What is face validity?

A test’s face validity refers to how closely it appears to measure the concept or quality it’s intended to. You might assess how appropriate it is for the subject or how relevant it is to it.

Face validity is based on the researcher’s or evaluator’s subjective judgment. Determining it doesn’t require statistical analysis.

For example, a survey that asks people about their job satisfaction might have high face validity if the questions appear to be directly related to job satisfaction and the words are easy to understand.

On the other hand, a survey that includes unrelated questions or is written in complicated technical language might have low face validity.

Face validity can be useful as a quick and easy way to assess a measure’s apparent validity. However, it does not reliably indicate the test’s actual validity.

To determine the measure’s true validity, you will need to use statistical methods to evaluate the degree to which it correlates with other related variables.

Face validity is essential because it affects a test’s perceived credibility and acceptability.

The people completing the test are more likely to think it’s valid if it has high face validity. If your test or technique has poor face validity, people won’t be sure what you are measuring or why you chose a specific method.

People will be more willing to participate in research or evaluations that use such a measure. It can also increase the likelihood that others will take the research or evaluation results seriously.

However, relying on face validity as the sole indicator of validity isn’t advisable.

There are several ways to assess a test’s face validity, including the following:

Expert review

Subject matter experts can review the test and provide their subjective judgment on whether it appears to be measuring what it’s intended to.

Pretest

A small group of people can be asked to complete the test and provide feedback on whether the questions seem to be measuring the intended construct.

Observations

The researcher can observe people completing the test and note any problems or difficulties they have when answering the questions.

Focus groups

You can conduct a focus group with people who represent the target population and discuss the test to gather feedback on its face validity.

Involving multiple and diverse perspectives in assessing face validity may be helpful. For example, suppose a measure intends to determine job satisfaction. To assess face validity in this case, it may be helpful to involve organizational psychology experts and employees who represent the target population.

Test the face validity of a test/technique as early as possible in the development process. It will enable you to identify any problems before you use it in a more extensive study or evaluation.

The feedback you get can confirm that the research tools will provide the answers you need.

The following are three scenarios where reassessing face validity is vital.

For brand-new tests

Testing the face validity of a brand-new test as part of the development process is a good idea. It helps you determine if the test, questionnaire, or whichever method you plan to use serves its purpose and is likely to produce valid answers.

Gathering data and finding it useless for your research is time-wasting and costly.

To use an existing test on a population that it wasn’t designed for

Suppose you are using an existing test designed for a different population than the one you intend to use the test on now. In this case, it’s important to consider the potential impact on the test’s face validity.

The risk of the test having a different level of face validity than it did for the original population is high. This could be due to differences in language, culture, or other factors that may affect the perceived relevance or appropriateness of the test for the new population.

Suppose you present an IQ test designed for US high school students to Brazilian students. If you are testing verbal and math skills, the scores may differ. Reviewers of your test in Brazil may attribute a good score for the math test but a poor score for the verbal skills. Some of the questions in the verbal section may be highly culture-bound to the US.

You might need to modify the test or provide additional context or instructions to address this issue. Doing so may help ensure that the new population understands and perceives the test as relevant. Alternatively, you might need to design a new test for the new population.

To use an existing test in a context that it wasn’t designed for

The test may have a different level of face validity than it did in its original context. This could be due to differences in how you administer or interpret the test or discrepancies in the expectations or experiences of the people taking it. 

Modifying the test or providing additional context or instructions is advised. Doing so will ensure that the participants understand and perceive it as relevant.

Here are a few examples of face validity:

1. A job satisfaction survey might have high face validity if the questions are directly related to job satisfaction and you word them in an easy-to-understand way.

2. A test intended to determine a person’s knowledge of a particular subject might have high face validity if the questions are directly related to the topic and you write them in an easy-to-understand way.

3. A physical fitness test might have high face validity if it includes a variety of exercises that are known to be good indicators of physical fitness, such as running, push-ups, and sit-ups.

4. A test that measures a person’s emotional intelligence might have low face validity if the questions are unrelated to emotional intelligence or are difficult for the participants to understand.

5. If a mathematical test has subtraction and addition questions, you can say it has good face validity. It would have low face validity if it contained questions related to depression.

While face validity can be useful as a quick and easy way to assess a measure’s apparent validity, it’s not a reliable indicator of the measure’s actual validity.

Various factors can influence a measure’s relevance or appropriateness, including personal bias, cultural differences, and the context in which you use the measure.

The apparent advantage of this type of validity is that it saves researchers money and time. If a technique or test fails at the most basic level, you won’t need to carry out complicated tests and deeper analysis to determine if it’s fit for purpose.

Face validity is based on the researcher’s and evaluator’s subjective judgment. Statistical analysis isn’t necessary to determine face validity. It’s similar to the “face value” principle, which depends on casual observations and first impressions.

Content validity refers to the extent to which a test covers all aspects of the construct it intends to measure. A test has high content validity if it represents a sample of items relevant to the construct.

How well does your test measure the concept you set out to investigate? Construct validity refers to how much a measure is related to other variables as it is expected to be based on theoretical considerations. You can assess the construct validity through statistical methods, such as correlations or factor analysis.

Start with face validity. If your test passes it, move on to content, construct, and criterion validity tests for a more in-depth analysis.

The following are qualities of good face validity:

• Measures what it’s intended to

• Appears to be relevant for the construct it’s intended to measure 

• Written in a way that is easy to understand and follow

• Appropriate for the participants

Anyone who reviews your test should agree that it measures what it sets out to evaluate. If reviewers seem confused about what you intend to measure, you should go back to the drawing board.

In summary, face validity refers to the appearance of a test’s validity and is based on subjective judgment. Good face validity can increase a measure’s perceived credibility and acceptability, but it is not a substitute for actual validity.

While it can be a quick way to assess a measure’s apparent validity, it is not a reliable indicator of actual validity. To determine a measure’s true validity, you should use statistical methods to assess its correlations with other relevant variables.