situations. For example, observing people using a computer program can help researchers understand how people navigate through it and solve problems.

Similarly, observing people in a conversation can provide insights into how they process and respond to information in real time.

Advantages of Naturalistic Observation

Naturalistic observation offers a number of benefits that can make it a good choice for research. 

Ecological Validity

One of the strengths of naturalistic observation is its ability to capture behavior in a natural setting, providing a more accurate and comprehensive picture of how people or animals behave in their everyday environment.

It is often more realistic than lab research, so it can give insight into how people behave authentically in everyday settings and situations.

Inspiration for Additional Research

Naturalistic observation can also generate new hypotheses and insights that may not be captured in other research methods. 

Research That Can’t Be Done in a Lab

Naturalistic observation allows the study of behaviors that cannot be replicated in a lab. Naturalistic observation is sometimes the only approach for studying behaviors that cannot be reproduced in a lab due to ethical reasons.

For example, researchers might use this approach to research prison behavior or the social impact of domestic violence on emotional health. Those are not situations they can manipulate in a lab, but they can observe the impact on people who have had those experiences.

Disadvantages of Naturalistic Observation

While naturalistic can be a valuable tool, it is not appropriate for every situation. Some potential downsides include: 

Bias and Lack of Control

Naturalistic observation is limited by its lack of environmental control and the potential for observer bias. Researchers must be careful to minimize the influence of their presence on the behavior being observed and to use systematic and objective methods for recording and analyzing the data. 

Inability to Infer Cause and Effect

Naturalistic observation is also limited by its inability to establish causality between variables.

Naturalistic Observation vs. Case Study

Naturalistic observation and case studies are both research methods used in psychology but differ in their approach and purpose. Naturalistic observation involves observing and recording the behavior of individuals or groups in their natural environment without any intervention or manipulation by the researcher.

On the other hand, a case study is an in-depth analysis of a single individual or a small group of individuals, often conducted through interviews, surveys, and other forms of data collection.

The key difference between naturalistic observation and a case study is that the former focuses more on observing and recording behaviors and interactions as they occur naturally, while the latter focuses on gathering detailed information about a specific individual or group.

Naturalistic observation is often used to study social interactions, group dynamics, and other natural behaviors in real-world settings. In contrast, case studies often explore complex psychological phenomena such as mental illness, personality disorders, or unusual behaviors.

Both naturalistic observation and case studies have their strengths and limitations. The choice of method depends on the research question, the level of detail needed, and the feasibility of conducting the study in a particular setting.

Naturalistic Observation Ideas

There are many potential ideas for studies that involve naturalistic observation. A few ideas include:

• Observe the behavior of animals in their natural habitats, studying their patterns of movement, foraging, and communication
• Observe human behavior in public spaces, such as parks or coffee shops, documenting patterns of social interaction and communication
• Focus on the behavior of individuals within specific social groups or communities, studying their interactions and relationships over time
• Watch the behavior of children in a classroom setting could provide insights into their learning and socialization processes

Frequently Asked Questions

Why do we use naturalistic observation.

Naturalistic observation is important because it allows researchers to better understand how individuals behave in their everyday lives. By observing behavior in a natural setting, researchers can obtain a more accurate representation of how people act and interact with each other in their normal environment. 

This method is particularly useful when studying social behavior, as it allows researchers to capture the complexity and nuances of social interactions that might not be apparent in a laboratory setting.

Naturalistic observation can also offer valuable insights into the development of certain behaviors, such as those related to child development or the formation of social groups.

What is the most famous example of naturalistic observation?

The most famous example of naturalistic observation is probably Jane Goodall’s study of chimpanzees in the wild. Goodall spent years observing the behavior of chimpanzees in Tanzania, documenting their social interactions, tool use, and other aspects of their lives. Her work helped to revolutionize our understanding of these animals and their place in the natural world.

In conclusion, naturalistic observation is a powerful research method that can be used effectively in various areas within psychology. Researchers can gain valuable insights into human behavior and cognition by observing people’s behavior in natural settings.

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Morrison C, Lee JP, Gruenewald PJ, Mair C. The reliability of naturalistic observations of social, physical and economic environments of bars . Addict Res Theory . 2016;24(4):330-340. doi:10.3109/16066359.2016.1145674

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• Research bias

Observer Bias | Definition, Examples, Prevention

Published on December 8, 2021 by Pritha Bhandari . Revised on March 13, 2023.

Observer bias happens when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It often affects studies where observers are aware of the research aims and hypotheses . Observer bias is also called detection bias.

