Usually first report of a notable issue ,
Their purpose may be descriptive, analytical or both.
Case reports and case series are strictly speaking not studies. However, they serve a useful role in describing new or notable events in detail. These events often warrant further formal investigation. Examples include reports of unexpected benefits or adverse events, such as a case report describing the use of high-dose quetiapine in treatment-resistant schizophrenia after intolerance to clozapine developed 9 and a case report of a medication error involving lookalike packaging. 10
Ecological studies are based on analysis of aggregated data at group levels (for example populations), and do not involve data on individuals. These data can be analysed descriptively, but not definitively for causation. Typical examples include studies that examine patterns of drug use over time. One example is the comparison of the use of non-steroidal anti-inflammatory drugs and COX-2 inhibitors in Australia and Canada. 11 Sometimes ecological studies describe associations between drugs and outcomes, such as changes in the rates of upper gastrointestinal haemorrhage after the introduction of COX-2 inhibitors. 12 However, because individual-level data are not presented, causality is at best only implied in ecological studies. The 'ecological fallacy' refers to the error of assuming that associations observed in ecological studies are causal when they are not.
Cross-sectional studies collect data at a single point in time for each single individual, but the actual data collection may take place over a period of time or on more than one occasion. There is no longitudinal follow-up of individuals. Cross-sectional studies represent the archetypal descriptive study. 1 Typically, they provide a profile of a population of interest, which may be broad, like the Australian Health Survey undertaken intermittently by the Australian Bureau of Statistics, 13 or focused on specific populations, such as older Australians. 14
Case-control studies focus on determining risk factors for an outcome of interest (such as a disease or a drug’s adverse effect) that has already occurred. 5
Second, data on previous exposure to selected risk factors are collected and compared to see if these risk factors are more (or less) common among cases versus controls. Case-control studies are useful for studying the risk factors of rare outcomes, as there is no need to wait for these to occur. Multiple risk factors can be studied, but each case-control study can involve only one outcome. 5 One example explored the relationship between the use of antiplatelet and anticoagulant drugs (risk factor) and the risk of hospitalisation for bleeding (outcome) in older people with a history of stroke. 15 Another case-control study explored the risk factors for the development of flucloxacillin-associated jaundice (outcome). 16
Cohort studies compare outcomes between or among subgroups of participants defined on the basis of whether or not they are exposed to a particular risk or protective factor (defined as an exposure). They provide information on how these exposures are associated with changes in the risk of particular downstream outcomes. Compared to case-control studies, cohort studies take individuals with exposures and look for outcomes, rather than taking those with outcomes and looking for exposures. Cohort studies are longitudinal, that is they involve follow-up of a cohort of participants over time. This follow-up can be prospective or retrospective. Retrospective cohort studies are those for which follow-up has already occurred. They are typically used to estimate the incidence of outcomes of interest, including the adverse effects of drugs.
Cohort studies provide a higher level of evidence of causality than case-control studies because temporality (the explicit time relationship between exposures and outcomes) is preserved. They also have the advantage of not being limited to a single outcome of interest. Their main disadvantage, compared to case-control studies, has been that longitudinal data are more expensive and time-consuming to collect. However, with the availability of electronic data, it has become easier to collect longitudinal data.
One prospective cohort study explored the relationship between the continuous use of antipsychotic drugs (exposure) and mortality (outcome) and hospitalisation (outcome) in older people. 17 In another older cohort, a retrospective study was used to explore the relationship between long-term treatment adherence (exposure) and hospital readmission (outcome). 18
Compared to randomised controlled trials, observational studies are relatively quick, inexpensive and easy to undertake. Observational studies can be much larger than randomised controlled trials so they can explore a rare outcome. They can be undertaken when a randomised controlled trial would be unethical. However, observational studies cannot control for bias and confounding to the extent that clinical trials can. Randomisation in clinical trials remains the best way to control for confounding by ensuring that potential confounders (such as age, sex and comorbidities) are evenly matched between the groups being compared. In observational studies, adjustment for potential confounders can be undertaken, but only for a limited number of confounders, and only those that are known. Randomisation in clinical trials also minimises selection bias, while blinding (masking) controls for information bias. Hence, for questions regarding drug efficacy, randomised controlled trials provide the most robust evidence.
