When we conduct experiments, there are other variables that can affect our results if we do not control them.
Anything that is not the independent variable that has the potential to affect the results is called an extraneous variable.
It can be a natural characteristic of the participant, such as intelligence level, gender, or age. Or it could be a feature of the environment, such as lighting or noise.
Key Takeaways
- Definition: Any variable other than the independent variable (IV) that could affect the dependent variable (DV), such as noise, lighting, or a participant’s mood.
- Extraneous vs Confounding: An extraneous variable only becomes a problem once it varies systematically with the IV. At that point it becomes a confounding variable, offering a rival explanation for the results.
- Participant Variables: Individual differences such as age, mood, or intelligence can differ between participants and are mainly controlled through random allocation.
- Situational Variables: Features of the environment or procedure, such as noise or the wording of instructions, are controlled through standardisation and counterbalancing.
- Investigator Effects: A researcher’s own expectations can unconsciously bias how they treat participants or interpret results. Double-blind procedures, where neither party knows the condition, help prevent this.
- Demand Characteristics: Participants often pick up cues about a study’s purpose and change their behaviour to match or defy it. Single-blind procedures reduce this risk.
Why Control Extraneous Variables
The researcher wants to make sure that it is the manipulation of the independent variable that has an effect on the dependent variable.
Hence, all the other variables that could affect the dependent variable must be controlled. These other variables are called extraneous variables.
Left uncontrolled, they threaten a study’s internal validity, our confidence that the IV caused any change in the DV. An extraneous variable turns dangerous once it tracks the IV. At that point it turns into a confounding variable, offering a rival explanation for the results.
Types of Extraneous Variables
1. Situational Variables
Situational variables are factors, conditions, or characteristics in the external environment that can influence behavior, decision-making, or outcomes. They are called “situational” because they belong to the context, not to a stable personal trait like personality.
Examples include physical aspects of the environment, such as weather, location, time of day, or noise level. Social aspects count too.
These include the presence of others, group dynamics, or societal norms, as well as more abstract factors like time pressure, level of risk, or unclear instructions. Situational variables should be controlled so they are the same for all participants.
Standardized procedures keep conditions the same for every participant. This means using the same instructions, timing, and testing environment for everyone.
2. Participant Variable
Participant variables are the individual differences between participants that could affect the results, such as mood, intelligence, anxiety, nerves, or concentration. They matter most in independent-groups designs.
For example, a tired or dyslexic participant with poor eyesight might perform worse on a memory test, regardless of the independent variable. The experimental design chosen can affect how much these differences matter.
Repeated-measures designs raise a related problem. This is called an order effect: practice can improve performance, or fatigue can worsen it, depending on the order conditions are completed in.
Counterbalancing controls this by varying that order, such as giving half the participants condition “A” first and the other half condition “B” first.
Participant variables are mainly controlled using random allocation to the conditions of the independent variable.
3. Experimenter / Investigator Effects
The experimenter can unconsciously convey how participants should behave, a bias known as experimenter bias. Subtle, unintentional clues about the study’s purpose can shape how participants respond, even when the experimenter has no idea they are giving them.
Rosenthal and Fode (1963) tested this directly. Students who were told they were running “maze-bright” rats got better results than students told they had “maze-dull” rats. In fact, the rats had been assigned to each group at random.
The rats hadn’t changed. What changed was how the experimenters handled and scored them, shaped entirely by their own expectations.
The experimenter’s own personal attributes, such as age, gender, accent, or manner, can also affect how participants behave.
4. Demand Characteristics
Demand characteristics are the clues in an experiment that reveal its purpose to participants. Participants rarely stay passive.
Orne (1962) argued that some try to guess what the researcher wants and give it to them, a pattern he called the “good subject” effect. Others deliberately do the opposite.
Many act from “evaluation apprehension,” behaving as they think they should be seen to behave, rather than as the independent variable dictates. Either way, participants are reacting to the situation, not to the independent variable. That reaction can look like a real effect.
Participants are affected by their surroundings, the researcher’s characteristics and behavior (such as non-verbal communication), and their own interpretation of what is going on. Good controls limit this.
Experimenters can minimize these factors by keeping the environment as natural as possible and carefully following standardized procedures. Using different experimenters to see if they obtain similar results is another safeguard.
Suppose we wanted to measure the effects of Alcohol (IV) on driving ability (DV). We would have to ensure that extraneous variables did not affect the results. These variables could include the following:
- Familiarity with the car: Some people may drive better because they have driven this make of car before.
- Familiarity with the test: Some people may do better than others because they know what to expect on the test.
- Used to drinking: The effects of alcohol on some people may be less than on others because they are used to drinking.
- Full stomach: The effect of alcohol on some subjects may be less than on others because they have just had a big meal.
If these extraneous variables are not controlled, they may become confounding variables because they could go on to affect the results of the experiment.
References
Orne, M. T. (1962). On the social psychology of the psychological experiment: With particular reference to demand characteristics and their implications. American Psychologist, 17(11), 776–783.
Rosenthal, R., & Fode, K. L. (1963). The effect of experimenter bias on the performance of the albino rat. Behavioral Science, 8(3), 183–189.