Table of contents

What is observational research, subjective methods, objective methods, how to minimize observer bias, other biases, other types of research bias, frequently asked questions about observer bias.

In observational studies, you often record behaviors or take measurements from participants without trying to influence the outcomes or the situation. Observational studies are used in many research fields, including medicine, psychology, behavioral science, and ethnography .

Observer bias can occur regardless of whether you use qualitative or quantitative research methods.

Subjective research methods involve some type of interpretation before you record the observations.

In any research involving others, your own experiences, habits, or emotions can influence how you perceive and interpret others’ behaviors. They may lead you to note some observations as relevant while ignoring other equally important observations.

Your expectations about the research may lead to skewed results. There’s a risk you may be subconsciously primed to see only what you expect to observe.

Observer bias may still influence your study even when you use more objective methods (e.g., physiological devices, medical images) for measurement.

That’s because people have a tendency to interpret readings differently, so results can vary between observers in a study.

A lack of training, poor control, and inadequate procedures or protocols may lead to systematic errors from observer bias.

Observer drift

As you collect data , you become more familiar with the procedures and you might become less careful when taking or recording measurements. Observer drift happens when observers depart from the standard procedures in set ways and therefore rate the same events differently over time.

It’s important to design research in a way that minimizes observer bias. Note that, while you can try to reduce observer bias, you may not be able to fully eliminate it from your study.

Use masking

Masking , or blinding , helps you make sure that both your participants and your observers are unaware of the research aims.

This can remove some of the research expectations that come from knowing the study purpose, so observers are less likely to be biased in a particular way.

You can implement masking by involving other people in your studies as observers and giving them a cover story to mislead them about the true purpose of your study.

Use triangulation

Triangulation means using multiple observers, information sources, or research methods to make sure your findings are credible . It’s always a good idea to use triangulation to corroborate your measurements and check that they line up with each other.

To reduce observer bias, it’s especially important to involve multiple observers and to try to use multiple data collection methods for the same observations. When the data from different observers or different methods converge, you reduce the risk of bias and can feel more confident in your results.

Multiple observers

With more than one observer, you make sure that your data are consistent and unlikely to be skewed by any single observer’s biases.

When you have multiple observers , it’s important to check and maintain high interrater reliability. Interrater reliability refers to how consistently multiple observers rate the same observation.

With quantitative data , you can compare data from multiple observers, calculate interrater reliability, and set a threshold that you want to meet. Usually, you train observers in the procedures until they can consistently produce the same or similar observations for every event in training sessions.

Train observers

Before you start any study, it’s a good idea to train all observers to make sure everyone collects and records data in exactly the same way.

It’s important to calibrate your methods so that there’s very little or no variation in how different observers report the same observation. You can recalibrate your procedures between observers at various points in the study to keep interrater reliability high and minimize observer drift as well.

Standardize your procedures

It’s best to create standardized procedures or protocols that are structured and easy to understand for all observers. For example, if your study is about behaviors, make sure to specify all behaviors that observers should note.

Record these procedures (in videos or text) so you can refer back to them at any point in the research process to refresh your memory.

Observer bias is closely related to several other types of research bias.

Observer-expectancy effect

The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.

Researchers may unintentionally signal their own beliefs and expectations about the study and influence participants through demand characteristics .

The observer-expectancy effect also goes by other names:

• Experimenter-expectancy effect
• Rosenthal effect
• Pygmalion effect
• Group A (treatment group) receives the actual treatment with the new painkiller
• Group B ( control group ) receives no treatment, but instead takes a placebo

Actor–observer bias

The actor–observer bias is an attributional bias where you tend to attribute the cause of something differently depending on whether you’re the actor or observer in that situation.

As an actor in a situation, you may tend to attribute your own behavior to external factors. As an observer, you may instead attribute another person’s behavior, even if it’s the same as yours, to internal factors. The actor–observer bias is a social psychological topic.

• Hawthorne effect

The Hawthorne effect refers to some research participants’ tendency to work harder in order to perform better when they believe they’re being observed. It describes what participants being observed may inadvertently do in a study.

The Hawthorne effect is named after Hawthorne Works, a company where employee productivity supposedly improved, regardless of the experimental treatment , due to the presence of observers.

Experimenter bias

Experimenter bias covers all types of biases from researchers that may influence their studies. This includes observer bias, observer expectancy effects, actor–observer bias, and other biases. Experimenter bias is also called experimenter effect.

