observational research topic ideas

21 Naturalistic Observation Examples

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

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Naturalistic observation is a data collection method that involves observing behavior as it occurs in a natural environment. It is a common methodology in psychology and anthropology .

The main idea is to see how people or animals act in their natural habitat, as opposed to a research laboratory. This will give researchers insights into a particular phenomenon under study that could not be obtained in the artificial setting of a lab. Sometimes, we also call this observational research .

Naturalistic Observation Examples

• Observing chimpanzees in the wild and recording their social interactions – Jane Goodall
• Observing children playing at different ages and examining their stages of cognitive development – Jean Piaget
• Observing how students interact in the workplace to get insights into classroom layout and teaching styles – This Study
• Observing an indigenous group of cattle herders in East Africa to see how they educate their youth – George J. Klima
• Observing how working-class high school students are taught differently to middle-class students – Paul Willis, Learning to Labour
• Observing a left-wing cooperative attempting to run their business collaboratively and democratically – Avi Lewis, The Take
• Observing the relationship between mothers and their children in their home to determine a taxonomy of attachment styles – Mary Ainsworth
• Following emergency room staff to see how their professional culture is developed and operates under pressure – Person et al.
• Placing cameras in wombat burrows to observe how they live, mate, and survive – Swinbourne et al.
• Observing a busy intersection to see how traffic jams begin and explore how changing the traffic light cadence can decrease congestion
• An experienced teacher sitting-in on a trainee teacher to observe them teaching

Famous Examples

1. jane goodall’s research.

Dr. Valerie Jane Morris-Goodall is one of the most famous scientists in history. Her research on chimpanzees in Kenya and work in conservation are well-known throughout the world.

Her primary research method was naturalistic observation. She entered the natural habitat of the subject of her study, sat down with pen and paper, and began taking detailed notes of her observations. Those notes were later transcribed into numerous research papers for other scientists to learn from.

Her research produced many groundbreaking insights into animal behavior, including the fact that chimpanzees use tools, such as twigs and straw to “fish” for termites. This was an incredible discover, which led to the now famous quote by Louis Leakey, “we must now redefine tool, redefine man, or accept chimps as humans.”

To learn about other fascinating uses of naturalistic observation, including links to numerous research tools like live cams at the Cornell Lab of Ornithology, check-out this amazing resource page from National Geographic .

2. Linguistic Development of Children

Language development is a fascinating phenomenon. Human beings go from not being able to utter a single word, to having a vocabulary existing of thousands of words by the age of 5.

A typical study involves researchers training their research team on how to conduct objective observations of parental interactions with their children. The observers will then go to a family’s home, sit quietly in a corner of a room, and take detailed notes.

The data can include recording the number of interactions, number of words directed at the child, and types of words (e.g., expressive or factual). After all the data is collected, it is analyzed using statistical software and patterns of parental behavior that are linked to language development can be discovered.

Although naturalistic observation can give us valuable insights into the role of parental interactions in child development, this type of research is quite difficult to carry-out.

3. Observing Workplaces to Study Ergonomics  

Ergonomics is the study of how human beings function in the environment, such as a work setting, or how they interact with various products or machine interfaces. This branch of study is sometimes referred to as “human factors.”

The goal is to improve people’s experience with the object of study to make it more efficient, effective, or pleasant.

The basic procedure is for a trained professional to observe people using the equipment, or product, while taking detailed notes on the user’s experience. This is often followed-up with a one-on-one interview, a survey, or focus group .

This type of naturalistic observation is so widely used today that there probably is not a single electronic gadget on the market that has not gone through some version of ergonomic analysis.

4. Satellite Images of Walmart

As reported by NPR , some stock market analysts use naturalistic observation of Walmart parking lots to earn huge profits. With the purchase of satellite images of selected Walmart parking lots, an analyst can count the number of cars and estimate how well business is going.

From other sources, the analyst knows the average amount of money spent by customers, broken down by time of day and geographic location. When combining that information with the satellite images, they start to build a detailed picture of the company’s sales.

Later, they can compare their estimates with the actual numbers released by the company during their quarterly reports. That will give the analyst an opportunity to refine how they collect their data and lead to more accurate estimates in the future.

This is a type of naturalistic observation that results in huge profits for companies that know how to use the data. For other examples, click here .

5. Spying on Farms

Although naturalistic observation is usually used when studying human or animal behavior, it can also be used to observe plant growth.

Believe it or not, big money can be made in the futures markets by predicting the price of various agricultural commodities.

Some companies use infrared imaging software to observe how well various crops are developing all over the world, such as corn and wheat. The images not only track the number of acres being planted, but can also assess how well they are growing by measuring the amount of chlorophyll in the plants.

By tracking growth over time, analysts can identify any changes that may significantly affect supply and demand in the future. Having that edge can lead to massive profits.

6. Observing Group Dynamics During Office Meetings

Understanding the dynamics of how work teams make decisions is a well-researched area in Industrial Psychology. This involves naturalistic observations of team interactions at work.

Bad decisions can lead to disastrous results. On the other hand, making wise decisions regarding strategic planning or product selection can generate tremendous profits.

One insight revealed through naturalistic observation research is that various members of a work-team play different roles.

For example, some play the role of task-master. They like to keep the team focused on objectives and meeting deadlines. While others serve to help the team get along. They’re called harmonizers and they try to defuse conflicts.

The research typically involves trained observers sitting to the side or watching the team conduct their meetings through CCTV. The observers take notes on who says what to whom, and the nature of those comments.

By examining the observations later, it is possible to identify weaknesses in how decisions are made and suggest ways to improve the decision-making process .

7. Observing Screentime vs Quality of Romantic Relationships

Social scientists have expressed concern that screentime, or social media use, may impact the quality of romantic relationships ( Quiroz & Mickelson, 2021). But one researcher took this to a new level by watching romantic couples’ phone usage!

Unfortunately, a lot of research in this area relies on surveys. One survey will assess frequency of social media use and another survey will assess quality of the current romantic relationship.

Naturalist observation could provide more realistic information. For example, two trained observers could be placed at various public places, such as a farmer’s market.

One observer tracks the touching behavior of couples, an acceptable indicator of romantic involvement (Gulledge et al., 2003), while the other tracks screentime.

Once all the data is collected, a simple analysis comparing the rate of touching to screentime could reveal if there is an association, or not.  

Of course, to fully answer any question requires multiple studies using different methods. Combined, a clearer understanding of the phenomenon under study gradually (i.e., years) emerges.

8. Naturalistic Observation of Infant Attachment

Mary Ainsworth is well-known for her strange situations test to assess attachment quality. However, before developing this test, she conducted naturalistic observations of infant/caregiver behavior in Uganda for 2 years starting in 1954, after a 4-year collaboration with John Bowlby.

She visited the homes of 26 families with babies during bi-monthly, 2-hour visits. She wrote detailed notes on the infants’ interactions with their mothers and in the presence of others, in addition to mothers’ responses to her questions about infant care.

The notes were then expanded and summarized into reports and checked for accuracy by an interpreter that accompanied her during the visits.

As reported by Bretherton (2013), “… secure-attached infants cried little and engaged in exploration when their mother was present, while insecure-attached infants were frequently fussy even with mother in the same room” (p. 461).

9. Observing Subliminal Messaging and Popcorn Sales Correlation

The idea that messages presented below the threshold of conscious awareness could affect behavior has been around for decades. It all began with a 1957 study that claimed subliminal messages in a movie increased popcorn sales by nearly 60%.

As it turns out, the research was never conducted.

However, if a person wanted to actually conduct this kind of research it could be done. First, messages that suggested eating popcorn would have to be spliced into a film; another version f the film would not contain the messages.

Both films would be shown simultaneously at the same theatre. As customers purchased tickets, they would be randomly assigned to watch one of the two versions. A trained observer would sit nearby the concession stand and keep track of how many customers viewing each version purchased popcorn during and after the film finished. This is the naturalistic observation component.

A simple comparison of popcorn sales between each film would test the hypothesis and settle the issue forever.  

10. Time and Motion Studies to Increase Productivity

A time and motion study is a method for making work processes more efficient. Being more efficient means higher profits.

First, workers are observed and recorded. Then, some steps to complete a task may be eliminated while ways to shorten the time it takes to complete other steps are identified.

Frank and Lillian Gilbreth were early pioneers in this type of naturalistic observation study.  

Frank owned a construction company and Lilian was a psychologist. They observed Frank’s bricklayers and reduced the number of movements needed to carry out their work from 18 to 4.

From there they started a consulting business, helping manufacturers improve efficiency during the industrial revolution. After Frank’s early passing at the age of 54, Lillian went on to become the first female member of the Society for Industrial Engineers and the only psychologist to appear on a postage stamp (in 1884).

Types of Naturalistic Observation

There are many versions of naturalistic observation. Below are two common onese:

• Participant/Non-participant refers to whether the person collecting the data is also participating in the activity being studied or is solely observing from the sidelines.

Understanding the customs of an exotic culture by participating in some of the rituals may provide some very valuable insights from a personal perspective. Or, the researcher may prefer to observe the cultural practices from a distance, which can also provide a lot of valuable information.

• Covert/Overt observation refers to whether the people being observed are aware that they are under study.  Since people may change their behavior if they know they are being watched, a researcher may choose to not inform the people that they are under study. Overt observation means that the people under study are fully aware of the researcher’s presence.

As with all scientific studies in the social sciences conducted by university scientists, each study must be evaluated by an Institutional Review Board (IRB) before it can begin. The IRB scrutinizes the methods for ethical issues and may require researchers to make adjustments to the procedures before being approved.

Benefits of Naturalistic Observation

Sometimes people will act differently in a laboratory setting because they know they are being observed. They may try to act more polite or portray themselves in a favorable light.

In a naturalistic observation study, participants are often unaware they are being observed, so they do not try to alter their behavior.

In animal studies, conducting research in the field may be the only way to study the phenomenon of interest, as one cannot construct a rainforest or similar habitat in the lab.

Naturalistic observation is a great way to collect data on a phenomenon as it exists in its natural environment. If studying people, there are aspects of behavior that cannot be observed in a laboratory setting, and people often change their behavior if they know a social scientist is watching them.

If studying animals, it is just simply not possible to recreate an entire habitat in a research lab. So, scientists must venture into the wild and observe animals on their own turf. This will provide insights into their behavior that cannot be obtained in a laboratory.

We can even use naturalistic observation to track consumer behavior and make predictions regarding corporate sales or agricultural futures. That information can lead to huge profits.

Naturalistic observation is an incredibly valuable research tool that has application in science and business.

Ainsworth, M. D. S. (1967). Infancy in Uganda . Baltimore: Johns Hopkins University Press.

Bretherton, I. (2013). Revisiting Mary Ainsworth’s conceptualization and assessments of maternal sensitivity-insensitivity. Attachment & Human Development, 15 (5–6), 460–484. http://dx.doi.org/10.1080/14616734.2013.835128

d’Apice, K., Latham, R., & Stumm, S. (2019). A naturalistic home observational approach to children’s language, cognition, and behavior. Developmental Psychology, 55 (7),1414-1427. https://doi.org/10.1037/dev0000733

Gulledge, A. K., Gulledge, M. H., & Stahmannn, R. F. (2003). Romantic physical affection types and relationship satisfaction.  The American Journal of Family Therapy ,  31 (4), 233-242.

Lenhart, A., & Duggan, M. (2014). Couples, the internet, and social media: How American couples use digital technology to manage life, logistics, and emotional intimacy within their relationships. Pew Research Center. Retrieved from https://www.pewinternet.org/2014/02/11/couples-the-internet-and-social-media/

Quiroz, S., Mickelson, K. (2021). Are online behaviors damaging our in-person connections? Passive versus active social media use on romantic relationships. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 15 (1). https://doi.org/10.5817/CP2021-1-1

Ulvi, O., Karamehic-Muratovic, A., Baghbanzadeh, M., Bashir, A., Smith, J., & Haque, U. (2022). Social Media Use and Mental Health: A Global Analysis. https://doi.org/10.3390/epidemiologia3010002

Wagner, S. A., Mattson, R. E., Davila, J., Johnson, M. D., & Cameron, N. M. (2020). Touch me just enough: The intersection of adult attachment, intimate touch, and marital satisfaction.  Journal of Social and Personal Relationships , 37(6), 1945-1967. https://doi.org/10.1177/0265407520910791

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Home » Observational Research – Methods and Guide

Observational Research – Methods and Guide

Table of Contents

Observational Research

Definition:

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

Observation

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

Types of Observational Research

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

Naturalistic Observation

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

Controlled Observation

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

Participant Observation

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

Structured Observation

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

Unstructured Observation

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

Cross-Sectional Observation

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

Longitudinal Observation

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

Data Collection Methods

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

Field Notes

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

Audio and Video Recordings

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

Surveys and Questionnaires

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

Time Sampling

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

Event Sampling

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

Checklists and Rating Scales

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

Observational Data Analysis Methods

Observational Data Analysis Methods are:

Descriptive Statistics

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

Qualitative Analysis

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

Content Analysis

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

Time-series Analysis

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

Inter-observer Reliability Analysis

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

Multivariate Analysis

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

Event Coding

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

Cluster Analysis

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

Latent Class Analysis

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

Social network Analysis

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

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

Applications of Observational Research

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

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

Observational Research Examples

Here are some real-time observational research examples:

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

How to Conduct Observational Research

Here are some general steps for conducting Observational Research:

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

When to use Observational Research

Here are some situations where observational research can be useful:

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

Purpose of Observational Research

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

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

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

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

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

Advantages of Observational Research

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

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

Disadvantages of Observational Research

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

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

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Muhammad Hassan

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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.

Table of contents

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.

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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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Observational Research: What is, Types, Pros & Cons + Example

Researchers can gather customer data in a variety of ways, including surveys, interviews, and research. But not all data can be collected by asking questions because customers might not be conscious of their behaviors. 

