The goal of external validity is to assure that the results of a study are generalizable.
True
False
The correct answer and explanation is:
True
External validity refers to the extent to which the results of a study can be generalized to, or have relevance for, settings, people, times, or situations beyond the study itself. The goal is to ensure that the findings are not limited to the specific sample, location, or conditions used in the research, but can be applied to broader contexts.
In scientific research, studies are often conducted under controlled conditions with specific groups of participants. This controlled environment is important for internal validity because it helps isolate the effects of the variables being studied. However, if a study is too narrowly focused, its findings may only apply to the specific group or setting involved in the study, limiting the broader applicability of the results.
For example, a clinical trial for a new medication conducted on a small, homogeneous group of participants might show that the drug works effectively for this specific population. However, the external validity of the study might be questioned if it is not clear whether the same results would apply to a larger, more diverse group of people, or to people in different geographical locations.
External validity involves multiple aspects, such as:
- Population Validity: The ability to generalize findings to other populations beyond the study sample.
- Ecological Validity: The ability to generalize findings to real-world settings outside the controlled environment of the study.
- Temporal Validity: The extent to which the findings can be generalized over time.
In order to achieve high external validity, researchers often conduct studies with diverse samples, in varied environments, and over long periods. However, there is always a trade-off between internal and external validity. Studies designed with high internal validity may limit generalizability, while studies with high external validity may face challenges in controlling confounding variables.