External Validity

September 26, 2019

Explain what is meant by the term "External validity"
External validity is the validity of applying the conclusions of a scientific study outside the context of that study. In other words, it is the extent to which the results of a study can be generalized to and across other situations, people, stimuli, and times. The purpose of the research is to say something about the real world. But how can a researcher generalize results to the world at large? In this lesson, we'll answer that question as we learn about external validity. Internal and external validity are concepts that reflect whether or not the results of a study are trustworthy and meaningful. While internal validity relates to how well a study is conducted (its structure), external validity relates to how applicable the findings are to the real world.
External Validity
External validity refers to how well the outcome of a study can be expected to apply to other settings. In other words, this type of validity refers to how generalizable the findings are. For instance, do the findings apply to other people, settings, situations, and time periods?
Ecological validity, an aspect of external validity, refers to whether a study's findings can be generalized to the real world.
While rigorous research methods can ensure internal validity, external validity, on the other hand, maybe limited by these methods.
Another term called transferability relates to external validity and refers to a qualitative research design. Transferability refers to whether results transfer to situations with similar characteristics.
Factors that Improve External Validity
What can you do to improve the external validity of your study? Inclusion and exclusion criteria should be used to ensure that you have clearly defined the population that you are studying in your research. Psychological realism refers to making sure that participants are experiencing the events of a study as a real event and can be achieved by telling them a "cover story" about the aim of the study. Otherwise, in some cases, participants might behave differently than they would in real life if they know what to expect or know what the aim of the study is. Replication refers to conducting the study again with different samples or in different settings to see if you get the same results. When many studies have been conducted, meta-analysis can also be used to determine if the effect of an independent variable is reliable (based on examining the findings of a large number of studies on one topic). Field experiments can also be used in which you conduct a study outside the laboratory in a natural setting. Reprocessing or calibration refers to using statistical methods to adjust for problems related to external validity. For example, if a study had uneven groups for some characteristic (such as age), reweighting might be used.
Factors That Threaten External Validity
External validity is threatened when a study does not take into account the interactions of variables in the real world. Situational factors such as time of day, location, noise, researcher characteristics, and how many measures are used may affect the generalizability of findings. Pre- and post-test effects refer to the situation in which the pre- or post-test is in some way related to the effect seen in the study, such that the cause-and-effect relationship disappears without these added tests. Sample features refer to the situation in which some feature of the particular sample was responsible for the effect (or partially responsible), leading to limited generalizability of the findings. Selection bias refers to the problem of differences between groups in a study that may relate to the independent variable (once again, something like motivation or willingness to take part in the study, specific demographics of individuals being more likely to take part in an online survey). This can also be considered a threat to internal validity.
What are the similarities between internal and external validity? They are both factors that should be considered when designing a study, and both have implications in terms of whether the results of a study have meaning. Both are not "either/or" concepts, and so you will always be deciding to what degree your study performs in terms of both types of validity. Each of these concepts is typically reported in a research article that is published in a scholarly journal. This is so that other researchers can evaluate the study and make decisions about whether the results are useful and valid.
The essential difference between internal and external validity is that internal validity refers to the structure of a study and its variables while external validity relates to how universal the results are. There are further differences between the two as well.
An example of a study with good external validity would be in the above example, the researcher also ensured that the study had external validity by having participants use the app at home rather than in the laboratory. The researcher clearly defines the population of interest and choosing a representative sample, and he/she replicates the study for different technological devices.
A Word From Verywell
Setting up an experiment so that it has sound internal and external validity involves being mindful from the start about factors that can influence each aspect of your research. It's best to spend extra time designing a structurally sound study that has far-reaching implications rather than to quickly rush through the design phase only to discover problems later on. Only when both internal and external validity is high can strong conclusions be made about your results.

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