It is when observational research comes in. This research is a way to learn about people by observing them in their natural environment. This kind of research helps researchers figure out how people act in different situations and what things in the environment affect their actions.

This blog will teach you about observational research, including types and observation methods. Let’s get started.

What is observational research?

Observational research is a broad term for various non-experimental studies in which behavior is carefully watched and recorded.

The goal of this research is to describe a variable or a set of variables. More broadly, the goal is to capture specific individual, group, or setting characteristics.

Since it is non-experimental and uncontrolled, we cannot draw causal research conclusions from it. The observational data collected in research studies is frequently qualitative observation , but it can also be quantitative or both (mixed methods).

Types of observational research

Conducting observational research can take many different forms. There are various types of this research. These types are classified below according to how much a researcher interferes with or controls the environment.

Naturalistic observation

Taking notes on what is seen is the simplest form of observational research. A researcher makes no interference in naturalistic observation. It’s just watching how people act in their natural environments. 

Importantly, there is no attempt to modify factors in naturalistic observation, as there would be when comparing data between a control group and an experimental group.

Case studiesCase studies

A case study is a sort of observational research that focuses on a single phenomenon. It is a naturalistic observation because it captures data in the field. But case studies focus on a specific point of reference, like a person or event, while other studies may have a wider scope and try to record everything that happens in the researcher’s eyes. 

For example, a case study of a single businessman might try to find out how that person deals with a certain disease’s ups and down or loss.

Participant observation

Participant observation is similar to naturalistic observation, except that the researcher is a part of the natural environment they are studying. In such research, the researcher is also interested in rituals or cultural practices that can only be evaluated by sharing experiences. 

For example, anyone can learn the basic rules of table Tennis by going to a game or following a team. Participant observation, on the other hand, lets people take part directly to learn more about how the team works and how the players relate to each other.

It usually includes the researcher joining a group to watch behavior they couldn’t see from afar. Participant observation can gather much information, from the interactions with the people being observed to the researchers’ thoughts.

Controlled observation

A more systematic structured observation entails recording the behaviors of research participants in a remote place. Case-control studies are more like experiments than other types of research, but they still use observational research methods. When researchers want to find out what caused a certain event, they might use a case-control study.

Longitudinal observation

This observational research is one of the most difficult and time-consuming because it requires watching people or events for a long time. Researchers should consider longitudinal observations when their research involves variables that can only be seen over time. 

After all, you can’t get a complete picture of things like learning to read or losing weight in a single observation. Longitudinal studies keep an eye on the same people or events over a long period of time and look for changes or patterns in behavior.

Observational research methods

When doing this research, there are a few observational methods to remember to ensure that the research is done correctly. Along with other research methods, let’s learn some key research methods of it:

Have a clear objective

For an observational study to be helpful, it needs to have a clear goal. It will help guide the observations and ensure they focus on the right things.

Get permission

Get permission from your participants. Getting explicit permission from the people you will be watching is essential. It means letting them know that they will be watched, the observation’s goal, and how their data will be used.

Unbiased observation

It is important to make sure the observations are fair and unbiased. It can be done by keeping detailed notes of what is seen and not putting any personal meaning on the data.

Hide your observers

In the observation method, keep your observers hidden. The participants should be unaware of the observers to avoid potential bias in their actions.

Documentation

It is important to document the observations clearly and straightforwardly. It will allow others to examine the information and confirm the observational research findings.

Data analysis

Data analysis is the last method. The researcher will analyze the collected data to draw conclusions or confirm a hypothesis.

Pros and cons of observational research

Observational studies are a great way to learn more about how your customers use different parts of your business. There are so many pros and cons of observational research. Let’s have a look at them.

• It provides a practical application for a hypothesis. In other words, it can help make research more complete.
• You can see people acting alone or in groups, such as customers. So, you can answer a number of questions about how people act as customers.
• There is a chance of researcher bias in observational research. Experts say that this can be a very big problem.
• Some human activities and behaviors can be difficult to understand. We are unable to see memories or attitudes. In other words, there are numerous situations in which observation alone is inadequate.

Example of observational research

The researcher observes customers buying products in a mall. Assuming the product is soap, the researcher will observe how long the customer takes to decide whether he likes the packaging or comes to the mall with his decision already made based on advertisements.

If the customer takes their time making a decision, the researcher will conclude that packaging and information on the package affect purchase behavior. If a customer makes a quick decision, the decision is likely predetermined. 

As a result, the researcher will recommend more and better advertisements in this case. All of these findings were obtained through simple observational research.

How to conduct observational research with QuestionPro?

QuestionPro can help with observational research by providing tools to collect and analyze data. It can help in the following ways:

Define the research goals and question types you want to answer with your observational study . Use QuestionPro’s customizable survey templates and questions to do a survey that fits your research goals and gets the necessary information. 

You can distribute the survey to your target audience using QuestionPro’s online platform or by sending a link to the survey. 

With QuestionPro’s real-time data analysis and reporting features, you can collect and look at the data as people fill out the survey. Use the advanced analytics tools in QuestionPro to see and understand the data and find insights and trends. 

If you need to, you can export the data from QuestionPro into the analysis tools you like to use. Draw conclusions from the collected and analyzed data and answer the research questions that were asked at the beginning of the research.

For a deeper understanding of human behaviors and decision-making processes, explore the realm of Behavioral Research .

To summarize, observational research is an effective strategy for collecting data and getting insights into real-world phenomena. When done right, this research can give helpful information and help people make decisions. 

QuestionPro is a valuable tool that can help with observational research by letting you create online surveys, analyze data in real time, make surveys your own, keep your data safe, and use advanced analytics tools.

To do this research with QuestionPro, researchers need to define their research goals, do a survey that matches their goals, send the survey to participants, collect and analyze the data, visualize and explain the results, export data if needed, and draw conclusions from the data collected.

By keeping in mind what has been said above, researchers can use QuestionPro to help with their observational research and gain valuable data. Try out QuestionPro today!

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Frequently Asked Questions (FAQ)

Observational research is a method in which researchers observe and systematically record behaviors, events, or phenomena without directly manipulating them.

There are three main types of observational research: naturalistic observation, participant observation, and structured observation.

Naturalistic observation involves observing subjects in their natural environment without any interference.

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Non-Experimental Research

32 Observational Research

Learning objectives.

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

What Is Observational Research?

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

Naturalistic Observation

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

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

Participant Observation

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

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

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

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

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

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

Structured Observation

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

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

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

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

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

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

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

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

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

Case Studies

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

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

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

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

The Case of “Anna O.”

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

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

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

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

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

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

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

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

Archival Research

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

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

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

Media Attributions

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

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

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

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

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

Refers to when a measure changes participants’ behavior.

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

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

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

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

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

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

An in-depth examination of an individual.

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

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

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Research Question Examples 🧑🏻‍🏫

25+ Practical Examples & Ideas To Help You Get Started 

By: Derek Jansen (MBA) | October 2023

A well-crafted research question (or set of questions) sets the stage for a robust study and meaningful insights.  But, if you’re new to research, it’s not always clear what exactly constitutes a good research question. In this post, we’ll provide you with clear examples of quality research questions across various disciplines, so that you can approach your research project with confidence!

Research Question Examples

• Psychology research questions
• Business research questions
• Education research questions
• Healthcare research questions
• Computer science research questions

Examples: Psychology

Let’s start by looking at some examples of research questions that you might encounter within the discipline of psychology.

How does sleep quality affect academic performance in university students?

This question is specific to a population (university students) and looks at a direct relationship between sleep and academic performance, both of which are quantifiable and measurable variables.

What factors contribute to the onset of anxiety disorders in adolescents?

The question narrows down the age group and focuses on identifying multiple contributing factors. There are various ways in which it could be approached from a methodological standpoint, including both qualitatively and quantitatively.

Do mindfulness techniques improve emotional well-being?

This is a focused research question aiming to evaluate the effectiveness of a specific intervention.

How does early childhood trauma impact adult relationships?

This research question targets a clear cause-and-effect relationship over a long timescale, making it focused but comprehensive.

Is there a correlation between screen time and depression in teenagers?

This research question focuses on an in-demand current issue and a specific demographic, allowing for a focused investigation. The key variables are clearly stated within the question and can be measured and analysed (i.e., high feasibility).

Examples: Business/Management

Next, let’s look at some examples of well-articulated research questions within the business and management realm.

How do leadership styles impact employee retention?

This is an example of a strong research question because it directly looks at the effect of one variable (leadership styles) on another (employee retention), allowing from a strongly aligned methodological approach.

What role does corporate social responsibility play in consumer choice?

Current and precise, this research question can reveal how social concerns are influencing buying behaviour by way of a qualitative exploration.

Does remote work increase or decrease productivity in tech companies?

Focused on a particular industry and a hot topic, this research question could yield timely, actionable insights that would have high practical value in the real world.

How do economic downturns affect small businesses in the homebuilding industry?

Vital for policy-making, this highly specific research question aims to uncover the challenges faced by small businesses within a certain industry.

Which employee benefits have the greatest impact on job satisfaction?

By being straightforward and specific, answering this research question could provide tangible insights to employers.

Examples: Education

Next, let’s look at some potential research questions within the education, training and development domain.

How does class size affect students’ academic performance in primary schools?

This example research question targets two clearly defined variables, which can be measured and analysed relatively easily.

Do online courses result in better retention of material than traditional courses?

Timely, specific and focused, answering this research question can help inform educational policy and personal choices about learning formats.

What impact do US public school lunches have on student health?

Targeting a specific, well-defined context, the research could lead to direct changes in public health policies.

To what degree does parental involvement improve academic outcomes in secondary education in the Midwest?

This research question focuses on a specific context (secondary education in the Midwest) and has clearly defined constructs.

What are the negative effects of standardised tests on student learning within Oklahoma primary schools?

This research question has a clear focus (negative outcomes) and is narrowed into a very specific context.

Need a helping hand?

Examples: Healthcare

Shifting to a different field, let’s look at some examples of research questions within the healthcare space.

What are the most effective treatments for chronic back pain amongst UK senior males?

Specific and solution-oriented, this research question focuses on clear variables and a well-defined context (senior males within the UK).

How do different healthcare policies affect patient satisfaction in public hospitals in South Africa?

This question is has clearly defined variables and is narrowly focused in terms of context.

Which factors contribute to obesity rates in urban areas within California?

This question is focused yet broad, aiming to reveal several contributing factors for targeted interventions.

Does telemedicine provide the same perceived quality of care as in-person visits for diabetes patients?

Ideal for a qualitative study, this research question explores a single construct (perceived quality of care) within a well-defined sample (diabetes patients).

Which lifestyle factors have the greatest affect on the risk of heart disease?

This research question aims to uncover modifiable factors, offering preventive health recommendations.

Examples: Computer Science

Last but certainly not least, let’s look at a few examples of research questions within the computer science world.

What are the perceived risks of cloud-based storage systems?

Highly relevant in our digital age, this research question would align well with a qualitative interview approach to better understand what users feel the key risks of cloud storage are.

Which factors affect the energy efficiency of data centres in Ohio?

With a clear focus, this research question lays a firm foundation for a quantitative study.

How do TikTok algorithms impact user behaviour amongst new graduates?

While this research question is more open-ended, it could form the basis for a qualitative investigation.

What are the perceived risk and benefits of open-source software software within the web design industry?

Practical and straightforward, the results could guide both developers and end-users in their choices.

Remember, these are just examples…

In this post, we’ve tried to provide a wide range of research question examples to help you get a feel for what research questions look like in practice. That said, it’s important to remember that these are just examples and don’t necessarily equate to good research topics . If you’re still trying to find a topic, check out our topic megalist for inspiration.

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Ideas for Observational Studies

Kimberley mcgee, 24 jul 2018.

The world is a fascinating place with wonders that can often be overlooked in the hustle of daily life. Making an observational study can bring the world around us into focus. Finding observation project ideas is a relatively simple process. Creating easy observational studies is a matter of plotting your path to prove your hypothesis.

Explore this article

• Preparing to Study
• Types of Observation Studies
• Observation Project Ideas

1 Preparing to Study

Approach the observation study with a strong hypothesis that you hope to prove or disprove by studying a certain population. Consider your interests for easy observational studies. Consider conducting the study in a natural setting so that the information that you gather is not muddied or influenced by atypical factors. A true observation study allows the observer to partake of a population, or independent variable, that is in no way influenced by the observer or the observer’s intentions. Prepare to take notes so have a dedicated notebook or electronic device handy at all times during the observation period.

2 Types of Observation Studies

Any observation project ideas that you are considering should be things that are in your daily life or otherwise easily accessible. Naturalistic observation ideas will come to you easily if you take time to look around what you walk past or encounter on a daily basis. If the person or things you are observing do not realize you are studying them, it is called a disguised observation. If the subjects understand that they are part of a study you are conducting, it is called a non-disguised observation.

Structured observations collect data that can easily be organized into distinct categories. A non-structured observation is when the observer is attempting to find everything about a subject and gathering things as they occur to support their hypothesis. A direct observation involves studying the actual behavior during the occurrence. An indirect observation finds information after the occurrence. For instance, you could study what kids eat at lunch. A direct study has the observer watching what kids order at the cafeteria counter. An indirect study has the observer monitoring what was thrown away after the lunch period to discern what kids ate.

3 Observation Project Ideas

There are a few easy observational studies to get a student started in this exciting endeavor. Create a list of naturalistic observation ideas or mechanical observation ideas to pinpoint what interests you the most. Easy observational studies are those that you can conduct within the parameters of your daily life.

If you live in a tall building, a study of the habits of those who ride the elevator can be revealing about human nature. At lunch or recess, observe students and how they interact. Do girls gravitate toward large groups? Do boys tend to play more on the playground equipment than in the field? Naturalistic observation ideas include monitoring ant hills and the behavior of the inhabitants, bird behaviors and diet interests or household pet activities.

