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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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Observation

Observation, as the name implies, is a way of collecting data through observing. This data collection method is classified as a participatory study, because the researcher has to immerse herself in the setting where her respondents are, while taking notes and/or recording. Observation data collection method may involve watching, listening, reading, touching, and recording behavior and characteristics of phenomena.

Observation as a data collection method can be structured or unstructured. In structured or systematic observation, data collection is conducted using specific variables and according to a pre-defined schedule. Unstructured observation, on the other hand, is conducted in an open and free manner in a sense that there would be no pre-determined variables or objectives.

Moreover, this data collection method can be divided into overt or covert categories. In overt observation research subjects are aware that they are being observed. In covert observation, on the other hand, the observer is concealed and sample group members are not aware that they are being observed. Covert observation is considered to be more effective because in this case sample group members are likely to behave naturally with positive implications on the authenticity of research findings.

Advantages of observation data collection method include direct access to research phenomena, high levels of flexibility in terms of application and generating a permanent record of phenomena to be referred to later. At the same time, this method is disadvantaged with longer time requirements, high levels of observer bias, and impact of observer on primary data, in a way that presence of observer may influence the behaviour of sample group elements.

It is important to note that observation data collection method may be associated with certain ethical issues. As it is discussed further below in greater details, fully informed consent of research participant(s) is one of the basic ethical considerations to be adhered to by researchers. At the same time, the behaviour of sample group members may change with negative implications on the level of research validity if they are notified about the presence of the observer.

This delicate matter needs to be addressed by consulting with dissertation supervisor, and commencing the primary data collection process only after ethical aspects of the issue have been approved by the supervisor.

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6.5 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 research designs 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. 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 at times acting like complete fools in front of the entire nation.

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 is 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 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 passive deception is being used. The researcher is passively 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) [1] 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 (published in Social Psychology Quarterly ) on a university-based religious organization that emphasized how happy its members were (Wilkins, 2008) [2] . 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 researcher is in a much better position to understand the viewpoint and experiences of the people they are studying when they are apart 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 when researchers because active members of the social group they are studying, additional concerns arise 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 and participant observation. Often the setting in which the observations are made is not the natural setting, rather 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 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 and 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.

Structured observation is very similar to naturalistic observation and participant observation in that in all 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 and 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) [3] . 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) [4] . 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.

When the observations require a judgment on the part of the observers—as in Kraut and Johnston’s study—this process is often described as coding . 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 different observers code them in the same way. This difficulty with coding is 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 interested 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 individuals’ 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).

www.youtube.com/watch?v=KkaXNvzE4pk

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) [5] , who learned to fear a white rat—along with other furry objects—when the researchers made a loud noise while he was playing with the rat.

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) [6] . (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, 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.

Figure 10.1 Anna O. “Anna O.” was the subject of a famous case study used by Freud to illustrate the principles of psychoanalysis. Source: http://en.wikipedia.org/wiki/File:Pappenheim_1882.jpg

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 to 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 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 (indeed questioning into the possibility of a separate brain lesion began after HM’s death and dissection of his brain) 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 a very 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 is the use of archival research which involves analyzing 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) [7] . 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) [8] . 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.

Key Takeaways

There are several different approaches to observational research including naturalistic observation, participant observation, structured observation, case studies, and archival research.
Naturalistic observation is used to observe people in their natural setting, participant observation involves becoming an active member of the group being observed, structured observation involves coding a small number of behaviors in a quantitative manner, case studies are typically used to collect in-depth information on a single individual, and archival research involves analysing existing data.
Describe one problem related to internal validity.
Describe one problem related to external validity.
Generate one hypothesis suggested by the case study that might be interesting to test in a systematic single-subject or group study.
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. ↵
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. ↵

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What Is an Observational Study? | Guide & Examples

What Is an Observational Study? | Guide & Examples

Published on 5 April 2022 by Tegan George . Revised on 20 March 2023.

An observational study is used to answer a research question based purely on what the researcher observes. There is no interference or manipulation of the research subjects, and no control and treatment groups .

These studies are often qualitative in nature and can be used for both exploratory and explanatory research purposes. While quantitative observational studies exist, they are less common.

Observational studies are generally used in hard science, medical, and social science fields. This is often due to ethical or practical concerns that prevent the researcher from conducting a traditional experiment . However, the lack of control and treatment groups means that forming inferences is difficult, and there is a risk of confounding variables impacting your analysis.

Types of observation, types of observational studies, observational study example, advantages and disadvantages of observational studies, observational study vs experiment, frequently asked questions.

There are many types of observation, and it can be challenging to tell the difference between them. Here are some of the most common types to help you choose the best one for your observational study.


	The researcher observes how the participants respond to their environment in ‘real-life’ settings but does not influence their behavior in any way	Observing monkeys in a zoo enclosure
	Also occurs in ‘real-life’ settings, but here, the researcher immerses themselves in the participant group over a period of time	Spending a few months in a hospital with patients suffering from a particular illness
	Utilising coding and a strict observational schedule, researchers observe participants in order to count how often a particular phenomenon occurs	Counting the number of times children laugh in a classroom
	Hinges on the fact that the participants do not know they are being observed	Observing interactions in public spaces, like bus rides or parks
	Involves counting or numerical data	Observations related to age, weight, or height
	Involves ‘five senses’: sight, sound, smell, taste, or hearing	Observations related to colors, sounds, or music
	Investigates a person or group of people over time, with the idea that close investigation can later be to other people or groups	Observing a child or group of children over the course of their time in elementary school
	Utilises primary sources from libraries, archives, or other repositories to investigate a research question	Analysing US Census data or telephone records

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There are three main types of observational studies: cohort studies, case–control studies, and cross-sectional studies.

Cohort studies

Cohort studies are more longitudinal in nature, as they follow a group of participants over a period of time. Members of the cohort are selected because of a shared characteristic, such as smoking, and they are often observed over a period of years.

Case–control studies

Case–control studies bring together two groups, a case study group and a control group . The case study group has a particular attribute while the control group does not. The two groups are then compared, to see if the case group exhibits a particular characteristic more than the control group.

