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Observational Research – Methods and Guide

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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.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Laboratory Observation Methods

Steps & Procedures for Conducting Scientific Research

Laboratory observations happen when a person gathers and records information about an experiment within a laboratory setting. Examples of lab observations include noting the formation of crystals and recording survey results. There are several ways of conducting observations in a lab, and the method that you choose often depends on the type of experiment you are doing.

Natural and Contrived

Natural observations are observations that you make of subjects while they are in their real-life or natural environment. You have little control over your subjects when performing this type of observation, so gathering the right type of data may be more time consuming, but the information gathered accurately reflects your subjects’ natural behavior. Using the natural observation method can be difficult in a laboratory setting, as subjects typically are not in their natural setting in a laboratory environment. On the other hand, contrived observations are conducted in settings created by the observer, as within a laboratory. Contrived observations offer you more control over the data gathering process, but the data may not reflect real-life phenomena.

Disguised and Non-Disguised

Within a laboratory setting, scientists can conduct both disguised and non-disguised observations. Disguised observations are made when the subject does not know he or she is being observed. Subjects tend to act more naturally during disguised observations, and the information collected is more apt to reflect their true reactions. There are ethical concerns with this method of data gathering, however, because the subject might not want private information recorded by the researcher. Non-disguised observations, on the other hand, occur when the subject knows that observations are taking place. The ethical concerns are alleviated but you may not get accurate or true information when using this method.

Direct and Indirect

Laboratory observation can use direct or indirect observation methods. Making a direct observation is looking at or studying an actual behavior or occurrence instead of the result of that behavior or occurrence. An indirect observation happens when the researcher studies the results or consequences of an occurrence instead of the actual occurrence itself. An example of a direct observation is watching birds feeding and taking note of what types of food they eat. An example of an indirect observation is analyzing bird droppings to see what type of foods they ate.

Human and Mechanical

Within a laboratory setting, scientists can make human or mechanical observations. Human observations are made when the observer or researcher collects data using his eyes, ears, nose and other senses. Mechanical observations are those made using mechanical devices such as video cameras, microscopes and weather balloons. After data has been collected by the devices, it is interpreted by the researcher. Mechanical devices offer a way of collecting more precise data than simply through human observations.

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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.

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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

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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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• What Is Participant Observation? | Definition & Examples

What Is Participant Observation? | Definition & Examples

Published on March 10, 2023 by Tegan George .

Participant observation is a research method where the researcher immerses themself in a particular social setting or group, observing the behaviors, interactions, and practices of the participants. This can be a valuable method for any research project that seeks to understand the experiences of individuals or groups in a particular social context.

In participant observation, the researcher is called a participant-observer , meaning that they participate in the group’s activities while also observing the group’s behavior and interactions. There is flexibility in the level of participation, ranging from non-participatory (the weakest) to complete participation (the strongest but most intensive.) The goal here is to gain a deep understanding of the group’s culture, beliefs, and practices from an “insider” perspective.

You immerse yourself in this subculture by spending time at skateparks, attending skateboarding events, and engaging with skateboarders. Perhaps you may even learn to skateboard yourself, in order to better understand the experiences of your study participants.

As you observe, you take notes on the behavior, language, norms, and values you witness and also conduct informal unstructured interviews with individual skateboarders to gain further insight into their thoughts and lived experiences.

Typically used in fields like anthropology, sociology, and other social sciences, this method is often used to gather rich and detailed data about social groups or phenomena through ethnographies or other qualitative research .

Table of contents

When to use participant observation, examples of participant observation, how to analyze data from participant observation, advantages and disadvantages of participant observations, other types of research bias, frequently asked questions.

Participant observation is a type of observational study . Like most observational studies, these are primarily qualitative in nature, used to conduct both explanatory research and exploratory research . Participant observation is also often used in conjunction with other types of research, like interviews and surveys .

This type of study is especially well suited for studying social phenomena that are difficult to observe or measure through other methods. As the researcher observes, they typically take detailed notes about their observations and interactions with the group. These are then analyzed to identify patterns and themes using thematic analysis or a similar method.

A participant observation could be a good fit for your research if:

• You are studying subcultures or groups with unique practices or beliefs. Participant observation fosters a deep and intimate understanding of the beliefs, values, and practices of your group or subculture of interest from an insider’s perspective. This can be especially useful when studying marginalized groups or groups that are resistant to observation.
• You are studying complex social interactions . Participant observation can be a powerful tool for studying the complex social interactions that occur within a particular group or community. By immersing yourself in the group and observing these interactions firsthand, you can gain a much more nuanced understanding of how these interactions flow.
• You are studying behaviors or practices that may be difficult to self-report . In some cases, participants may be unwilling or unable to accurately report their own behaviors or practices. Participant observation allows researchers to observe these behaviors directly, allowing for more accuracy in the data collection phase.

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Participant observation is a common research method in social sciences, with findings often published in research reports used to inform policymakers or other stakeholders.

Over the course of several months, you observe and take notes on the social interactions, customs, and beliefs of the community members, conducting informal interviews with individual residents to gain further insight into their experiences and perspectives. Through your observations, you gain a deep understanding of the community’s culture, including its values, traditions, and social hierarchy.

Participant observations are often also used in sociology to study social groups and related phenomena, like group formation, stratification, or conflict resolution.

Through this participant observation, you soon see that the group is highly stratified, with certain individuals occupying positions of social power and others being marginalized or even largely excluded. You also observe patterns of conformity within the group, alongside complex interpersonal dynamics.

Data analysis in participant observation typically involves a step-by-step process of immersion, categorization, and interpretation.

• After finishing up your observations, you read through your field notes or transcripts multiple times in the immersion phase. This helps you reflect on what you studied, and is well paired with conducting data cleansing to ensure everything is clear and correct prior to proceeding.
• You then create categories or themes to organize the data. This helps with identifying patterns, behaviors, and interactions relevant to your research question or study aims. In turn, these categories help you to form a coding system that labels or “tags” the aspects of the data that you want to focus on. These can be specific behaviors, emotions, or social interactions—whatever helps you to identify connections between different elements of your data.
• Next, your data can be analyzed using a variety of qualitative research methods, such as thematic analysis , grounded theory, or discourse analysis using the coded categories you created. This helps you interpret the data and develop further theories. You may also want to use triangulation , comparing data from multiple sources or methods, to bolster the reliability and validity of your findings.
• Lastly, it’s always a good research practice to seek feedback on your findings from other researchers in your field of study, as well as members of the group you studied. This helps to ensure the accuracy and reliability of your analysis and can mitigate some potential research biases .

Participant observations are a strong fit for some research projects, but with their advantages come their share of disadvantages as well.

Advantages of participant observations

• Participant observations allow you to generate rich and nuanced qualitative data —particularly useful when seeking to develop a deep understanding of a particular social context or experience. By immersing yourself in the group, you can gain an unrivaled insider perspective on the group’s beliefs, values, and practices.
• Participant observation is a flexible research method that can be adapted to fit a variety of research questions and contexts. Metrics like level of participation in the group, the length of the observation period, and the types of data collected all can be adjusted based on research goals and timeline.
• Participant observation is often used in combination with other research methods, such as interviews or surveys , to provide a more complete picture of the phenomenon being studied. This triangulation can help to improve the reliability and validity of the research findings, as participant observations are not particularly strong as a standalone method.

Disadvantages of participant observations

• Like many observational studies, participant observations are at high risk for many research biases , particularly on the side of the researcher. Because participant observation involves the researcher immersing themselves in the group being studied, there is a risk that their own biases could influence the data they collect, leading to observer bias . Likewise, the presence of a researcher in the group being studied can potentially influence the behavior of the participants. This can lead to inaccurate or biased data if participants alter their behavior in response to the researcher’s presence, leading to a Hawthorne effect or social desirability bias .
• Participant observations can be very expensive, time-consuming, and challenging to carry out. They often require a long period of time to build trust and gather sufficient data, with the data usually collected in an intensive, in-person manner. Some participant observations take generations to complete, which can make it difficult to conduct studies with limited time or resources.
• Participant observation can raise ethical concerns , requiring measured ethical consideration on the part of the researcher with regard to informed consent, privacy, and confidentiality. The researcher must take care to protect the privacy and autonomy of the participants and ensure that they are not placed at undue risk by the research.
• Confirmation bias
• Baader–Meinhof phenomenon
• Availability heuristic
• Halo effect
• Hindsight bias
• Ingroup bias
• Outgroup bias
• Perception bias
• Framing effect
• Self-serving bias
• Affect heuristic
• Representativeness heuristic
• Anchoring heuristic
• Primacy bias
• Optimism bias
• Sampling bias
• Ascertainment bias
• Attrition bias
• Self-selection bias
• Survivorship bias
• Nonresponse bias
• Undercoverage bias
• Hawthorne effect
• Observer bias
• Omitted variable bias
• Publication bias
• Conformity bias
• Pygmalion effect
• Recall bias
• Social desirability bias
• Placebo effect
• Actor-observer bias
• Ceiling effect
• Ecological fallacy
• Affinity bias

Ethical considerations in participant observation involve:

• Obtaining informed consent from all participants
• Protecting their privacy and confidentiality
• Ensuring that they are not placed at undue risk by the research, and
• Respecting their autonomy and agency as participants

Researchers should also consider the potential impact of their research on the community being studied and take steps to minimize any negative after-effects.

Participant observation is a type of qualitative research method . It involves active participation on the part of the researcher in the group being studied, usually over a longer period of time.

Other qualitative research methods, such as interviews or focus groups , do not involve the same level of immersion in the research and can be conducted in a less intense manner.

In participant observation , the researcher plays an active role in the social phenomenon, group, or social context being studied. They may move into the community, attend events or activities, or even take on specific roles within the group— fully joining the community over the course of the study. However, the researcher also maintains an observer role here, taking notes on the behavior and interactions of the participants to draw conclusions and guide further research.

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Research Methods In Psychology

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.

Hypotheses are statements about the prediction of the results, that can be verified or disproved by some investigation.

There are four types of hypotheses :

• Null Hypotheses (H0 ) – these predict that no difference will be found in the results between the conditions. Typically these are written ‘There will be no difference…’
• Alternative Hypotheses (Ha or H1) – these predict that there will be a significant difference in the results between the two conditions. This is also known as the experimental hypothesis.
• One-tailed (directional) hypotheses – these state the specific direction the researcher expects the results to move in, e.g. higher, lower, more, less. In a correlation study, the predicted direction of the correlation can be either positive or negative.
• Two-tailed (non-directional) hypotheses – these state that a difference will be found between the conditions of the independent variable but does not state the direction of a difference or relationship. Typically these are always written ‘There will be a difference ….’

All research has an alternative hypothesis (either a one-tailed or two-tailed) and a corresponding null hypothesis.

Once the research is conducted and results are found, psychologists must accept one hypothesis and reject the other. 

So, if a difference is found, the Psychologist would accept the alternative hypothesis and reject the null.  The opposite applies if no difference is found.

Sampling techniques

Sampling is the process of selecting a representative group from the population under study.

A sample is the participants you select from a target population (the group you are interested in) to make generalizations about.

Representative means the extent to which a sample mirrors a researcher’s target population and reflects its characteristics.

Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

• Volunteer sample : where participants pick themselves through newspaper adverts, noticeboards or online.
• Opportunity sampling : also known as convenience sampling , uses people who are available at the time the study is carried out and willing to take part. It is based on convenience.
• Random sampling : when every person in the target population has an equal chance of being selected. An example of random sampling would be picking names out of a hat.
• Systematic sampling : when a system is used to select participants. Picking every Nth person from all possible participants. N = the number of people in the research population / the number of people needed for the sample.
• Stratified sampling : when you identify the subgroups and select participants in proportion to their occurrences.
• Snowball sampling : when researchers find a few participants, and then ask them to find participants themselves and so on.
• Quota sampling : when researchers will be told to ensure the sample fits certain quotas, for example they might be told to find 90 participants, with 30 of them being unemployed.

Experiments always have an independent and dependent variable .

• The independent variable is the one the experimenter manipulates (the thing that changes between the conditions the participants are placed into). It is assumed to have a direct effect on the dependent variable.
• The dependent variable is the thing being measured, or the results of the experiment.

Operationalization of variables means making them measurable/quantifiable. We must use operationalization to ensure that variables are in a form that can be easily tested.

For instance, we can’t really measure ‘happiness’, but we can measure how many times a person smiles within a two-hour period. 

By operationalizing variables, we make it easy for someone else to replicate our research. Remember, this is important because we can check if our findings are reliable.

Extraneous variables are all variables which are not independent variable but could affect the results of the experiment.

It can be a natural characteristic of the participant, such as intelligence levels, gender, or age for example, or it could be a situational feature of the environment such as lighting or noise.

Demand characteristics are a type of extraneous variable that occurs if the participants work out the aims of the research study, they may begin to behave in a certain way.

For example, in Milgram’s research , critics argued that participants worked out that the shocks were not real and they administered them as they thought this was what was required of them. 

Extraneous variables must be controlled so that they do not affect (confound) the results.

Randomly allocating participants to their conditions or using a matched pairs experimental design can help to reduce participant variables. 

Situational variables are controlled by using standardized procedures, ensuring every participant in a given condition is treated in the same way

Experimental Design

Experimental design refers to how participants are allocated to each condition of the independent variable, such as a control or experimental group.

• Independent design ( between-groups design ): each participant is selected for only one group. With the independent design, the most common way of deciding which participants go into which group is by means of randomization. 
• Matched participants design : each participant is selected for only one group, but the participants in the two groups are matched for some relevant factor or factors (e.g. ability; sex; age).
• Repeated measures design ( within groups) : each participant appears in both groups, so that there are exactly the same participants in each group.
• The main problem with the repeated measures design is that there may well be order effects. Their experiences during the experiment may change the participants in various ways.
• They may perform better when they appear in the second group because they have gained useful information about the experiment or about the task. On the other hand, they may perform less well on the second occasion because of tiredness or boredom.
• Counterbalancing is the best way of preventing order effects from disrupting the findings of an experiment, and involves ensuring that each condition is equally likely to be used first and second by the participants.

If we wish to compare two groups with respect to a given independent variable, it is essential to make sure that the two groups do not differ in any other important way. 

Experimental Methods

All experimental methods involve an iv (independent variable) and dv (dependent variable)..

The researcher decides where the experiment will take place, at what time, with which participants, in what circumstances,  using a standardized procedure.

• Field experiments are conducted in the everyday (natural) environment of the participants. The experimenter still manipulates the IV, but in a real-life setting. It may be possible to control extraneous variables, though such control is more difficult than in a lab experiment.
• Natural experiments are when a naturally occurring IV is investigated that isn’t deliberately manipulated, it exists anyway. Participants are not randomly allocated, and the natural event may only occur rarely.

Case studies are in-depth investigations of a person, group, event, or community. It uses information from a range of sources, such as from the person concerned and also from their family and friends.

Many techniques may be used such as interviews, psychological tests, observations and experiments. Case studies are generally longitudinal: in other words, they follow the individual or group over an extended period of time. 

Case studies are widely used in psychology and among the best-known ones carried out were by Sigmund Freud . He conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

Case studies provide rich qualitative data and have high levels of ecological validity. However, it is difficult to generalize from individual cases as each one has unique characteristics.

Correlational Studies

Correlation means association; it is a measure of the extent to which two variables are related. One of the variables can be regarded as the predictor variable with the other one as the outcome variable.

Correlational studies typically involve obtaining two different measures from a group of participants, and then assessing the degree of association between the measures. 

The predictor variable can be seen as occurring before the outcome variable in some sense. It is called the predictor variable, because it forms the basis for predicting the value of the outcome variable.

Relationships between variables can be displayed on a graph or as a numerical score called a correlation coefficient.

• If an increase in one variable tends to be associated with an increase in the other, then this is known as a positive correlation .
• If an increase in one variable tends to be associated with a decrease in the other, then this is known as a negative correlation .
• A zero correlation occurs when there is no relationship between variables.

After looking at the scattergraph, if we want to be sure that a significant relationship does exist between the two variables, a statistical test of correlation can be conducted, such as Spearman’s rho.

The test will give us a score, called a correlation coefficient . This is a value between 0 and 1, and the closer to 1 the score is, the stronger the relationship between the variables. This value can be both positive e.g. 0.63, or negative -0.63.

A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. A correlation only shows if there is a relationship between variables.

Correlation does not always prove causation, as a third variable may be involved. 

Interview Methods

Interviews are commonly divided into two types: structured and unstructured.

A fixed, predetermined set of questions is put to every participant in the same order and in the same way. 

Responses are recorded on a questionnaire, and the researcher presets the order and wording of questions, and sometimes the range of alternative answers.

The interviewer stays within their role and maintains social distance from the interviewee.

There are no set questions, and the participant can raise whatever topics he/she feels are relevant and ask them in their own way. Questions are posed about participants’ answers to the subject

Unstructured interviews are most useful in qualitative research to analyze attitudes and values.

Though they rarely provide a valid basis for generalization, their main advantage is that they enable the researcher to probe social actors’ subjective point of view. 

Questionnaire Method

Questionnaires can be thought of as a kind of written interview. They can be carried out face to face, by telephone, or post.

The choice of questions is important because of the need to avoid bias or ambiguity in the questions, ‘leading’ the respondent or causing offense.

• Open questions are designed to encourage a full, meaningful answer using the subject’s own knowledge and feelings. They provide insights into feelings, opinions, and understanding. Example: “How do you feel about that situation?”
• Closed questions can be answered with a simple “yes” or “no” or specific information, limiting the depth of response. They are useful for gathering specific facts or confirming details. Example: “Do you feel anxious in crowds?”

Its other practical advantages are that it is cheaper than face-to-face interviews and can be used to contact many respondents scattered over a wide area relatively quickly.

Observations

There are different types of observation methods :

• Covert observation is where the researcher doesn’t tell the participants they are being observed until after the study is complete. There could be ethical problems or deception and consent with this particular observation method.
• Overt observation is where a researcher tells the participants they are being observed and what they are being observed for.
• Controlled : behavior is observed under controlled laboratory conditions (e.g., Bandura’s Bobo doll study).
• Natural : Here, spontaneous behavior is recorded in a natural setting.
• Participant : Here, the observer has direct contact with the group of people they are observing. The researcher becomes a member of the group they are researching.  
• Non-participant (aka “fly on the wall): The researcher does not have direct contact with the people being observed. The observation of participants’ behavior is from a distance

Pilot Study

A pilot  study is a small scale preliminary study conducted in order to evaluate the feasibility of the key s teps in a future, full-scale project.

A pilot study is an initial run-through of the procedures to be used in an investigation; it involves selecting a few people and trying out the study on them. It is possible to save time, and in some cases, money, by identifying any flaws in the procedures designed by the researcher.

A pilot study can help the researcher spot any ambiguities (i.e. unusual things) or confusion in the information given to participants or problems with the task devised.

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all or can complete the task – all performances are low.

The opposite effect is a ceiling effect, when the task is so easy that all achieve virtually full marks or top performances and are “hitting the ceiling”.

Research Design

In cross-sectional research , a researcher compares multiple segments of the population at the same time

Sometimes, we want to see how people change over time, as in studies of human development and lifespan. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.

In cohort studies , the participants must share a common factor or characteristic such as age, demographic, or occupation. A cohort study is a type of longitudinal study in which researchers monitor and observe a chosen population over an extended period.

Triangulation means using more than one research method to improve the study’s validity.

Reliability

Reliability is a measure of consistency, if a particular measurement is repeated and the same result is obtained then it is described as being reliable.

• Test-retest reliability :  assessing the same person on two different occasions which shows the extent to which the test produces the same answers.
• Inter-observer reliability : the extent to which there is an agreement between two or more observers.

Meta-Analysis

Meta-analysis is a statistical procedure used to combine and synthesize findings from multiple independent studies to estimate the average effect size for a particular research question.

Meta-analysis goes beyond traditional narrative reviews by using statistical methods to integrate the results of several studies, leading to a more objective appraisal of the evidence.

This is done by looking through various databases, and then decisions are made about what studies are to be included/excluded.

• Strengths : Increases the conclusions’ validity as they’re based on a wider range.
• Weaknesses : Research designs in studies can vary, so they are not truly comparable.

Peer Review

A researcher submits an article to a journal. The choice of the journal may be determined by the journal’s audience or prestige.

The journal selects two or more appropriate experts (psychologists working in a similar field) to peer review the article without payment. The peer reviewers assess: the methods and designs used, originality of the findings, the validity of the original research findings and its content, structure and language.

Feedback from the reviewer determines whether the article is accepted. The article may be: Accepted as it is, accepted with revisions, sent back to the author to revise and re-submit or rejected without the possibility of submission.

The editor makes the final decision whether to accept or reject the research report based on the reviewers comments/ recommendations.

Peer review is important because it prevent faulty data from entering the public domain, it provides a way of checking the validity of findings and the quality of the methodology and is used to assess the research rating of university departments.

Peer reviews may be an ideal, whereas in practice there are lots of problems. For example, it slows publication down and may prevent unusual, new work being published. Some reviewers might use it as an opportunity to prevent competing researchers from publishing work.

Some people doubt whether peer review can really prevent the publication of fraudulent research.

The advent of the internet means that a lot of research and academic comment is being published without official peer reviews than before, though systems are evolving on the internet where everyone really has a chance to offer their opinions and police the quality of research.

Types of Data

• Quantitative data is numerical data e.g. reaction time or number of mistakes. It represents how much or how long, how many there are of something. A tally of behavioral categories and closed questions in a questionnaire collect quantitative data.
• Qualitative data is virtually any type of information that can be observed and recorded that is not numerical in nature and can be in the form of written or verbal communication. Open questions in questionnaires and accounts from observational studies collect qualitative data.
• Primary data is first-hand data collected for the purpose of the investigation.
• Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.

Validity means how well a piece of research actually measures what it sets out to, or how well it reflects the reality it claims to represent.

Validity is whether the observed effect is genuine and represents what is actually out there in the world.

