Construct Validity
If you want to check how well the test you have developed can measure the subject you need for your research, use construct validity. It demonstrates the full validity of your method, too.
Evaluation of the method with the help of construct validity is especially important when the subject of your research cannot be observed or measured physically. Such concepts as aggression, happiness, stress, intellect, or self-esteem cannot be measured with any physical scale or tools. So, you need to invent some other measurable or observable indicators to assess your subject of research via them.
Construct validity is the main validity type among the four. The other three types are content, face, and criterion validity.
The article provides a detailed explanation of what construct validity is, how to use it in your research design, and how to avoid threats and discrepancies related to it.
What Stands Behind the Conception of a Construct?
A construct is always based on practical observations, though it is a theoretic concept referring to a theme or idea that has more abstract content. In fact, it is also a variable, but you cannot measure it directly.
Since constructs are essential for psychologists and their research methods, they usually develop them to find and test individual or collective differences within groups, samples, or populations. They may use such constructs as motivation, logical intelligence, self-confidence, or social anxiety measurements. Of course, they cannot accurately measure them with a specific tool in the real world. That is why they research the indicators that help test their hypotheses about the performance and impact of these constructs.
Constructs can be simple and complex.
You can easily assess the concept of satisfaction by asking a simple survey question, “Are you satisfied with this product?” Or you can observe the levels of satisfaction with different models of the product by giving them to the participants and asking the respondents to perform several operations these items are meant for. However, self-esteem is a more complex concept that needs more detailed and consistent systems of measurement, for example, psychological research interviews or elaborated psychometric questionnaires.
You can define simple constructs via narrow measurements, but you cannot do it with one or several measurements for complex constructs because they consist of dimensions. They are parts of the construct linked coherently to compose a whole unit.
Agoraphobia is a bad fear of crowded places and large groups of people. As with all other phobias, it badly
affects daily routines and work performance.
Agoraphobia can be regarded as a construct made of a few
dimensions:
- physiological - sweating, fainting, and other indicators of stress and social anxiety;
- psychological - related to severe fear, inability to calm down, talk to people, or stay with them in one space;
- behavioral - causes an urgent desire to escape the place, quit the crowd, stay alone, and not talk to anyone.
What Does Construct Validity Mean?
This term is applied to the accuracy of measurements provided by the test you use to research the subject you intend to. You need to operationalize such constructs to add measurable characteristics to them related to your ideas and construct dimensions.
To start with, you have to define the construct and its dimensions clearly before you begin to collect and analyze the data. You need it to check whether your measurement method can accurately assess the concrete construct.
You want to explore self-esteem in first-year college students. First, you make up a simple questionnaire that may include such questions as:
- How sociable are you?
- Do other people think about you as an interesting or boring person?
- How often do you socialize with your group mates, friends, or other people?
- Do you like to get to know new people and talk to them?
- If you are given a challenging task, do you feel engaged or frustrated?
- How often do you ask questions to your professors in class?
- How do you feel when you had planned to do something, but your plans were ruined by something unexpected?
When you design the questionnaire and think about the measures you can apply to it, consider whether all your questions are aimed at the target construct or some other ones that are separate, similar, or related to it.
Differentiation of the target construct from the related ones is crucial because it allows you to ensure that every component of your measurement technique is aimed at the specific construct you want to measure. So, look through your questions once again and think about the following:
- Does your questionnaire measure only self-esteem in first-year students or does it refer to anything else?
- Do the questions cover all the aspects of self-esteem?
- Can these questions be applied to measuring other relevant constructs, such as social anxiety or introversion?
As for the example questions, we can notice that some of them refer to introversion or even social anxiety. It means that you need to narrow down the questionnaire to concentrate on self-esteem.
Two Types of Construct Validity
Convergent and discriminant validity are the two types of construct validity.
- Convergent validity shows how well the measure in the test complies with the measures of similar or related constructs.
- Discriminant validity demonstrates whether your measure relates to the other measures of the constructs, does not, or negatively relates to them.
More About Convergent Validity
This validity shows how much your measures correlate with the same constructs and to what extent they can correspond to similar constructs. You may expect that all these related constructs will correlate with one another and with your construct, but you need to check this.
You may develop two different scales that are related by their subjects of measurement. You can see that the respondents who scored poorly on one scale will tend to score the same poorly on the other one.