For example, if you compared smokers (the case study group) with non-smokers (the control group), you could observe whether the smokers had more instances of lung disease than the non-smokers.

Cross-sectional studies

Cross-sectional studies analyse a population of study at a specific point in time.

This often involves narrowing previously collected data to one point in time to test the prevalence of a theory—for example, analysing how many people were diagnosed with lung disease in March of a given year. It can also be a one-time observation, such as spending one day in the lung disease wing of a hospital.

Observational studies are usually quite straightforward to design and conduct. Sometimes all you need is a notebook and pen! As you design your study, you can follow these steps.

Step 1: Identify your research topic and objectives

The first step is to determine what you’re interested in observing and why. Observational studies are a great fit if you are unable to do an experiment for ethical or practical reasons, or if your research topic hinges on natural behaviors.

Step 2: Choose your observation type and technique

In terms of technique, there are a few things to consider:

Are you determining what you want to observe beforehand, or going in open-minded?
Is there another research method that would make sense in tandem with an observational study?
If yes, make sure you conduct a covert observation.
If not, think about whether observing from afar or actively participating in your observation is a better fit.
How can you preempt confounding variables that could impact your analysis?
You could observe the children playing at the playground in a naturalistic observation.
You could spend a month at a day care in your town conducting participant observation, immersing yourself in the day-to-day life of the children.
You could conduct covert observation behind a wall or glass, where the children can’t see you.

Overall, it is crucial to stay organised. Devise a shorthand for your notes, or perhaps design templates that you can fill in. Since these observations occur in real time, you won’t get a second chance with the same data.

Step 3: Set up your observational study

Before conducting your observations, there are a few things to attend to:

Plan ahead: If you’re interested in day cares, you’ll need to call a few in your area to plan a visit. They may not all allow observation, or consent from parents may be needed, so give yourself enough time to set everything up.
Determine your note-taking method: Observational studies often rely on note-taking because other methods, like video or audio recording, run the risk of changing participant behavior.
Get informed consent from your participants (or their parents) if you want to record: Ultimately, even though it may make your analysis easier, the challenges posed by recording participants often make pen-and-paper a better choice.

Step 4: Conduct your observation

After you’ve chosen a type of observation, decided on your technique, and chosen a time and place, it’s time to conduct your observation.

Here, you can split them into case and control groups. The children with siblings have a characteristic you are interested in (siblings), while the children in the control group do not.

When conducting observational studies, be very careful of confounding or ‘lurking’ variables. In the example above, you observed children as they were dropped off, gauging whether or not they were upset. However, there are a variety of other factors that could be at play here (e.g., illness).

Step 5: Analyse your data

After you finish your observation, immediately record your initial thoughts and impressions, as well as follow-up questions or any issues you perceived during the observation. If you audio- or video-recorded your observations, you can transcribe them.

Your analysis can take an inductive or deductive approach :

If you conducted your observations in a more open-ended way, an inductive approach allows your data to determine your themes.
If you had specific hypotheses prior to conducting your observations, a deductive approach analyses whether your data confirm those themes or ideas you had previously.

Next, you can conduct your thematic or content analysis . Due to the open-ended nature of observational studies, the best fit is likely thematic analysis.

Step 6: Discuss avenues for future research

Observational studies are generally exploratory in nature, and they often aren’t strong enough to yield standalone conclusions due to their very high susceptibility to observer bias and confounding variables. For this reason, observational studies can only show association, not causation .

If you are excited about the preliminary conclusions you’ve drawn and wish to proceed with your topic, you may need to change to a different research method , such as an experiment.

Observational studies can provide information about difficult-to-analyse topics in a low-cost, efficient manner.
They allow you to study subjects that cannot be randomised safely, efficiently, or ethically .
They are often quite straightforward to conduct, since you just observe participant behavior as it happens or utilise preexisting data.
They’re often invaluable in informing later, larger-scale clinical trials or experiments.

Disadvantages

Observational studies struggle to stand on their own as a reliable research method. There is a high risk of observer bias and undetected confounding variables.
They lack conclusive results, typically are not externally valid or generalisable, and can usually only form a basis for further research.
They cannot make statements about the safety or efficacy of the intervention or treatment they study, only observe reactions to it. Therefore, they offer less satisfying results than other methods.

The key difference between observational studies and experiments is that a properly conducted observational study will never attempt to influence responses, while experimental designs by definition have some sort of treatment condition applied to a portion of participants.

However, there may be times when it’s impossible, dangerous, or impractical to influence the behavior of your participants. This can be the case in medical studies, where it is unethical or cruel to withhold potentially life-saving intervention, or in longitudinal analyses where you don’t have the ability to follow your group over the course of their lifetime.

An observational study may be the right fit for your research if random assignment of participants to control and treatment groups is impossible or highly difficult. However, the issues observational studies raise in terms of validity , confounding variables, and conclusiveness can mean that an experiment is more reliable.

If you’re able to randomise your participants safely and your research question is definitely causal in nature, consider using an experiment.

An observational study could be a good fit for your research if your research question is based on things you observe. If you have ethical, logistical, or practical concerns that make an experimental design challenging, consider an observational study. Remember that in an observational study, it is critical that there be no interference or manipulation of the research subjects. Since it’s not an experiment, there are no control or treatment groups either.

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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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?

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

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

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:

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

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.

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,

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

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.

Figure 6.8 Anna O. “Anna O.” was the subject of a famous case study used by Freud to illustrate the principles of psychoanalysis. Source: http://en.wikipedia.org/wiki/File:Pappenheim_1882.jpg

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.

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

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

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

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

Refers to when a measure changes participants’ behavior.

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

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

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

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

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

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

An in-depth examination of an individual.

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

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

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Qualitative Research: Observation

Getting Started
Focus Groups
Observation
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Data Collection
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Participant Observation

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Field Guide

Participant Observation Field Guide

What is an observation?