• Concurrent validity is the extent to which a psychological measure relates to an existing similar measure and obtains close results. For example, a new intelligence test compared to an established test.
• Face validity : does the test measure what it’s supposed to measure ‘on the face of it’. This is done by ‘eyeballing’ the measuring or by passing it to an expert to check.
• Ecological validit y is the extent to which findings from a research study can be generalized to other settings / real life.
• Temporal validity is the extent to which findings from a research study can be generalized to other historical times.

Features of Science

• Paradigm – A set of shared assumptions and agreed methods within a scientific discipline.
• Paradigm shift – The result of the scientific revolution: a significant change in the dominant unifying theory within a scientific discipline.
• Objectivity – When all sources of personal bias are minimised so not to distort or influence the research process.
• Empirical method – Scientific approaches that are based on the gathering of evidence through direct observation and experience.
• Replicability – The extent to which scientific procedures and findings can be repeated by other researchers.
• Falsifiability – The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue.

Statistical Testing

A significant result is one where there is a low probability that chance factors were responsible for any observed difference, correlation, or association in the variables tested.

If our test is significant, we can reject our null hypothesis and accept our alternative hypothesis.

If our test is not significant, we can accept our null hypothesis and reject our alternative hypothesis. A null hypothesis is a statement of no effect.

In Psychology, we use p < 0.05 (as it strikes a balance between making a type I and II error) but p < 0.01 is used in tests that could cause harm like introducing a new drug.

A type I error is when the null hypothesis is rejected when it should have been accepted (happens when a lenient significance level is used, an error of optimism).

A type II error is when the null hypothesis is accepted when it should have been rejected (happens when a stringent significance level is used, an error of pessimism).

Ethical Issues

• Informed consent is when participants are able to make an informed judgment about whether to take part. It causes them to guess the aims of the study and change their behavior.
• To deal with it, we can gain presumptive consent or ask them to formally indicate their agreement to participate but it may invalidate the purpose of the study and it is not guaranteed that the participants would understand.
• Deception should only be used when it is approved by an ethics committee, as it involves deliberately misleading or withholding information. Participants should be fully debriefed after the study but debriefing can’t turn the clock back.
• All participants should be informed at the beginning that they have the right to withdraw if they ever feel distressed or uncomfortable.
• It causes bias as the ones that stayed are obedient and some may not withdraw as they may have been given incentives or feel like they’re spoiling the study. Researchers can offer the right to withdraw data after participation.
• Participants should all have protection from harm . The researcher should avoid risks greater than those experienced in everyday life and they should stop the study if any harm is suspected. However, the harm may not be apparent at the time of the study.
• Confidentiality concerns the communication of personal information. The researchers should not record any names but use numbers or false names though it may not be possible as it is sometimes possible to work out who the researchers were.

5 Naturalistic Observation Strengths and Weaknesses

Psychologists and other social scientists make use of the naturalistic observation research method to observe subjects in their natural environment. This kind of research is mostly used when lab research is proven to be unrealistic, cost prohibitive or may affect the behavior of a subject.

Naturalistic observation differs from structured observation in that the observer doesn’t intervene with what the subject is doing. For instance, a school principal might want to sit in a certain class to observe the interaction between students and teachers. Having to do this in a lab would require setting up a classroom which would likely alter the behavior of participants. But is it the most useful king of research method? Here’s a look at its strengths and weaknesses:

List of Naturalistic Observation Strengths

1. It allows for observation without having to manipulate anything How do you study group behavior in a prison setting? Do you forcefully imprison people just to get results? That wouldn’t be fair to them and it raises a lot of ethical concerns as well. So the best thing to do would be to gain a permit to observe inmates at an actual information. There, you can gather by the hour and daily information which you can use to draw conclusions for your research.

2. It helps bring validity to the research An event that happened in the lab isn’t proof that the same would happen in a real-world scenario. Lab settings are different from a natural setting. And every detail matters. This is why your research would be so much more reliable if you can observe your subjects when they are in their natural setting. It would be difficult to conclude that this is how a koala behaves if you only observe them in a lab setting.

List of Naturalistic Observation Weaknesses

1. Subjects behave differently when they know they are being observed Take the classroom observation example, it is difficult to determine the true behavior of students based on one sit-in alone. For one, they know you are there and are paying attention and would most likely behave rather than do what they normally do. This may impact your findings even though the setting is already natural but the behavior may not be as much.

2. Researchers have different opinions If there is more than one researcher involved, conflicts may arise due to a difference in opinion. Or, researchers couldn’t come to conclusion about why a certain animal behaves in a particular way. Actions are open to interpretation and an act done by a kangaroo might be interpreted as playing by one researcher while the other argues it was aggression.

3. Results will be affected by outside influences Suppose you want to observe a bear during mating season. What happens when that bear couldn’t find a mate? After all, the world is changing and their environment is surely changing. Can you guarantee that a potential mate would appear during the season? What all this means is you could get results or you couldn’t.

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Introductory Psychology Blog (S14)_C

Making connections between theory and reality…, laboratory and naturalistic observations.

Today laboratory observations are very common while trying to understand the behavior of a person and even in some cases of an animal. Along with laboratory observations, naturalistic observations can also be made. The two different observations help researchers find out what is wrong with a specific person or animal and what could possibly be causing that. Observations allow researchers to gather their information, and form conclusions in order to help someone out. Laboratory and naturalistic observations are both successful in seeking out the information needed, however they both contain a number of advantages and disadvantages making them more appealing in certain conditions.

Naturalistic observation allows the patient to be very comfortable in their setting and eliminates the fear of the patient being uncomfortable. Natural settings allow the patient to act natural, and have a great possibility of matching up with the real life behavior of the person. However a disadvantage is that when someone knows they are being observed they can change the results of the study without noticing. If someone knows they are being watched it can alter their behavior and change the results, which has the potential to possibly mess up the information gathered by the researchers.

On the other had laboratory observations occur in a laboratory because special equipment might be needed to perform the experiment and it might be hard to provide that equipment in a natural setting. Advantages of observations taken from a laboratory include a much more controlled setting. Being in a laboratory, the researchers are able to control everything that is happening and can minimize any outside influences. Another advantage to this kind of observation is the use of specialized equipment; it can help produce results that would not be able to be observed outside of a laboratory. However, being observed in a laboratory can be very uncomfortable to some people. When a patient knows they are being observed it can be very hard for them to focus and can possibly alter the results.

My friend recently has been having problems when she is sleeping and doctors have a feeling that she stops breathing in her sleep. While she was explaining all of this to me she said she was scared to go in for testing. Ironically we had just discussed behavioral observations in class, and I knew why she was so nervous. She had said that they want to watch her sleep, in order to determine if she does indeed stop breathing while she is sleeping. I knew she was going to feel uncomfortable since she would be sleeping in a new environment but I kept reinforcing her that they only want to find out what is wrong with her. Although she was very scared and nervous for the testing to be done, she knew that it needed to be done for them to figure out what is wrong with her when she is sleeping.

I thought it was very interesting that she had mentioned this right after we had learned about it. Everyday people are undergoing observational studies in order to figure out what could possibly be wrong with them, if anything is wrong. A laboratory observation does have many advantages however, for some people it can be very unpleasing and very nerve-racking. At the end of the day, the process of being observed is worth it because researchers and specialists gather the information needed to help figure out what is wrong with someone.

One thought on “ Laboratory and Naturalistic Observations ”

I can only imagine how nervous she was to be tested. I would definitely feel uncomfortable in that situation and probably wouldn’t be able to fall asleep for them to test anything. Do you know if they give the patients any form of sleeping drug to allow them to fall asleep more easily? Because I can imagine the problem arises among many patients that they can’t fall asleep when they know they are being tested.

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The Pros and Cons of Using Observation in Research

Table of Contents

Have you ever wondered how researchers capture human behavior in its most natural state? It’s like trying to photograph a butterfly without startling it – a delicate task that requires patience and skill. One such method that has long intrigued psychologists and researchers alike is the observation method . Let’s embark on an insightful journey to explore the depths of this research tool, disclosing its merits and demerits along the way.

Advantages of Observation

Like a detective piecing together clues, observation allows researchers to collect data unobtrusively. Let’s dive into some of its standout benefits.

Authentic Data from Natural Environments

One of the most significant advantages of the observation method is its ability to record behavior as it occurs naturally. Researchers get a front-row seat to genuine interactions, untainted by the artificiality of a lab setting. This authenticity can lead to findings that are more applicable to real-world situations.

Detailed Qualitative Insights

Observation is a goldmine for qualitative data . It provides a depth of context and detail that surveys and experiments may miss. By observing, researchers can notice subtleties and nuances in behavior, giving them a richer understanding of their subjects.

Non-verbal Cues and Dynamics

Humans communicate a lot without saying a word. Through observation, researchers can interpret non\-verbal cues , body language, and social dynamics that might otherwise go unnoticed. This silent information can be incredibly telling and valuable.

Disadvantages of Observation

However, even the most skilled observer cannot escape the method’s inherent limitations. Let’s scrutinize the drawbacks that challenge the integrity of observational data.

Observer Bias

Researchers are only human, and they carry their own perceptions and biases. An observer’s expectations can skew their interpretation of what they witness, potentially contaminating the data. It’s a classic case of ‘seeing what you want to see’.

The Hawthorne Effect

People often change their behavior when they know they’re being watched – this is known as the Hawthorne effect. This reactivity can lead to distorted data, as subjects may alter their natural responses due to the observer’s presence.

Time-Consuming and Costly

Good observation takes time. Researchers may have to invest hours, days, or even weeks collecting data. And with time comes cost – more hours mean more resources spent, making observation a potentially expensive method.

Navigating the Pros and Cons

Understanding these advantages and disadvantages is crucial for researchers to navigate the complex terrain of observational studies. So, how does one strike a balance?

Minimizing Observer Bias

Training observers thoroughly and using multiple observers can dilute individual biases. Additionally, employing blind observation , where the observer is unaware of the study’s aims, can further reduce bias.

Accounting for the Hawthorne Effect

To counteract the Hawthorne effect, researchers can use covert observation , where the observer is hidden or the subjects are unaware of the observation. This strategy aims to capture behavior that is as natural and unaffected as possible.

Optimizing Time and Resources

While observation can indeed be time-consuming, careful planning and clear objectives can streamline the process. Researchers should also weigh the value of the rich data they expect to collect against the costs incurred.

Through the lens of the observation method, we can glimpse the intricate tapestry of human behavior. As with any research tool, it comes with its own set of challenges and rewards. The key lies in understanding these dynamics and deploying strategies to mitigate the disadvantages while capitalizing on the advantages.

How do you think observation compares to other research methods in terms of reliability and authenticity? Could the potential for bias be offset by the depth of understanding it provides? Let’s discuss the intricate balance between the observer and the observed.