New and upcoming developments
New methods of analysis and advances in technology are changing the way observational studies are performed.
Clinical registries are essentially cohort studies, and are gaining importance as a method to monitor and improve the quality of care. 19 These registries systematically collect a uniform longitudinal dataset to evaluate specific outcomes for a population that is identified by a specific disease, condition or exposure. This allows for the identification of variations in clinical practice 20 and benchmarking across practitioners or institutions. These data can then be used to develop initiatives to improve evidence-based care and patient outcomes. 21
An example of a clinical registry in Australia is the Australian Rheumatology Association Database, 22 which collects data on the biologic disease-modifying antirheumatic drugs used for inflammatory arthritis. Clinical data from treating specialists are combined with patient-reported quality of life data and linked to national databases such as Medicare and the National Death Index. This registry has provided insight into the safety and efficacy of drugs and their effect on quality of life. It was used by the Pharmaceutical Benefits Advisory Committee to assess cost-effectiveness of these drugs. 23
Another example is the Haemostasis Registry. It was used to determine the thromboembolic adverse effects of off-label use of recombinant factor VII. 24
Clinical registries can also be used to undertake clinical trials which are nested within the registry architecture. Patients within a registry are randomised to interventions and comparators of interest. Their outcome data are then collected as part of the routine operation of the registry. The key advantages are convenience, reduced costs and greater representativeness of registry populations as opposed to those of traditional clinical trials.
One of the first registry-based trials was nested within the SWEDEHEART registry. 25 This prospectively examined manual aspiration of thrombus at the time of percutaneous coronary intervention in over 7000 patients. 26 The primary endpoint of all-cause mortality was ascertained through linkage to another Swedish registry. The cost of the trial was estimated to be US$400 000, which was a fraction of the many millions that a randomised controlled trial would have cost.
Even without randomising people within cohorts, methods have emerged in recent years that allow for less biased comparisons of two or more subgroups. Propensity score matching is a way to assemble two or more groups for comparison so that they appear like they had been randomised to an intervention or a comparator. 27 In short, the method involves logistic regression analyses to determine the likelihood (propensity) of each person within a cohort being on the intervention, and then matching people who were on the intervention to those who were not on the basis of propensity scores. Outcomes are then compared between the groups. Propensity score analysis of a large cohort of patients with relapsing remitting multiple sclerosis found that natalizumab was superior to interferon beta and glatiramer acetate in terms of improved outcomes. 28
Increasing sophistication in techniques for data collection will lead to ongoing improvements in the capacity to undertake observational studies (and also clinical trials). Data linkage already offers a convenient way to capture outcomes, including retrospectively. However, ethical considerations must be taken into account, such as the possibility that informed consent might be required before linking data. Machine learning will soon allow for easy analyses of unstructured text (such as free text entries in an electronic prescription). 29 Patient-reported outcome measures are important and in future will be greatly facilitated by standardised, secure hardware and software platforms that allow for their capture, processing and analyses.
While clinical trials remain the best source of evidence regarding the efficacy of drugs, observational studies provide critical descriptive data. Observational studies can also provide information on long-term efficacy and safety that is usually lacking in clinical trials. New and ongoing developments in data and analytical technology offer a promising future for observational studies in pharmaceutical research.
Conflict of interest: Julia Gilmartin-Thomas is a Dementia research development fellow with the National Health and Medical Research Council (NHMRC) - Australian Research Council (ARC). Ingrid Hopper is supported by an NHMRC Early Career Fellowship.
Categories Research Methods
Naturalistic observation is a psychological research method that involves observing and recording behavior in the natural environment. Unlike experiments, researchers do not manipulate variables. This research method is frequently used in psychology to help researchers investigate human behavior.
This article explores how naturalistic observation is used in psychology. It offers examples and the potential advantages and disadvantages of this type of research.
Table of Contents
In naturalistic observation, the researcher observes the participants’ behavior in their natural setting, taking notes on their behavior and interactions. The researcher may use various tools, such as video or audio recordings, to help capture the behavior accurately. The researcher may also use coding systems or other quantitative measures to systematically record observed behavior.
