Published on May 8, 2020 by Pritha Bhandari. Revised on October 10, 2022. 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. In qualitative studies, external validity is referred to as transferability. There are two main types of external validity: population validity and ecological 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. You recruit over 200 participants. They are science and engineering majors; most of them are American, male, 18–20 years old and from a high socioeconomic background. In a laboratory setting, you administer a mathematics and science test and then ask them to rate how well they think performed. You find that the average participant believes they are smarter than 66% of their peers. Can you conclude that most people believe themselves to be much better than others at maths and science? 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 validityEcological validity refers to whether you can reasonably generalize the findings of a study to other situations and settings in the ‘real world’. Example: low ecological validityYou want to test the hypothesis that driving reaction times become slower when people pay attention to others talking.In a laboratory setting, you set up a simple computer-based task to measure reaction times. Participants are told to imagine themselves driving around the racetrack and double-click the mouse whenever they see an orange cat on the screen. For one round, participants listen to a podcast. In the other round, they do not need to listen to anything. After assessing the results, you find that reaction times are much slower when listening to the podcast. Can you conclude that driving reaction times are slower when people listen to others talking? 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 validityInternal 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. Internal vs. external validity exampleIn the driving reaction times study, you are able to control the conditions of the experiment and ensure that there are no extraneous factors that could explain the outcome. Because the experiment has high internal validity, you can confidently conclude that listening to the podcast causes slower reaction times.Moving the experiment to a real-life driving course significantly increases external validity at the expense of internal validity. That’s because you risk introducing extraneous and confounding factors (e.g. weather or visibility conditions) that affect the outcome. Receive feedback on language, structure and formattingProfessional editors proofread and edit your paper by focusing on:
See an example  Threats to external validity and how to counter themThreats to external validity are important to recognize and counter in a research design for a robust study. Research exampleA researcher wants to test the hypothesis that people with clinical diagnoses of mental disorders can benefit from practicing mindfulness daily in just two months time. They recruit people who have been diagnosed with depression for at least a year, are aged between 20–29, and live locally.Participants are given a pretest and a post-test measuring how often they experienced anxiety in the past week. During the study, all participants are given an individual mindfulness training and asked to practice mindfulness daily for 15 minutes in the morning. Since the levels of anxiety decreased between the pre- and post-test, the researcher concludes that all clinical populations can benefit from mindfulness. Threats to external validity
How to counter threats to external validityThere are several ways to counter threats to external validity:
Frequently asked questions about external validityCite this Scribbr articleIf 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.
Is this article helpful?You have already voted. Thanks :-) Your vote is saved :-) Processing your vote... What is the best way to ensure that results of a study are generalizable to population?Use random sampling. If the sample is truly random (i.e., everyone in the population is equally likely to be chosen for the sample), then you can avoid sampling bias and ensure that the sample will be representative of the population.
What is Generalisability in research?Generalisability is the extent to which the findings of a study can be applied to other situations. Generalisability can be divided into population generalisability, environmental generalisability and temporal generalisability.
Which of the following are types of sampling that are generalizable?Sampling techniques can be grouped into two broad categories: probability (random) sampling and non-probability sampling. Probability sampling is ideal if generalizability of results is important for your study, but there may be unique circumstances where non-probability sampling can also be justified.
How can quantitative research generalize an entire population?For quantitative research to be generalizable to a larger population, a probability sampling method must be used. The most basic probability sampling method is simple random sampling, in which the people to be studied are selected from the complete sampling frame only by chance.
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