A way to gather data by watching people, events, or noting physical characteristics in their natural setting. Observations can be overt (subjects know they are being observed) or covert (do not know they are being watched).

Researcher becomes a participant in the culture or context being observed.
Requires researcher to be accepted as part of culture being observed in order for success

Direct Observation

Researcher strives to be as unobtrusive as possible so as not to bias the observations; more detached.
Technology can be useful (i.e video, audiorecording).

Indirect Observation

Results of an interaction, process or behavior are observed (for example, measuring the amount of plate waste left by students in a school cafeteria to determine whether a new food is acceptable to them).

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Observation Methods

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Malgorzata Ciesielska 4 ,
Katarzyna W. Boström 5 &
Magnus Öhlander 6

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Observation may be seen as the very foundation of everyday social interaction: as people participate in social life, they are diligent observers and commentators of others’ behavior. Observation is also one of the most important research methods in social sciences and at the same time one of the most complex. It may be the main method in the project or one of several complementary qualitative methods. As a scientific method it is has to be carried out systematically, with a focus on specific research questions. Therefore, we start with practical guide on clarifying research objectives, accessing the research field, selecting subjects, observer’s roles, and tips on documenting the data collected. The observation comprises several techniques and approaches that can be combined in a variety of ways. Observation can be either participant or not, direct or indirect. Further in this chapter, the main characteristics of three types of observations are outlined (the fourth type—direct non-participant—is discussed in the chapter on shadowing). While participant observation follows the ideal of a long-time immersion in a specific culture as a marginal member, researcher conducting non-participant observation takes position of an outsider and tries to distance him/herself from the taken-for-granted categorizations and evaluations. In the case of indirect observation, the researcher relies on observations of others (e.g. other researchers), various types of documentation, or self-observation. The chapter discusses the differences between those types of observation, shows inspirational examples from previous studies, and summarizes the method.

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Ciesielska, M., Boström, K.W., Öhlander, M. (2018). Observation Methods. In: Ciesielska, M., Jemielniak, D. (eds) Qualitative Methodologies in Organization Studies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-65442-3_2

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Research Methods In Psychology

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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.

types of correlation. Scatter plot. Positive negative and no correlation

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.

Types of correlation. Strong, weak, and perfect positive correlation, strong, weak, and perfect negative correlation, no correlation. Graphs or charts ...

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.

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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."

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v.5(4); September 2014-November 2014

Qualitative research method-interviewing and observation

Shazia jamshed.

Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan Campus, Pahang, Malaysia

Buckley and Chiang define research methodology as “a strategy or architectural design by which the researcher maps out an approach to problem-finding or problem-solving.”[ 1 ] According to Crotty, research methodology is a comprehensive strategy ‘that silhouettes our choice and use of specific methods relating them to the anticipated outcomes,[ 2 ] but the choice of research methodology is based upon the type and features of the research problem.[ 3 ] According to Johnson et al . mixed method research is “a class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, theories and or language into a single study.[ 4 ] In order to have diverse opinions and views, qualitative findings need to be supplemented with quantitative results.[ 5 ] Therefore, these research methodologies are considered to be complementary to each other rather than incompatible to each other.[ 6 ]

Qualitative research methodology is considered to be suitable when the researcher or the investigator either investigates new field of study or intends to ascertain and theorize prominent issues.[ 6 , 7 ] There are many qualitative methods which are developed to have an in depth and extensive understanding of the issues by means of their textual interpretation and the most common types are interviewing and observation.[ 7 ]

Interviewing

This is the most common format of data collection in qualitative research. According to Oakley, qualitative interview is a type of framework in which the practices and standards be not only recorded, but also achieved, challenged and as well as reinforced.[ 8 ] As no research interview lacks structure[ 9 ] most of the qualitative research interviews are either semi-structured, lightly structured or in-depth.[ 9 ] Unstructured interviews are generally suggested in conducting long-term field work and allow respondents to let them express in their own ways and pace, with minimal hold on respondents’ responses.[ 10 ]

Pioneers of ethnography developed the use of unstructured interviews with local key informants that is., by collecting the data through observation and record field notes as well as to involve themselves with study participants. To be precise, unstructured interview resembles a conversation more than an interview and is always thought to be a “controlled conversation,” which is skewed towards the interests of the interviewer.[ 11 ] Non-directive interviews, form of unstructured interviews are aimed to gather in-depth information and usually do not have pre-planned set of questions.[ 11 ] Another type of the unstructured interview is the focused interview in which the interviewer is well aware of the respondent and in times of deviating away from the main issue the interviewer generally refocuses the respondent towards key subject.[ 11 ] Another type of the unstructured interview is an informal, conversational interview, based on unplanned set of questions that are generated instantaneously during the interview.[ 11 ]

In contrast, semi-structured interviews are those in-depth interviews where the respondents have to answer preset open-ended questions and thus are widely employed by different healthcare professionals in their research. Semi-structured, in-depth interviews are utilized extensively as interviewing format possibly with an individual or sometimes even with a group.[ 6 ] These types of interviews are conducted once only, with an individual or with a group and generally cover the duration of 30 min to more than an hour.[ 12 ] Semi-structured interviews are based on semi-structured interview guide, which is a schematic presentation of questions or topics and need to be explored by the interviewer.[ 12 ] To achieve optimum use of interview time, interview guides serve the useful purpose of exploring many respondents more systematically and comprehensively as well as to keep the interview focused on the desired line of action.[ 12 ] The questions in the interview guide comprise of the core question and many associated questions related to the central question, which in turn, improve further through pilot testing of the interview guide.[ 7 ] In order to have the interview data captured more effectively, recording of the interviews is considered an appropriate choice but sometimes a matter of controversy among the researcher and the respondent. Hand written notes during the interview are relatively unreliable, and the researcher might miss some key points. The recording of the interview makes it easier for the researcher to focus on the interview content and the verbal prompts and thus enables the transcriptionist to generate “verbatim transcript” of the interview.