Naturalistic observation can be used to investigate a wide range of psychological phenomena, such as social interaction patterns, parental behavior, or animal behavior.
Naturalistic observation can be:
The observer can either watch and record everything that happens, or they can have a checklist or form to guide their observations.
The observer can be an active participant, or they can remain separate from the subject and view from the sidelines.
The observer can either openly watch and record the subjects’ behaviors, or they can keep their presence hidden from the individual or group.
The specific type of naturalistic observation that researchers use depends on the situation, what they are researching, and the resources available. No matter the type, the observation must occur in a natural setting rather than in an experimental lab.
There are a number of methods that researchers might utilize to record data about the behaviors and events they observe. Some of these include:
While naturalistic observation is not an experimental design, researchers still want to ensure that the data they collect represents what is happening in the group. To do this, researchers must collect a representative sample. When a sample is representative, it means that it accurately reflects what is happening in a given population.
To do this, researchers may utilize three primary sampling approaches:
Event sampling involves the researcher creating a set of predefined categories and behaviors they will observe. This method is useful when the researcher wants to collect data on specific behaviors or events, allowing for more precise data collection.
Using this approach, the research would note every occurrence of a specific behavior.
Situation sampling involves observing participants in more than one situation. This approach can give researchers more insight and allow them to determine if certain behaviors only occur in specific contexts or settings.
Time sampling is a type of systematic observation that involves the researcher observing and recording the subjects’ behavior at predetermined intervals. This method is useful when the researcher wants to collect data on the frequency and duration of specific behaviors.
Each method of data collection has its strengths and weaknesses, and the choice of method depends on the research question and the nature of the subjects being observed.
It can be helpful to look at a few different examples to learn more about how naturalistic observation can be used:
Researchers use this research method in various fields, including animal researchers and anthropologists.
The work of zoologist Konrad Lorenz, for example, relied on the use of naturalistic observation. Lorenz observed the behavior of ducklings after they hatched and noted that they became attached to the first possible parent figure they saw, a phenomenon known as imprinting. Once imprinted on a parent figure, the duckling would follow and learn from their parent.
From his naturalistic observations, Lorenz hypothesized that there was a critical period immediately after hatching where ducklings needed to imprint on a parent. Based on his observations, Lorenz conducted further experiments that confirmed his hypothesis.
Naturalistic observation is a research method commonly used in various areas of psychology.
Naturalistic observation can provide valuable insights into people’s behavior in different social situations. By observing people’s behavior in a crowded public place like a shopping mall or train station, researchers can better understand how social norms are established and maintained and how people interact in various social groups.
Consumer research is another area where naturalistic observation can be used effectively. By observing shoppers in a grocery store or shopping mall, researchers can study how people make purchasing decisions in real-life situations.
Researchers can gain valuable insights into consumer behavior by analyzing what catches their attention, how they interact with different products, and how they decide what to buy.
Observing children playing in a playground or a classroom can help researchers understand how children develop and learn new skills in natural settings.
Researchers can gain insights into the developmental process by observing children as they interact with each other and learn social skills or as they learn new concepts and skills in a classroom.
Naturalistic observation can be used to study how people think and process information in real-life situations. For example, observing people using a computer program can help researchers understand how people navigate through it and solve problems.
Similarly, observing people in a conversation can provide insights into how they process and respond to information in real time.
Naturalistic observation offers a number of benefits that can make it a good choice for research.
One of the strengths of naturalistic observation is its ability to capture behavior in a natural setting, providing a more accurate and comprehensive picture of how people or animals behave in their everyday environment.
It is often more realistic than lab research, so it can give insight into how people behave authentically in everyday settings and situations.
Naturalistic observation can also generate new hypotheses and insights that may not be captured in other research methods.
Naturalistic observation allows the study of behaviors that cannot be replicated in a lab. Naturalistic observation is sometimes the only approach for studying behaviors that cannot be reproduced in a lab due to ethical reasons.
For example, researchers might use this approach to research prison behavior or the social impact of domestic violence on emotional health. Those are not situations they can manipulate in a lab, but they can observe the impact on people who have had those experiences.