Let’s have a more thorough look at our questionnaire about self-esteem in college students. When it is ready, you distribute it to a sample of the first-year college students you have chosen for your research. Some questions are accompanied by rating scales. One of these scales is widely used in psychological research to measure self-esteem in adult office workers.
You check these scales and see that your specific questionnaire demonstrates convergent validity because the obtained responses are similar to those given for the existing scale.
How Is Discriminant Validity Different?
In contrast, discriminant validity should show that the two measures belonging to unrelated constructs are truly unrelated, poorly related, or negatively related.
Check your questionnaire for discriminant validity with the same technique. Compare the results obtained for different measures, and you will see how much they correlate. However, you need to pick the unrelated constructs for checking first. They can be constructs with different theoretical basis or just some entirely opposing concepts that belong to the same category.
If your construct is high self-esteem in most first-year college students, choose low self-esteem for comparison. As you understand, the results of your high self-esteem test should be negatively correlated with the results of the test aimed at the identification of low self-esteem in certain groups of people.
You can also choose non-opposing or unrelated concepts and ensure that they do not have any correlations with your measures.
Check your self-esteem questionnaire for discriminant validity by comparing the questions with those meant to identify the sociopathic disorder in people. Sociopathic disorder and self-esteem are theoretically different concepts, so you cannot expect any relations or correlations between the measures.
You can distribute both questionnaires within your sample (remember that the sample should be large enough to provide desirable results), and evaluate validity. You will see no correlation (or possibly, a weak correlation) between the results. It means that your questionnaire has acceptable discriminant validity.
Ways to Measure Construct Validity
You may need to evaluate construct validity after you have introduced a new measure. A pilot study is the best way to test this measure, or you may think about some other techniques.
A pilot study is the first run of your research method meant for a trial. You can use a small sample to test the measure’s validity, reliability, and feasibility. Such testing will show what you need to revise or correct in your measure to make testing the construct more accurate.
You can also apply statistical analysis to test construct validity. Use the data provided by your measures. You need to check both convergent and discriminant validity to see either positive or negative relations or correlations between the constructs established with the help of test results.
Regression analyses are also effective in understanding whether your measure can be predictive of the theoretical outcomes you expect to obtain from your test. If the regression analysis proves your expectations, you may ensure the construct validity is high.
What Are the Main Threats to Construct Validity?
You need to recognize and prevent possible threats to construct validity coming from your research design. The most widely encountered threats include the following:
- ✔️ overestimated expectancies of the researcher;
- ✔️ inappropriate operationalization;
- ✔️ subjective bias related to treatment procedures.
Inappropriate Operationalization
Poor or inconsistent operationalization makes up a bad threat to construct validity. If you provide a consistent operational definition of the main construct, you can receive accurate and precise measures. Your measuring protocol will be unique and understandable, and other researchers will be able to use it in different situations and conditions.
However, if you do not provide a well-structured operational definition, all your efforts may lead to systematic or random errors that will cast doubt on your results. It means that no measure you obtain will accurately evaluate the construct in this case.
Overestimated or Wrong Researcher’s Expectancies
If you have developed certain expectancies for the study results, everything you obtain can be heavily biased. Consider the possibility of such bias and try to avoid it.
Researcher triangulation is the best way to cope with this threat or prevent it. It means you need to involve someone else in your research who does not know your hypothesis. This person will take measurements without any pacific expectations, so they are likely to obtain unbiased results.
Subjective Bias Within Research Procedures
When respondents or participants in your sample know what is expected from them, all their answers and actions will be heavily influenced. That will become a severe threat to your construct validity because all the measures you may obtain will not be accurate and true to life.
You need to minimize such bias with the help of blinding or masking. It means you have to conceal the true purposes and expectations related to the research from your participants. You can offer them a cover story to explain what they are supposed to do so that their personal perception of the study stages will not bias the final outcomes.
Final Thoughts
Now, you can see how important construct validity is for the assessment of the final outcomes and findings of your study. You have learned here how to deal with construct validity and how to formulate the aims and purposes of your research design to avoid unnecessary bias and discrepancies.
All in all, construct validity is the most crucial element of overall research validity. If you want to reach your academic goals and make progress, the information given here will be of vital importance.