Cognitive bias

• Confirmation bias
• Baader–Meinhof phenomenon
• Availability heuristic
• Halo effect
• Hindsight bias
• Framing effect
• Ingroup bias
• Affect heuristic
• Representativeness heuristic
• Anchoring heuristic
• Primacy bias
• Optimism bias

Selection bias

• Sampling bias
• Ascertainment bias
• Attrition bias
• Self-selection bias
• Survivorship bias
• Nonresponse bias
• Undercoverage bias
• Observer bias
• Omitted variable bias
• Publication bias
• Recall bias
• Social desirability bias
• Placebo effect
• Actor-observer bias
• Ceiling effect
• Ecological fallacy
• Affinity bias

Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. This type of research bias is also called detection bias or ascertainment bias .

It’s impossible to completely avoid observer bias in studies where data collection is done or recorded manually, but you can take steps to reduce this type of bias in your research .

You can use several tactics to minimize observer bias .

• Use masking (blinding) to hide the purpose of your study from all observers.
• Triangulate your data with different data collection methods or sources.
• Use multiple observers and ensure interrater reliability.
• Train your observers to make sure data is consistently recorded between them.
• Standardize your observation procedures to make sure they are structured and clear.

Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics .

The observer-expectancy effect is often used synonymously with the Pygmalion or Rosenthal effect .

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Observer Bias: Definition, Examples & Prevention

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Observer bias is a type of experimenter bias that occurs when a researcher’s expectations, perspectives, opinions, or prejudices impact the results of an experiment. This type of research bias is also called detection bias or ascertainment bias.

This typically occurs when a researcher is aware of the purpose and hypotheses of a study and holds expectations about what will happen.

If a researcher is trying to find a particular result to support the hypothesis of the study or has a predetermined idea of what the results should be, they will have the incentive to twist the data to make them more in line with their predictions.

This bias occurs most often in observational studies or any type of research where measurements are taken and recorded manually. In observational studies, a researcher records behaviors or takes measurements from participants without trying to influence the outcome of the experiment.

Observational studies are used in a number of different research fields, most specifically medicine, psychology, behavioral science, and ethnography.

For Example

You are performing an observational study to investigate the effects of a new medication to treat nausea. Group A receives the actual treatment with the new medication, while group B receives a placebo.

The participants do not know which group they are a part of, but you – the researcher – do.

Unconsciously, you treat the two groups differently, framing questions more negatively towards Group B and commenting that those in Group A seem more energized and upbeat.

Impact of Observer Bias

Observer bias can result in misleading and unreliable results. A researcher’s biases and prejudices can affect data collection and observer interpretation, leading to results that fail to represent accurately what exists in reality.

It might also result in inaccurate data sets, misleading information, or biased treatment from researchers. 

Observer bias can damage scientific research and policy decisions and lead to negative outcomes for people involved in the research studies.

Why Observer Bias Can Happen 

Subjective methods.

Subjective research methods are those that involve some type of interpretation before you record the observations. Subjectivity refers to the way research is influenced by the perspectives, values, emotions, social experiences, and viewpoints of the researcher.

This could lead a researcher to record some observations as relevant while ignoring other equally important observations.

Even if a researcher is subconsciously primed to see only what they expect to observe, subjective research methods could lead to skewed conclusions. 

Objective Methods

Although objective research tends to be impartial and fact-based, observer bias might still influence studies that use more objective methods.

This is because researchers tend to interpret or record readings differently, skewing the results to be more in line with their predictions.

For example, when measuring blood pressure using a blood pressure monitor, a researcher might round up the blood pressure to the nearest whole number.

Or, due to familiarity with the procedures of measuring blood pressure, a researcher might be less careful when taking the measurements and thus record inaccurate results.

How to Minimize Observer Bias 

Blinding, or masking, ensures that the participants and researchers are all unsure of the goals of the study.

This will help eliminate some of the research expectations that come from knowing the study’s purpose so observers are less likely to be biased.

Additionally, in double-blind studies , neither the researchers nor the subjects know which treatments are being used or which group they belong to.

Random Assignment

Randomly assigning subjects to groups instead of choosing the subjects themselves will help minimize observer bias. 

Multiple Observers

Having multiple researchers involved in the research study will ensure that your data is consistent and make it less likely that one researcher’s biases will significantly affect the project’s outcome.

It can also be beneficial to use multiple data collection methods for the same observations to corroborate your findings and check that they line up with each other.

Train Observers

Before beginning a study, it is beneficial to train all observers in the procedures to ensure everyone collects and records data exactly the same way.