While naturalistic can be a valuable tool, it is not appropriate for every situation. Some potential downsides include:
Naturalistic observation is limited by its lack of environmental control and the potential for observer bias. Researchers must be careful to minimize the influence of their presence on the behavior being observed and to use systematic and objective methods for recording and analyzing the data.
Naturalistic observation is also limited by its inability to establish causality between variables.
Naturalistic observation and case studies are both research methods used in psychology but differ in their approach and purpose. Naturalistic observation involves observing and recording the behavior of individuals or groups in their natural environment without any intervention or manipulation by the researcher.
On the other hand, a case study is an in-depth analysis of a single individual or a small group of individuals, often conducted through interviews, surveys, and other forms of data collection.
The key difference between naturalistic observation and a case study is that the former focuses more on observing and recording behaviors and interactions as they occur naturally, while the latter focuses on gathering detailed information about a specific individual or group.
Naturalistic observation is often used to study social interactions, group dynamics, and other natural behaviors in real-world settings. In contrast, case studies often explore complex psychological phenomena such as mental illness, personality disorders, or unusual behaviors.
Both naturalistic observation and case studies have their strengths and limitations. The choice of method depends on the research question, the level of detail needed, and the feasibility of conducting the study in a particular setting.
There are many potential ideas for studies that involve naturalistic observation. A few ideas include:
Why do we use naturalistic observation.
Naturalistic observation is important because it allows researchers to better understand how individuals behave in their everyday lives. By observing behavior in a natural setting, researchers can obtain a more accurate representation of how people act and interact with each other in their normal environment.
This method is particularly useful when studying social behavior, as it allows researchers to capture the complexity and nuances of social interactions that might not be apparent in a laboratory setting.
Naturalistic observation can also offer valuable insights into the development of certain behaviors, such as those related to child development or the formation of social groups.
The most famous example of naturalistic observation is probably Jane Goodall’s study of chimpanzees in the wild. Goodall spent years observing the behavior of chimpanzees in Tanzania, documenting their social interactions, tool use, and other aspects of their lives. Her work helped to revolutionize our understanding of these animals and their place in the natural world.
In conclusion, naturalistic observation is a powerful research method that can be used effectively in various areas within psychology. Researchers can gain valuable insights into human behavior and cognition by observing people’s behavior in natural settings.
Bornstein MH, Cheah CSL. Audiovisual records, encoding of . In: Encyclopedia of Social Measurement . Elsevier; 2005:103-110. doi:10.1016/B0-12-369398-5/00400-X
Erdley CA, Jankowski MS. Assessing youth . In: Social Skills Across the Life Span . Elsevier; 2020:69-90. doi:10.1016/B978-0-12-817752-5.00004-4
Helmchen H. Ethical issues in naturalistic versus controlled trials . Dialogues Clin Neurosci . 2011;13(2):173-182. doi:10.31887/DCNS.2011.13.2/hhelmchen
Mehl MR, Robbins ML, Deters FG. Naturalistic observation of health-relevant social processes: the electronically activated recorder methodology in psychosomatics . Psychosom Med . 2012;74(4):410-417. doi:10.1097/PSY.0b013e3182545470
Morrison C, Lee JP, Gruenewald PJ, Mair C. The reliability of naturalistic observations of social, physical and economic environments of bars . Addict Res Theory . 2016;24(4):330-340. doi:10.3109/16066359.2016.1145674
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Published on December 8, 2021 by Pritha Bhandari . Revised on March 13, 2023.
Observer bias happens when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It often affects studies where observers are aware of the research aims and hypotheses . Observer bias is also called detection bias.
What is observational research, subjective methods, objective methods, how to minimize observer bias, other biases, other types of research bias, frequently asked questions about observer bias.
In observational studies, you often record behaviors or take measurements from participants without trying to influence the outcomes or the situation. Observational studies are used in many research fields, including medicine, psychology, behavioral science, and ethnography .
Observer bias can occur regardless of whether you use qualitative or quantitative research methods.
Subjective research methods involve some type of interpretation before you record the observations.
In any research involving others, your own experiences, habits, or emotions can influence how you perceive and interpret others’ behaviors. They may lead you to note some observations as relevant while ignoring other equally important observations.
Your expectations about the research may lead to skewed results. There’s a risk you may be subconsciously primed to see only what you expect to observe.