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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
• Writing Style of the Report
• Report Writing – the Do’s and the Don’ts
• Format for Report in Psychology Area
• Major Sections in a Report

14 Review of Literature

• Purposes of Review of Literature
• Sources of Review of Literature
• 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
• Guidelines for Writing a Summary
• 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
• General Guidelines to Write References

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Fish consumption, cognitive impairment and dementia: an updated dose-response meta-analysis of observational studies

• Open access
• Published: 20 August 2024
• Volume 36 , article number  171 , ( 2024 )

Cite this article

You have full access to this open access article

• Justyna Godos 1 , 2 ,
• Agnieszka Micek 3 ,
• Walter Currenti 1 ,
• Carlotta Franchi 4 , 5 ,
• Andrea Poli 6 ,
• Maurizio Battino 7 , 8 , 9 ,
• Alberto Dolci 10 ,
• Cristian Ricci 11 ,
• Zoltan Ungvari 12 , 13 , 14 , 15 , 16 &
• Giuseppe Grosso 1 , 2  

Cognitive impairment is projected to affect a preponderant proportion of the aging population. Lifelong dietary habits have been hypothesized to play a role in preventing cognitive decline. Among the most studied dietary components, fish consumptionhas been extensively studied for its potential effects on the human brain.

To perform a meta-analysis of observational studies exploring the association between fish intake and cognitive impairment/decline and all types of dementia.

A systematic search of electronic databases was performed to identify observational studies providing quantitative data on fish consumption and outcomes of interest. Random effects models for meta-analyses using only extreme exposure categories, subgroup analyses, and dose-response analyses were performed to estimate cumulative risk ratios (RRs) and 95% confidence intervals (CIs).

The meta-analysis comprised 35 studies. Individuals reporting the highest vs. the lowest fish consumption were associated with a lower likelihood of cognitive impairment/decline (RR = 0.82, 95% CI: 0.75, 0.90, I 2  = 61.1%), dementia (RR = 0.82, 95% CI: 0.73, 0.93, I 2  = 38.7%), and Alzheimer’s disease (RR = 0.80, 95% CI: 0.67, 0.96, I 2  = 20.3%). The dose-response relation revealed a significantly decreased risk of cognitive impairment/decline and all cognitive outcomes across higher levels of fish intake up to 30% for 150 g/d (RR = 0.70, 95% CI: 0.52, 0.95). The results of this relation based on APOE ε4 allele status was mixed based on the outcome investigated.

Conclusions

Current findings suggest fish consumption is associated with a lower risk of cognitive impairment/decline in a dose-response manner, while for dementia and Alzheimer’s disease there is a need for further studies to improve the strength of evidence.

Avoid common mistakes on your manuscript.

Introduction

Over the last decades, the increase in human lifespan and the growing older population worldwide has changed the epidemiology of diseases leading to a substantial rise in age-related health conditions [ 1 , 2 ]. Mental and cognitive health have been reported to represent an emerging global issue for elderly individuals worldwide [ 3 ]. Specifically concerning cognitive-related conditions, Alzheimer’s disease (AD) and other dementias have been estimated to account for about nearly 60 million cases globally projected to rise 3-fold by 2050 [ 4 ]. [ 5 , 6 ] Diet is nowadays recognized to affect human brain and mental health conditions [ 7 , 8 ]. Several dietary components, such as healthy fats, certain amino acids and oligopeptides, antioxidant vitamins and phytochemicals [i.e., (poly)phenols] are recognized to play a role in preserving neuron stability and functionality as well as counteracting neuroinflammation [ 9 , 10 , 11 ]. Dietary patterns characterized by fish consumption as one of the main sources of protein [i.e., the Mediterranean diet, the Nordic diet, and the Dietary Approach to Stop Hypertension (DASH)] have been consistently associated with lower risk of neurodegenerative conditions [ 12 , 13 , 14 ]. Fish has long been studied for its role on human health [ 15 ]. Its content in omega-3 polyunsaturated fatty acids (PUFAs) is considered the culprit for the potentially beneficial effects of seafood on mental health [ 16 ], while only relatively recently additional attention has been paid to bioactive oligopeptides (bioactive molecules composed of only few amino acids) and their ability to exert direct effects in the brain, demonstrating anti-inflammatory and antioxidant activities [ 17 , 18 ]. Although the rationale behind the potential beneficial effects of fish intake in neurodegenerative diseases is quite convincing, it is still unclear whether fish consumption per se might play a role in the prevention of cognitive decline and dementia. Two recent meta-analyses explored the role of fish and cognitive outcomes reporting a dose-response association with lower risk of dementia and Alzheimer’s disease [ 19 , 20 ]: however, the results are outdated, a broader exploration of cognitive outcomes could be further implemented, risk estimates were only provided by weekly intakes, and some missing entries could be integrated. Hence, the aim of the present study was to update current evidence of the association between fish consumption and cognitive decline, impairment, and dementia risk reported in observational studies and provide a summary meta-analysis of the results.

The design and reporting of this study followed the Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines (Supplementary Table 1 ) [ 21 ]. The systematic review protocol was registered in the PROSPERO International Prospective Register of Systematic Reviews database (ID: CRD42024501232, at https://www.crd.york.ac.uk/prospero/ ).

Search strategy and study selection

To identify potentially eligible studies, a systematic literature search of PubMed and Scopus databases was performed from their inception up to March 2024. The search strategy was based on the combination of the relevant keywords imputed as text words and MeSH terms, related to fish, seafood and shellfish and cognitive outcomes (Supplementary Table 2 ). Eligibility criteria for the systematic review and meta-analysis were specified using the PICOS approach (Supplementary Table 3 ). Studies were eligible if they met the following inclusion criteria: (1) conducted on older adults (i.e., mean age > 50 years old) or, more in general, investigating cognitive outcomes occurring at older age; (2) had observational design (cohort studies, cross-sectional studies, case-control studies); (2) reported exposures to habitual fish, seafood, or shellfish consumption assessed through either 24-h recalls, food frequency questionnaires (FFQ), or dietary diaries; (4) investigated cognitive impairment, cognitive decline, and/or any type of dementia (including Alzheimer’s disease) as outcome; and (5) provided probability measures [odds ratios (ORs), relative risks (RRs), or hazard ratios (HRs)] for the cognitive outcomes investigated. Although the systematic search was not language restricted, only English language studies were eligible. Reference lists of all eligible studies were also examined for any additional studies not previously identified. If more than one study reported results on the same cohort, only the study including the larger cohort size, the longest follow-up, or the most comprehensive data was included in the meta-analysis. The systematic literature search and study selection were performed by two independent authors (J.G. and G.G.) and any incongruity was resolved through a discussion and reaching consensus.

Data extraction and quality assessment

Data from all eligible studies were extracted using a standardized electronic form. The following information was collected: first author name, publication year, study design and location, population age and gender, sample size, details on the assessment method of dietary habits, details on the exposure, details on the assessment method of the outcome of interest, outcome of interest, main findings of the study, measures of association including 95% confidence intervals. The quality of each eligible study was evaluated using the Newcastle-Ottawa Quality Assessment Scale, consisting of 3 domains of quality (selection, comparability, and outcome) and assessing specific study characteristics depending on the type of study design [ 22 ]: in general, studies scoring over 5 and 7 points for cross-sectional and prospective studies, respectively, were identified as being of good/high quality. Two investigators extracted the data and assessed the methodological quality independently and any incongruity was resolved through a discussion and reaching consensus.

Statistical analysis

Various risk measures, such as odds ratios (ORs) and hazard ratios (HRs) under the rare disease assumption were treated approximately equivalent to risk ratios and further all were consistently denoted by RRs. The logarithms of RRs from fully adjusted models were pooled in meta-analysis to compare the risk of cognitive events between extreme categories of fish consumption and to reveal dose-dependent relationships. Cognitive impairment and cognitive decline were deemed as a single outcome because, although not clearly stated in all studies providing such outcomes, they both most likely referred to age-related conditions or early-stage disease. All-type dementias and Alzheimer’s disease were investigated as individual separate endpoints. No further data on other specific types of dementia was available in the included studies. RRs for independent studies reported in the same article (i.e., for NHS and HPFS cohorts), were analyzed as separate estimates. When risk estimates were provided for males, females and both sexes together, the latter were used in the main analyses;. when pooled data by sex was not provided in the original study, risk estimates were first pooled using a fixed effect meta-analysis to obtain the joint RR. Der Simonian and Laird random-effects model was applied in which weights of the studies were calculated as the inverse of the sum of both within- and between-study variance [ 23 ]. The differences in the research results included in the meta-analysis reflected by the degree of heterogeneity were assessed by the Cochran’s Q-test and the I² index. For Q-test the level of significance was set at p  < 0.10 and the value of I 2 statistic exceeding 50% was regarded as considerable heterogeneity between studies. A non-linear dose–response meta-analysis was performed only for studies which reported RRs for at least 3 different levels of well-defined fish intake. If the range of fish consumption was not given, the right-unbounded interval was assumed to be the same width as of the adjacent category, while the left-unbounded interval we set to zero. For each category of exposure, the medians, means or midpoints of ranges of daily consumption were extracted directly from the original studies and assigned to the corresponding RRs. When specific quantity of fish intake was not available, daily fish consumption was calculated by multiplying the frequency of consumption (number of serving per day) by the average portion size estimated as 105 g [ 24 , 25 ]. A dose–response meta-analysis was modeled by restricted cubic splines with the knots at fixed percentiles of the fish intake distribution (10%, 50%, and 90%) [ 26 ]. If the distribution of cases and number of participants or person-years was accessible for all categories of fish consumption, we applied the generalized least squares method to estimate trend from summarized dose-response data accounting for the correlation between extracted RRs [ 27 , 28 ]. Otherwise, a standard technique based on weighted least squares analysis was adapted [ 27 ]. The between-study variance-covariance matrices were assessed via multivariate extension of the method of moments to combine all the regression coefficients across studies. A non-linearity was tested by verifying whether the coefficient of the second spline differ from zero. To compare the effects of fish consumption on cognitive function in specific subgroups in which the risk of disease could potentially differ, analyses in strata of APOE genotype (carrying APOE ε4 allele vs. possessing ε2 or ε3 alleles) were performed. Sensitivity and subgroup analysis were also conducted to explore potential sources of heterogeneity. A one-by-one exclusion method was adopted by recalculating combined effect sized after removing one at the time each study. Subgroup analyses were conducted according to year of publication, study quality, age of participants at baseline, study design, length of follow-up, sample size, and type of dementia diagnosis. Small-study effects being the indicator of possible publication bias was examined quantitatively via Egger’s regression test as well as using graphical technique based on visual assessment of asymmetry patterns of funnel plots further adjusting for the number and outcomes of missing studies using trim-and-fill method. R version 4.3.0 (Development Core Team) was used for the statistical analysis. All tests were two-tailed and statistical significance was defined as P  < 0.05.

A total of 1169 studies were deemed of potential interest for this systematic search. After removal of 130 duplicates and exclusion of 813 studies through title and abstract evaluation, the full-text from 226 studies were examined. An initial screening was applied based on the following reasons: lack of exposure ( n  = 85), no outcome of interest ( n  = 90), different study design ( n  = 2), only reported on biomarkers of consumption ( n  = 3), and conducted on younger population ( n  = 8). The resulting 38 studies were further examined for overlaps. After the final exclusion of 3 studies conducted on the same cohorts, a total of 35 studies [ 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 ] were included in the present meta-analysis (Supplementary Fig.  1 ).

