You probably have already heard about external validity in research. As you know, the critical goal for each research is to make it useful for people or institutions. Or in other words, we are talking about the ability to extend your study results to a broader audience. This is external validity – a research term we are going to discuss in this blog.
How to make your academic work important? How to ensure that your results can be generalized for bigger targets? Here, we are going to discuss:
- Types of external validity
- How to establish it
- External validity threats
- How to minimize potential risks.
Our researh paper writing service will also share valuable external validity examples to support your study and future research ideas. We hope this guide will benefit your work and scientific career.
What Is External Validity: Definition
First and foremost, what is external validity in research? When you understand its fundamental principles, it will be easier to get externally valid data for study results in the future. It helps you define whether you can apply your research results to real-world examples.
External validity is the extent to which you can expand your results for other target audiences, circumstances, or settings. Unlike internal validity, it deals with generalizability of study outcomes. In other words, the external validity of a study is the ability to use your insights from quantitative or qualitative research to make a conclusion for the broader public.
To achieve high external validity, researchers must meet 2 criteria:
- Sample should be representative of the population.
- Methods and measures are appropriate for the research question.
Why Is External Validity Important?
Another essential question is why you even need to care about it. You have research questions, and you have your answers. But this is not a goal for almost all academics. Your aim is to change this situation and help essential institutions to be more productive.
You need to ensure external validity for valuable research to achieve such goals:
- Ensure that findings can be applied to similar populations or circumstances
- Make your study more valuable
- Extend future research
- Make a connection between scientific findings and real-world issues
- Complete a stronger study.
External Validity Example
To understand the transferability of your research results better, and go deeper into different types of validity, let’s start with a basic example.
Here you can see a common example of external validity, and next, we will focus on its types and specifics.
For instance, let's say you're conducting research on how using mobile phones, iPads, or computers 2 hours before bedtime can affect the quality of sleep. To investigate this, you have recruited 100 participants to spend a night in a sleep lab while using their electronic devices before bed. You're measuring their brain activity during sleep to determine any effects from using blue screens before bedtime. After analyzing the data, you discover that using blue screens 2 hours before going to bed makes it harder to fall asleep. The generalizability of results allows you to apply findings to all people, not only to your experimental group.
Types of External Validity
There are 2 main types of external validity that you may face while working on research:
- Population validity
- Ecological validity.
In the following paragraphs, we will briefly discuss each type and share examples of external validity.
Population validity means that you can generalize your findings from your smaller samplings to a larger group of people with the same characteristics. Your results may be limited to the population you are researching in case of applying a non-probability sampling method. However, in some situations, you can easily extend your results to bigger groups of people.
Example of Low Population Validity
Let's take a look at an example of research that examines the usage of recreation centers and gyms among students in a US school. For instance, the results of a survey research of 1000 students from this school show that regular gym usage is positively correlated with higher grades in other disciplines. However, it does not mean that these results can be applied to all students in high schools worldwide, as the representation of sampling was too narrow. This study has low external validity. But it’s still valuable for improving grade scores in this particular school, even if not all students were surveyed.
Why do we define this type of validity as low, and how to ensure strong external validity for your study? A problem with these examples is that they did not consider other institutions. In other universities, the number of male and female students can be different, and some cultural differences may also exist. This is why we call this type of external validity low. Researchers should consider conducting this study in multiple settings to ensure that the results are consistent across different contexts. Additionally, using multiple data collection techniques and analysis methods can help increase the generalizability of study results.
Another type of external validity is ecological validity – the extent to which your result can be generalized for other circumstances or environmental conditions. In other words, can we make a conclusion and apply insights to the same sampling but in other situations? This type of external validity is very similar to population validity, but instead of examining different groups of people, it examines different settings.
In some cases, your study results can not be applied to all settings, as the experiment was conducted in quite specific circumstances (e.g.,using a computer instead of a simulation). We would call it low ecological validity.
Below, you will find an exact example of ecological validity.
Example of Low Ecological Validity
To understand external validity, we need to look precisely into the test environment. Let’s use the study of establishing driving habits as an example. You have a group of people and a computer with a driving simulation. For this experiment, you tested how different circumstances affect the drivers’ accuracy. For instance, you looked at how music would affect their focus and how noise will influence a driving technique. You also may try to change the road from the village to see how aggressive a driver can be because of city noise. You may have pretty interesting results!
Why would we call this experiment a low ecological validity? First of all, scientists used a simulation on a computer instead of real driving. You may think that there is no difference, but you are wrong. When a person is really driving, they may have more focus just because they assess the danger of the road and the possible consequences of driving accidents. In simulation, people know that they are sitting in front of a computer, and they will still be alive in any circumstances. That is why we can’t use these test results for a real-world situation with drivers, as changing the circumstances can change insights.
How to Establish External Validity
It can be challenging for some research to ensure its external validity. Scientists need to understand all details of assessing external validity and examine all options for improving it. The only way to ensure that your results can be used for solving real-life problems is to repeat your study for other target audiences or use other settings. You may increase the validity by expanding the criteria for your samplings. However, before you try to enhance validity, you need to figure it out and define if you have any problems.
How to Increase External Validity?
As we have already mentioned, increasing external validity can be challenging and require a lot of additional research work. However, if the purpose of the study is to expand the insight for a broad audience, you need to focus on how to improve the external validity of the research.
Here’s how to improve external validity and make it more applicable for real-live:
- Use random selection for your samplings if it’s possible.
- Bring more focus on researching the group for your samples, and outline similarities of different groups that are a part of your work.
- Use conceptual framework to understand the degree of similarities between target groups.