Observer bias may still influence your study even when you use more objective methods (e.g., physiological devices, medical images) for measurement.
That’s because people have a tendency to interpret readings differently, so results can vary between observers in a study.
A lack of training, poor control, and inadequate procedures or protocols may lead to systematic errors from observer bias.
As you collect data , you become more familiar with the procedures and you might become less careful when taking or recording measurements. Observer drift happens when observers depart from the standard procedures in set ways and therefore rate the same events differently over time.
It’s important to design research in a way that minimizes observer bias. Note that, while you can try to reduce observer bias, you may not be able to fully eliminate it from your study.
Masking , or blinding , helps you make sure that both your participants and your observers are unaware of the research aims.
This can remove some of the research expectations that come from knowing the study purpose, so observers are less likely to be biased in a particular way.
You can implement masking by involving other people in your studies as observers and giving them a cover story to mislead them about the true purpose of your study.
Triangulation means using multiple observers, information sources, or research methods to make sure your findings are credible . It’s always a good idea to use triangulation to corroborate your measurements and check that they line up with each other.
To reduce observer bias, it’s especially important to involve multiple observers and to try to use multiple data collection methods for the same observations. When the data from different observers or different methods converge, you reduce the risk of bias and can feel more confident in your results.
With more than one observer, you make sure that your data are consistent and unlikely to be skewed by any single observer’s biases.
When you have multiple observers , it’s important to check and maintain high interrater reliability. Interrater reliability refers to how consistently multiple observers rate the same observation.
With quantitative data , you can compare data from multiple observers, calculate interrater reliability, and set a threshold that you want to meet. Usually, you train observers in the procedures until they can consistently produce the same or similar observations for every event in training sessions.
Before you start any study, it’s a good idea to train all observers to make sure everyone collects and records data in exactly the same way.
It’s important to calibrate your methods so that there’s very little or no variation in how different observers report the same observation. You can recalibrate your procedures between observers at various points in the study to keep interrater reliability high and minimize observer drift as well.
It’s best to create standardized procedures or protocols that are structured and easy to understand for all observers. For example, if your study is about behaviors, make sure to specify all behaviors that observers should note.
Record these procedures (in videos or text) so you can refer back to them at any point in the research process to refresh your memory.
Observer bias is closely related to several other types of research bias.
The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.
Researchers may unintentionally signal their own beliefs and expectations about the study and influence participants through demand characteristics .
The observer-expectancy effect also goes by other names:
The actor–observer bias is an attributional bias where you tend to attribute the cause of something differently depending on whether you’re the actor or observer in that situation.
As an actor in a situation, you may tend to attribute your own behavior to external factors. As an observer, you may instead attribute another person’s behavior, even if it’s the same as yours, to internal factors. The actor–observer bias is a social psychological topic.
The Hawthorne effect refers to some research participants’ tendency to work harder in order to perform better when they believe they’re being observed. It describes what participants being observed may inadvertently do in a study.
The Hawthorne effect is named after Hawthorne Works, a company where employee productivity supposedly improved, regardless of the experimental treatment , due to the presence of observers.
Experimenter bias covers all types of biases from researchers that may influence their studies. This includes observer bias, observer expectancy effects, actor–observer bias, and other biases. Experimenter bias is also called experimenter effect.
Cognitive bias
Selection bias
Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. This type of research bias is also called detection bias or ascertainment bias .
It’s impossible to completely avoid observer bias in studies where data collection is done or recorded manually, but you can take steps to reduce this type of bias in your research .
You can use several tactics to minimize observer bias .
Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics .
The observer-expectancy effect is often used synonymously with the Pygmalion or Rosenthal effect .
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Observer bias is a type of experimenter bias that occurs when a researcher’s expectations, perspectives, opinions, or prejudices impact the results of an experiment. This type of research bias is also called detection bias or ascertainment bias.
This typically occurs when a researcher is aware of the purpose and hypotheses of a study and holds expectations about what will happen.
If a researcher is trying to find a particular result to support the hypothesis of the study or has a predetermined idea of what the results should be, they will have the incentive to twist the data to make them more in line with their predictions.