Study characteristics exploring fish consumption and cognitive outcomes

The main background characteristics of the studies included, and an overview of the main findings are reported in Table  1 . A total of 25 had a prospective design, 8 were cross-sectional and 2 were case-control studies. Ten studies were conducted in Western countries, with 8 specifically involving Northern American cohorts and 13 conducted in European countries, while 13 including Eastern Asian countries. Most studies involved both sexes with just a few exceptions. Among the outcomes investigated through a variety of diagnostic and screening tools, 18 studies explored the relation between fish intake and cognitive decline 15 accounted for diagnosis of dementia, and 11 specifically investigated the risk of Alzheimer’s disease. In general (depending on the differential inclusion in specific analysis), the whole sample included a total of about 849,263 individuals, 8537 comprehensive cases of cognitive impairment/decline, 12,148 cases of dementia, and 5320 cases of Alzheimer’s disease. The quality of the studies scored over 5 for cross-sectional and over 7 for case-control and prospective studies, suggesting an overall good quality of the reports included in this meta-analysis (Supplementary Tables 4 – 6 ).

Comparison of the risk of cognitive disorders between extreme categories of fish intake

The analysis of the association between fish consumption and dementia, Alzheimer’s disease, and cognitive impairment/decline was based on 15, 10 and 18 studies, respectively (Fig.  1 and Supplementary Table 7 ). Comparing with the lowest category of fish consumption, the highest consumption was related to 18%, 15% and 18% lower risk of each aforementioned outcome, respectively (RR = 0.82, 95% CI: 0.73–0.93 for dementia, RR = 0.80, 95% CI: 0.67–0.96 for Alzheimer’s disease, and RR = 0.82, 95% CI: 0.75–0.90 for cognitive impairment/decline; Fig.  1 ). The evidence of substantial heterogeneity was detected for cognitive impairment/decline ( I 2  = 61%, P  < 0.001; Fig.  1 ). Exclusion of one study at the time did not considerably change any of the results (Supplementary Fig.  2 ); however, the analysis for cognitive impairment/decline risk resulted in a decrement of I 2 statistic to 42% while still maintaining the similar estimate of size effect (RR = 0.76, 95% CI: 0.66–0.88) after exclusion of one study [ 52 ]. The inspection of funnel plots and the results of the Egger’s test revealed some evidence of asymmetry in all outcomes except for cognitive impairment/decline (Supplementary Fig.  3 ): trim-and-fill analysis adjusting for potential publication bias by complementing 5 and 4 missing studies in the case of dementia and Alzheimer’s disease, respectively, confirmed the previous findings (Supplementary Table 7 , Supplementary Fig.  4 ). Subgroup analysis for each outcome showed substantially stable results, with some minor loss of significance in certain subgroups, such as results in European countries in the case of dementia and Alzheimer’s disease, analysis in studies with longer follow-up, and participants below 70 years (Table  2 ). Additional sub-group analyses focused on prospective studies only showed consistent results with only minor changes (i.e., no significant results in Asian countries, studies with longer follow-up, and larger samples for dementia) (Supplementary Table 8 ). Notably, most studies on cognitive decline relied on self-reported diagnosis through screening tools, while analyses on dementia and Alzheimer’s disease relied on clinical diagnosis, in both cases reporting stronger reduced risks with the most used diagnostic approach used (Supplementary Table 8 ).

Meta-analysis of the risk of cognitive outcomes for the highest vs. the lowest fish consumption

Comparison of the risk of cognitive disorders dependent on the amount of fish consumption

The dose-response analysis using restricted cubic splines is graphically presented in Fig.  2 and RRs are reported in Table  3 . A significant decreased risk of cognitive impairment/decline across higher levels of fish intake up to 30% for 150 g/d was found (RR = 0.70, 95% CI: 0.52–0.95), although with large confidence intervals and evidence of significant heterogeneity ( I² >90%, P  < 0.001). No significant findings were found for dementia and Alzheimer’s disease, although a decreased risk of the latter for up to 50 g/d of fish was reported (Fig.  2 and Table  3 ).

Graphical representation of dose-response meta-analysis of the risk of cognitive outcomes for various servings of fish intake

Fish intake and cognitive outcomes by APOE genotype strata analysis

A limited number of studies presented results by APOE genotype strata (up to 3 studies, dependent on the endpoint) and results were rather contrasting (Supplementary Fig.  5 and Supplementary Table 9 ). Results from pooled analyses for dementia resulted in null findings although with a trend toward decreased risk in APO ε2 or ε3 allele carriers (RR = 0.77, 95% CI: 0.58–1.03). However, the only study specifically conducted on cognitive impairment/decline showed a decreased risk for higher fish consumers among APOE ε4 allele carriers (RR = 0.18, 95% CI: 0.05–0.63). No significant associations were found between fish intake and Alzheimer’s disease risk by APOE genotype strata.

The aim of this study was to explore the relation between fish consumption and the risk of a variety of cognitive outcomes in observational studies. The main results of the meta-analysis showed that higher fish consumption was associated with lower risk of cognitive impairment/decline, dementia, and Alzheimer’s disease, although a clear dose-response relation could only be observed for the former. A certain degree of heterogeneity could only be partially explained by some variables (i.e., age groups), while differences by genetic background may in fact play a role, yet only limitedly investigated, with not enough studies to effectively draft conclusions on this matter.

Aside from a para-physiological decline in cognitive abilities associated with the growing age, pathological cognitive impairment may depend on a variety of changes in the older brain both determined by genetic and environmental stimuli [ 65 ]. Alteration of brain structure, neurotransmission, vascular irroration, and deposit of abnormal proteins (i.e., beta amyloid) are the most common pathological processes determining an alteration of cognitive abilities in older individuals [ 66 , 67 , 68 ]. Fish is rich in omega-3 PUFA, which have been widely demonstrated to exert a variety of actions in the human brain, including modulating the immune response to insulting stimuli and eventually counteracting neuroinflammation by serving as precursors of pro-resolving mediators, affecting nitric oxide synthesis, decreasing reactive oxygen species (ROS), and more in general improving endothelial dysfunction characterizing certain types of dementia [ 69 , 70 , 71 ]. Omega-3 PUFA also play an important role in maintaining structural function of the brain, preserving the integrity of the blood-brain barrier, counteract brain atrophy, promoting neurogenesis and increased volume of certain brain area deputed to cognitive functions, the hippocampus [ 72 , 73 , 74 ]. Although much evidence for such mechanisms is often supported by only preclinical models, current findings match the rationale behind the results from most observational studies conducted so far on fish and cognitive outcomes.

Aside from omega-3 PUFA, recent research has focused on other components of fish that may result in effects on the human brain. Oligopeptides found in fish have been shown to potentially exert neuroprotective effects by serving as precursors of biologically active agents that may counteract some processes occurring in the brain promoting cognitive decline [ 75 ]. Some of the mechanisms potentially playing a role against neurodegenerative diseases reported to be exerted by bioactive peptides from seafood include modulation of inflammatory pathways and pro-survival and neurotrophic gene expression, improvement of cell viability, inhibition of acetylcholinesterase and endothelial nitric oxide synthase, and reduction of intracellular antioxidant enzymes depletion [ 76 ]. Moreover, inhibitory effects on the beta-secretase enzyme involved in the generation of amyloid-beta peptides that aggregate in the brain of Alzheimer’s patients have also been reported from marine-derived peptides [ 77 ]. Although most evidence is yet based on preclinical studies, there is much interest in further investigating the efficacy of such compounds in human in vivo trials. Certain limitations should be considered when exploring their actual capacity to exert effects on human health, including the resistance to digestion operated by proteases and peptidases occurring all over the gastrointestinal tract and the capacity to cross the blood-brain barrier [ 78 ]. Nonetheless, the aforementioned mechanisms could support the hypothesis that neuroprotective peptides from fish could play a role against cognitive impairment.

Fish is also a rich source of vitamins and minerals that can play, to a certain extent, a role in brain health [ 79 ]. A large variety of minerals, such as iron, magnesium, zinc, phosphorus, and selenium, as well as vitamins, such as group B and D vitamins, are generally well represented in seafood. While there is not much evidence of meaningful effects of supplementation on cognitive decline or dementia [ 80 ], all the aforementioned micronutrients are known to play important physiological actions in brain cells, including maintenance of a functional neuroglia, synthesis of precursors of neurotransmitters and control of intracellular calcium release, both important for synaptic excitability and neurotransmission [ 81 ]. Nutritional deficiencies lead to documented neurological malfunctioning possibly due to failure of defense mechanisms (i.e., against oxidative stress and inflammation) or age-related frailty, including fatigue and decrease in cognitive performance [ 82 ]. Although it is unclear whether the vitamin and mineral content in fish may play a substantial role in preventive dementia and Alzheimer’s disease, they are most likely to affect cognitive abilities and long-term exposure or, on the contrary, chronic deficiency may in fact be an important factor for the maintenance of a healthy brain and decrease the risk of neurodegenerative conditions [ 83 ].

The findings on the associating between fish and cognitive outcomes may display a certain degree of heterogeneity across studies because of some variables that should be taken into account when exploring such topic. First, the positive effects of intake of omega-3 toward the central nervous system has been demonstrated to be valid in individuals with cognitive decline or dementia, although the impact on the basic pathological lesion (i.e., amyloid deposition) and more advanced stages of dementia is still unclear [ 84 , 85 ]. Other factors to be considered to interpret heterogeneity of results include the potential discrepancy between omega-3 PUFA dietary consumption, plasma concentrations, and brain membrane composition, which may be eventually influenced by age or genetic factors [ 86 ]. In fact, older individuals may have been suggested to exhibit higher omega-3 PUFA plasma concentrations and yet lower content in their brains [ 87 , 88 ], leading to a higher susceptibility to potential deficiency and, consequently, stronger effect following exposure. This hypothesis is in line with the results of the present study, being the retrieved association reported especially in individuals older than 70 years old. Among genetic factors, APOE variants (a lipid transporter within the brain) and genes encoding enzymes involved in the leukotriene synthesis, has been shown to interact, albeit with contrasting results, with dietary PUFA intake and their related health effects [ 89 ]. Such strata analysis has also been performed in the present meta-analysis and the results pointed to a potential weaker association between fish consumption and APOE ε4 allele, a genetic marker associated with disturbed omega-3 PUFA metabolism leading to lower plasma concentrations than in non-carriers [ 90 , 91 ], in which significant associations with lower risk of dementia and cognitive impairment were found. Other potential sources of heterogeneity may depend on the type of outcome investigated as well as the type of diagnosis (evaluation through screening tools vs. clinical assessment). For both variables, considering the results reported in this study, we may hypothesize that the risk reduction may occur when considering age-related cognitive decline or generic cognitive deficits and disorders, not just yet developed into well-identified clinical conditions, such as certain types of dementia, including Alzheimer’s disease. Eventually, other factors (i.e., genetic and environmental) may concur to the development of specific neurocognitive disfunctions and diet alone may not be sufficient to actually significantly reduce the risk of their insurgence (at least not observed for fish with the models currently used).

