There are many things that can influence a study along the way. Especially research bias is a topic that should be addressed in this case because warped results always make your study unreliable and in the worst case worthless. One type of bias is especially important, as it impacts the researcher as well as the participants. This type is called observer bias, which will be explained thoroughly in the following article.
Definition: Observer bias
Observer bias is when observers tend to see not what is there, but what they want or expect. As a result, it leads to a systematic difference between the actual value and the observed one. This divergence typically stems from a researcher’s conscious or unconscious prejudices. When this type of research bias manifests, it can lead a scientific inwaistcoatigator to portray findings that stray from genuine accuracy and verity.
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Impact
The impact of observer bias can influence the researcher as well as the participants in their perception of a situation. This can lead to misinterpreted information and an inaccuracy in the description of reality. If the answers of the participants do not match the actual situation, the researcher will draw wrong conclusions that can affect the measurements taken based on the results.
Source
The source of observer bias is of course the humans themselves. Although it might be evident that observer bias will influence subjective methods, objective ones can also autumn victim to this type of research bias.
- Subjective research methods, especially in behavioural science, require of an interpretation to produce results, which means they are prone to bias. Every researcher has their own way of weighting events, which greatly influences the results of their observations.
- Objective methods seem to have a less high probability of being biased. However, as there are still humans conducting the study, even objective studies can end up biased, if the researchers are not equally strict in measuring.
Prevent observer bias
Many types of research bias are impossible to avoid completely. This is also the case for observer bias. However, there are a few measurements that can be taken to minimize the risk of observer bias in your study.
- Blind or double-blind your study. This means that the researcher and the participants do not know who is in the treatment and control group. This way, the researcher’s expectations cannot influence biased treatment or their perception of the results.
- Use triangulation. This means that the researcher will use different methods to achieve certain information by exploring different datasets, methods, theories, etc. The more sources there are, the less likely it becomes that a study becomes biased.
- Multiple observers. One person can easily be influenced by bias without noticing. However, if more people observe the same scenario, each of them can compare their findings to the others, making them aware of different opinions and biases.
- Standardize procedures. If procedures are standardized and every researcher follows the same protocol or set of questions, the possibility of introducing bias is reduced.
- Random sampling. Sampling your participants randomly can also minimize the influence of observer bias because this helps blind the study.
- Specially training study observers. To further reduce observer bias, you can train the observers to be more aware of what influences their perception and what impact their prejudices have on the study. This can help them realise the bias while observing and staying more objective.
- Be diligent in your evaluation. After conducting the observation, make sure to double-check your notes and replay the whole scenario in your head. Sometimes you may be able to reflect on your own biased view.
Observer bias: Examples
Example 1: The case of the clever horse
Example 2: The case of the dull rats
Types of observer bias
The types of observer bias include:
- The observer-expectancy effect is usually used in a research context to describe how the observer’s perceived expectations subconsciously influence the study participants’ behaviour.
- This effect may include influences on participants’ behaviour, including the creation of demand characteristics that affect the participants or selective recording of the research data.
- The observer-expectancy effect is also known as expectancy bias or the Pygmalion effect.
- The actor-observer bias is a bias when one tends to attribute the causes of actions differently depending on whether they are an observer or an actor.
- As the actor, one’s behaviour is attributed to external factors, while as an observer, the behaviour of others is attributed to internal factors.
- It is an attributional bias that influences how we interact with and perceive others.
- This bias is mainly caused by the difficulty actors have in seeing their situation objectively, while as an observer, they can view a situation with perspective.
- It is also known as actor-observer asymmetry.
- The Hawthorne effect describes how a study’s participants alter their behaviour when they know they are being observed.
- This effect was discovered through research conducted at the Hawthorne Western Electric Plant (which is how it came to be named).
- The original research was initially designed to observe the effects of floor lighting on workers’ productivity. However, their productivity increased when the lighting was diminished and improved and when the researchers also changed other variables.
- They discovered that the increase in productivity was not because of a change in lighting but the increased attention from their supervisors.
Experimenter bias
Experimenter bias is a broad term used to cover the different types of biases that influence researchers in their studies. These biases include the actor-observer bias and the observer expectancy effect, among others.
FAQs
No, you cannot. It is impossible to avoid observer bias entyrely, especially in studies where data is collected manually, but there are ways to minimize it as much as possible.
Researchers can minimize observer bias by standardized training of observers, using blinded protocols, identifying any potential conflicts of interest, and doing continued monitoring of objectivity in observers.
A researcher who has taken no steps to minimize this bias is more likely to misinterpret data. Observer bias has been shown to affect the validity of the results of studies significantly.
The Hawthorne effect describes a type of observer bias where the participants’ behaviour changes after realising they are being observed.