This bias occurs most often in observational studies or any type of research where measurements are taken and recorded manually. In observational studies, a researcher records behaviors or takes measurements from participants without trying to influence the outcome of the experiment.
Observational studies are used in a number of different research fields, most specifically medicine, psychology, behavioral science, and ethnography.
You are performing an observational study to investigate the effects of a new medication to treat nausea. Group A receives the actual treatment with the new medication, while group B receives a placebo.
The participants do not know which group they are a part of, but you – the researcher – do.
Unconsciously, you treat the two groups differently, framing questions more negatively towards Group B and commenting that those in Group A seem more energized and upbeat.
Observer bias can result in misleading and unreliable results. A researcher’s biases and prejudices can affect data collection and observer interpretation, leading to results that fail to represent accurately what exists in reality.
It might also result in inaccurate data sets, misleading information, or biased treatment from researchers.
Observer bias can damage scientific research and policy decisions and lead to negative outcomes for people involved in the research studies.
Subjective methods.
Subjective research methods are those that involve some type of interpretation before you record the observations. Subjectivity refers to the way research is influenced by the perspectives, values, emotions, social experiences, and viewpoints of the researcher.
This could lead a researcher to record some observations as relevant while ignoring other equally important observations.
Even if a researcher is subconsciously primed to see only what they expect to observe, subjective research methods could lead to skewed conclusions.
Although objective research tends to be impartial and fact-based, observer bias might still influence studies that use more objective methods.
This is because researchers tend to interpret or record readings differently, skewing the results to be more in line with their predictions.
For example, when measuring blood pressure using a blood pressure monitor, a researcher might round up the blood pressure to the nearest whole number.
Or, due to familiarity with the procedures of measuring blood pressure, a researcher might be less careful when taking the measurements and thus record inaccurate results.
Blinding, or masking, ensures that the participants and researchers are all unsure of the goals of the study.
This will help eliminate some of the research expectations that come from knowing the study’s purpose so observers are less likely to be biased.
Additionally, in double-blind studies , neither the researchers nor the subjects know which treatments are being used or which group they belong to.
Randomly assigning subjects to groups instead of choosing the subjects themselves will help minimize observer bias.
Having multiple researchers involved in the research study will ensure that your data is consistent and make it less likely that one researcher’s biases will significantly affect the project’s outcome.
It can also be beneficial to use multiple data collection methods for the same observations to corroborate your findings and check that they line up with each other.
Before beginning a study, it is beneficial to train all observers in the procedures to ensure everyone collects and records data exactly the same way.
This will eliminate any variation in how different observers report the same observation, keeping interrater reliability high and minimizing observer bias.
It is important to create standardized procedures or protocols that are easy for all observers to follow.
You can record these procedures so that the researchers can refer back to them at any point in the research process.
Observer bias is closely related to several other types of research bias.
The observer-expectancy effect occurs when a researcher’s cognitive bias causes them to subconsciously influence the results of their own study through interactions with participants.
Researchers might unconsciously or deliberately treat certain subjects differently, leading to unequal results between groups.
For example, a researcher might ask different questions or give different directions to one group and not another, or influence certain participants’ behavior by changing their body language, posture, tone of voice, or appearance in certain ways.
Actor-observer bias is an attributional bias where a researcher attributes their own actions to external factors while attributing other people’s behaviors to internal causes.
This bias can help explain why we are inclined to blame others for things that happen, even when we would not blame ourselves for acting in the same way.
For example, if you perform poorly on a test, you might blame the result on external factors such as teacher bias or the questions being harder than usual.
However, if a classmate fails the same test, you might attribute their failure to a lack of intelligence or preparation.
The Hawthorne effect refers to some participants’ tendency to work harder and perform better when they know they are being observed.
This effect also suggests that individuals may change their behavior due to the attention they are receiving from researchers rather than because of any manipulation of independent variables.
Experimenter bias is any type of cognitive bias that occurs when experimenters allow their expectations to affect their interpretation of observations.
Experimenter bias typically refers to all types of biases from researchers that might influence a study, including observer bias, the observer-expectancy effect, actor-observer bias, and the Hawthorne effect.
When a researcher has a predetermined idea of the results of their study, they might conduct the study or record results in a way that confirms their theory.