Other limitations potentially determining the heterogeneity of the results (as well as affecting the strength of evidence) include technical and methodological features from the original studies included in the meta-analysis. First, most studies used self-reported dietary information to assess fish consumption, which may be subject to recall bias and social desirability bias. Second, although the quality of the included studies was high, the original study design cannot detect any causal inference, but only associations with risk. Moreover, the adjustment for several potential confounding factors do not guarantee the presence of unmeasured variables potentially playing a role in brain health (i.e., overall diet quality). Ultimately, fish consumption is relatively easy to be estimated and would allow to consider not only the role of omega-3 PUFA but also other components potentially important to exert putative effects on human brain: nonetheless, investigating specific markers in blood or brain would be a further necessary step to increase precision of measurements and inference, ultimately potentially reducing the heterogeneity of findings. Finally, concerning the outcomes, the use of several different tools across the studies may limit the univocity and the consistency of the endpoints investigated.

In conclusion, the present study showed that higher fish intake may be associated with better cognitive status in older individuals. Whether fish consumption may actually decrease the risk of dementia and Alzheimer’s disease is still to be confirmed, but current results are promising. The observed trends of risk estimates suggest a lower risk of disease with increasing consumption of fish starting 50 g per day, while findings for higher intakes are more heterogeneous. The existing mechanistic evidence providing a sound rationale in support of such findings and the consistency of results foster the inclusion of fish in a healthy, balanced dietary pattern. While fish consumption may naturally occur in more coastal areas or, more in general, countries with historical and cultural habits characterized by its inclusion in traditional dietary patterns (i.e., the Mediterranean diet), it is important to consider the importance of food availability and affordability globally. Although evidence from the scientific literature support the mechanical role of omega-3 PUFA in improving certain brain structure, further studies are needed to shed the doubts concerning the actual role of fish intake in more pathophysiological complex conditions, to estimate whether the beneficial effects are in fact exerted by its content in omega-3 or rather other compounds (such as, peptides), and to understand the extent of efficacy also in relation to age and genetic factors. Although interesting and giving the chance for speculation, the findings of this study are yet preliminary and need additional proof to further investigate the role of unmeasured factors, including mechanisms (such as, transportation, membrane incorporation, etc.) related to personalized inter-individual response to omega-3 PUFA or other nutritional compounds retrieved in fish. Also, a more precise clinical characterization of cognitive disorders could help to reduce the heterogeneity of findings and identifying potential specific conditions particularly sensible to the beneficial effects of inclusion of fish in a healthy diet.

Data availability

All data supporting the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

J.G. was supported by the co-financing of the European Union—FSE-REACT-EU, PON Research and Innovation 2014–2020 DM1062/2021; CUP: E65F21002560001.

This study was supported by Bolton Food S.P.A. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data.

Open access funding provided by Università degli Studi di Catania within the CRUI-CARE Agreement.

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Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy

Justyna Godos, Walter Currenti & Giuseppe Grosso

Center for Human Nutrition and Mediterranean Foods (NUTREA), University of Catania, Catania, Italy

Justyna Godos & Giuseppe Grosso

Statistical Laboratory, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, 31-501, Poland

Agnieszka Micek

Laboratory of Pharmacoepidemiology and Human Nutrition, Department of Health Policy, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, 20156, Italy

Carlotta Franchi

Italian Institute for Planetary Health (IIPH), Milan, 20124, Italy

Nutrition Foundation of Italy (NFI), Milan, 20124, Italy

Andrea Poli

Department of Clinical Sciences, Università Politecnica Delle Marche, Ancona, Italy

Maurizio Battino

Research Group on Food, Nutritional Biochemistry and Health, Universidad Europea del Atlántico, Isabel Torres 21, Santander, 39011, Spain

International Joint Research Laboratory of Intelligent Agriculture and Agri-Products Processing, Jiangsu University, Zhenjiang, Jiangsu, China

Sustainable Development Department, Bolton Food SpA, Milan, 20124, Italy

Alberto Dolci

Africa Unit for Transdisciplinary Health Research (AUTHeR), North-West University, Potchefstroom, 2531, South Africa

Cristian Ricci

Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

Zoltan Ungvari

Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

International Training Program in Geroscience, Department of Public Health, Doctoral College, Semmelweis University, Budapest, Hungary

Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA

Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

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Conceptualization: C.F., A.P., M.B., A.D., C.R., and G.G.; Methodology: J.G., A.M. and G.G.; Formal analysis and investigation: J.G., A.M. and G.G.; Writing - original draft preparation: J.G. and W.C.; Writing - review and editing: J.G., A.M., W.C., C.F., A.P., M.B., A.D., C.R., Z.U. and G.G.; Funding acquisition: A.D.; Supervision: C.F., A.P., M.B., A.D., C.R., Z.U. and G.G.

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Godos, J., Micek, A., Currenti, W. et al. Fish consumption, cognitive impairment and dementia: an updated dose-response meta-analysis of observational studies. Aging Clin Exp Res 36 , 171 (2024). https://doi.org/10.1007/s40520-024-02823-6

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A modular model of immune response as a computational platform to investigate a pathogenesis of infection disease

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The COVID-19 pandemic significantly transformed the field of mathematical modeling in immunology. International collaboration among numerous research groups yielded a substantial amount of experimental data, which greatly facilitated model validation and led to the development of new mathematical models. The aim of the study is an improvement of system understanding of the immune response to SARS-CoV-2 infection based on the development of a modular mathematical model which provides a foundation for further research on host-pathogen interactions. We utilized the open-source BioUML platform to develop a model using ordinary, delay and stochastic differential equations. The model was validated using experimental data from middle-aged individuals with moderate COVID-19 progression, including measurements of viral load, antibodies, CD4+ and CD8+ T cells, and interleukin-6 levels. Parameter optimization and sensitivity analysis were conducted to refine the model`s accuracy. The model effectively reproduces moderate, severe, and critical COVID-19 progressions, consistent with experimental observations. We investigated the efficiency and contributions of innate and adaptive immunity in response to SARS-CoV-2 infection and assessed immune system behavior during co-infection with HIV and organ transplantation. Additionally, we studied therapy methods, such as interferon administration. The developed model can be employed as a framework for simulating other infectious diseases taking into account follow-up immune response.

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Aug. 16, 2024

New twist on synthesis technique developed at rice promises sustainable manufacturing.

James Tour’s lab at Rice University has developed a new method known as flash-within-flash Joule heating (FWF) that could transform the synthesis of high-quality solid-state materials, offering a cleaner, faster and more sustainable manufacturing process. The findings were published in Nature Chemistry on Aug. 8.

Traditionally, synthesizing solid-state materials has been a time-consuming and energy-intensive process, often accompanied by the production of harmful byproducts. But FWF enables gram-scale production of diverse compounds in seconds while reducing energy, water consumption and greenhouse gas emissions by more than 50%, setting a new standard for sustainable manufacturing.

The innovative research builds on Tour’s 2020 development of waste disposal and upcycling applications using flash Joule heating , a technique that passes a current through a moderately resistive material to quickly heat it to over 3,000 degrees Celsius (over 5,000 degrees Fahrenheit) and transform it into other substances.

“The key is that formerly we were flashing carbon and a few other compounds that could be conductive,” said Tour, the T.T. and W.F. Chao Professor of Chemistry and professor of materials science and nanoengineering. “Now we can flash synthesize the rest of the periodic table. It is a big advance.”

FWF’s success lies in its ability to overcome the conductivity limitations of conventional flash Joule heating methods. The team — including Ph.D. student Chi Hun “Will” Choi and corresponding author Yimo Han , assistant professor of chemistry, materials science and nanoengineering — incorporated an outer flash heating vessel filled with metallurgical coke and a semiclosed inner reactor containing the target reagents. FWF generates intense heat of about 2,000 degrees Celsius, which rapidly converts the reagents into high-quality materials through heat conduction.

This novel approach allows for the synthesis of more than 20 unique, phase-selective materials with high purity and consistency, according to the study. FWF’s versatility and scalability is ideal for the production of next-generation semiconductor materials such as molybdenum diselenide (MoSe2), tungsten diselenide and alpha phase indium selenide, which are notoriously difficult to synthesize using conventional techniques.

“Unlike traditional methods, FWF does not require the addition of conductive agents, reducing the formation of impurities and byproducts,” Choi said.

This advancement creates new opportunities in electronics, catalysis, energy and fundamental research. It also offers a sustainable solution for manufacturing a wide range of materials. Moreover, FWF has the potential to revolutionize industries such as aerospace, where materials like FWF-made MoSe2 demonstrate superior performance as solid-state lubricants.

“FWF represents a transformative shift in material synthesis,” Han said. “By providing a scalable and sustainable method for producing high-quality solid-state materials, it addresses barriers in manufacturing while paving the way for a cleaner and more efficient future.”

This study was supported by the Air Force Office of Scientific Research, U.S. Army Corp of Engineers, and Welch Foundation.

First meeting of the International Health Regulations (2005) Emergency Committee regarding the upsurge of mpox 2024

The Director-General of the World Health Organization (WHO), having concurred with the advice offered by the International Health Regulations (2005) (IHR or Regulations)  Emergency Committee regarding the upsurge of mpox 2024  during its first meeting, held on 14 August 2024, has determined, on the same date, that the ongoing upsurge of mpox in the Democratic Republic of the Congo (DRC) and in a growing number of countries in Africa constitutes a public health emergency of international concern (PHEIC) under the provisions of the Regulations. The communication of the Director-General regarding the determination of the above-mentioned PHEIC on 14 August 2024 is available  here .

The Director-General is hereby transmitting the report of the first meeting of the IHR Emergency Committee regarding the upsurge of mpox 2024.

Noting that the Director-General will be communicating to States Parties a 12-month extension of the current  standing recommendations for mpox , the temporary recommendations, issued by the Director-General in relation to the PHEIC associated with the ongoing upsurge of mpox are presented in the last section of this statement and reflect the advice offered by the Committee.

The Director-General is taking the opportunity to express his most sincere gratitude to the Chair, Vice-Chair, and Members of the IHR Emergency Committee, as well as to its Advisors. 

Proceedings of the meeting

Sixteen (16) Members of, and two Advisors to, the Emergency Committee were convened by teleconference, via Zoom, on Wednesday, 14 August 2024, from 12:00 to 17:00 CEST. Fifteen (15) of the 16 Committee Members and the two Advisors to the Committee participated in the meeting.

The Director-General of the World Health Organization (WHO) joined in person and welcomed the participants. The opening remarks by the Director-General are available  here .

The Representative of the Office of Legal Counsel briefed the Members and Advisers on their roles and responsibilities and identified the mandate of the Emergency Committee under the relevant articles of the IHR. The Ethics Officer from the Department of Compliance, Risk Management, and Ethics provided the Members and Advisors with an overview of the WHO Declaration of Interests process. The Members and Advisors were made aware of their individual responsibility to disclose to WHO, in a timely manner, any interests of a personal, professional, financial, intellectual or commercial nature that may give rise to a perceived or actual conflict of interest. They were additionally reminded of their duty to maintain the confidentiality of the meeting discussions and the work of the Committee. Each Member and Advisor was surveyed, with no conflicts of interest identified.

The Representative of the Office of Legal Counsel then facilitated the election of officers of the Committee, in accordance with the rules of procedures and working methods of the Emergency Committee. Professor Dimie Ogoina was elected as Chair of the Committee, Professor Inger Damon as Vice-Chair, and Professor Lucille Helen Blumberg as Rapporteur, all by acclamation.

The meeting was handed over to the Chair who introduced the objectives of the meeting, which were to provide views to the Director-General on whether the event constitutes a public health emergency of international concern (PHEIC), and if so, to provide views on the potential proposed temporary recommendations.  