• 1 Very Well Mind: Psychology Experiment Ideas for Assignments

About the Author

Kimberley McGee is an award-winning journalist with 20+ years of experience writing about education, jobs, business and more for The New York Times, Las Vegas Review-Journal, Today’s Parent and other publications. She graduated with a B.A. in Journalism from UNLV. Her full bio and clips can be seen at www.vegaswriter.com.

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Direct observation methods: A practical guide for health researchers

Gemmae m. fix.

a VA Center for Healthcare Organization and Implementation Research, Bedford and Boston, MA, USA

b General Internal Medicine, Boston University School of Medicine, Boston, MA, USA

c Department of Psychiatry, Harvard Medical School, Boston, MA, USA

Mollie A. Ruben

d Department of Psychology, University of Maine, Orono, ME, USA

Megan B. McCullough

e Department of Public Health, University of Massachusetts Lowell, Lowell, MA, USA

To provide health research teams with a practical, methodologically rigorous guide on how to conduct direct observation.

Synthesis of authors’ observation-based teaching and research experiences in social sciences and health services research.

This article serves as a guide for making key decisions in studies involving direct observation. Study development begins with determining if observation methods are warranted or feasible. Deciding what and how to observe entails reviewing literature and defining what abstract, theoretically informed concepts look like in practice. Data collection tools help systematically record phenomena of interest. Interdisciplinary teams--that include relevant community members-- increase relevance, rigor and reliability, distribute work, and facilitate scheduling. Piloting systematizes data collection across the team and proactively addresses issues.

Observation can elucidate phenomena germane to healthcare research questions by adding unique insights. Careful selection and sampling are critical to rigor. Phenomena like taboo behaviors or rare events are difficult to capture. A thoughtful protocol can preempt Institutional Review Board concerns.

This novel guide provides a practical adaptation of traditional approaches to observation to meet contemporary healthcare research teams’ needs.

Graphical abstract

• • 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
• • Multidisciplinary teams, data collection tools and detailed protocols enhance rigor

1. Introduction

Health research studies increasingly include direct observation methods [ [1] , [2] , [3] , [4] , [5] ]. Observation provides unique information about human behavior related to healthcare processes, events, norms and social context. Behavior is difficult to study; it is often unconscious or susceptible to self-report biases. Interviews or surveys are limited to what participants share. Observation is particularly useful for understanding patients’, providers’ or other key communities’ experiences because it provides an “emic,” insider perspective and lends itself to topics like patient-centered care research [ 1 , 5 , 6 ]. This insider perspective allows researchers to understand end users’ experiences of a problem. For example, patients may be viewed as “non-compliant,” while observations can reveal daily lived experiences that impede adherence to recommended care [ [7] , [8] , [9] , [10] ]. Observation can examine the organization and structure of healthcare delivery in ways that are different from, and complementary to, methods like surveys, interviews, or database reviews. However, there is limited guidance for health researchers on how to use observation.

Observation has a long history in the social sciences, with participant observation as a defining feature of ethnography [ [11] , [12] , [13] ]. Observation in healthcare research differs from the social sciences. Traditional social science research may be conducted by a single individual, while healthcare research is often conducted by multidisciplinary teams. In social science studies, extended time in the field is expected [ 11 ]. In contrast, healthcare research timelines are often compressed and conducted contemporaneous with other work. Compared to social science research questions, healthcare studies are typically targeted with narrowly defined parameters.

These disciplinary differences may pose challenges for healthcare researchers interested in using observation. Given observation’s history in the social sciences there is a need to tailor observation to the healthcare context, with attention to the dynamics and needs of the research team. This paper provides contemporary healthcare research teams a practical, methodologically rigorous guide on when and how to conduct observation.

This article synthesizes the authors’ experiences conducting observation in social science and health services research studies, key literature and experiences teaching observation. The authors have diverse training in anthropology (GF, MM), systems engineering (BK) and psychology (MR). To develop this guide, we reflected on our own experiences, identified literature in our respective fields, found common considerations across these, and had consensus-reaching discussions. We compiled this information into a format initially delivered through courses, workshops, and conferences. In keeping with this pedagogical approach, the format below follows the linear process of study development.

Following the trajectory of a typical health research project, from study development through data collection, analysis and dissemination ( Fig. 1 ), we describe how to design and conduct observation in healthcare related settings. We conclude with data analysis, dissemination of findings, and other key guidance. Importantly, while illustrated as a linear process, many steps inform each other. For example, analysis and dissemination, can inform data collection.

Direct observation across a health research study.

3.1. Study development

3.1.1. study design and research questions.

In developing research using observation, the first step is determining if observation is appropriate. Observation is ideal for studies about naturally occurring behaviors, actions, or events. These include explorations of patient or provider behaviors, interactions, teamwork, clinical processes, or spatial arrangements. The phenomena must be feasible to collect. Sensitive or taboo topics like substance use or sexual practices are better suited to other approaches, like one-on-one interviews or anonymous surveys. Additionally, the phenomena must occur frequently enough to be captured. Trying to observe rare events requires considerable time while yielding little data. Early in the study design process, the scope and resources should be considered. The project budget and the timeline need to account for staffing, designing data collection tools, and pilot testing.

Research questions establish the study goals and inform the methods to accomplish them. In a study examining patients’ experiences of recovery from open heart surgery, the ethnographic study design included medical record data, in-depth interviews, surveys, and observations of patients in their homes, collected over three months following surgery [ 7 ]. By observing patients in their homes GF saw how the household shaped post-surgical diet and exercise. Table 1 provides additional examples of healthcare studies using observation, often as part of a larger, mixed-method design [ 14 , 15 ].

Example studies that use observation.

3.1.2. Data collection procedures

The phenomena to observe should be clearly defined. Research team discussions create a unified understanding of the phenomena, clarify what to observe and record, and ensure data collection consistency. This explication specifies what to look for during observation. For example, a team might operationalize the concept of patient-centered care into specific actions, like how the provider greets the patient. Further, additional nuances within broader domains (e.g., patient-centered care) could be identified while observations are ongoing. The team may identify unanticipated ways that providers enact patient-centered care (e.g., raising non-clinical, but relevant psychosocial topics- like vacations or hobbies- prior to gathering biomedical information). It is also important to look for negative instances, or behaviors that did not happen that should have, or surprising, unexpected findings. A surprise finding during observation was the impetus for further analysis examining how HIV providers think about their patients. While observing HIV care, a provider made an unexpected, judgmental comment about patients who seek pre-exposure prophylaxis (PrEP) to prevent HIV. This statement was documented in the fieldnotes (see 3.1.3 for a further description of fieldnotes) and later discussed with the team, leading to review of other study data and an eventual paper (see Fix et al 2018) [ 1 ]. Leaving room, both literally on the template and conceptually, can provide space for new, unexpected insights.

The sampling strategy outlines the frequency and duration of what is observed and recorded. It requires determining the unit of observation and the observation period. Units of observation are sometimes called “slices” of data. Ambady and Rosenthal [ 20 ] coined the term thin slices, using brief exposures of behavior (6s, 15s, and 30s) to predict teacher effectiveness. While thin slices are predominantly used in psychology, healthcare researchers can apply this concept by recording data for set blocks of time in a larger process, such as recording emergency department activity for the first 15 minutes of each hour.

The unit of observation can be a person (e.g., patient, provider), their behavior (e.g., smiling, eye rolling), an event (e.g., shift change) or interaction (e.g., clinical encounter). Using interactions as the unit of observation requires consideration for repeat observations of some individuals. For example, a fixed number of providers may be repeatedly observed with different patients.

Observation frequency will depend on the frequency of the phenomena. Enough data is needed for variation while also achieving “saturation,” a concept from qualitative methods, which means the point in data collection when no new information is obtained [ 21 ]. For quantitative studies, when examining the relationship between a direct observation measure (e.g., patient smiling) and an outcome (e.g., patient satisfaction), effect sizes from past research should dictate the number of interactions needed to achieve power to detect an effect. The duration of observation (the data slice) can be constrained using parameters as broad as a clinic workday, to distinct events like a clinical encounter.

Observation data can be collected on a continuous, rolling basis, or at predefined intervals. Continuous sampling is analogous to a motion picture—the recorded data mirrors the flow of information captured in a video [ 22 ]. Continuous observation is ideal for understanding what happens throughout an event. It is labor intensive and time-consuming and may result in a small number of observations, although each observation can yield considerable data. For example, a team may want to know about the patient-centeredness of patient-provider interactions. Continuous sampling of a clinical encounter could start when the patient arrives through when they leave, with detailed data collected about both the verbal and nonverbal communication. This could be considered an N of one observation but would yield substantial data. This information could be collected over a continuous day of encounters across several providers and patients, resulting in a considerable amount of data for a small group of people.

In contrast, instantaneous sampling can be conceptualized as snapshots, and is analogous to the thin slice methodology. Psychology research sometimes uses random intervals, while in healthcare research it may be preferable to use predetermined criteria or intervals [ 23 ]. Instantaneous sampling is economical and data collection can happen flexibly across a variety of individuals or times of day or weeks. Disadvantages include losing some of the context that is gained through continuous sampling.

3.1.3. Data collection tools

Data collection tools enable systematic observations, codifying what to observe and record. These tools vary from open-ended to highly structured, depending on the research question(s) and what is known a priori. We describe below three general tool categories—descriptive fieldnotes, semi-structured templates, and structured templates.

3.1.3.1. Descriptive fieldnotes

Descriptive fieldnotes, common in anthropology, are open-ended notes recorded with minimal a priori fields. Descriptive fieldnotes are ideal for research questions where less is known. An almost blank page is used to record the phenomena of interest. Key information such as date, time, location, people present and who recorded the information are useful for later analysis. These notes are jotted sequentially in real-time to maximize data collection, and are filled out and edited later for clarity and details. The flexible and open format facilitates the capture of unanticipated events or interactions.

Descriptive fieldnotes describe in detail what is observed (e.g., who is present, paraphrased statements), while leaving out interpretation. Analytic notes, that interpret what is being observed, can accompany the descriptive notes (e.g., the doctor is frowning and seems skeptical of what the patient is saying), but these analytic notes should be clearly marked as interpretation. One author (GF) demarcates interpretive portions of her fieldnotes using [closed brackets] to identify this portion of the fieldnote as distinct from the descriptive data. Interpretive notes should explain why the observer thinks this might be the case, using supporting data from the observation. Building on the example above, an accompanying interpretive note might say, “[the doctor raised their eyebrows, and does not seem to believe what the patient is saying, similar to what was observed in another encounter- see site 5 fieldnote). This information can be valuable during analysis to contextualize what was recorded and used in a later report or paper. Observation experience builds comfort and expertise with the open-ended, unstructured format.

3.1.3.2. Semi-structured templates

A semi-structured template comprises both open-ended and structured fields ( Fig. 2 ). It includes the same key information described above (i.e., date, time, etc.), then provides prompts for a priori concepts underlying the research questions, often derived from a theoretical model. These literature-based, theoretical concepts should be clearly defined and operationalized. For example, drawing from Street et al’s [ 24 ] framework for patient-centered communication, we can use their six functions (fostering the patient-clinician relationship, exchanging information, responding to emotions, managing uncertainty, making decisions, and enabling self-management) to develop categories for semi-structured coding a template. Like descriptive fieldnotes, the template also provides open-ended space for capturing contextual details about the a priori data recorded in the structured section.

Semi-Structured Observation Template.

3.1.3.3. Structured templates

A structured template in the form of a checklist or recording sheet captures specific, pre-determined phenomena. Structured templates are most useful when the phenomena are known. These templates are commonly used in psychology and engineering. Structured observations are more deductive and based on theoretical models or literature-based concepts. The template prompts the observer to record whether a phenomenon occurred, its frequency, and sometimes its duration or quality. See Keen [ 5 ] or Roter [ 25 ] for example structured templates for recording patient-centered care or patient-provider communication.

All templates should include key elements like the date, time and observer. Descriptive fieldnotes and semi-structured templates should be briefly filled out during the observation, and then written more thoroughly immediately afterwards. Setting aside time during data collection, such as a few hours at the end of each day, facilitates completion of this step. Recording information immediately, rather than weeks or months later, enhances data quality by minimizing recall bias. If written too much later, the recorder might fill in holes in their memory with inaccurate information. Further, small details, written while memories are fresh, may seem unremarkable but later provide critical insights.

For the semi-structured and structured templates, which contain prepopulated fields, there should be an accompanying “codebook” of definitions describing the parameters for each field. For example, building on the previous example using Street et al’s constructs, the code “responding to emotions” could identify instances where patients appear to be sad or worried and the provider responds to these emotions (also termed empathic opportunities and empathic responses) by eliciting, exploring, and validating the patients’ emotions [ 25 , 26 ]. This process operationally defines each concept and facilitates more reliable data capture. If space allows, the codebook can be included in the template and referenced during data collection. Codebooks should be updated through team discussion and as observations are piloted. Definitions from the codebook can be used in later reports and manuscripts.

3.2. Piloting

Given the real-world context within which observation data is collected, pilot-testing helps ensure that ideas work in practice. Piloting provides an opportunity to ensure the research plan works and reduce wasted resources. For example, piloting could reveal issues with the sampling plan (e.g., the phenomena do not happen frequently enough), staffing capacity (e.g., there are too many people to follow) or the codebook (e.g., few of the items specified in the data collection template are observed). Further, piloting gives the team a chance to systematize data collection and address issues before they interfere with the overall study integrity. This process guides what refinements need to be made to the data collection procedures. Piloting should be done at least once in a setting comparable to the intended setting.

