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. Internal validity is the extent to which a study establishes a trustworthy cause-and-effect relationship between a treatment and an outcome. Internal validity also reflects that a given study makes it possible to eliminate alternative explanations for a finding. For example, if you implement a smoking cessation program with a group of individuals, how sure can you be that any improvement seen in the treatment group is due to the treatment that you administered?
Internal validity depends largely on the procedures of a study and how rigorously it is performed. Internal validity is not a "yes or no" type of concept. Instead, we consider how confident we can be with the findings of a study, based on whether it avoids traps that may make the findings questionable. The less chance there is for "confounding" in a study, the higher the internal validity and the more confident we can be in the findings. Confounding refers to a situation in which other factors come into play that confuses the outcome of a study. For instance, a study might make us unsure as to whether we can trust that we have identified the above "cause-and-effect" scenario. In short, you can only be confident that your study is internally valid if you can rule out alternative explanations for your findings. As a brief summary, you can only assume cause-and-effect when you meet the following three criteria in your study:
If you are looking to improve the internal validity of a study, you will want to consider aspects of your research design that will make it more likely that you can reject alternative hypotheses. There are many factors that can improve internal validity.
Just as there are many ways to ensure that a study is internally valid, there is also a list of potential threats to internal validity that should be considered when planning a study.
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, may be 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. What can you do to improve the external validity of your study?
External validity is threatened when a study does not take into account the interactions of variables in the real world.
Internal and external validity are like two sides of the same coin. You can have a study with good internal validity, but overall it could be irrelevant to the real world. On the other hand, you could conduct a field study that is highly relevant to the real world, but that doesn't have trustworthy results in terms of knowing what variables caused the outcomes that you see. 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.
Internal Validity
External Validity
Internal validity focuses on showing a difference that is due to the independent variable alone, whereas external validity results can be translated to the world at large. An example of a study with good internal validity would be if a researcher hypothesizes that using a particular mindfulness app will reduce negative mood. To test this hypothesis, the researcher randomly assigns a sample of participants to one of two groups: those who will use the app over a defined period, and those who engage in a control task. The researcher ensures that there is no systematic bias in how participants are assigned to the groups, and also blinds his research assistants to the groups the students are in during experimentation. A strict study protocol is used that outlines the procedures of the study. Potential confounding variables are measured along with mood, such as the participants socioeconomic status, gender, age, among other factors. If participants drop out of the study, their characteristics are examined to make sure there is no systematic bias in terms of who stays in the study. 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. 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 are high can strong conclusions be made about your results. |