Observer bias is a type of experimenter bias where a researcher’s predetermined expectations, perspectives, opinions, or prejudices can impact the results of an experiment.
Confirmation bias is a type of cognitive bias that occurs when a researcher favors information or interprets findings to favor their existing beliefs.
Unlike observer bias which can be intentional in some instances, confirmation bias happens due to the natural way our brains work, so it cannot be eliminated.
The observer effect in psychology is also known as the Hawthorne effect. It refers to how people change their behavior when they know they are being observed in a study.
Observer bias is a related term in the social sciences that refers to the error that results from an observer’s cognitive biases, particularly when observers overemphasize behavior they expect to find and fail to notice behavior they do not expect.
The observer effect is not to be confused with the observer-expectancy effect or the actor-observer bias, discussed above.
Burghardt, G. M., Bartmess‐LeVasseur, J. N., Browning, S. A., Morrison, K. E., Stec, C. L., Zachau, C. E., & Freeberg, T. M. (2012). Perspectives–minimizing observer bias in behavioral studies: a review and recommendations . Ethology , 118 (6), 511-517.
Hróbjartsson, A., Thomsen, A. S. S., Emanuelsson, F., Tendal, B., Hilden, J., Boutron, I., … & Brorson, S. (2013). Observer bias in randomized clinical trials with measurement scale outcomes: a systematic review of trials with both blinded and nonblinded assessors . Cmaj , 185 (4), E201-E211.
Salvia, J. A., & Meisel, C. J. (1980). Observer bias: A methodological consideration in special education research. The Journal of Special Education , 14 (2), 261-270.
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How scientific is cognitive load theory research compared to the rest of educational psychology.
1.1. overview, 1.2. causal conclusions and recommendations for practice, 1.3. the present review, 2.1. journal selection and search process, 2.2. coding and analysis, 3.1. research designs, 3.2. recommendations for practice, 4. discussion, 4.1. limitations and future directions, 4.2. conclusions, author contributions, conflicts of interest.
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Authors | Journal | Method | Recommendations for Practice? |
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2020 | |||
Bichler et al. [ ] | Journal of Educational Psychology | Experimental | -- |
de Koning et al. [ ] | Contemporary Educational Psychology | Experimental | -- |
Merkt et al. [ ] | Journal of Educational Psychology | Experimental | -- |
Miller-Cotto & Byrnes [ ] | Journal of Educational Psychology | Observational/ Correlational | No |
Schneider et al. [ ] | Journal of Educational Psychology | Experimental | -- |
Zu et al. [ ] | Journal of Educational Psychology | Experimental | -- |
2023 | |||
Buchin & Mulligan [ ] | Journal of Educational Psychology | Experimental | -- |
Ehrhart & Lindner [ ] | Contemporary Educational Psychology | Experimental | -- |
Hoch et al. [ ] | Educational Psychology Review | Experimental | -- |
Martin et al. [ ] | Contemporary Educational Psychology | Observational/ Correlational | No |
Park el al. [ ] | Educational Psychology Review | Experimental | -- |
Pengelley et al. [ ] | Educational Psychology Review | Experimental | -- |
Rau & Beier [ ] | Journal of Educational Psychology | Intervention | -- |
Sondermann & Merket [ ] | Contemporary Educational Psychology | Experimental | -- |
Wang et al. [ ] | Journal of Educational Psychology | Experimental | -- |
Yang et al. [ ] | Journal of Educational Psychology | Experimental | -- |
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Martella, A.M.; Lawson, A.P.; Robinson, D.H. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology? Educ. Sci. 2024 , 14 , 920. https://doi.org/10.3390/educsci14080920
Martella AM, Lawson AP, Robinson DH. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology? Education Sciences . 2024; 14(8):920. https://doi.org/10.3390/educsci14080920
Martella, Amedee Marchand, Alyssa P. Lawson, and Daniel H. Robinson. 2024. "How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?" Education Sciences 14, no. 8: 920. https://doi.org/10.3390/educsci14080920
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The observation method in psychology involves directly and systematically witnessing and recording measurable behaviors, actions, and responses in natural or contrived settings without attempting to intervene or manipulate what is being observed. Used to describe phenomena, generate hypotheses, or validate self-reports, psychological observation can be either controlled or naturalistic with ...