3.3. Collecting data, analysis and dissemination

Healthcare studies are commonly conducted by interdisciplinary teams. The observation team should include at minimum two people, including someone with prior observation experience. Having more than one person collecting data increases capacity, distributes the workload and facilitates scheduling flexibility. Multiple observers complement each other’s perspectives and can provide diverse analytic insights. The observers should be engaged early in the research process. Having regular debriefing meetings during data collection ensures data quality and reliability in data collection. Adding key members of relevant communities to the team, such as patients or providers, can further enhance the relevance and help the research team think about the implications of the work.

Observational data collection often takes place in fast-paced clinical settings. For paper-based data collection, consolidating the materials on a clipboard and/or using colored papers or tabs, facilitates access. An electronic tablet to enter information directly bypasses the need for later, manual data entry.

Data analysis should be considered early in the research process. The analytic plan will be informed by both the principles of the epistemological tradition from which the overall study design is drawn and the research questions. Studies using observation are premised on a range of epistemological traditions. Analytical approaches, standards, and terminology differ between anthropologically informed qualitative observations recorded using descriptive fieldnotes versus structured, quantitative checklists premised on psychological or systems engineering principles. A full description of analysis is thus beyond the scope of this guide. Analytic strategies can be found in discipline-specific texts, such as Musante and DeWalt [ 27 ], anthropology; Suen and Ary [ 28 ], psychology; or Lopetegui et al [ 29 ], systems engineering. Regardless of discplinary tradition, analytic decisions should be made based on the study design, research question(s), and objective(s).

Dissemination is a key, final step of the research process. Observation data lends itself to a rich description of the phenomena of interest. In health research, this data is often part of a larger mixed methods study. The observation protocol should be described in a manuscript’s methods section; the results should report on what was observed. Similar to reporting of interview data, the observed data should include key descriptors germane to the research question, like actors, site number, or setting. See Fix et al [ 1 ] and McCullough et al [ 4 ] for examples on how to include semi-structured, qualitative observation data in a manuscript and Waisel et al [ 17 ] and Kuhn et al [ 19 ] for examples of reporting structured, quantitative data in a manuscript.

3.4. Institutional review boards

Healthcare Institutional Review Boards may be unfamiliar with observation. Being explicit about data collection can proactively address concerns. The protocol should detail which individuals will be observed, if and how they will be consented and what will and will not be recorded. Using a reference like the Health Insurance Portability and Accountability Act (HIPAA) identifiers (e.g., name, street address) can guide what identifiable information is collected. The protocol should also describe how the team will protect data, especially while in the field (e.g., “immediately after data collection, written informed consents will be taken to an office and locked in a filing cabinet”).

There are unique risks in studies using observation because data is collected in “the field.” Precautions attentive to these settings protect both participants and research team members. A detailed protocol should describe steps to address potential issues, including rare or distressing events, or what to do if a team member witnesses a clinical emergency or a participant discloses trauma. Additionally, team members may need to debrief after distressing experiences.

4. Discussion & conclusion

4.1. discussion.

The ability to improve healthcare is limited if real-world data are not taken into account. Observation methods can elucidate phenomena germane to healthcare’s most vexing problems. Considerable literature documents the discrepancy between what people report and their behavior [ [30] , [31] , [32] ]. Direct observation can provide important insights into human behavior. In their ethnographic evaluation of an HIV intervention, Evans and Lambert [ 31 ] found, “observation of actual intervention practices can reveal insights that may be hard for [participants] to articulate or difficult to pinpoint, and can highlight important points of divergence and convergence from intervention theory or planning documents.” Further, they saw ethnographic methods as a tool to understand “hidden” information in what they call “private contexts of practice.” While in Rich et al.’s work [ 32 ], asthmatic children were asked about exposure to smoking. Despite not reporting smoking in the home, videos recorded by the children—part of the study design—documented smokers outside their home. The use of observation can help explain research questions as diverse as patients’ health behaviors [ 7 , 10 , 32 ], healthcare delivery [ 3 , 4 ] or the outcomes of a clinical trial [ 9 , 33 ].

A common critique in healthcare research is that observing behavior will change behavior, a concept known as the Hawthorne Effect. Goodwin’s study [ 34 ], using direct observation of physician-patient interactions, explicitly examined this phenomena and found a limited effect. We authors have observed numerous instances of unexpected behavior of healthcare employees such as making disparaging comments about patients, eye rolling, or eating in sterile areas. Thus, those of us who conduct observation often say that if behavior change were as easy as observing people, we could simply place observers in problematic healthcare settings.

The descriptions above on how to use observation are applicable to fields like health services research and implementation and improvement sciences which have similarly adapted other social science approaches.[ [35] , [36] , [37] , [38] , [39] , [40] ] Notably, unlike the social sciences, many health researchers work in teams and thus this guide is written for team-based work. Yet, health researchers sometimes also conduct observations without support from a larger team. While this may be done because of resource constraints, it may raise concerns about the validity of the observations. First, social sciences have a long history of solo researchers collecting and analyzing data, yielding robust, rigorous findings [ 13 , [41] , [42] , [43] ]. Using strategies, such as those outlined above (i.e., writing detailed, descriptive fieldnotes immediately; keeping interpretations separate from the data; looking for negative cases) can enhance rigor. Further, constructs like validity are rooted in quantitative, positivist epistemologies and need to be adapted for naturalistic study designs, like those that include direct observation [ 44 ].

4.2. Innovation

Social science-informed research designs, such as those that include observation, are needed to tackle the dynamic, complex, “wicked problem” that impede high quality healthcare [ 45 ]. Thoughtful, rigorous use of observation tailored to the unique context of healthcare can provide important insights into healthcare delivery problems and ultimately improve healthcare.

Additionally, observation provides several ways to involve key communities, like patients or providers, as participants. Observing patient participants can provide information about healthcare processes or structures, and inform research about patient experiences of care or the extent of patient-centeredness. With the movement towards engaging end users in research, these individuals can contribute more meaningfully [ 46 , 47 ]. As team members, they can define the problem, inform what to observe, how to observe, help interpret data and disseminate findings.

4.3. Conclusion

Observation’s long history in the social sciences provides a robust body of work with strategies that can be inform healthcare research. Yet, traditional social science approaches, such as extended, independent fieldwork may be untenable in healthcare settings. Thus, adapting social science approaches can better meet healthcare researchers’ needs.

This paper provides an innovative, yet practical adaptation of social science approaches to observation that can be feasibly used by health researchers. Team meetings, developing data collection tools and protocols, and piloting, each enhance study quality. During development, teams should determine if observation is an appropriate method. If so, the team should then discuss what and how to collect the data, as described above. Piloting improves data collection procedures. While many aspects of observation can be tailored to health research, analysis is informed by epistemological traditions. Having clear steps for health researchers to follow can increase the rigor or credibility of observation.

Rigorous utilization of observation can enrich healthcare research by adding unique insights into complex problems. This guide provides a practical adaptation of traditional approaches to observation to meet healthcare researchers’ needs and transform healthcare delivery.

This work was supported by the US Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Health Services Research and Development. Dr. Fix is a VA HSR&D Career Development awardee at the Bedford VA (CDA 14-156). Drs. Fix, Kim and McCullough are employed at the Center for Healthcare Organization and Implementation Research, where Dr. Ruben was a postdoctoral fellow. The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Competing Interest

All authors declared no conflict of interests.

Acknowledgements

This work has been previously presented as workshops at the 2015 Veteran Affairs Health Services Research & Development / Quality Enhancement Research Initiative National Meeting (Philadelphia, PA) and the 2016 Academy Health Annual Research Meeting (Boston, MA). We would like to acknowledge Dr. Shihwe Wang for participating in the 2015 workshop; Dr. Adam Rose for encouragement and helpful comments; and the VA Anthropology Group for advancing the utilization of direct observation in the US Department of Veteran Affairs. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

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Statistics By Jim

Making statistics intuitive

What is an Observational Study: Definition & Examples

By Jim Frost 10 Comments

What is an Observational Study?

An observational study uses sample data to find correlations in situations where the researchers do not control the treatment, or independent variable, that relates to the primary research question. The definition of an observational study hinges on the notion that the researchers only observe subjects and do not assign them to the control and treatment groups. That’s the key difference between an observational study vs experiment. These studies are also known as quasi-experiments and correlational studies .

True experiments assign subject to the experimental groups where the researchers can manipulate the conditions. Unfortunately, random assignment is not always possible. For these cases, you can conduct an observational study.

In this post, learn about the types of observational studies, why they are susceptible to confounding variables, and how they compare to experiments. I’ll close this post by reviewing a published observational study about vitamin supplement usage.

Observational Study Definition

In an observational study, the researchers only observe the subjects and do not interfere or try to influence the outcomes. In other words, the researchers do not control the treatments or assign subjects to experimental groups. Instead, they observe and measure variables of interest and look for relationships between them. Usually, researchers conduct observational studies when it is difficult, impossible, or unethical to assign study participants to the experimental groups randomly. If you can’t randomly assign subjects to the treatment and control groups, then you observe the subjects in their self-selected states.

Observational Study vs Experiment

Randomized experiments provide better results than observational studies. Consequently, you should always use a randomized experiment whenever possible. However, if randomization is not possible, science should not come to a halt. After all, we still want to learn things, discover relationships, and make discoveries. For these cases, observational studies are a good alternative to a true experiment. Let’s compare the differences between an observational study vs. an experiment.

Random assignment in an experiment reduces systematic differences between experimental groups at the beginning of the study, which increases your confidence that the treatments caused any differences between groups you observe at the end of the study. In contrast, an observational study uses self-formed groups that can have pre-existing differences, which introduces the problem of confounding variables. More on that later!

In a randomized experiment, randomization tends to equalize confounders between groups and, thereby, prevents problems. In my post about random assignment , I describe that process as an elegant solution for confounding variables. You don’t need to measure or even know which variables are confounders, and randomization will still mitigate their effects. Additionally, you can use control variables in an experiment to keep the conditions as consistent as possible. For more detail about the differences, read Observational Study vs. Experiment .

If you’re looking for a middle ground choice between observational studies vs experiments, consider using a quasi-experimental design. These methods don’t require you to randomly assign participants to the experimental groups and still allow you to draw better causal conclusions about an intervention than an observational study. Learn more about Quasi-Experimental Design Overview & Examples .

Related posts : Experimental Design: Definition and Examples , Randomized Controlled Trials (RCTs) , and Control Groups in Experiments

Observational Study Examples

Consider using an observational study when random assignment for an experiment is problematic. This approach allows us to proceed and draw conclusions about effects even though we can’t control the independent variables. The following observational study examples will help you understand when and why to use them.

For example, if you’re studying how depression affects performance of an activity, it’s impossible to assign subjects to the depression and control group randomly. However, you can have subjects with and without depression perform the activity and compare the results in an observational study.

Or imagine trying to assign subjects to cigarette smoking and non-smoking groups randomly?! However, you can observe people in both groups and assess the differences in health outcomes in an observational study.

Suppose you’re studying a treatment for a disease. Ideally, you recruit a group of patients who all have the disease, and then randomly assign them to the treatment and control group. However, it’s unethical to withhold the treatment, which rules out a control group. Instead, you can compare patients who voluntarily do not use the medicine to those who do use it.

In all these observational study examples, the researchers do not assign subjects to the experimental groups. Instead, they observe people who are already in these groups and compare the outcomes. Hence, the scientists must use an observational study vs. an experiment.

Types of Observational Studies

The observational study definition states that researchers only observe the outcomes and do not manipulate or control factors . Despite this limitation, there various types of observational studies.

The following experimental designs are three standard types of observational studies.

• Cohort Study : A longitudinal observational study that follows a group who share a defining characteristic. These studies frequently determine whether exposure to risk factor affects an outcome over time.
• Case-Control Study : A retrospective observational study that compares two existing groups—the case group with the condition and the control group without it. Researchers compare the groups looking for potential risk factors for the condition.
• Cross-Sectional Study : Takes a snapshot of a moment in time so researchers can understand the prevalence of outcomes and correlations between variables at that instant.

Qualitative research studies are usually observational in nature, but they collect non-numeric data and do not perform statistical analyses.

Retrospective studies must be observational.

Later in this post, we’ll closely examine a quantitative observational study example that assesses vitamin supplement consumption and how that affects the risk of death. It’s possible to use random assignment to place each subject in either the vitamin treatment group or the control group. However, the study assesses vitamin consumption in 40,000 participants over the course of two decades. It’s unrealistic to enforce the treatment and control protocols over such a long time for so many people!

Drawbacks of Observational Studies

While observational studies get around the inability to assign subjects randomly, this approach opens the door to the problem of confounding variables. A confounding variable, or confounder, correlates with both the experimental groups and the outcome variable. Because there is no random process that equalizes the experimental groups in an observational study, confounding variables can systematically differ between groups when the study begins. Consequently, confounders can be the actual cause for differences in outcome at the end of the study rather than the primary variable of interest. If an experiment does not account for confounding variables, confounders can bias the results and create spurious correlations .

Performing an observational study can decrease the internal validity of your study but increase the external validity. Learn more about internal and external validity .

Let’s see how this works. Imagine an observational study that compares people who take vitamin supplements to those who do not. People who use vitamin supplements voluntarily will tend to have other healthy habits that exist at the beginning of the study. These healthy habits are confounding variables. If there are differences in health outcomes at the end of the study, it’s possible that these healthy habits actually caused them rather than the vitamin consumption itself. In short, confounders confuse the results because they provide alternative explanations for the differences.

Despite the limitations, an observational study can be a valid approach. However, you must ensure that your research accounts for confounding variables. Fortunately, there are several methods for doing just that!

Learn more about Correlation vs. Causation: Understanding the Differences .