Session open to representatives of States Parties invited to present their views

The WHO Secretariat presented an overview of the global epidemiological situation of mpox, highlighting that, during the first six months of 2024, the 1854 confirmed cases of mpox reported by States Parties in the WHO African Region account for 36% (1854/5199) of the cases observed worldwide. Of these confirmed cases in the WHO African region in 2024, 95% (1754/1854) were reported in the Democratic Republic of the Congo (DRC), that is experiencing an upsurge of cases of mpox, with more than 15,000 clinically compatible cases and over 500 deaths reported, already exceeding the number of cases observed in the DRC in 2023.

The upsurge of mpox cases in the DRC is being driven by outbreaks associated with two sub-clades of clade I monkeypox virus (MPXV) – clade Ia and clade Ib. Clade I mpox was classically described in studies conducted by WHO in the 1980’s to have a mortality rate of approximately 10%, with most deaths occurring in children.

MPXV clade Ia is endemic in the DRC, the disease primarily affects children, data available for 2024 show an aggregated case fatality rate of 3.6%, and the spread is likely sustained through multiple modes of transmission including person-to-person transmission following zoonotic introduction in a community.

MPXV clade Ib is a new strain of MPXV that emerged in the DRC  is transmitting between people, presumed via sexual contact, which has been spreading in the eastern part of the country. Although first characterized in 2024, estimates suggest it emerged around September 2023. The outbreak associated with clade Ib in the DRC primarily affects adults and is spreading rapidly, sustained largely, but not exclusively, through transmission linked to sexual contact and amplified in networks associated with commercial sex and sex workers.

Since July 2024, cases of mpox due to MPXV clade Ib, epidemiologically and phylogenetically linked to the outbreak in the eastern provinces of DRC, have been detected in four countries, neighbouring the DRC, which had not reported cases of mpox before: Burundi, Kenya, Rwanda and Uganda.

Additionally, in 2024, cases of mpox linked to MPXV clade Ia have been reported in the Central African Republic and the Republic of Congo, and cases linked to MPXV clade II have been reported in Cameroon, Côte d’Ivoire, Liberia, Nigeria and South Africa.

The clinical presentation of mpox associated with MPXV clade Ia has historically been characterized by more severe disease than that associated with MPXV clade II. Clade IIb viruses circulated during the multi-country outbreak that constituted a PHEIC from July 2022 to May 2023. There is, as yet, insufficient information available to fully characterize mpox severity due to clade Ib as data are emerging and, so far, few deaths were recorded, precluding age-stratified analyses.

The secretariat outlined challenges in understanding the true extent of infection, epidemiologic trends and morbidity and mortality, thus cautioning overinterpretation of available data to calculate crude CFRs by different clades/outbreaks.

The assessed risk presented by the WHO Secretariat – grouping geographical areas as a result of the assessment of population groups affected, predominant modes of transmission, and MPXV clades involved –, was: “high” for eastern DRC and neighbouring countries; “high” for areas of the DRC where mpox is known to be endemic; “moderate” for Nigeria and countries of West, Central and East Africa where mpox is endemic; and “moderate” for other countries in Africa and around the world.

The WHO Secretariat additionally provided an overview of the actions already taken to support readiness and response interventions in States Parties experiencing the upsurge of cases of mpox and facing such risk. These include, inter alia: the release of USD 1.45 million from the WHO Contingency Fund for Emergencies; initiating the process for including Emergency Use Listing two mpox vaccines; coordinating with partners and stakeholders, including to facilitate equitable access to vaccines, therapeutics, and diagnostics; the development of a regional response plan, costed at an initial USD 15 million, and more.

Representatives of Burundi, the Democratic Republic of the Congo, Kenya, Rwanda, South Africa and Uganda updated the Committee on the mpox epidemiological situation in their countries and the current response efforts, needs and challenges. Although most reported few cases of MPXV clade Ib related mpox, Burundi reported one hundred confirmed cases of mpox associated with clade Ib since July 2024, identified in multiple districts and 28% of cases were amongst children less than five years of age.

Members of, and Advisors to, the Committee then engaged in questions and answers with the presenters. The questions and discussions focused around the issues and challenges enumerated below:

• Scientific uncertainties and evidence gaps (e.g., role of ecological changes in the spread of mpox, modes of disease transmission, transmission dynamics, risk factors, disease severity and case fatality rate associated with the different MPXV clades, outcome of pregnancy in women infected with different MPXV clades);
• Adequacy of capacities, recognizing capacities gained during COVID-19, and heterogeneity thereof, across States Parties for surveillance, diagnostic capacities, surveillance modalities at borders, access to clinical care, integration of HIV/STI services in prevention and treatment, and risk communication and community engagement, vaccination delivery, and other capacities to support prevention, readiness and response activities;
• Lack of full understanding of the geographical spread and detailed epidemiology of the dynamic mpox outbreaks, including of molecular epidemiology, to optimize targeted prevention and control measures, including risk communication and community engagement with local partners to enable appropriate support and behavior modifications, as well as the targeted use of mpox vaccines in at risk groups;
• Availability and access to laboratory tests that can be used in challenging environments, and where necessary, methods to distinguish between circulating MPXV clades; and
• An incomplete mapping of mpox-related research and development efforts underway, noting several initiatives underway, including a WHO and Africa Centers for Disease Control and Prevention (Africa CDC) consultation to be held in August 2024;
• The unpredictability and lack of financial resources at both, national and international levels to scale up and sustain interventions to prevent and control the spread of mpox, despite the development of costed global, regional and national response plans;
• The needs-based access to mpox vaccines, given the current limited available globally; the currently limited production of the vaccine, conditional to orders placed to the manufacturer; and the extensive time to develop legal agreements in relation to donation of mpox vaccines, as opposed to direct procurement. With respect to access to vaccines, the WHO Secretariat informed the Committee of its ongoing work with numerous partners through the Interim coordination mechanism for medical countermeasures (i-MCM-Net), including Gavi and the United Nations Children's Fund on the coordination of the donation and allocation process in an equitable, needs-based manner;
• The access to the antiviral drug tecovirimat, considering that both, the minimum amount for orders to be placed with the manufacturer and the price of the product represent key challenges for many States Parties. While evidence is being gathered on its use for the treatment of cases of mpox, it can be accessed under protocol for Monitored Emergency Use of Unregistered and Experimental Interventions (MEURI); as well as optimized and safe clinical care; and
• The need for information on the implementation, by States Parties, of the standing recommendation for mpox issued on 21 August 2023.

Deliberative session

Following the session open to invited States Parties, the Committee reconvened in a closed session to examine the questions in relation to whether the event constitutes a PHEIC or not, and if so, to consider the temporary recommendations drafted by the WHO Secretariat in accordance with IHR provisions.

The Chair reminded the Committee Members of their mandate and recalled that a PHEIC is defined in the IHR as an  “extraordinary event, which constitutes a public health risk to other States through the international spread of disease, and potentially requires a coordinated international response” .

The Committee was unanimous in expressing the views that the ongoing upsurge of mpox meets the criteria of a PHEIC and that the Director-General be advised accordingly.

The considerations underpinning the unanimous views of the Committee further elaborated upon issues and challenges addressed during the question and answers session.

The Committee considered the event as  “extraordinary”  because of (a) the increase in mpox clade I disease occurrence in the DRC and the emergence of the new MPXV clade Ib, the human-to-human transmission context in which it is occurring, its rapid spread in some settings, and available evidence suggesting that MPXV clade I is associated with a more severe clinical presentation with respect to MPXV clade II; (b) the diverse, complex, dynamic, and rapidly evolving epidemiology observed across States Parties in the WHO African Region in terms of: overall rapid increase of the number of cases reported in some settings, differences in population age-groups affected, routes and modes sustaining transmissions in different contexts; and (c) the severity of the clinical presentation in children and immunocompromised individuals, including people living with uncontrolled HIV infection or advanced HIV disease, as well as the long-term consequences of MPXV infection.

Additionally, the Committee strongly underscored that its level of concern is further heightened by (a) uncertainties and gaps in knowledge and evidence related to (i) multiple epidemiological aspects, including drivers of transmission, morbidity and mortality associated with infections with different MPXV sub-clades; (ii) the incompleteness and uncertainties of available epidemiological data and considered by the Committee, due to the limitations of current surveillance (e.g., sub-optimal levels of case detection and case reporting), the availability and performance of laboratory diagnostics, and ongoing conflicts and humanitarian challenges in certain areas of the DRC experiencing the upsurge of mpox, that, ultimately, hamper the implementation of control measures; (iii) the impact of control measures, including the targeted use of vaccines and their overall effectiveness; and (b) the risk of occurrence of additional mutations of MPXV clade I and clade II, and their subsequent emergence and spread in the context of limited capacity to implement control measures.

The Committee considered that the event  “ constitutes a public health risk to other States through the international spread of disease”  because of (a) the documented recent spread of MPXV clade Ib from eastern DRC to Burundi, Kenya, Rwanda and Uganda; (b) the limited capacity to control transmission in endemic situations and in areas of upsurge through enhanced surveillance enabling the implementation of targeted response interventions that are ultimately subordinated to (i) the unavailability of sustainable funding, and (ii) the limited ability to access vaccines, therapeutics, and diagnostics; and (c) the challenges in implementing concerted surveillance and response interventions in contiguous areas of bordering States Parties, in particular where borders are porous.

The Committee considered that the event  “requires a coordinated international response” . The Committee noted that (a) mpox is endemic in parts of Africa, with surges increasingly reported, and also resulting in a multi-country outbreak determined to constitute a PHEIC in 2022-2023; and (b) the event is occurring in the context of standing recommendations issued by the Director-General in August 2023 under IHR provisions and following the termination of the afore mentioned PHEIC; the presence of the “WHO Strategic framework for enhancing prevention and control of mpox- 2024-2027”; and the activation for mpox of the i-MCM-Net. In that light and noting the declaration of the event as a Public Health Emergency of Continental Security by the Africa CDC on 13 August 2024, the Committee considered that international cooperation requires enhanced and coordination, in particular with respect to (a) the facilitation of equitable access to vaccines, therapeutics, and diagnostics; and (b) the mobilization of financial resources.

The Committee subsequently considered the draft of the temporary recommendations proposed by   the WHO  Secretariat , briefly presented during the meeting. The Committee indicated that it would be giving further consideration to the proposed temporary recommendations while finalizing the report of the meeting.

The Committee noted that, in his opening remarks, the Director-General communicated the 12-month extension of the current  standing recommendations for mpox , which were set to expire on 20 August 2024. The Committee also noted that, should the Director-General determine that the upsurge of mpox constitutes a PHEIC, it would be the first time, since the entry into force of the Regulations, that temporary and standing recommendations to States Parties related to the same public health risk would coexist.

Therefore, the Committee underscored that any temporary recommendation that may be issued by the Director-General should be very specific and targeted, and hence, not duplicate the standing recommendations.

Notwithstanding that both, temporary and standing recommendations constitute non-binding advice to States Parties, the Committee advised that mechanisms to monitor the uptake, implementation and impact of such recommendations should be embedded in the set of temporary recommendations to States Parties that the Director-General may issue in relation to the event considered.