Similarly, in focus groups, invited groups of people are interviewed in a discussion setting in the presence of the session moderator and generally these discussions last for 90 min.[ 7 ] Like every research technique having its own merits and demerits, group discussions have some intrinsic worth of expressing the opinions openly by the participants. On the contrary in these types of discussion settings, limited issues can be focused, and this may lead to the generation of fewer initiatives and suggestions about research topic.

Observation

Observation is a type of qualitative research method which not only included participant's observation, but also covered ethnography and research work in the field. In the observational research design, multiple study sites are involved. Observational data can be integrated as auxiliary or confirmatory research.[ 11 ]

Research can be visualized and perceived as painstaking methodical efforts to examine, investigate as well as restructure the realities, theories and applications. Research methods reflect the approach to tackling the research problem. Depending upon the need, research method could be either an amalgam of both qualitative and quantitative or qualitative or quantitative independently. By adopting qualitative methodology, a prospective researcher is going to fine-tune the pre-conceived notions as well as extrapolate the thought process, analyzing and estimating the issues from an in-depth perspective. This could be carried out by one-to-one interviews or as issue-directed discussions. Observational methods are, sometimes, supplemental means for corroborating research findings.

cropped Screenshot 2023 08 20 at 23.18.57

Behavioral Observation: A Comprehensive Guide to Understanding and Applying This Crucial Research Method

A keen eye and a systematic approach unlock the secrets of behavior, as researchers delve into the fascinating world of observing and analyzing the actions of individuals and groups. This captivating field of study, known as behavioral observation, has become an indispensable tool for understanding the intricacies of human and animal conduct across various disciplines.

Behavioral observation is more than just watching people or animals go about their daily lives. It’s a meticulous process of recording, analyzing, and interpreting actions and interactions in a structured manner. This method has proven invaluable in fields ranging from psychology and education to anthropology and zoology. By peering into the nuances of behavior, researchers can uncover patterns, motivations, and underlying factors that shape our world.

The roots of behavioral observation stretch back to the early days of scientific inquiry. Ancient philosophers like Aristotle pondered the nature of human behavior, but it wasn’t until the late 19th and early 20th centuries that systematic observation truly took hold. Pioneers like Charles Darwin and Jean Piaget laid the groundwork for modern behavioral observation techniques, demonstrating the power of careful, methodical study in understanding the complexities of life.

Key Components of Behavioral Observation: The Building Blocks of Understanding

At the heart of effective behavioral observation lies a systematic approach. This isn’t about casual people-watching at your local café (though that can be fun too!). Instead, researchers employ rigorous methods to ensure their observations are reliable and meaningful. They might use predefined categories of behavior, specific time intervals for recording, or standardized rating scales to capture the essence of what they’re seeing.

Objectivity is the name of the game in behavioral observation. Researchers strive to record what they see without letting personal biases or interpretations color their data. This can be trickier than it sounds – after all, we’re all human, with our own perspectives and preconceptions. That’s why many studies use multiple observers and compare their findings to ensure consistency.

The setting of behavioral observation can vary widely depending on the research goals. Some studies take place in natural environments, like observing children at play in a schoolyard or animals in their native habitats. Others might occur in more controlled settings, such as laboratories or specially designed observation rooms. Each approach has its pros and cons, and researchers must carefully consider which setting will yield the most valuable insights for their particular study.

As for the types of behaviors observed, the sky’s the limit! Researchers might focus on specific actions (like how often a person checks their phone), verbal communications, non-verbal cues (body language, facial expressions), or even physiological responses (heart rate, pupil dilation). The key is to define clearly what constitutes a “behavior” for the purposes of the study and to record it consistently.

Methods and Techniques: The Observer’s Toolkit

Behavioral observation comes in many flavors, each suited to different research questions and contexts. Let’s explore some of the most common methods:

Naturalistic observation is all about observing behavior in its natural habitat, with minimal interference from the researcher. This approach can yield rich, authentic data about how people or animals behave in real-world situations. For example, an anthropologist might use naturalistic observation to study social interactions in a remote village, or a marine biologist might observe the feeding habits of whales in the open ocean.

Participant observation takes things a step further, with the researcher actively joining in the activities they’re studying. This method can provide unique insights into the subjective experiences of group members. Imagine an ethnographer living with a indigenous tribe for months or years, participating in daily life while also carefully documenting their observations. It’s a delicate balance between involvement and objectivity, but when done well, it can yield incredibly rich data.

Structured observation introduces more control into the process. Researchers might use predetermined categories or checklists to record specific behaviors of interest. This approach is particularly useful when comparing behaviors across different groups or situations. For instance, a study on Safety Behavior Observation: Implementing Effective Programs for Workplace Safety might use structured observation to assess how often employees follow safety protocols in different departments.

Time sampling and event sampling are two techniques used to manage the often overwhelming amount of data in behavioral observation. Time sampling involves recording behaviors at set intervals (e.g., every 30 seconds), while event sampling focuses on recording specific behaviors of interest whenever they occur. These methods help researchers balance the need for comprehensive data with practical limitations on time and resources.

Tools of the Trade: From Pencil and Paper to High-Tech Gadgets

The tools used in behavioral observation have come a long way since the days of Darwin scribbling notes in his journal. Today’s researchers have a vast array of options at their disposal, ranging from simple checklists to sophisticated digital systems.

Checklists and rating scales remain popular tools for their simplicity and versatility. They allow observers to quickly record the presence or frequency of specific behaviors, or to rate the intensity of observed actions on a predefined scale. For example, a Behavioral Observation Scales: Enhancing Performance Evaluation in the Workplace might use a rating scale to assess employee performance across various job-related behaviors.

Video recording equipment has revolutionized behavioral observation by allowing researchers to capture and review behaviors in exquisite detail. This is particularly useful for studying fast-paced interactions or subtle non-verbal cues that might be missed in real-time observation. Plus, it allows for multiple researchers to analyze the same footage, enhancing reliability.

Software for data analysis has become increasingly sophisticated, allowing researchers to process vast amounts of observational data quickly and accurately. These programs can identify patterns, calculate frequencies, and even generate visualizations to help make sense of complex behavioral data.