Accounting for Confounding Variables in an Observational Study

Because observational studies don’t use random assignment, confounders can be distributed disproportionately between conditions. Consequently, experimenters need to know which variables are confounders, measure them, and then use a method to account for them. It involves more work, and the additional measurements can increase the costs. And there’s always a chance that researchers will fail to identify a confounder, not account for it, and produce biased results. However, if randomization isn’t an option, then you probably need to consider an observational study.

Trait matching and statistically controlling confounders using multivariate procedures are two standard approaches for incorporating confounding variables.

Related post : Causation versus Correlation in Statistics

Matching in Observational Studies

Matching is a technique that involves selecting study participants with similar characteristics outside the variable of interest or treatment. Rather than using random assignment to equalize the experimental groups, the experimenters do it by matching observable characteristics. For every participant in the treatment group, the researchers find a participant with comparable traits to include in the control group. Matching subjects facilitates valid comparisons between those groups. The researchers use subject-area knowledge to identify characteristics that are critical to match.

For example, a vitamin supplement study using matching will select subjects who have similar health-related habits and attributes. The goal is that vitamin consumption will be the primary difference between the groups, which helps you attribute differences in health outcomes to vitamin consumption. However, the researchers are still observing participants who decide whether they consume supplements.

Matching has some drawbacks. The experimenters might not be aware of all the relevant characteristics they need to match. In other words, the groups might be different in an essential aspect that the researchers don’t recognize. For example, in the hypothetical vitamin study, there might be a healthy habit or attribute that affects the outcome that the researchers don’t measure and match. These unmatched characteristics might cause the observed differences in outcomes rather than vitamin consumption.

Learn more about Matched Pairs Design: Uses & Examples .

Using Multiple Regression in Observational Studies

Random assignment and matching use different methods to equalize the experimental groups in an observational study. However, statistical techniques, such as multiple regression analysis , don’t try to equalize the groups but instead use a model that accounts for confounding variables. These studies statistically control for confounding variables.

In multiple regression analysis, including a variable in the model holds it constant while you vary the variable/treatment of interest. For information about this property, read my post When Should I Use Regression Analysis?

As with matching, the challenge is to identify, measure, and include all confounders in the regression model. Failure to include a confounding variable in a regression model can cause omitted variable bias to distort your results.

Next, we’ll look at a published observational study that uses multiple regression to account for confounding variables.

Related post : Independent and Dependent Variables in a Regression Model

Vitamin Supplement Observational Study Example

Murso et al. (2011)* use a longitudinal observational study that ran 22 years to assess differences in death rates for subjects who used vitamin supplements regularly compared to those who did not use them. This study used surveys to record the characteristics of approximately 40,000 participants. The surveys asked questions about potential confounding variables such as demographic information, food intake, health details, physical activity, and, of course, supplement intake.

Because this is an observational study, the subjects decided for themselves whether they were taking vitamin supplements. Consequently, it’s safe to assume that supplement users and non-users might be different in other ways. From their article, the researchers found the following pre-existing differences between the two groups:

Supplement users had a lower prevalence of diabetes mellitus, high blood pressure, and smoking status; a lower BMI and waist to hip ratio, and were less likely to live on a farm. Supplement users had a higher educational level, were more physically active and were more likely to use estrogen replacement therapy. Also, supplement users were more likely to have a lower intake of energy, total fat, and monounsaturated fatty acids, saturated fatty acids and to have a higher intake of protein, carbohydrates, polyunsaturated fatty acids, alcohol, whole grain products, fruits, and vegetables.

Whew! That’s a long list of differences! Supplement users were different from non-users in a multitude of ways that are likely to affect their risk of dying. The researchers must account for these confounding variables when they compare supplement users to non-users. If they do not, their results can be biased.

This example illustrates a key difference between an observational study vs experiment. In a randomized experiment, the randomization would have equalized the characteristics of those the researchers assigned to the treatment and control groups. Instead, the study works with self-sorted groups that have numerous pre-existing differences!

Using Multiple Regression to Statistically Control for Confounders

To account for these initial differences in the vitamin supplement observational study, the researchers use regression analysis and include the confounding variables in the model.

The researchers present three regression models. The simplest model accounts only for age and caloric intake. Next, are two models that include additional confounding variables beyond age and calories. The first model adds various demographic information and seven health measures. The second model includes everything in the previous model and adds several more specific dietary intake measures. Using statistical significance as a guide for specifying the correct regression model , the researchers present the model with the most variables as the basis for their final results.

It’s instructive to compare the raw results and the final regression results.

Raw results

The raw differences in death risks for consumers of folic acid, vitamin B6, magnesium, zinc, copper, and multivitamins are NOT statistically significant. However, the raw results show a significant reduction in the death risk for users of B complex, C, calcium, D, and E.

However, those are the raw results for the observational study, and they do not control for the long list of differences between the groups that exist at the beginning of the study. After using the regression model to control for the confounding variables statistically, the results change dramatically.

Adjusted results

Of the 15 supplements that the study tracked in the observational study, researchers found consuming seven of these supplements were linked to a statistically significant INCREASE in death risk ( p-value < 0.05): multivitamins (increase in death risk 2.4%), vitamin B6 (4.1%), iron (3.9%), folic acid (5.9%), zinc (3.0%), magnesium (3.6%), and copper (18.0%). Only calcium was associated with a statistically significant reduction in death risk of 3.8%.

In short, the raw results suggest that those who consume supplements either have the same or lower death risks than non-consumers. However, these results do not account for the multitude of healthier habits and attributes in the group that uses supplements.

In fact, these confounders seem to produce most of the apparent benefits in the raw results because, after you statistically control the effects of these confounding variables, the results worsen for those who consume vitamin supplements. The adjusted results indicate that most vitamin supplements actually increase your death risk!

This research illustrates the differences between an observational study vs experiment. Namely how the pre-existing differences between the groups allow confounders to bias the raw results, making the vitamin consumption outcomes look better than they really are.

In conclusion, if you can’t randomly assign subjects to the experimental groups, an observational study might be right for you. However, be aware that you’ll need to identify, measure, and account for confounding variables in your experimental design.

Jaakko Mursu, PhD; Kim Robien, PhD; Lisa J. Harnack, DrPH, MPH; Kyong Park, PhD; David R. Jacobs Jr, PhD; Dietary Supplements and Mortality Rate in Older Women: The Iowa Women’s Health Study ; Arch Intern Med . 2011;171(18):1625-1633.

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Reader Interactions

December 30, 2023 at 5:05 am

I see, but our professor required us to indicate what year it was put into the article. May you tell me what year was this published originally? <3

December 30, 2023 at 3:40 pm

December 29, 2023 at 10:46 am

Hi, may I use your article as a citation for my thesis paper? If so, may I know the exact date you published this article? Thank you!

December 29, 2023 at 2:13 pm

Definitely feel free to cite this article! 🙂

When citing online resources, you typically use an “Accessed” date rather than a publication date because online content can change over time. For more information, read Purdue University’s Citing Electronic Resources .

November 18, 2021 at 10:09 pm

Love your content and has been very helpful!

Can you please advise the question below using an observational data set:

I have three years of observational GPS data collected on athletes (2019/2020/2021). Approximately 14-15 athletes per game and 8 games per year. The GPS software outputs 50+ variables for each athlete in each game, which we have narrowed down to 16 variables of interest from previous research.

2 factors 1) Period (first half, second half, and whole game), 2) Position (two groups with three subgroups in each – forwards (group 1, group 2, group 3) and backs (group 1, group 2, group 3))

16 variables of interest – all numerical and scale variables. Some of these are correlated, but not all.

My understanding is that I can use a oneway ANOVA for each year on it’s own, using one factor at a time (period or position) with post hoc analysis. This is fine, if data meets assumptions and is normally distributed. This tells me any significant interactions between variables of interest with chosen factor. For example, with position factor, do forwards in group 1 cover more total running distance than forwards in group 2 or backs in group 3.

However, I want to go deeper with my analysis. If I want to see if forwards in group 1 cover more total running distance in period 1 than backs in group 3 in the same period, I need an additional factor and the oneway ANOVA does not suit. Therefore I can use a twoway ANOVA instead of 2 oneway ANOVA’s and that solves the issue, correct?

This is complicated further by looking to compare 2019 to 2020 or 2019 to 2021 to identify changes over time, which would introduce a third independent variable.

I believe this would require a threeway ANOVA for this observational data set. 3 factors – Position, Period, and Year?

Are there any issues or concerns you see at first glance?

I appreciate your time and consideration.

April 12, 2021 at 2:02 pm

Could an observational study use a correlational design.

e.g. measuring effects of two variables on happiness, if you’re not intervening.

April 13, 2021 at 12:14 am

Typically, with observational studies, you’d want to include potential confounders, etc. Consequently, I’ve seen regression analysis used more frequently for observational studies to be able to control for other things because you’re not using randomization. You could use correlation to observe the relationship. However, you wouldn’t be controlling for potential confounding variables. Just something to consider.

April 11, 2021 at 1:28 pm

Hi, If I am to administer moderate doses of coffee for a hypothetical experiment, does it raise ethical concerns? Can I use random assignment for it?

April 11, 2021 at 4:06 pm

I don’t see any inherent ethical problems here as long as you describe the participant’s experience in the experiment including the coffee consumption. They key with human subjects is “informed consent.” They’re agreeing to participate based on a full and accurate understanding of what participation involves. Additionally, you as a researcher, understand the process well enough to be able to ensure their safety.

In your study, as long as subject know they’ll be drinking coffee and agree to that, I don’t see a problem. It’s a proven safe substance for the vast majority of people. If potential subjects are aware of the need to consume coffee, they can determine whether they are ok with that before agreeing to participate.

June 17, 2019 at 4:51 am

Really great article which explains observational and experimental study very well. It presents broad picture with the case study which helped a lot in understanding the core concepts. Thanks

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Best Observation Essay Topics for Students

Typically, you can use these observation essay topics when your professor decides to put your empirical skills to the test. Choosing a problem you understand is crucial in such a situation, as it should project your point of view connected to sufficient facts intelligible to the reader. It may be quite a challenge for students because it's tricky to write an astounding essay with those goals in mind. That's why choosing a topic subject requires careful evaluation, sound judgment, and a lot of effort above all. You should keep it front and center when it comes to this assignment.

A better example will serve you right. Imagine that you are in charge of a warehouse, in a company where they store goods like apples, and you are responsible for all activities that happen in the warehouse daily. At the end of your shift, you have to report every little thing you observed or saw happening around you in the warehouse during the day.

Furthermore, it is essential to learn how to write or jot down the ideas because some people have trouble meeting the requirements and deadlines or just recording a sighting. Say, a group of students observed a series of events during their practice session. Afterward, they must write a report or an observation essay about what they saw step by step.

The majority of students would falter at this task, unsure how to proceed. First, there is nothing wrong with planning, but be careful and don't overdo it. Sure, you have to plot your assignment, its structure at the least, to make it work. But, is reproducing every single detail in your essay really needed? Writing an observation essay ought to be more or less like composing a short story: spontaneous, self-generated, and growing with ease. So, don't overthink it. Come up with a simple outline and then allow your thoughts to take their course.

Let us give you some more structure tips!

• Be watchful during the first stage, the observations, to examine how everything ticks. Note down all the details you deem necessary to include in your writing. Organize your notes to make it easier to navigate them later.
• Start the essay with an introduction, the first paragraph. Describe why you selected the subject or topic, what you managed to observe, and where exactly it happened. Make sure to place your thesis statement at the end of the introduction paragraph.
• Write the body of the observation essay, where all the main points and ideas are explained clearly. You should arrange the previously jotted notes in proper order. Everything narrated should be in the present and not the past tense. All the data must be detailed precisely so that the audience feel as though they were present at the scene where the event happened.
• Summarise what you saw at the end. Give your opinion about your observation by explaining everything and connect all the dots for the reader.
• Go through your essay, check and correct your spellings, grammar, and punctuation, and make sure you convey the information in the right tense. The narrative should be in a linear progression, going from the strong points to the weak ones.

List of Topic Examples for an Observation Essay

To show the ability to be observant, the student needs to pick a good topic. You are supposed to have a point of view relevant to the subject you have selected, be it scenarios, pets, places, or trips. However, below are some examples of observation topics you may find helpful:

• That time I bumped into my favorite artist.
• Describe the treatment you received on your first day at high school.
• What was the most dramatic scene you ever observed?
• The impact of social media like Twitter, Snapchat, and Instagram you have witnessed.
• Describe your first time at the zoo.
• How do people behave at science fairs?
• Why is tolerance essential in our society?
• What are the advantages of living in harmony, how to make it possible?
• Explain some of the superstitious beliefs and how they affect people's lives.
• What is the hardest challenge you have been through that took you a lot of effort to handle?
• Write about a city you have been to and will never forget the visit.
• The road accident that almost took the life of my best friend.
• A novel you enjoy reading over and over again without getting bored of it.
• Your first time at the beach during the summer vacation.
• The best gift you ever received from your parents or friends at Christmas.
• The longest road trip with your family.
• My first ever rock concert.
• The first time I drove a car.
• The day I will never forget.
• The best summer camp I've ever been to.

These are a few observation paper ideas among many others you can use to master your writing skills. Sometimes, students still find it hard to write an essay and prefer our professional writers to do it for them. Feel free to contact us at any time!

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what are some interesting ideas for an observational study?

i need to do an observational study for uni and write a scientific report about it. our coordinator proposed some ideas such as, "do men or women study more" or "what are the differences in non-verbal behavior between men and women during public speaking". these topics don't really peak my interest and there's already some research on them so i'd prefer to find my own idea insetad.

as this is an observational experiment, i can only observe behavior, no questionnaires/interviews are allowed. basically the subjects can't be aware they are part of an experiment. however, we are allowed to create setups, meaning i could throw myself on the floor in public and observe how long it takes for people to come and help me up lol. or i can have no setup and just go observe the behavior of children on a playground, without intervening.

i would really like to have an original topic that doesn't already have extensive research on it. if you guys have any ideas, i'd appreciate it a lot! ofc keep in mind, they have to be realistic and ethical.

