External Validity | Definition, Types, Threats & Examples
External validity is the extent to which you can generalize the findings of a study to other situations, people, settings, and measures. In other words, can you apply the findings of your study to a broader context?
The aim of scientific research is to produce generalizable knowledge about the real world. Without high external validity, you cannot apply results from the laboratory to other people or the real world. These results will suffer from research biases like undercoverage bias.
In qualitative studies, external validity is referred to as transferability.
Types of external validity
There are two main types of external validity: population validity and ecological validity.
Population validity
Population validity refers to whether you can reasonably generalize the findings from your sample to a larger group of people (the population).
Population validity depends on the choice of population and on the extent to which the study sample mirrors that population. Non-probability sampling methods are often used for convenience. With this type of sampling, the generalizability of results is limited to populations that share similar characteristics with the sample.
Here, your sample is not representative of the whole population of students at your university. The findings can only reasonably be generalized to populations that share characteristics with the participants, e.g. college-educated men and STEM majors.
For higher population validity, your sample would need to include people with different characteristics (e.g., women, non-binary people, and students from different majors, countries, and socioeconomic backgrounds).
Samples like this one, from Western, Educated, Industrialized, Rich and Democratic (WEIRD) countries, are used in an estimated 96% of psychology studies, even though they represent only 12% of the world’s population. Since they are outliers in terms of visual perception, moral reasoning and categorization (among many other topics), WEIRD samples limit broad population validity in the social sciences.
Ecological validity
Ecological validity refers to whether you can reasonably generalize the findings of a study to other situations and settings in the ‘real world’.
In the example above, it is difficult to generalize the findings to real-life driving conditions. A computer-based task using a mouse does not resemble real-life driving conditions with a steering wheel. Additionally, a static image of an orange cat may not represent common real-life hurdles when driving.
To improve ecological validity in a lab setting, you could use an immersive driving simulator with a steering wheel and foot pedal instead of a computer and mouse. This increases psychological realism by more closely mirroring the experience of driving in the real world.
Alternatively, for higher ecological validity, you could conduct the experiment using a real driving course.
Trade-off between external and internal validity
Internal validity is the extent to which you can be confident that the causal relationship established in your experiment cannot be explained by other factors.
There is an inherent trade-off between external and internal validity; the more applicable you make your study to a broader context, the less you can control extraneous factors in your study.
Threats to external validity and how to counter them
Threats to external validity are important to recognize and counter in a research design for a robust study.
Threat | Meaning | Example |
---|---|---|
Sampling bias | The sample is not representative of the population. | The sample includes only people with depression. They have characteristics (e.g., negative thought patterns) that may make them very different from other clinical populations, like people with personality disorders or schizophrenia. |
History | An unrelated event influences the outcomes. | Right before the pre-test, a natural disaster takes place in a neighbouring state. As a result, pre-test anxiety scores are higher than they might be otherwise. |
Observer bias | The characteristics or behaviors of the experimenter(s) unintentionally influence the outcomes, leading to bias and other demand characteristics. | The trainer of the mindfulness sessions unintentionally stressed the importance of this study for the research department’s funding. Participants work extra hard to reduce their anxiety levels during the study as a result. |
Hawthorne effect | The tendency for participants to change their behaviors simply because they know they are being studied. | The participants actively avoid anxiety-inducing situations for the period of the study because they are conscious of their participation in the research. |
Testing effect | The administration of a pre- or post-test affects the outcomes. | Because participants become familiar with the pre-test format and questions, they are less anxious during the post-test and remember less anxiety then, leading to recall bias. |
Aptitude-treatment | Interactions between characteristics of the group and individual variables together influence the dependent variable. | Interactions between certain characteristics of the participants with depression (e.g., negative thought patterns) and the mindfulness exercises (e.g., focus on the present) improve anxiety levels. The findings are not replicated with people with personality disorders or schizophrenia. |
Situation effect | Factors like the setting, time of day, location, researchers’ characteristics, etc. limit generalizability of the findings. | The study is repeated with one change; the participants practice mindfulness at night rather than in the morning. The outcomes do not show any improvement this time. |
How to counter threats to external validity
There are several ways to counter threats to external validity:
- Replications counter almost all threats by enhancing generalizability to other settings, populations and conditions.
- Field experiments counter testing and situation effects by using natural contexts.
- Probability sampling counters selection bias by making sure everyone in a population has an equal chance of being selected for a study sample.
- Recalibration or reprocessing also counters selection bias using algorithms to correct weighting of factors (e.g., age) within study samples.
Other interesting articles
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.
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Frequently asked questions about external validity
- What is external validity?
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The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.
- What is the difference between internal and external validity?
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Internal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables.
External validity is the extent to which your results can be generalized to other contexts.
The validity of your experiment depends on your experimental design.
- What are threats to external validity?
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There are seven threats to external validity: selection bias, history, experimenter effect, Hawthorne effect, testing effect, aptitude-treatment and situation effect.
- What are the two types of external validity?
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The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).
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