- Conduct your study with different groups of people in various circumstances and time slots.
Threats to External Validity
Finally, we came to the most important part of your research – identifying threats to external validity
External validity can be compromised by various extraneous variables that may influence the causal relationship. These variables may include external factors such as the research setting, participant characteristics, and the method of data collection.
Your opponents can use external validity threats to make your work weak. That’s why you need to know all possible threats to be able to avoid them.
One of the common threats to external validity is when research samples are not representative and do not illustrate the whole population you want to generalize the study. In other words, your sampling group includes only one type of people but not the average data about the population you are looking for.
You are doing research on how the citizens support one of the candidates for mayor. You have a survey, but your sampling is mostly women in age 60+. However, this is a city where 40% of the population is students, and 55% are male. Your survey data won’t represent the real situation of how your candidate will be supported on election day.
Other external threats to validity are some events that occur during your tests or gathering samples that affect study results but are not directly related to your study. It can be natural disasters or political rallies that make your target audience answer in a different way. As a result, your data can be compromised.
You are researching a stress level among people who live on Hawaii islands. You get your surveys that represent the target audience. But during this research, a tsunami destroyed one of the small islands not far from Hawaii. This event definitely affected how people answered questions about stress.
One common threat to external validity is how the behavior or other characteristics of the person who is conducting research influence your results. For instance, people often react to an instructor instead of research questions during focus groups.
You have a focus group for researching the best marketing advertisement campaign. Initially, the instructor tells people that one of the firms will happily give everyone presents if they choose their work. And after that, they point to this work. Of course, people will be focused on how to get presents instead of being honest.
Pre and post-test communication also threatens the external validity of a study. In other words, how your research team or instructor organizes pre and post-test directly influences how people behave during the survey. For instance, how stressed they will be about tests or experiments.
A great example is the study of how effective people can be in taking standardized tests. In most cases, when people are aware of how the test will be going, for instance, they have a detailed overview of how the test will be going. It means their stress level will be different than in case the whole test is a surprise for them.
One more threat that affects external validity is the Hawthorne effect. It stands on the point that people can change their behavior if they know that they are part of an experiment or study. People usually try to behave better than usual in case they know that researchers observe this behavior.
For example, you are studying how people form good habits, like going jogging every morning. In case they know that they are part of an experiment, they will more actively try to form this habit and not skip it. But it does not mean that their habit will be formed the same in case people will know that nobody is watching.
In some cases, researchers can’t apply external validation of their study. For example, they are not sure if the results depend on the novelty of the treatment. Or if any study disruptions affect the insights of the study. This is often a threat in medicine and ecology studies.
In medicine, scientists may test a new treatment on patients but not be sure if positive results are the cause of this new treatment or if the organism just reacted positively to something new. It can be a huge problem for hospitals.
This is one more threat to external validity! It is also possible that group characteristics, together with some individual variables, influence your dependent variable. That is why the insights from the study can be criticized and cannot be expanded to a broader audience or different circumstances.
The study focuses on how positive thinking and meditation can help people to organize their everyday life. However, you may find that some participants of this study have a problem with panic attacks, but also meditation helped them with organizational issues. But does it mean that it will help people with depression, for example?
There are a lot of factors, like day time, weather, specific season, or other circumstances, that can undermine your study outcomes. In this case, the scientists should ensure that all independent variables are analyzed and nothing can influence the final results. However, this thread is often used to manipulate data.
For example, you are looking at what type of bank advertisement is perceived better by people. However, you need to know that people will be more likely to click the link with bank advertisements right after they get a salary or in the early morning. And if you run this ad research only in the mornings, your results can be limited.
How to Minimize Threats to External Validity?
After you are aware of key threats to your research, you also need to know how to counter threats to external validity. We would say that the essential part is to understand all the threats and try to prevent them. However, there are a few things to consider for minimizing threats:
- Random sampling By selecting participants randomly from the target population, you can ensure that no participants are underrepresented.
- Increase sample size The larger your sample size, the more likely it is that your outcomes will be accurate.
- Diverse samples Try to recruit participants from various backgrounds to investigate multiple perspectives.
- Naturalistic settings Use natural context for experiments you are going to conduct.
- Replication By conducting the same study several times with different samples, researchers can determine if findings remain consistent.
Bottom Line on External Validity
External validity is referred to the ability to extend the research results to a broad audience or various circumstances. It helps scientists to understand how their work can be applied to solving real-life problems. This is why every researcher needs to understand its importance and know how to improve the data and results. In this text, we also outlined key threats to external validity and focused on some steps that can help you to minimize them.
However, every time you are launching research, you need to start with your aims. After you understand it and have a clear vision of what you are going to study, you can easily navigate external validity and make your findings applicable to broader cases.
Hire an expert paper writer to ensure that your study is conducted with strong external validity, and delivered within your specified timeframe. Trust our writing service to get reliable results effort-free.
FAQ About External Validity
1. What is external validity in research?
External validity in research is the extent to which you can generalize your study findings. In other words, it shows if your results are applicable to a broad audience and can be used for solving a real-life problem. This is the key point for any type of research in various fields, as all scientists aim to be helpful to society.
2. What factors determine external validity?
There are a few threats that determine the external validity of the research. It can be sampling bias, history threat, observer bias, pre, and post-test effect, Hawthorne effect, novelty effect, and others. You need to focus on all factors that can have an influence on the result's objectivity in your study.
3. How do you ensure external validity?
If you want your study expanded to a broader audience and applied to other circumstances, you need to look carefully at all validity threats, use natural context for your field experiment, ensure that the whole population is represented in your experiment, and use some algorithms to correct all the factors that can change your results.