Wearable devices for physiological measurements are pushing the boundaries of what can be observed. These gadgets can track heart rate, skin conductance, and even brain activity, providing a window into the internal states that accompany observable behaviors. Imagine studying stress responses in the workplace by combining traditional observation with data from wearable heart rate monitors – it’s a whole new level of insight!

Applications: Behavioral Observation in Action

The applications of behavioral observation are as diverse as human (and animal) behavior itself. Let’s explore some key areas where this method shines:

In psychology and mental health, behavioral observation is a cornerstone of diagnosis and treatment. Clinicians use structured observation techniques to assess symptoms, monitor progress, and evaluate the effectiveness of interventions. For instance, Behavioral Observation and Screening (BOSR): Enhancing Early Intervention and Support can be crucial in identifying children at risk for developmental disorders or mental health issues.

Education and child development rely heavily on behavioral observation to understand how children learn, interact, and grow. Teachers and researchers use these techniques to assess social skills, cognitive development, and learning styles. Behavioral Observation Audiometry: A Comprehensive Guide to Assessing Infant Hearing is a perfect example of how observation can be used to assess even the youngest children who can’t yet participate in traditional hearing tests.

Animal behavior studies have been transformed by systematic observation techniques. From Jane Goodall’s groundbreaking work with chimpanzees to modern studies of marine life and endangered species, behavioral observation helps us understand and protect the diverse creatures we share our planet with.

In the world of business, organizational behavior and management benefit greatly from behavioral observation. Companies use these techniques to assess employee performance, study customer behavior, and improve workplace dynamics. Onlooker Behavior: The Psychology Behind Bystander Reactions might be studied to understand how employees respond to workplace incidents or conflicts.

Challenges and Limitations: Navigating the Pitfalls

While behavioral observation is a powerful tool, it’s not without its challenges. Researchers must navigate a minefield of potential pitfalls to ensure their findings are valid and meaningful.

Observer bias is perhaps the most significant challenge. No matter how objective we try to be, our personal experiences, expectations, and cultural backgrounds can influence what we see and how we interpret it. Researchers use various strategies to mitigate this, such as using multiple observers, standardized coding systems, and regular reliability checks.

The Hawthorne effect, named after a series of studies at the Hawthorne Works factory in the 1920s and 30s, refers to the tendency for people to change their behavior when they know they’re being observed. This can be a significant confound in behavioral studies, potentially skewing results away from natural behavior. Researchers often use unobtrusive observation methods or extended observation periods to minimize this effect.

Ethical considerations loom large in behavioral observation, particularly when studying human subjects. Issues of privacy, informed consent, and potential harm to participants must be carefully navigated. Researchers must balance the pursuit of knowledge with respect for individual rights and well-being.

Finally, the time and resource intensity of behavioral observation can be a significant limitation. Collecting and analyzing observational data can be incredibly time-consuming and expensive, particularly for large-scale or long-term studies. This can limit the scope and sample size of observational research.

The Future of Behavioral Observation: New Frontiers and Ethical Imperatives

As we look to the future, behavioral observation continues to evolve and expand its reach. Emerging technologies like artificial intelligence and machine learning are opening up new possibilities for analyzing vast amounts of observational data. Imagine AI systems that can automatically code and analyze hours of video footage, identifying subtle behavioral patterns that might escape the human eye.

Virtual and augmented reality technologies are also creating new avenues for behavioral observation. These tools allow researchers to create highly controlled yet realistic environments for studying behavior, potentially bridging the gap between laboratory and real-world studies.

However, with these exciting developments come new ethical challenges. As our ability to observe and analyze behavior becomes more sophisticated, we must grapple with questions of privacy, consent, and the potential for misuse of behavioral data. Behavior Coding: Enhancing Research Quality Through Systematic Observation must be balanced with robust ethical frameworks to ensure that these powerful tools are used responsibly.

In conclusion, behavioral observation remains a cornerstone of scientific inquiry into human and animal behavior. From its roots in the careful observations of early naturalists to the high-tech methods of today, this approach continues to yield valuable insights across a wide range of disciplines. As we move forward, it’s crucial that we continue to refine our methods, embrace new technologies, and most importantly, use these tools ethically and responsibly.

The power of behavioral observation lies in its ability to reveal the hidden patterns and motivations behind our actions. By systematically studying behavior, we gain a deeper understanding of ourselves, our society, and the world around us. Whether you’re a researcher delving into the intricacies of Observable Behavior: Skinner’s Approach to Understanding Human Actions , or simply a curious observer of the human condition, the principles of behavioral observation offer a valuable lens through which to view the world.

So the next time you find yourself people-watching at a busy café or observing animals at the zoo, remember – you’re tapping into a rich tradition of scientific inquiry. Who knows? Your keen observations might just lead to the next breakthrough in understanding the fascinating world of behavior!

References:

1. Altmann, J. (1974). Observational study of behavior: Sampling methods. Behaviour, 49(3-4), 227-266.

2. Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis. Cambridge University Press.

3. Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches. Sage Publications.

4. Dawkins, M. S. (2007). Observing animal behaviour: Design and analysis of quantitative data. Oxford University Press.

5. Eibl-Eibesfeldt, I. (1989). Human ethology. Aldine de Gruyter.

6. Goodall, J. (1986). The chimpanzees of Gombe: Patterns of behavior. Belknap Press of Harvard University Press.

7. Martin, P., & Bateson, P. (2007). Measuring behaviour: An introductory guide. Cambridge University Press.

8. Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation. John Wiley & Sons.

9. Noldus, L. P., Trienes, R. J., Hendriksen, A. H., Jansen, H., & Jansen, R. G. (2000). The Observer Video-Pro: New software for the collection, management, and presentation of time-structured data from videotapes and digital media files. Behavior Research Methods, Instruments, & Computers, 32(1), 197-206.