This will eliminate any variation in how different observers report the same observation, keeping interrater reliability high and minimizing observer bias.

Standardized Procedures

It is important to create standardized procedures or protocols that are easy for all observers to follow.

You can record these procedures so that the researchers can refer back to them at any point in the research process.

Related Biases

Observer bias is closely related to several other types of research bias.

Observer-Expectancy Effect

The observer-expectancy effect occurs when a researcher’s cognitive bias causes them to subconsciously influence the results of their own study through interactions with participants.

Researchers might unconsciously or deliberately treat certain subjects differently, leading to unequal results between groups.

For example, a researcher might ask different questions or give different directions to one group and not another, or influence certain participants’ behavior by changing their body language, posture, tone of voice, or appearance in certain ways.

Actor-Observer Bias

Actor-observer bias is an attributional bias where a researcher attributes their own actions to external factors while attributing other people’s behaviors to internal causes.

This bias can help explain why we are inclined to blame others for things that happen, even when we would not blame ourselves for acting in the same way.

For example, if you perform poorly on a test, you might blame the result on external factors such as teacher bias or the questions being harder than usual.

However, if a classmate fails the same test, you might attribute their failure to a lack of intelligence or preparation. 

Hawthorne Effect

The Hawthorne effect refers to some participants’ tendency to work harder and perform better when they know they are being observed.

This effect also suggests that individuals may change their behavior due to the attention they are receiving from researchers rather than because of any manipulation of independent variables.

Experimenter Bias

Experimenter bias is any type of cognitive bias that occurs when experimenters allow their expectations to affect their interpretation of observations.

Experimenter bias typically refers to all types of biases from researchers that might influence a study, including observer bias, the observer-expectancy effect, actor-observer bias, and the Hawthorne effect.

When a researcher has a predetermined idea of the results of their study, they might conduct the study or record results in a way that confirms their theory.

What is the difference between observer bias and confirmation bias?

Observer bias is a type of experimenter bias where a researcher’s predetermined expectations, perspectives, opinions, or prejudices can impact the results of an experiment.

Confirmation bias is a type of cognitive bias that occurs when a researcher favors information or interprets findings to favor their existing beliefs.

Unlike observer bias which can be intentional in some instances, confirmation bias happens due to the natural way our brains work, so it cannot be eliminated. 

What is the difference between observer bias and the observer effect?

The observer effect in psychology is also known as the Hawthorne effect. It refers to how people change their behavior when they know they are being observed in a study.

Observer bias is a related term in the social sciences that refers to the error that results from an observer’s cognitive biases, particularly when observers overemphasize behavior they expect to find and fail to notice behavior they do not expect.

The observer effect is not to be confused with the observer-expectancy effect or the actor-observer bias, discussed above.

Further Reading

Burghardt, G. M., Bartmess‐LeVasseur, J. N., Browning, S. A., Morrison, K. E., Stec, C. L., Zachau, C. E., & Freeberg, T. M. (2012). Perspectives–minimizing observer bias in behavioral studies: a review and recommendations .  Ethology ,  118 (6), 511-517.

Hróbjartsson, A., Thomsen, A. S. S., Emanuelsson, F., Tendal, B., Hilden, J., Boutron, I., … & Brorson, S. (2013). Observer bias in randomized clinical trials with measurement scale outcomes: a systematic review of trials with both blinded and nonblinded assessors .  Cmaj ,  185 (4), E201-E211.

Salvia, J. A., & Meisel, C. J. (1980). Observer bias: A methodological consideration in special education research.   The Journal of Special Education ,  14 (2), 261-270.

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How scientific is cognitive load theory research compared to the rest of educational psychology.

1. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?

1.1. overview, 1.2. causal conclusions and recommendations for practice, 1.3. the present review, 2.1. journal selection and search process, 2.2. coding and analysis, 3.1. research designs, 3.2. recommendations for practice, 4. discussion, 4.1. limitations and future directions, 4.2. conclusions, author contributions, conflicts of interest.

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Share and Cite

Martella, A.M.; Lawson, A.P.; Robinson, D.H. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology? Educ. Sci. 2024 , 14 , 920. https://doi.org/10.3390/educsci14080920

Martella AM, Lawson AP, Robinson DH. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology? Education Sciences . 2024; 14(8):920. https://doi.org/10.3390/educsci14080920

Martella, Amedee Marchand, Alyssa P. Lawson, and Daniel H. Robinson. 2024. "How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?" Education Sciences 14, no. 8: 920. https://doi.org/10.3390/educsci14080920

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