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Two examples of on-site observational studies with older persons

In some cases, it is necessary to bring your research to your participants. For example, you might want to observe people in a natural setting: at home , in a shop, in the classroom, or in the office.

Another case where on-site research would be beneficial  is when your participants are experiencing health issues, preventing them from travelling to your lab. Conducting your research on location enables you to study people that are otherwise difficult to reach.

These factors should be taken into consideration when choosing the location for your research, especially when conducting studies with older age groups.

Practical aspects of on-site observational studies

If you want to conduct your study in another location, there are some practical aspects to think about. For example, you have to set the right lighting conditions and camera position. You also have to make sure that you capture voices and other sounds accurately.

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Observational research examples

The first study we describe in this blog post explores how familiarity influences the use of electronic devices in different age groups. In the second study, researchers compared different methods of observing pain expressions in dementia patients.

Example 1: Familiarity and intuitive use

Improving products for older age groups.

It is generally assumed that older adults have difficulty using modern electronic devices, such as mobile telephones or computers. Because this age group is growing in most countries, changing products and processes to adapt to their needs is increasingly more important.  

Improving technological experiences in older age groups supports their social inclusion, productivity, and their independence. To gain more insight in the learning processes involved in using electronic devices, Lawry and his colleagues compared levels of familiarity between age groups.

Comparing familiarity between older and younger adults

Familiarity describes the way an action is recognized or understood, based on prior experience and knowledge. It develops from a general level of knowledge, to knowledge that is based on experience, and finally to effortless and unconscious action.

The researchers identified several behaviors that suggest familiarity with an action. These include anticipation and planning, relative speed, verbalization, and task attention. They recorded these behaviors during a verbal report of how participants thought they would perform a task, as well as during the performance of the task itself.

Specifically, participants were asked to use a product they were familiar with and a product that was new to them.  The study included 32 participants with different educational backgrounds, who were divided into different age groups (18-44, 45-59, 60-74, and 75+).

Observing familiarity at home

What better place to study familiarity than in the familiar place of home? By conducting part of their research in the participants’ homes, researcher Lawry and his team created a more realistic learning environment, had easy access to familiar products, and were able to recruit older participants more easily.

They coded verbal and visual data from both studies using The Observer XT , and used this software to calculate inter-rater reliability as well. Results showed significant differences in familiarity between age groups, concerning both known and new products.

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Differences between younger and older adults

When using their own products, the youngest adult group showed more familiar behaviors than the two oldest groups. These younger participants also showed more familiarity when using a new product, compared to all other age groups.

Importantly, these results indicate that intuitive use of new products declines as early as during middle age. Therefore, the researchers advise product designers to incorporate more features that are based on prior knowledge of both middle-aged and older adults.

Example 2: Pain expressions in dementia

Observing pain expressions.

In dementia, severe cognitive impairment can lead to an inability to communicate verbally. When these patients can’t tell their caregivers about the pain they feel, an accurate assessment of pain expressions becomes essential.

Browne and her colleagues examined how the angle of observation influences this assessment, both in trained and untrained observers. It is widely assumed that a front view provides the most information on pain. However, caregivers also often observe patients from the side.

Not only can this information be used to improve human observations, but it can also support the development of computer vision systems, further improving care for people with dementia.

On-site observational study

The researchers included 102 adults over the age of 65 in their study, with and without dementia.

Video recordings were made from both the front and profile of their faces, during a physiotherapy examination and a baseline period. Observers used this video data to assess pain expressions with two different coding systems.

They made their observations in long-term care facilities and an outpatient physiotherapy clinic. This approach provided opportunities to observe participants in their beds, as well as during their treatments.

When analyzing their data, Browne and her colleagues used The Observer XT to code the video data and calculate reliability between raters.

Benefits of a profile view

Both trained and untrained observers were able to discriminate between pain and pain-free situations. When comparing assessments between these observers, results showed that undergraduate students relied less on specific pain cues when making their observations.

During physiotherapy, the students also rated pain intensity higher and more accurately when viewing patients’ profiles. This suggests that the assessments of less experienced observers could improve when including a profile view.

Observer accuracy may also benefit from the use of computerized systems, particularly when viewing patients from the front.

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• Lawry, S.; Popovic, V.; Blackler, A.; Thompson, H. (2019). Age, familiarity, and intuitive use: an empirical investigation. Applied Ergonomics , 74 , 74-84.
• Browne, E.; Hadjistavropoulos, T.; Prkachin, K.; Ashraf, A.; Taati, B. (2019). Pain expressions in dementia: validity of observers’ pain judgments as a function of angle of observation. Journal of Nonverbal Behavior , https://doi.org/10.1007/s10919-019-00303-4.

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• 15 Great Observation Essay Topic Ideas You Should Not Miss

15 Observation Essay Topics & Tips Used to Write More Brilliant Papers

“Nothing has such power to broaden the mind as the ability to investigate systematically and all that comes under thy observation in life.” Marcus Aurelius

Every person faces various life situations when it is important to acquire information from a primary source to answer specific questions. Grab an observation essay example to see how experts arrange such information. Fact, observation, and inference are three words students should memorize. Writing a good observation essay makes a movie director out of the writer: he/she is focused on describing a particular experience using five senses:

Do you want your essay to make an imprint in the reader’s memory/leave an unforgettable impression? Buy an essay paper online from one of the best writing companies in the US!

What Is an Observation Essay and Its Purpose

Observation essay example of outline.

Read our unique guideline to have an observation essay example of outline!

You should face the problem discussed in your paper at least once in your life. To create a powerful observation essay, the author has to be a topic guru: describe what you survived or what inspires you.

Example: you decide to cover the topic of how safe it is to fly on a plane. It is not enough to take statistics and say it is the safest type of transport in the world without being the passenger. A good writer must share personal experience in order to support this claim. Attend a new restaurant before writing a review. Watch the latest movie before criticizing it in your work.

The planned experience involves taking notes, so carry a blank sheet of paper or mobile phone everywhere to write a part of what you wish to share. Leave the details for your first observation essay draft. Describe the entire process: from entering the restaurant and making an order to accepting the bill from the waiter. Conclude your impressions in the paper’s draft. Select several criteria to put a specific grade: quality of service, a variety of food, the location of the table, etc.

Each time your personal opinion changes (e.g., you order a different dish), write down these modifications. Put the events in a chronological order not to get confused. Ask your friends about the same restaurant to have a fuller picture before concluding.

Do not forget to obtain rights reserved once you’re done so that no one steals your words.

Write an Outline

To have a proper, logical paper structure, it is important to come up with an outline. Every time you get stuck, have a look at your observation essay plan to arrange the thoughts. You may change your final draft, but you must stick to the prepared outline. If your teacher requires, make a separate page with a detailed outline.

Do not hesitate to contact professional writing services in case you have problems with writing an outline or any other page.

1. Introduction

Wonder how to start off an essay ? Try to provide the reading audience with the unique opportunity to familiarize them with the described event/experience. Start with creating a sound hook sentence to catch your reader’s eyes. Share some background information to let the readers know why you have chosen the specific observation essay topics. Example: you discuss the political elections campaign; tell several words about the candidates and the general mood of the event. Write your thesis statement at the end of the paragraph. It will be the essay’s fundament.

        How to start an observation essay

• shocking statistics
• interesting or unknown fact
• provocative question
• an anecdote
• a relevant quote. Avoid using trivial quotes. If you choose this option, use up-to-date ones, said by successful people of at least 20-21 century
• real- life example. This option usually works well. We recommend to use it to quotes..

2. Three-Paragraph Body

An observational essay has a body like any other type of academic assignment: research paper, article review, book report , etc. Teachers recommend developing a three-paragraph body with three powerful, supporting arguments. Arrange the notes according to your paper’s outline; add more details. Remember:

“Often it is tiny fragments which either make a picture convincing or incidental." Simone Bingemer

3. Concluding

Let's find out how to summarize an article . It is crucial to prevent your last paragraph from being wordy. Write a summary of the main points (arguments), restate your thesis sentence, and finish your paper with a call-to-action or another technique applied to leave powerful impressions. You may end with a rhetorical action, for example. Do not forget about the paper’s last page! The last page of an observation essay must contain a full bibliography list (list of references) to stress the author respects works with all rights reserved.

Proofread & Edit!

Want someone to check your final essay page by page? Place an order with the experienced online writing service, which serves college students around the English-speaking world!

Once you are done with your observation essay, do not hurry to submit your paper - there are several factors to check on every page:

• Spelling & Punctuation

Check whether the paper’s formatting corresponds to the instructor’s requirements; scan the final draft to see if it is 100% unique.

15 Most Effective Observation Essay Topics

Here is the list of observation essay topics to choose from:

• Thoughts on body piercing and tattoo
• Is tolerance important?
• Which video game may result in death?
• Significance of freedom and independence (Look at American Dream essay .)
• Meaning of money in modern world
• Sports develop leadership
• How I met my favorite movie star
• Is it dangerous to fly on the planes?
• Which book is worth reading at any age?
• New restaurant next-door
• The perfect birthday/wedding gift
• How must the word “honesty” be defined in dictionaries?
• Music as a great healing therapy
• How I personally became successful after writing the first page of my short story
• The qualities of true leaders based on people I met in my life

Type the  essay title you like in Google search field to find a good observation essay example to use in your work.

Get Several Good Observation Essay Writing Tips

• Stay concise on the personal impression . Remember: the main goal of your personal paper is to ensure the reader’s experience will be enriched with your impressions.
• Get a notebook or mobile phone writing app to jot down every detail regarding your personal experience. A written word is more powerful than the one said before.
• Do not overload your observation essay with too many words ; try to avoid wordiness by ignoring transitional & introductory words (try to limit their usage). Structure your thesis statement clearly by selecting only the most important words on the chosen topic.
• Apply several examples related to your topic by describing several situations you faced during the entire life in details. It helps the readers to get a wider picture as well as share your personal experience.
• An observation essay has a lot of common features with the descriptive narrative. Studying descriptive writing will come in handy. Play with five human senses. Make sure every page of your paper makes the reader taste, hear, smell, see, and even touch your topic.
• No matter what place or subject you describe, try to remain objective in order to make the readers trust you .
• Do not forget to insert quotes from the reliable primary sources . Mention all works with rights reserved on the last page called Bibliography.

Remember: it is necessary to share lessons learned in order to highlight the importance of your selected topic. You can find excellent observation essay examples online. If you feel your observation essay lacks something, or you want a professional writer to proofread & edit your paper, feel free to order online academic assistance from one of the most credible companies.

Enrich your outlook by getting involved in something completely new. Share your personal experience in your own words!

More than 80% of students share they understand the topic better with the help of examples. Teachers who realize the power of visualization in learning try to involve images/videos in their lessons to explain the material in-depth. They may assign an illustration essay to teach this trick to their s...

Informative essay writing is an art that every student needs to master. In order to graduate from any educational establishment, one has to accomplish a lot of writing assignments successfully. Thus, essay writing skills are of utmost importance when it comes to student’s academic performance and gr...

Descriptive essay is one of the most popular types of academic writing for college, high school, and middle school students. The goal of writing a descriptive essay is to break down a certain thing, event, person, or phenomenon and provide its detailed description. A descriptive essay is a short pap...