10. Suen, H. K., & Ary, D. (2014). Analyzing quantitative behavioral observation data. Psychology Press.

Behavioral Neuropsychology: Bridging Brain Function and Human Behavior

Deciphering the intricate interplay between the brain’s inner workings and the tapestry of human behavior, behavioral neuropsychology emerges as a captivating field that holds the key to unlocking the mysteries of the mind. This fascinating discipline bridges the gap between neuroscience and psychology, offering a unique lens through which we can explore the complex relationship…

Behavioral Neurology and Neuropsychiatry: Bridging Brain Function and Mental Health

In the remarkable tapestry of the human mind, where thoughts and emotions intertwine, the fields of behavioral neurology and neuropsychiatry emerge as essential threads, illuminating the complex relationship between brain function and mental health. These intertwined disciplines offer a unique lens through which we can explore the intricate dance between our neural circuitry and our…

Behavior Study: Unveiling the Secrets of Human Actions and Interactions

Picture a world where every action, every interaction, is a piece of a grand puzzle waiting to be solved – welcome to the captivating realm of behavior study. It’s a world where the seemingly mundane becomes extraordinary, where a simple smile or a fleeting glance can reveal volumes about the human psyche. As we embark…

Right-Sided Stroke and Impulsive Behavior: Navigating Emotional and Behavioral Changes

A sudden shift in personality, marked by impulsive decisions and inappropriate behavior, can be a perplexing and distressing consequence for survivors of right-sided strokes and their loved ones. Imagine waking up one day to find that your once-reserved spouse now blurts out inappropriate comments at social gatherings, or your typically cautious parent suddenly engages in…

Unbounded Behavior Limits: Navigating Challenges in Behavioral Analysis

The elusive nature of unbounded behavior limits presents a perplexing paradox for behavioral analysts, as they grapple with the complexities of studying that which defies conventional boundaries. It’s a bit like trying to catch a cloud with your bare hands – just when you think you’ve got it, it slips through your fingers, leaving you…

TBI Behavioral Symptoms: Navigating the Emotional and Cognitive Challenges

A sudden blow to the head can shatter lives, leaving behind a trail of emotional and cognitive challenges that often go unseen, yet profoundly impact the lives of those affected by traumatic brain injury (TBI). The human brain, that intricate masterpiece of evolution, can be so easily disrupted by a single moment of impact. It’s…

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Research on in situ observation method of plankton based on convolutional neural network.

1. Introduction

2. materials and methods, 2.1. materials, 2.1.1. dataset description, 2.1.2. data preprocessing, 2.2. methods, 2.2.1. mobilenetv2 model structure, 2.2.2. attention module, 2.2.3. feature classification module, 2.2.4. overall network introduction, 3.1. training methods, 3.1.1. network training, 3.1.2. evaluation indicators, 3.2. model performance evaluation, 3.2.1. ablation experiment, 3.2.2. identification result analysis, 3.2.3. contrast experiment, 3.2.4. application, 4. discussion, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Click here to enlarge figure

No.	Category	Original Quantity	Enhanced Quantity
1	copepod	608	1216
2	radiolaria	504	1044
3	medusa	108	276
4	foraminifera	320	816
5	chaetognatha	53	244
6	tunicata	201	458
7	snow	228	648
8	faeces	243	660
9	diatom	238	516
10	chaetoceros	137	338
11	krill	42	222
12	ceratium	46	236

Input	Operator	t	c	n	s
224 × 224 × 3	Conv2d	-	32	1	2
112 × 112 × 32	Bottleneck	1	16	1	1
112 × 112 × 16	Bottleneck	6	24	2	2
56 × 56 × 24	Bottleneck	6	32	3	2
28 × 28 × 32	Bottleneck	6	64	4	2
28 × 28 × 64	Bottleneck	6	96	3	1
14 × 14 × 96	Bottleneck	6	160	3	2
7 × 7 × 160	Bottleneck	6	320	1	1
7 × 7 × 320	Conv2d 1 × 1	-	1280	1	1
7 × 7 × 1280	Avgpool 7 × 7	-	-	1	-
1 × 1 × 1280	Conv2d 1 × 1	-	k	-	-

Input	Operator	Output
7 × 7 × 320	Conv2d 1 × 1, Relu6	7 × 7 × 192
7 × 7 × 192	Conv2d 3 × 3, Relu6	4 × 4 × 64
4 × 4 × 64	Avg pool	1 × 1 × 64
1 × 1 × 64	Linear	1 × 1 × 12

Model	Pares	Size/M	MFLOPs	Time/ms	Acc/%	Pre/%	Rec/%	F1/%
A	2,239,244	8.54	326.29	5.78	94.40	93.96	91.95	92.05
B	589,836	2.25	158.22	2.73	92.74	91.37	91.12	90.89
C	656,862	2.51	161.74	6.06	93.80	92.49	92.28	92.14
D	616,414	2.35	156.36	6.15	95.46	94.07	94.99	94.48

	Improved Model			MobileNetV2
Class	Pre/%	Rec/%	F1/%	Pre/%	Rec/%	F1/%
01copepod	99.14	95.04	97.05	97.52	97.52	97.52
02radiolaria	97.06	95.19	96.12	93.58	98.08	95.77
03medusa	92.86	96.30	94.55	100.00	88.89	94.12
04foraminifera	96.30	96.30	96.30	98.68	92.59	95.54
05chaetognatha	85.19	95.83	90.20	94.12	66.67	78.05
06tunicata	91.30	93.33	92.31	97.67	93.33	95.45
07snow	94.03	98.44	96.18	94.12	100.00	96.97
08faeces	96.92	95.45	96.18	96.88	93.94	95.38
09diatom	94.23	96.08	95.15	100.00	94.12	96.97
10chaetoceros	100.00	100.00	100.00	100.00	100.00	100.00
11krill	90.91	90.91	90.91	55.00	100.00	70.97
12ceratium	90.91	86.96	88.89	100.00	78.26	87.80
macro avg	94.07	94.99	94.48	93.96	91.95	92.05