Conclusions

The Committee reiterated its concern regarding the evolution of the multi-faceted upsurge of mpox, including the many uncertainties surrounding it and the capacities in place to control the spread of mpox in States Parties experiencing the outbreaks, or in States Parties that may have to do so as a result of further international spread.

The Committee recognized the critical role of coordinated international cooperation in supporting States Parties’ efforts to control the spread of mpox in the WHO African Region – including in facilitating access to and use of vaccines, therapeutics, and diagnostics; mobilizing financial resources for States Parties experiencing the upsurge of disease; and synergic initiatives by WHO and partners, including Africa CDC.

Nevertheless, the Committee indicated that the development of strategic approaches for States Parties to become more self-reliant in controlling the spread of mpox are warranted. To that effect, the Committee considers that the determination by the Director-General that the upsurge of mpox constitutes a PHEIC would stimulate States Parties facing the outbreaks to more effectively commit and employ domestic resources.  

Temporary recommendations issued by the Director-General of the World Health Organization (WHO) to States Parties in relation to the public health emergency of international concern associated with the upsurge of mpox 

These temporary recommendations are issued to States Parties experiencing the upsurge of mpox,  including, but not limited to, the   Democratic Republic of the Congo and Burundi, Kenya, Rwanda, and Uganda .

They are intended to be implemented by those States Parties in addition to the current  standing recommendations for mpox , which will be extended until 20 August 2025 and are presented at the end of this document for easy reference. 

In the context of the global efforts to prevent and control the spread of mpox disease outlined in the  WHO Strategic framework for enhancing prevention and control of mpox- 2024-2027 , the aforementioned  standing recommendations  apply to  all States Parties . 

All current WHO interim technical guidance can be accessed on  this page  of the WHO website. WHO evidence-based guidance has been and will continue to be updated in line with the evolving situation, updated scientific evidence, and WHO risk assessment to support States Parties in the implementation of the WHO Strategic Framework for enhancing mpox prevention and control. 

Pursuant to Article 3 Principle of the International Health Regulations (2005) (IHR), the implementation of these temporary recommendations, as well as of the standing recommendations for mpox, by States Parties shall be with full respect for the dignity, human rights and fundamental freedoms of persons, in line with the principles set out in Article 3 of the IHR. 

 Emergency Coordination

• Establish or enhance national and local emergency response coordination arrangements;
• Establish or enhance the coordination of all partners and stakeholders engaged in or supporting response activities through cooperation, including by introducing accountability mechanisms;
• Engage partner organizations for collaboration and support, including humanitarian actors in contexts with insecurity or areas with internal or refugee population displacements and hosting communities insecure areas;

Collaborative Surveillance and Laboratory Diagnostics

• Enhance surveillance, by increasing the sensitivity of the approaches adopted and ensuring comprehensive geographical coverage;
• Expand access to accurate, affordable and available diagnostics to differentiate monkeypox virus clades, including through strengthening arrangements for the transport of samples, the decentralization of diagnostics, and arrangements to conduct genomic sequencing;
• Identify, monitor and support the contacts of people with mpox to prevent onward transmission;
• Scale up efforts to thoroughly investigate cases and outbreaks of mpox disease to elucidate the modes of transmission, and prevent its onward transmission to household members and communities;
• Report to WHO suspect, probable and confirmed cases of mpox in a timely manner and on a weekly basis;

Safe and Scalable Clinical Care

• Provide clinical, nutritional and psychosocial support for patients with mpox, including, as warranted and possible, isolation in care centres and guidance for home-based care;
• Develop and implement a plan to expand access to optimised supportive clinical care for all patients with mpox, including children, patients living with HIV and pregnant women. This includes offering HIV tests to adult patients who do not know their HIV status and to children as appropriate, with linkages to HIV treatment and care services when indicated; the prompt identification and effective management of endemic co-infections, such as malaria, varicella zoster and measles viruses, and other sexually transmitted infections (STIs) among cases linked to sexual contact;
• Strengthen health and care workers’ capacity, knowledge and skills in the clinical and infection and prevention and control pathways –from diagnosis to discharge of patients with suspected and confirmed mpox –, and provide them with personal protective equipment;
• Promote and implement infection prevention and control measures and basic water and sanitation services in health care facilities, household settings, congregate settings (e.g. prisons, internally displaced persons and refugee camps, schools, etc.), and cross border transit areas;

International traffic

• Establish or strengthen cross-border collaboration arrangements for surveillance and management of suspect cases of mpox, the provision of information to travellers and conveyance operators, without resorting to general travel and trade restrictions unnecessarily impacting local, regional or national economies;

Vaccination

• Prepare for the introduction of mpox vaccine for emergency response through convening of national immunization technical advisory groups, briefing of national regulatory authorities, preparing national policy mechanisms to apply for vaccines through available mechanisms;
• Initiate plans to advance mpox vaccination activities in the context of outbreak response in areas with incident cases (i.e. with disease onset in the previous 2-4 weeks), targeting people at high risk of infection (e.g., contacts of cases, including sexual contacts, children, and health and health care workers). This entails the agile adaptation of immunization strategies and plans to concerned areas; the availability of vaccines and supplies; the proactive community engagement, to generate and sustain demand for and trust in vaccination; and the collection of data during vaccination according to implementable research protocols;

Risk communication and community engagement

• Strengthen risk communication and community engagement systems with affected communities and local workforces for outbreak prevention, response and vaccination strategies, including through training, mapping high risk and vulnerable populations, social listening and community feedback, managing misinformation. This entails, inter alia, communicating effectively the uncertainties regarding the natural history of mpox, updated information about mpox including information from ongoing clinical trials, about the efficacy of vaccines against mpox, and the uncertainties regarding duration of protection following vaccination;
• Address stigma and discrimination of any kind via meaningful community engagement, particularly in health services and during risk communication activities;

Governance and financing

• Galvanize and scale up national funding and explore external opportunities for targeted funding of prevention, readiness and response activities;
• Integrate mpox prevention and response measures in existing programmes aimed at prevention, control and treatment of other endemic diseases – especially HIV, as well as STIs, malaria, tuberculosis, and COVID-19, as well as non-communicable diseases –, striving, to the extent possible, not to negatively impact their delivery;

Addressing research gaps

• Invest in addressing knowledge gaps and in generating evidence, during and after outbreaks, regarding the dynamics of transmission of mpox, risk factors, the social and behavioural drivers of transmission, the natural history of disease, through trials for novel therapeutics and vaccines against mpox, the effectiveness of public health interventions, with a One Health approach;

Reporting on the implementation of temporary recommendations

• Report quarterly to WHO on the status of, and challenges related to the implementation of these temporary recommendations, using a standardized tool and channels that will be made available WHO.

Standing recommendations for mpox issued by the Director-General of the World Health Organization (WHO) in accordance with the International Health Regulations (2005) (IHR)

A. States Parties are recommended to develop and implement national mpox plans that build on WHO strategic and technical guidance, outlining critical actions to sustain control of mpox and achieve elimination of human-to-human transmission in all contexts through coordinated and integrated policies, programmes and services. Actions are recommended to:

• Incorporate lessons learned from evaluation of the response (such as through intra- or after-action reviews) into related plans and policies in order to sustain, adapt, and promote key elements of the response and inform public health policies and programmes.
• Aim to eliminate human-to-human transmission of mpox by anticipating, detecting, preparing for and responding to mpox outbreaks and taking action to reduce zoonotic transmission, as appropriate.
• Build and retain capacity in resource-limited settings, and among marginalized groups, where mpox transmission continues to occur, to improve understanding of modes of transmission, quantify resource needs, and detect and respond to outbreaks and community transmission.

B. States Parties are recommended to, as a critical basis for actions outlined in A in support of the elimination goal, establish and sustain laboratory-based surveillance and diagnostic capacities to enhance outbreak detection and risk assessment. Actions are recommended to:

4. Include mpox as a notifiable disease in the national epidemiological surveillance system.

5. Strengthen diagnostic capacity at all levels of the health care system for laboratory and point of care diagnostic confirmation of cases.

6. Ensure timely reporting of cases to WHO, as per WHO guidance and Case Reporting Form, in particular reporting of confirmed cases with a relevant recent history of international travel.

7. Collaborate with other countries so that genomic sequencing is available in, or accessible to, all countries. Share genetic sequence data and metadata through public databases.

8. Notify WHO about significant mpox-related events through IHR channels.

C. States Parties are recommended to enhance community protection through building capacity for risk communication and community engagement, adapting public health and social measures to local contexts and continuing to strive for equity and build trust with communities through the following actions, particularly for those most at risk. Actions are recommended to:

9. Communicate risk, build awareness, engage with affected communities and at-risk groups through health authorities and civil society.

10. Implement interventions to prevent stigma and discrimination against any individuals or groups that may be affected by mpox.

D. States Parties are recommended to initiate, continue, support, and collaborate on research to generate evidence for mpox prevention and control, with a view to support elimination of human-to-human transmission of mpox. Actions are recommended to:

11. Contribute to addressing the global research agenda to generate and promptly disseminate evidence for key scientific, social, clinical, and public health aspects of mpox transmission, prevention and control.

12. Conduct clinical trials of medical countermeasures, including diagnostics, vaccines and therapeutics, in different populations, in addition to monitoring of their safety, effectiveness and duration of protection.

13. States Parties in West, Central and East Africa should make additional efforts to elucidate mpox-related risk, vulnerability and impact, including consideration of zoonotic, sexual, and other modes of transmission in different demographic groups.

E. States Parties are recommended to apply the following measures related to international travel. Actions are recommended to:

14. Encourage authorities, health care providers and community groups to provide travelers with relevant information to protect themselves and others before, during and after travel to events or gatherings where mpox may present a risk.

15. Advise individuals suspected or known to have mpox, or who may be a contact of a case, to adhere to measures to avoid exposing others, including in relation to international travel.

16. Refrain from implementing travel-related health measures specific for mpox, such as entry or exit screening, or requirements for testing or vaccination.

F. States Parties are encouraged to continue providing guidance and coordinating resources for delivery of optimally integrated clinical care for mpox, including access to specific treatment and supportive measures to protect health workers and caregivers as appropriate. States Parties are encouraged to take actions to:

17. Ensure provision of optimal clinical care with infection prevention and control measures in place for suspected and confirmed mpox in all clinical settings. Ensure training of health care providers accordingly and provide personal protective equipment.

18. Integrate mpox detection, prevention, care and research within HIV and sexually transmitted disease prevention and control programmes, and other health services as appropriate.

G. States Parties are encouraged to work towards ensuring equitable access to safe, effective and quality-assured countermeasures for mpox, including through resource mobilization mechanisms. States Parties are encouraged to take action to:

19. Strengthen provision of and access to diagnostics, genomic sequencing, vaccines, and therapeutics for the most affected communities, including in resource-constrained settings where mpox occurs regularly, and including for men who have sex with men and groups at risk of heterosexual transmission, with special attention to those most marginalized within those groups.

20. Make mpox vaccines available for primary prevention (pre-exposure) and post-exposure vaccination for persons and communities at risk of mpox, taking into account recommendations of the WHO Strategic Advisory Group of Experts on Immunization (SAGE).