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 ...
An observational study is used to answer a research question based purely on what the researcher observes. There is no interference or manipulation of the research subjects, and no control and treatment groups. These studies are often qualitative in nature and can be used for both exploratory and explanatory research purposes.
Observation research is a powerful method in psychology, allowing researchers to gather data in natural settings and gain insights that might otherwise be inaccessible. By following these guidelines, from choosing the right type of observation to effectively analyzing and reporting data, you can enhance the validity and reliability of your ...
Observational method is the basic research method of psychology that determines the psychological characteristics of an observed person by purposefully and systematically observing and recording his or her speech and behavior. Observational method has long been adopted by people. Confucius said, "It used to be that with people, when I heard ...
Observational methods in psychological research entail the observation and description of a subject's behavior. Researchers utilizing the observational method can exert varying amounts of control over the environment in which the observation takes place. This makes observational research a sort of middle ground between the highly controlled ...
Systematic observational methods have been a common technique employed by psychologists studying human and animal behavior since the inception of our field, and yet best practices for the use of observational instruments (see Table 15.1) are often not known or adopted by researchers in our field.As such, the quality of observational research varies widely, and thus, it is our goal in the ...
Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering with or influencing any variables in a naturalistic observation. You can think of naturalistic observation as "people watching" with a purpose. Note.
Olivia Guy-Evans, MSc. Research methods in psychology are systematic procedures used to observe, describe, predict, and explain behavior and mental processes. They include experiments, surveys, case studies, and naturalistic observations, ensuring data collection is objective and reliable to understand and explain psychological phenomena.
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. ... Psychology: Observational research is ...
Observational psychology is an interdisciplinary system of study that usually falls under the banner of the psychology of learning. The psychology of learning is a particular branch of psychological study that attempts to draw conclusions about how people learn, what it means to learn a behavior, and how this understanding of learning can be ...
Naturalistic observation is a research method that involves observing subjects in their natural environment. This approach is often used by psychologists and other social scientists. It is a form of qualitative research, which focuses on collecting, evaluating, and describing non-numerical data. It can be useful if conducting lab research would ...
Observation in qualitative research "is one of the oldest and most fundamental research methods approaches. This approach involves collecting data using one's senses, especially looking and listening in a systematic and meaningful way" (McKechnie, 2008, p. 573).Similarly, Adler and Adler (1994) characterized observations as the "fundamental base of all research methods" in the social ...
Introduction. Observational studies involve the study of participants without any forced change to their circumstances, that is, without any intervention.1 Although the participants' behaviour may change under observation, the intent of observational studies is to investigate the 'natural' state of risk factors, diseases or outcomes. For drug therapy, a group of people taking the drug ...
2.1 Introduction. Observation is one of the most important research methods in social sci-. ences and at the same time one of the most diverse. e term includes. several types, techniques, and ...
Naturalistic observation is a psychological research method that involves observing and recording behavior in the natural environment. Unlike experiments, researchers do not manipulate variables. This research method is frequently used in psychology to help researchers investigate human behavior. This article explores how naturalistic ...
Cross-Sectional vs. Longitudinal. A cross-sectional study design is a type of observational study, or descriptive research, that involves analyzing information about a population at a specific point in time. This design measures the prevalence of an outcome of interest in a defined population. It provides a snapshot of the characteristics of ...
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 ...
Observational studies are used in many research fields, including medicine, psychology, behavioral science, and ethnography. Observer bias can occur regardless of whether you use qualitative or quantitative research methods. Subjective methods. Subjective research methods involve some type of interpretation before you record the observations.
Observer Bias: Definition, Examples & Prevention. Observer bias is a type of experimenter bias that occurs when a researcher's expectations, perspectives, opinions, or prejudices impact the results of an experiment. This type of research bias is also called detection bias or ascertainment bias. This typically occurs when a researcher is aware ...
Cognitive load theory (CLT) has driven numerous empirical studies for over 30 years and is a major theme in many of the most cited articles published between 1988 and 2023. However, CLT articles have not been compared to other educational psychology research in terms of the research designs used and the extent to which recommendations for practice are justified. As Brady and colleagues found ...