Model	Pares	MFLOPs	Time/ms	Acc/%	Pre/%	Rec/%	F1/%
ResNet34	21,797,672	3678.74	4.40	94.70	93.98	93.26	93.58
EfficientNetb0	5,288,548	28.29	11.06	94.25	94.99	92.75	93.67
ShuffleNet0.5	1,366,792	44.57	6.79	90.47	88.21	88.00	88.00
ShuffleNet1.0	2,278,604	152.71	6.94	93.19	92.01	92.72	92.26
MobileViT_xxs	1,272,024	273.67	9.26	94.40	93.26	94.90	93.81
Improved model	616,414	156.36	6.15	95.46	94.07	94.99	94.48

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Yuan, C.; He, Z.; Ning, C.; Wang, W.; Zhao, J.; Yuan, G.; Li, C. Research on In Situ Observation Method of Plankton Based on Convolutional Neural Network. J. Mar. Sci. Eng. 2024 , 12 , 1702. https://doi.org/10.3390/jmse12101702

Yuan C, He Z, Ning C, Wang W, Zhao J, Yuan G, Li C. Research on In Situ Observation Method of Plankton Based on Convolutional Neural Network. Journal of Marine Science and Engineering . 2024; 12(10):1702. https://doi.org/10.3390/jmse12101702

Yuan, Chengzhi, Zhongjie He, Chunlin Ning, Weimin Wang, Jinkai Zhao, Guozheng Yuan, and Chao Li. 2024. "Research on In Situ Observation Method of Plankton Based on Convolutional Neural Network" Journal of Marine Science and Engineering 12, no. 10: 1702. https://doi.org/10.3390/jmse12101702

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

Qualitative vs. quantitative : Will your data take the form of words or numbers?
Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .


Qualitative		to broader populations. .
Quantitative		.

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.


Primary	.	methods.
Secondary

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.


Descriptive		. .
Experimental

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Research methods for collecting data
Research method	Primary or secondary?	Qualitative or quantitative?	When to use
	Primary	Quantitative	To test cause-and-effect relationships.
	Primary	Quantitative	To understand general characteristics of a population.
Interview/focus group	Primary	Qualitative	To gain more in-depth understanding of a topic.
Observation	Primary	Either	To understand how something occurs in its natural setting.
	Secondary	Either	To situate your research in an existing body of work, or to evaluate trends within a research topic.
	Either	Either	To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study.

Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

During an experiment .
Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

Research methods for analyzing data
Research method	Qualitative or quantitative?	When to use
	Quantitative	To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations).
Meta-analysis	Quantitative	To statistically analyze the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner.
	Qualitative	To analyze data collected from interviews, , or textual sources. To understand general themes in the data and how they are communicated.
	Either	To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words).

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square test of independence
Statistical power
Descriptive statistics
Degrees of freedom
Pearson correlation
Null hypothesis
Double-blind study
Case-control study
Research ethics
Data collection
Hypothesis testing
Structured interviews

Research bias

Hawthorne effect
Unconscious bias
Recall bias
Halo effect
Self-serving bias
Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Astrophysics > Instrumentation and Methods for Astrophysics

Title: interpreting multi-band galaxy observations with large language model-based agents.

Abstract: Astronomical research traditionally relies on extensive domain knowledge to interpret observations and narrow down hypotheses. We demonstrate that this process can be emulated using large language model-based agents to accelerate research workflows. We propose mephisto, a multi-agent collaboration framework that mimics human reasoning to interpret multi-band galaxy observations. mephisto interacts with the CIGALE codebase, which includes spectral energy distribution (SED) models to explain observations. In this open-world setting, mephisto learns from its self-play experience, performs tree search, and accumulates knowledge in a dynamically updated base. As a proof of concept, we apply mephisto to the latest data from the James Webb Space Telescope. mephisto attains near-human proficiency in reasoning about galaxies' physical scenarios, even when dealing with a recently discovered population of "Little Red Dot" galaxies. This represents the first demonstration of agentic research in astronomy, advancing towards end-to-end research via LLM agents and potentially expediting astronomical discoveries.

