External validity is known as generalizability or the extent to which scientific findings can be applied to other settings rather than the ones tested. In other words, external validity reveals if research outcomes apply to everyday life and the general population.

Note that external validity is a complex concept which can’t be measured in a single statistical analysis. Therefore, external validity must be agreed upon between experts. One of the good methods is to implement strict inclusion and exclusion criteria, especially in medical settings. For instance, in clinical trials, a study with good external validity would involve hospitalized patients and would reveal results which can be applied to the general population near the same hospital. On the other hand, in population research, random sampling and high response are needed to guarantee external validity (Peat, 2011).

Here we should mention a couple of curious examples, which tackle the problem of external validity. In psychology, for instance, conformity and diffusion of responsibility are common phenomena. Several studies replicated some alarming findings of people’s nature. For example, a study conducted by Latan and Darley (1968) tested if participants would help a sick person while waiting at a laboratory. The findings showed that people would only act if they thought they were the only person waiting in the laboratory. If there were more people around them, the chances to help someone sick decreased. This study has good external validity. The fatal case of Kitty Genovese who was stabbed near her apartment while her neighbors watched passively through their windows proved the existence of the bystander effect – or the mentioned phenomenon about observers being less likely to help in the presence of other people.