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to organize & manage your digital files & messages. Very soon, Dokkio will support Outlook as well as One Drive. Check it out today! to the workspace. Already have an account? !   last edited by 11 years, 5 months ago   Library observation: Do men or women study more in the library: AM VS PM. A variation – are people more likely to study alone or in   groups? Does it vary by gender?   Gym Observation: Do men or women go to the gym more often: AM VS PM.   To help or not help based on appearance (Did study AM vs PM and on and off campus)   Would you pick up a quarter or a condom? Men vs Woman- AM vs PM   Elevator Study- Facing wrong way in an elevator and seeing how people react. (On campus vs off campus) Vulgar, sexist speech – see how people respond?   Are men or women more frequently late to class? In the AM lecture or PM lecture?   Carrying a baby doll on and off campus, acting as though it is real and observing reactions   Stand outside and look up (stare at the roof, as though you are watching something carefully) – how many other people stop and look up?  How long do they stare until they move on?   If you cut in line, does the person behind you speak up? Are men or women more likely to say something?   Males dressing in clothing that is more feminine / females dressing in clothes that are more masculine   Dress up in a Santa suit and offer free hugs – what do people do?   Girl/guy dropping books – who offers to help them?   Take food off of people’s plates – see how they react.   Sit down with someone that is sitting alone.   Take someone’s Starbucks order.       Are men or women more likely to say thank you when a male or female opens the door for them? At work/school Depending on clothing   Wearing shoes on campus – male / female; clothing being worn   Eating dinner alone – or with an imaginary friend. How do people respond?   Shopping out of someone else’s grocery cart at HEB or WalMart – how do people respond/react? Insert links to other pages or uploaded files. Loading... To turn text into a link, highlight the text, then click on a page or file from the list above. Comments ( 0 ) You don't have permission to comment on this page. PBworks / Help Terms of use / Privacy policy / GDPR About this workspace Contact the owner / RSS feed / This workspace is public Join this workspace Already have an account? Log in ! Student Resources CASA Writing Center Fall 2014 - English 1301.415 (click here) Homework assignments Major Assignments  Archived Courses Recent Activity The Originator of Observational Learning: a Scholar’s Perspective This essay is about Albert Bandura’s contributions to the concept of observational learning in psychology and education. It discusses his famous Bobo doll experiments which demonstrated that individuals especially children learn behaviors by observing others. Bandura’s work challenged behaviorist views emphasizing cognitive processes in learning. His theory has practical applications in education and has influenced fields such as social learning theory cognitive psychology and behavioral therapy. Bandura’s integrative approach has significantly impacted modern psychology and educational practices. How it works Observant studies integral concept despite psychology and teaching spins his roots despite one opens work Albert bandura. Bandura famous psychology whose research has perceptibly influenced understanding human relation offered a theory observant studies in mid-20th century. Research bandura in observant studies began from his bobo experiments celebrate a doll conducted in beginning 1960 – ?. These experiments showed that types private person children study novice relation looks after other without a direct reinforcement. This concept contested behaviorist prevailing concept that studies in the type of exception manages direct experience and reinforcement. Work bandura distinguished a role cognitive processes in studies does an accent on a seriousness attention blocks up a weir printing-down and motive in enseigne observant process. In difference from different early behaviorists that concentrated he to unit on creation terms and theories reinforcement bandura united cognitive and dynamic access in his theory observant studies. His research opened out he after laboratories settlements to investigate how observant studies execute he in everyday life brings up a relation terms and acquisition habits social. Holding bandura to observant studies fished out he after theoretical skeletons. He contested for an appendix his espials in educational settlements offers that pedagogics was able to increase studies results assures examples for an imitation and positive possibilities for observant studies. This pragmatic application distinguished an appropriateness work bandura not only in psychology and and in educational psychology and instructional design. Moreover Bandura’s theory of observational learning has had profound implications in fields such as social learning theory cognitive psychology and behavioral therapy. It influenced subsequent research on imitation modeling and the social transmission of behavior contributing to a more comprehensive understanding of how individuals acquire new behaviors through observation and modeling. In conclusion Albert Bandura stands as the seminal figure who proposed observational learning revolutionizing the understanding of how individuals learn from others in their social environment. His integrative approach blending cognitive and behavioral principles has shaped modern psychology and educational practices. Bandura’s legacy continues to inspire research and applications in fields ranging from psychology to education demonstrating the enduring impact of his contributions to the study of human behavior and learning. This essay provides a comprehensive overview of Bandura’s seminal contributions to observational learning highlighting his theoretical insights experimental methods and practical implications. It avoids overly formal language to maintain readability while ensuring accuracy and depth in discussing Bandura’s scholarly impact. Cite this page The Originator of Observational Learning: A Scholar's Perspective. (2024, Jul 06). Retrieved from https://papersowl.com/examples/the-originator-of-observational-learning-a-scholars-perspective/ "The Originator of Observational Learning: A Scholar's Perspective." PapersOwl.com , 6 Jul 2024, https://papersowl.com/examples/the-originator-of-observational-learning-a-scholars-perspective/ PapersOwl.com. (2024). The Originator of Observational Learning: A Scholar's Perspective . [Online]. Available at: https://papersowl.com/examples/the-originator-of-observational-learning-a-scholars-perspective/ [Accessed: 7 Jul. 2024] "The Originator of Observational Learning: A Scholar's Perspective." PapersOwl.com, Jul 06, 2024. Accessed July 7, 2024. https://papersowl.com/examples/the-originator-of-observational-learning-a-scholars-perspective/ "The Originator of Observational Learning: A Scholar's Perspective," PapersOwl.com , 06-Jul-2024. [Online]. Available: https://papersowl.com/examples/the-originator-of-observational-learning-a-scholars-perspective/. [Accessed: 7-Jul-2024] PapersOwl.com. (2024). The Originator of Observational Learning: A Scholar's Perspective . [Online]. Available at: https://papersowl.com/examples/the-originator-of-observational-learning-a-scholars-perspective/ [Accessed: 7-Jul-2024] Don't let plagiarism ruin your grade Hire a writer to get a unique paper crafted to your needs. Our writers will help you fix any mistakes and get an A+! Please check your inbox. You can order an original essay written according to your instructions. Trusted by over 1 million students worldwide 1. Tell Us Your Requirements 2. Pick your perfect writer 3. Get Your Paper and Pay Hi! I'm Amy, your personal assistant! Don't know where to start? Give me your paper requirements and I connect you to an academic expert. short deadlines 100% Plagiarism-Free Certified writers Have a language expert improve your writing Run a free plagiarism check in 10 minutes, generate accurate citations for free. Knowledge Base Methodology What Is Qualitative Observation? | Definition & Examples What Is Qualitative Observation? | Definition & Examples Published on March 18, 2023 by Tegan George . Revised on June 22, 2023. 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. Qualitative observations can be done using various methods, including direct observation, interviews , focus groups , or case studies . They can provide rich and detailed information about the behavior, attitudes, perceptions, and experiences of individuals or groups. Table of contents When to use qualitative observation, examples of qualitative observation, types of qualitative observations, advantages and disadvantages of qualitative observations, other interesting articles, frequently asked questions. Qualitative observation is a type of observational study , often used in conjunction with other types of research through triangulation . It is often used in fields like social sciences, education, healthcare, marketing, and design. This type of study is especially well suited for gaining rich and detailed insights into complex and/or subjective phenomena. A qualitative observation could be a good fit for your research if: You are conducting exploratory research . If the goal of your research is to gain a better understanding of a phenomenon, object, or situation, qualitative observation is a good place to start. When your research topic is complex, subjective, or cannot be examined numerically. Qualitative observation is often able to capture the complexity and subjectivity of human behavior, particularly for topics like emotions, attitudes, perceptions, or cultural practices. These may not be quantifiable or measurable through other methods. You are relying on triangulation within your research approach. Qualitative observation is a solid addition to triangulation approaches, where multiple sources of data are used to validate and verify research findings. Prevent plagiarism. Run a free check. Qualitative observation is commonly used in marketing to study consumer behavior, preferences, and attitudes towards products or services. During the focus group, you focus particularly on qualitative observations, taking note of the participants’ facial expressions, body language, word choice, and tone of voice. Qualitative observation is often also used in design fields, to better understand user needs, preferences, and behaviors. This can aid in the development of products and services that better meet user needs. You are particularly focused on any usability issues that could impact customer satisfaction. You run a series of testing sessions, focusing on reactions like facial expressions, body language, and verbal feedback. There are several types of qualitative observation. Here are some of the most common types to help you choose the best one for your work. Type Definition Example 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. Here, the researcher immerses themself in the participant group over a period of time Spending a few months in a hospital with patients suffering from a particular illness Covert observation Hinges on the fact that the participants do not know they are being observed Observing interactions in public spaces, like bus rides or parks 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 Qualitative observations are a great choice of research method for some projects, but they definitely have their share of disadvantages to consider. Advantages of qualitative observations Qualitative observations allow you to generate rich and nuanced qualitative data —aiding you in understanding a phenomenon or object and providing insights into the more complex and subjective aspects of human experience. Qualitative observation is a flexible research method that can be adjusted based on research goals and timeline. It also has the potential to be quite non-intrusive, allowing observation of participants in their natural settings without disrupting or influencing their behavior. Qualitative observation is often used in combination with other research methods, such as interviews or surveys , to provide a more complete picture of the phenomenon being studied. This triangulation can help improve the reliability and validity of the research findings. Disadvantages of qualitative observations Like many observational studies, qualitative observations are at high risk for many research biases , particularly on the side of the researcher in the case of observer bias . These biases can also bleed over to the participant size, in the case of the Hawthorne effect or social desirability bias . Qualitative observations are typically based on a small sample size , which makes them very unlikely to be representative of the larger population. This greatly limits the generalizability of the findings if used as a standalone method, and the data collection process can be long and onerous. Like other human subject research, qualitative observation has its share of ethical considerations to keep in mind and protect, particularly informed consent, privacy, and confidentiality. Here's why students love Scribbr's proofreading services Discover proofreading & editing 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. Student’s  t -distribution Normal distribution Null and Alternative Hypotheses Chi square tests Confidence interval Quartiles & Quantiles Cluster sampling Stratified sampling Data cleansing Reproducibility vs Replicability Peer review Prospective cohort study Research bias Implicit bias Cognitive bias Placebo effect Hawthorne effect Hindsight bias Affect heuristic Social desirability bias Data analysis in qualitative observation often involves searching for any recurring patterns, themes, and categories in your data. This process may involve coding the data, developing conceptual frameworks or models, and conducting thematic analysis . This can help you generate strong hypotheses or theories based on your data. 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. An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups . Cite this Scribbr article If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator. George, T. (2023, June 22). What Is Qualitative Observation? | Definition & Examples. Scribbr. Retrieved July 5, 2024, from https://www.scribbr.com/methodology/qualitative-observation/ Is this article helpful? Tegan George Other students also liked, what is participant observation | definition & examples, naturalistic observation | definition, guide & examples, what is a cohort study | definition & examples, get unlimited documents corrected. ✔ Free APA citation check included ✔ Unlimited document corrections ✔ Specialized in correcting academic texts Government innovation Governments today must be able to adapt to changing environments, work in different ways, and find solutions to complex challenges. OECD work on public sector innovation looks at how governments can use novel tools and approaches to improve practices, achieve efficiencies and produce better policy results. Global Trends in Government Innovation Tackling Policy Challenges Through Public Sector Innovation Select a language Key messages, innovation is a strategic function that must be integrated into broader public sector governance.. Innovation rarely happens by accident. Governments can increase innovation in the public sector through deliberate efforts using many different levers, from investments in skills or technology, to applying new policymaking methods or adapting existing processes. Our work helps governments assess their innovative capacity, providing practical and evidence-based steps to embed innovation in policymaking and administration. This means governments are better able to respond to changing environments and develop more impactful policies. Behavioural science helps governments put people at the center of public policy. Understanding cognitive biases, behavioural barriers, and social norms  is essential for the development of impactful policies and public uptake. Behavioural science is an interdisciplinary approach, providing insights that enable policymakers to design more effective and targeted policies that reflect actual human behaviour and decision-making. Our work encompasses research on context-specific behavioural drivers and barriers to support countries in the use of behavioural science from policy design to implementation and evaluation. Through the OECD Network of Behavioural Science Experts in Government, we further foster the exchange of best behavioural science practices and mutual learning. Governments must anticipate, understand and prepare for the future as it emerges. The nature of policy issues that governments are confronted by is volatile, uncertain, complex and often ambiguous. Governments need to consider a variety of scenarios and act upon them in real time. This requires a new approach to policymaking, one that is future and action oriented, involves an innovation function and anticipates the changing environment. By governing with anticipation and innovation, governments can prepare for what’s coming next. They can identify, test, and implement innovative solutions to benefit from future opportunities while reducing risk and enhancing resilience. Innovation in public services unlocks efficiency, responsiveness and citizen satisfaction. Innovating and digitalising public services can bring many benefits, including improving the quality, efficiency and effectiveness of services, enhancing equitable access and reducing administrative burdens. While it holds tremendous benefits for supporting the overall well-being and satisfaction of citizens and public trust in institutions, governments must ensure high standards of transparency and ethics, particularly when employing the use of data and artificial intelligence to improve or deliver public services. Our work is building towards an OECD Recommendation on the design of government services to effectively improve people's experiences including through life events and the development of more effective and equitable services.   