Comments:	Submitted. Comments are welcome!
Subjects:	Instrumentation and Methods for Astrophysics (astro-ph.IM); Astrophysics of Galaxies (astro-ph.GA)
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Observational Research
Definition: 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.
Observation Methods: Naturalistic, Participant and Controlled
The observation method in psychology involves directly and systematically witnessing and recording measurable behaviors, actions, and responses in natural or contrived settings without attempting to intervene or manipulate what is being observed. Used to describe phenomena, generate hypotheses, or validate self-reports, psychological observation can be either controlled or naturalistic with ...
What Is an Observational Study?
Revised on June 22, 2023. An observational study is used to answer a research question based purely on what the researcher observes. There is no interference or manipulation of the research subjects, and no control and treatment groups. These studies are often qualitative in nature and can be used for both exploratory and explanatory research ...
Observation
Observation. Observation, as the name implies, is a way of collecting data through observing. This data collection method is classified as a participatory study, because the researcher has to immerse herself in the setting where her respondents are, while taking notes and/or recording. Observation data collection method may involve watching ...
Direct observation methods: A practical guide for health researchers
Health research study designs benefit from observations of behaviors and contexts. •. Direct observation methods have a long history in the social sciences. •. Social science approaches should be adapted for health researchers' unique needs. •. Health research observations should be feasible, well-defined and piloted.
Observations in Qualitative Inquiry: When What You See Is Not What You
Observation in qualitative research "is one of the oldest and most fundamental research methods approaches. This approach involves collecting data using one's senses, especially looking and listening in a systematic and meaningful way" (McKechnie, 2008, p. 573).Similarly, Adler and Adler (1994) characterized observations as the "fundamental base of all research methods" in the social ...
Naturalistic Observation
Revised on June 22, 2023. Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering with or influencing any variables in a naturalistic observation. You can think of naturalistic observation as "people watching" with a purpose.
6.5 Observational Research
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 ...
What Is an Observational Study?
An observational study is used to answer a research question based purely on what the researcher observes. There is no interference or manipulation of the research subjects, and no control and treatment groups. These studies are often qualitative in nature and can be used for both exploratory and explanatory research purposes.
Observation Methods
Observation is one of the most important research methods in social sciences and at the same time one of the most diverse. The term includes several types, techniques, and approaches, which may be difficult to compare in terms of enactment and anticipated results; the choice must be adapted to the research problem and the scientific context. As ...
Observational Methods
Systematic observational methods require clearly defined codes, structured sampling and recording procedures, and are subject to rigorous psychometric analysis. We review best practices in each of these areas with attention to the application of these methods for addressing empirical questions that quantitative researchers may posit.
Observational Research
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 ...
Observation
A way to gather data by watching people, events, or noting physical characteristics in their natural setting. Observations can be overt (subjects know they are being observed) or covert (do not know they are being watched). Participant Observation. Researcher becomes a participant in the culture or context being observed.
What Is Qualitative Observation?
Qualitative observation is a research method where the characteristics or qualities of a phenomenon are described without using any quantitative measurements or data. Rather, the observation is based on the observer's subjective interpretation of what they see, hear, smell, taste, or feel. You are interested in studying the behavior of ...
(PDF) Observation Methods
2.1 Introduction. Observation is one of the most important research methods in social sci-. ences and at the same time one of the most diverse. e term includes. several types, techniques, and ...
PDF Observation Methods
Observation Methods2. er2.1 IntroductionObservation is one of the most important research methods in social sci-ences and at the same time one. f the most diverse. The term includes several types, techniques, and approaches, which may be dificult to com-pare in terms of enactment and anticipated results; the choice must be adapted to the ...
Research Methods In Psychology
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.
PDF Observation: A Complex Research Method
Characteristics Unique to Observational Research. Observation has some aspects that are unique to this research method, including training, entering and leaving the study group, length of time in the fi eld, sampling, and data collection techniques. Each of these topics will be described briefl y below.
Naturalistic Observation: Definition, Examples, Pros and Cons
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 ...
Qualitative research method-interviewing and observation
Observation. Observation is a type of qualitative research method which not only included participant's observation, but also covered ethnography and research work in the field. In the observational research design, multiple study sites are involved. Observational data can be integrated as auxiliary or confirmatory research.
Observational Methods
Observation is one of the founding principles of the scientific method, and it can be a very effective tool for studying human-environment interactions. This chapter provides the reader with a practical guide for conducting observational research both in lab and field settings. Using casual, passive, and active observation, a researcher can ...
Behavioral Observation: Understanding and Applying Research Methods
Behavioral observation comes in many flavors, each suited to different research questions and contexts. Let's explore some of the most common methods: Naturalistic observation is all about observing behavior in its natural habitat, with minimal interference from the researcher.
What Is Participant Observation?
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 ...
Participant observation
Participant observation is one type of data collection method by practitioner-scholars typically used in qualitative research and ethnography.This type of methodology is employed in many disciplines, particularly anthropology (incl. cultural anthropology and ethnology), sociology (incl. sociology of culture and cultural criminology), communication studies, human geography, and social psychology.
Quantifying potential selection bias in observational research
We also note that, even if selection does not result in bias, methods to account for missing data—such as multiple imputation and weighting methods (Seaman & White, Citation 2013; Van Buuren, Citation 2018; White et al., Citation 2011)—may still be useful to help improve the efficiency of analyses (i.e., smaller standard errors/confidence ...
Observations Research Methods Lesson 10 AQA Psychology PowerPoint
Complete 1 hour lesson including starter, AO1, AO3 video, AFL, extension tasks, model answers. Carefully planned to meet the needs of all students. Part of full unit
Research on In Situ Observation Method of Plankton Based on ...
The marine ecosystem is one of the most extensive and abundant ecosystems on Earth. Marine plankton is an important component, and its abundance, number of species, and dominant species are regarded as important monitoring indicators. Aiming at the problems of low accuracy and high complexity in identifying plankton based on convolutional neural networks, this study proposes a lightweight ...
Research Methods
You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.. Primary vs. secondary research. Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys, observations and experiments). Secondary research is data that has already been collected by other researchers (e ...
[2409.14807] Interpreting Multi-band Galaxy Observations with Large
Astronomical research traditionally relies on extensive domain knowledge to interpret observations and narrow down hypotheses. We demonstrate that this process can be emulated using large language model-based agents to accelerate research workflows. We propose mephisto, a multi-agent collaboration framework that mimics human reasoning to interpret multi-band galaxy observations. mephisto ...

Observational Research – Methods and Guide

Observational Research

Observation

Types of Observational Research

Naturalistic Observation

Controlled Observation

Participant Observation

Structured Observation

Unstructured Observation

Cross-Sectional Observation

Longitudinal Observation

Data Collection Methods

Field Notes

Audio and Video Recordings

Surveys and Questionnaires

Time Sampling

Event Sampling

Checklists and Rating Scales

Observational Data Analysis Methods

Descriptive Statistics

Qualitative Analysis

Content Analysis

Time-series Analysis

Inter-observer Reliability Analysis

Multivariate Analysis

Event Coding

Cluster Analysis

Latent Class Analysis

Social network Analysis

Applications of Observational Research

Observational Research Examples

How to Conduct Observational Research

When to use Observational Research

Purpose of Observational Research

Advantages of Observational Research

Disadvantages of Observational Research

About the author

Muhammad Hassan

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Observation

6.5 Observational Research

What Is Observational Research?

Naturalistic Observation

Participant Observation

Structured Observation

Case Studies

The Case of “Anna O.”

Archival Research

Key Takeaways

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What Is an Observational Study? | Guide & Examples

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Cohort studies

Case–control studies

Cross-sectional studies

Step 1: Identify your research topic and objectives

Step 2: Choose your observation type and technique

Step 3: Set up your observational study

Step 4: Conduct your observation

Step 5: Analyse your data

Step 6: Discuss avenues for future research

Disadvantages

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Tegan George

32 Observational Research

What Is Observational Research?

Naturalistic Observation

Participant Observation

Structured Observation

Case Studies

The Case of “Anna O.”