The public has a lack of confidence in public agencies adopting innovative ideas. Governments must do better to respond to citizens’ concerns. Just fewer than one in four (38%, on average across OECD countries), feel that a public agency would be likely to adopt an innovative idea to improve a public service. Enhancing innovation capacity can strengthen resilience, responsiveness and trust in public institutions. Confidence in governments’ adoption of innovative ideas is directly related to trust in civil servants. People who say they are confident about innovation in a public office are more likely to trust civil servants. On average across OECD countries, the share of people who trust the civil service is equal to 70% among those who are confident about public sector innovation. This trust value is more than two times larger than among those who say that the public sector would not adopt innovative ideas. Latest insights Related publications Related policy issues Anticipatory governance In an era characterised by rapid technological advances, environmental shifts, changing demographics, geopolitical tensions, and evolving societal needs, traditional governance models are increasingly under pressure. Governments worldwide are seeking ways to not only respond to present challenges but also to anticipate and shape future possibilities. Anticipatory Innovation Governance is a proactive approach that integrates foresight, innovation, and continuous learning into the heart of public governance. Learn more Behavioural science Governments around the world are increasingly using behavioural science as a lens to better understand how behaviours and social context influence policy outcomes. At the OECD, we research context-specific behavioural drivers and barriers, and support countries in the use of behavioural insights, from policy design to implementation and evaluation. Learn more Digital government Digital government explores and supports the development and implementation of digital government strategies that bring governments closer to citizens and businesses. It recognises that today’s technology is a strategic driver not only for improving public sector efficiency, but also for making policies more effective and governments more open, transparent, innovative, participatory and trustworthy. Learn more Innovative capacity of governments Governments must develop their capacity to adapt and change the way policies and services are designed and delivered if they want to implement ambitious reform agendas, meet climate targets and respond to global crises. Without intentional efforts, innovation is left to chance, fuelled sporadically by circumstance and crises. Our work helps governments assess and improve their innovative capacity, providing practical and evidence-based steps to embed innovation in policymaking and administration. Learn more Innovative public participation Citizens must have a say in the decisions that affect them. Inclusive and impactful participation not only enriches the policymaking process by incorporating diverse views and harnessing collective knowledge, but also strengthens public understanding of outcomes, promotes policy uptake, and reinforces trust in public institutions. It is essential to institutionalise participatory and deliberative processes and better articulate them with representative democracies. Learn more strategic-foresight Learn more share this! July 2, 2024 This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility: fact-checked trusted source New satellite aims to show how AI advances Earth observation by European Space Agency Artificial intelligence technologies have achieved remarkable successes and continue to show their value as backbones in scientific research and real-world applications. ESA's new Φsat-2 mission, launching in the coming weeks, will push the boundaries of AI for Earth observation—demonstrating the transformative potential of AI for space technology . Earth observation has, for decades, provided a rich stream of actionable data for scientists, businesses and policymakers. Thanks to new satellites and advanced sensors, the scale and quality of available Earth observation data have risen exponentially in the past decade. The integration of AI has significantly enhanced Earth observation. AI capabilities allow for more data to be processed quickly and accurately, helping to enable to transform vast amounts of raw data into actionable insights. As part of an initiative to promote the development and implementation of innovative technologies onboard Earth observation missions, ESA launched Ф-sat-1 in 2020. It was ESA's first experiment to demonstrate how artificial intelligence can be used for Earth observation and paved the way for its successor: Φsat-2. Φsat-2 is a dedicated AI mission which will fully explore the benefits and capabilities of utilizing extended onboard processing and further demonstrate the benefits of using AI for innovative Earth observation. Measuring just 22 x 10 x 33 cm, ESA's Φsat-2 satellite is equipped with a multispectral camera and powerful AI computer that analyzes and processes imagery in real-time—promising to deliver smarter and more efficient ways of monitoring our planet. With six AI applications running onboard, the satellite is designed to turn images into maps, detect clouds in the images, classify them and provide insight into cloud distribution, detect and classify vessels, compress images on board and reconstruct them in the ground reducing the download time, spot anomalies in marine ecosystems and detect wildfires. ESA's Φsat-2 Technical Officer Nicola Melega, commented, "Φsat-2 will unlock a new era of real-time insights from space and will allow for custom AI apps to be easily developed, installed, and operated on the satellite even while in orbit. This adaptability maximizes the satellite's value for scientists, businesses and governments." The Φsat-2 mission is a collaborative effort between ESA and Open Cosmos who serves as the prime contractor, supported by an industrial consortium including Ubotica, GGI, CEiiA, GEO-K, KP-Labs, and SIMERA. Φsat-2, which shares its ride into orbit with ESA's Arctic Weather Satellite, is scheduled to liftoff in July 2024 on a SpaceX Falcon 9 from the Vandenberg Air Force Base, California, in the U.S. Φsat-2 carries a multispectral instrument that images Earth in seven different bands and, through its AI applications, is capable of many things that can provide actionable information on the ground, including: Cloud detection Unlike traditional satellites that downlink all captured images, including those obscured by clouds, Φsat-2 processes these images directly in orbit, ensuring that only clear, usable images are sent back to Earth. Developed by KP Labs, this application can also classify clouds and provide insights into cloud distribution. This gives users more flexibility when it is time to decide whether an image is usable or not. Street map generation The Sat2Map application, developed by CGI, converts satellite imagery into street maps. This capability is particularly beneficial for emergency response teams, enabling them to identify accessible roads during disasters such as floods or earthquakes. When the satellite orbits over the affected area and acquires images, the images are passed to the onboard processer that will identify streets and generate a corresponding map. Initially, this application will be demonstrated over Southeast Asia, showcasing its potential to aid in crisis management. Maritime vessel detection The maritime vessel detection application, developed by CEiiA, utilizes machine learning techniques to automatically detect and classify vessels in specified regions, facilitating the monitoring of activities like illegal fishing. This application underscores the satellite's role in supporting maritime security and environmental conservation efforts. On-board image compression and reconstruction Developed by GEO-K, this application is responsible for compressing images on board. By significantly reducing file sizes, this application increases the volume and speed of data downloads. After being downlinked to the ground, the images are reconstructed using a dedicated decoder. The first demonstrations of this technology will occur over Europe, focusing on the detection of buildings. Φsat-2's capabilities have been further expanded with the incorporation of two additional AI applications that will be uploaded once the satellite is in orbit. These AI applications were the winning entries in the OrbitalAI challenge organized by ESA's Φ-lab and was designed to give companies the change to pioneer in-orbit Earth observation data processing. The winning applications are: Marine anomaly detection Developed by IRT Saint Exupery Technical Research, this application uses machine learning algorithm to spot anomalies in marine ecosystems—identifying threats to the marine ecosystem such as oil spills, harmful algae blooms and heavy sediment discharges in real-time. Wildfire detection The wildfire detection system, developed by Thales Alenia Space, uses machine learning to provide critical real-time information to response teams. The tool provides a classification report that helps firefighters locate wildfires, track fire spread and identify potential hazards. 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Here's how to spot it Analysis of NASA InSight data suggests Mars hit by meteoroids more often than thought Let us know if there is a problem with our content. Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ). Please select the most appropriate category to facilitate processing of your request Thank you for taking time to provide your feedback to the editors. Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages. E-mail the story Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Phys.org in any form. Newsletter sign up Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties. More information Privacy policy Donate and enjoy an ad-free experience We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account. E-mail newsletter Raising Sand's Value Awareness: Science and Communication Initiatives. Drago, Teresa Santos, Jacqueline Surducan, Emanuel Alberto, Ana Afonso, João. Fernandes, Aurélie Sand is one of the most used resources in the world (50 billion tonnes per year). It plays a strategic key role in delivering geosystems services, maintaining biodiversity, supporting economic development, and securing livelihoods within communities (UNEP, 2022). Sand is everywhere in our societies: buildings, roads, dams and other infrastructures. Despite this "endless" use, sand is a finite resource, and its use occurs at a faster rate than its generation by geological processes. However, the importance of sand and the need of a sustainable management of this raw material are unknow to students at basic and secondary levels and to the public in general.The EDUCOAST project (funded by EEAGrants) aims to promote nature-based education in coastal and marine geosciences through experimental learning. A series of initiatives to increase awareness on sand conservation were carried out as part of the EDUCOAST project. They included field and lab activities for basic and secondary school students at sandy environments (such as barrier islands and dunes) and observation of various types of sand from around the world under binocular microscope. These "hands-on" activities focused on topics such as "what is the sand made of?" and "Let's get to know sand better". In total, about 500 students participated in these "hands-on" activities and the conducted surveys showed very positive feedback, where the students learnt more about these sandy environments (origin and their processes), the sand characteristics (grain-size, composition, carbonates contents) and the need for more sustainable management practices for the environmental conservation of the coastal systems.Communication and outreach play an important role in achieving the proposed objectives. In this context, the project also participated in various initiatives such as the "European Research Night", "Science in Summer" (promoted by the Portuguese Programme "Ciência Viva") and the "Week of Science and Technology" among others, making it possible to increase awareness in addressing issues like sand importance and conservation for approximately 700 people.These initiatives contributed to highlight the importance of public awareness and the potential for positive change through informed and engaged students and general public.This is a contribution of the EDUCOAST (EEAGrants, PT-INNOVATION-0067) and EMSO-PT (PINFRA/22157/2016) projects.This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) - UIDB/50019/2020 (https://doi.org/10.54499/ UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020)Reference: UNEP 2022. Sand and sustainability: 10 strategic recommendations to avert a crisis. GRID-Geneva, United Nations Environment Programme, Geneva, Switzerland No Sources Found 406 IMAGES 10 Observational Research Examples (2024) Observational Research Observational Research PowerPoint and Google Slides Template PPT Observational Research and How it Can Benefit You PPT VIDEO Introduction to Research and how to choose a research topic @TheSocialFactory @SatoshiSea @TotalGaming093 Understanding Observational Studies: A Guide to Real-World Research PRESENTATION OF RESEARCH TITLE AND STATEMENT OF THE PROBLEM (Qualitative Research) Research Methodology for Observational Research What is research topic? Criteria for selecting topic, components and examples #health #research COMMENTS 10 Observational Research Examples (2024) Examples of Observational Research. 1. Jane Goodall's Research. Jane Goodall is famous for her discovery that chimpanzees use tools. It is one of the most remarkable findings in psychology and anthropology. Her primary method of study involved simply entering the natural habitat of her research subjects, sitting down with pencil and paper ... 21 Naturalistic Observation Examples (2024) Famous Examples. 1. Jane Goodall's Research. Dr. Valerie Jane Morris-Goodall is one of the most famous scientists in history. Her research on chimpanzees in Kenya and work in conservation are well-known throughout the world. Her primary research method was naturalistic observation. 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 ... 7 Types of Observational Studies (With Examples) There are seven types of observational studies. Researchers might choose to use one type of observational study or combine any of these multiple observational study approaches: 1. Cross-sectional studies. Cross-sectional studies happen when researchers observe their chosen subject at one particular point in time. 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. What Is an Observational Study? 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 ... Observational Research: What is, Types, Pros & Cons + Example Observational research is a broad term for various non-experimental studies in which behavior is carefully watched and recorded. The goal of this research is to describe a variable or a set of variables. More broadly, the goal is to capture specific individual, group, or setting characteristics. Since it is non-experimental and uncontrolled, we ... 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 ... Naturalistic Observation Naturalistic observation is a valuable tool because of its flexibility, external validity, and suitability for research topics that can't be studied in a lab. Flexibility; Because naturalistic observation is a non-experimental method, you're not bound to strict procedures. Research Question Examples & Ideas: The ULTIMATE List Research Question Examples 🧑🏻‍🏫. 25+ Practical Examples & Ideas To Help You Get Started. By: Derek Jansen (MBA) | October 2023. A well-crafted research question (or set of questions) sets the stage for a robust study and meaningful insights. But, if you're new to research, it's not always clear what exactly constitutes a good ... Ideas for Observational Studies Easy observational studies pinpoint the wonder that exists in natural occurrences, human behavior, social sciences, statistics, animal behavior and more. To begin an observational study, create an extensive plan and a hypothesis about what test results you may encounter along the way. Direct observation methods: A practical guide for health researchers Observation is particularly useful for understanding patients', providers' or other key communities' experiences because it provides an "emic," insider perspective and lends itself to topics like patient-centered care research [1,5,6]. This insider perspective allows researchers to understand end users' experiences of a problem. What Is Participant Observation? Participant observation is a common research method in social sciences, with findings often published in research reports used to inform policymakers or other stakeholders. Example: Rural community participant observation. You are studying the social dynamics of a small rural community located near where you grew up. What is an Observational Study: Definition & Examples Observational Study Definition. In an observational study, the researchers only observe the subjects and do not interfere or try to influence the outcomes. In other words, the researchers do not control the treatments or assign subjects to experimental groups. Instead, they observe and measure variables of interest and look for relationships ... 20 Excellent Observation Essay Topic Ideas for You to Use Give your opinion about your observation by explaining everything and connect all the dots for the reader. Go through your essay, check and correct your spellings, grammar, and punctuation, and make sure you convey the information in the right tense. The narrative should be in a linear progression, going from the strong points to the weak ones. observational studies research: Topics by Science.gov Practical Hints for Observational Research.. ERIC Educational Resources Information Center. Washington, Wanda; And Others. The Austin Independent School District's Research and Evaluation Office presents practical information concerning observational research.This paper focuses on five topics: (1) what makes a good observer (setting the ground rules, training observers in details, and practice ... Observational Studies 16 answers. Jul 9, 2020. There are two ways one can classify Cluster Sampling technique. First, based on the number of stages followed to obtain the cluster sample (i.e., one -stage, two-stage ... what are some interesting ideas for an observational study? Ideas. i need to do an observational study for uni and write a scientific report about it. our coordinator proposed some ideas such as, "do men or women study more" or "what are the differences in non-verbal behavior between men and women during public speaking". these topics don't really peak my interest and there's already some research on ... Two examples of on-site observational studies Observational research examples. The first study we describe in this blog post explores how familiarity influences the use of electronic devices in different age groups. In the second study, researchers compared different methods of observing pain expressions in dementia patients. Example 1: Familiarity and intuitive use 15 Great Observation Essay Topic Ideas You Should Not Miss 2. Three-Paragraph Body. An observational essay has a body like any other type of academic assignment: research paper, article review, book report, etc. Teachers recommend developing a three-paragraph body with three powerful, supporting arguments. Arrange the notes according to your paper's outline; add more details. Observational Research 7 Canons of Validity. Field observational research aims to maximize validity—'the degree to which scientific observations actually measure or record what they purport to measure'—rather than reliability—'the repeatability, including interpersonal replicability, of scientific observations' (Pelto and Pelto 1978, p. 33). Observational Study Ideas dawndowell [licensed for non-commercial use only] / Observational Study Ideas. If you are citizen of an European Union member nation, you may not use this service unless you are at least 16 years old. You already know Dokkio is an AI-powered assistant to organize & manage your digital files & messages. Very soon, Dokkio will support Outlook as ... The Originator of Observational Learning: a Scholar's Perspective Bandura famous psychology whose research has perceptibly influenced understanding human relation offered a theory observant studies in mid-20th century. ... This essay is about Albert Bandura's contributions to the concept of observational learning in psychology and education. ... 19 students ordered this very topic and got original papers ... Fresh wind blows from historical supernova Due to its rare nature and location within our galaxy, SNR 1181 has been the subject of much observational research. This suggested that SNR 1181 is made up of two shock regions, an outer region ... What Is Qualitative Observation? A qualitative observation could be a good fit for your research if: You are conducting exploratory research. If the goal of your research is to gain a better understanding of a phenomenon, object, or situation, qualitative observation is a good place to start. When your research topic is complex, subjective, or cannot be examined numerically. Government innovation Our work encompasses research on context-specific behavioural drivers and barriers to support countries in the use of behavioural science from policy design to implementation and evaluation. Through the OECD Network of Behavioural Science Experts in Government, we further foster the exchange of best behavioural science practices and mutual ... New satellite aims to show how AI advances Earth observation ESA's new Φsat-2 mission, launching in the coming weeks, will push the boundaries of AI for Earth observation—demonstrating the transformative potential of AI for space technology.. Earth ... Raising Sand's Value Awareness: Science and Communication Initiatives Sand is one of the most used resources in the world (50 billion tonnes per year). It plays a strategic key role in delivering geosystems services, maintaining biodiversity, supporting economic development, and securing livelihoods within communities (UNEP, 2022). Sand is everywhere in our societies: buildings, roads, dams and other infrastructures. Despite this "endless" use, sand is a finite ... assignment essay homework paper phd report resume review speech thesis