What is construct validity? Construct validity is a crucial concept in research, particularly in the social sciences and psychology, where many of the variables under investigation are abstract and not directly observable. It refers to the extent to which a measurement or test accurately reflects and represents the theoretical construct it is intended to measure.
Types of measurement validity
Construct validity is one of the four main types of measurement validity, along with face validity, content validity and criterion validity.
- Content validity: Refers to the extent to which a measure adequately covers and represents the entire domain or content area of interest.
- Criterion validity: Refers to the degree to which a measure is related to an external criterion or outcome that is considered a direct measure of the construct of interest.
- Face validity: Refers to the extent to which a measure or test appears to be a good reflection or indicator of the construct it is intended to measure, based on a subjective evaluation.
What is a construct?
A construct is an abstract or theoretical concept that cannot be directly observed or measured. It is a hypothetical variable that is inferred based on observed behaviors, attitudes, or manifestations.
Example: Constructs
Some examples of constructs in psychology and social sciences include:
- Intelligence
- Personality traits (e.g., extroversion, neuroticism)
- Self-esteem
- Depression
- Motivation
- Organizational commitment
Constructs can vary in their level of complexity, ranging from relatively simple and straightforward concepts to highly complex and multidimensional ones. A simple construct, such as hand preference, can be assessed fairly easily through direct methods:
- A simple survey question: Participants can be asked which hand they consider their dominant hand through a straightforward self-report item.
- Observations: Researchers can observe participants performing simple tasks, such as picking up an object or drawing, and note which hand they naturally use to execute these activities.
Simple constructs tend to be narrowly defined and focused on a specific, well-delineated concept. Complex constructs, on the other hand, are typically broader and comprised of multiple dimensions or components that are coherently linked together to form the overall construct.
Example: Dimensions of a construct
Here are some more examples of constructs and their potential dimensions:
Depression
- Affective dimension: Low mood, sadness, anhedonia (inability to experience pleasure)
- Cognitive dimension: Negative thoughts, hopelessness, poor concentration
- Somatic dimension: Sleep disturbances, changes in appetite, fatigue
Organizational Commitment
- Affective dimension: Emotional attachment and identification with the organization
- Continuance dimension: Perceived costs of leaving the organization
- Normative dimension: Perceived obligation to remain in the organization
Self-Esteem
- Self-worth dimension: Overall feelings of self-respect and self-acceptance
- Social competence dimension: Perceptions of one’s abilities and skills in social situations
- Physical appearance dimension: Evaluations of one’s physical attractiveness and body image
What is construct validity?
Construct validity refers to the degree to which a measure or test accurately captures and represents the theoretical construct it is intended to measure. It is concerned with ensuring that the operationalization (or measurement) of a construct accurately reflects the true nature and meaning of the underlying concept.
Example: Construct measure
A researcher wants to develop a measure to assess the construct of “organizational commitment” among employees in various companies. Organizational commitment refers to an individual’s attachment, loyalty, and dedication to their organization.
To capture the different dimensions of this construct, the researcher creates a questionnaire with the following items:
- I feel a strong sense of belonging to my organization.
- I would be very happy to spend the rest of my career with this organization.
- I really feel as if this organization’s problems are my own.
- I do not feel emotionally attached to this organization. (Reverse-coded)
- Too much of my life would be disrupted if I decided to leave my organization now.
- I feel that I have too few options to consider leaving this organization.
- This organization deserves my loyalty because of what it has done for me.
- I would not leave my organization right now because I have a sense of obligation to the people in it.
- I owe a great deal to my organization.
Rate the extent to which you agree or disagree with each statement using the following scale:
- = Strongly Disagree
- = Disagree
- = Neutral
- = Agree
- = Strongly Agree
When designing or evaluating a measure, it’s crucial to ensure that it specifically targets the intended construct and does not inadvertently assess separate but related constructs. It is essential to clearly differentiate the focal construct from related constructs and verify that every component of the measurement approach is solely focused on assessing the specific construct of interest. Construct-irrelevant variance, where the measure captures other distinct constructs, should be minimized to establish robust construct validity.
Example: Evaluating your measure
After going through your questionnaire, you have some question:
- Does your questionnaire solely measure organizational commitment?
- Are all aspects of organizational commitment covered by the questions?
- Do your questions avoid measuring other relevant constructs like job satisfaction or work engagement?
Upon evaluation, you realize that most of the items in your questionnaire seem to be focused on assessing the different dimensions of organizational commitment, such as affective commitment (e.g., items 1, 2, 3, 4), continuance commitment (e.g., items 5, 6), and normative commitment (e.g., items 7, 8, 9).
However, some of the items may be overlapping with or capturing other related constructs. To ensure that your measure solely assesses organizational commitment and avoids capturing other related constructs, you may need to modify or remove some of the problematic items.
Types of construct validity
There are two main types of construct validity: convergent validity and discriminant validity.
Convergent validity
Convergent validity refers to the degree to which a measure is positively correlated with or converges with other measures of the same or similar constructs. In other words, it examines whether the measure is related to other measures or indicators that should theoretically be related to the construct of interest.
Example: Convergent validity
If a researcher wants to assess the convergent validity of a new measure of depression, they could examine its correlation with an existing, well-established measure of depression. If the two measures are strongly positively correlated, it would provide evidence of convergent validity for the new measure.
Discriminant validity
Discriminant validity refers to the degree to which a measure is not related to or diverges from other measures or constructs that should theoretically be unrelated. It ensures that the measure is distinct from and does not overlap with conceptually different constructs.
Example: Discriminant validity
Suppose a researcher wants to assess the discriminant validity of a measure of job satisfaction. They could examine its correlation with a measure of intelligence. If the two measures are not significantly correlated or show a very weak relationship, it would provide evidence of discriminant validity, suggesting that the job satisfaction measure is distinct from the construct of intelligence.
How do you measure construct validity?
Researchers employ various methods to assess and establish the construct validity of a measure:
Pilot study
Conducting a pilot study or preliminary testing can provide valuable insights into the construct validity of a measure. By administering the measure to a small sample and collecting qualitative feedback or observations, researchers can evaluate whether the items or tasks accurately capture the intended construct.
Statistical analyses
Various statistical analyses can be used to assess construct validity, such as:
- Factor analysis: This technique examines the underlying factor structure of a measure and determines whether the items or subscales load onto the expected factors or dimensions of the construct.
- Correlation analysis: Examining the correlations between the measure and other related or unrelated measures can provide evidence of convergent and discriminant validity.
- Group comparisons: Comparing the scores on the measure between groups that should theoretically differ on the construct can provide evidence of construct validity.
Regression analyses
Regression analyses can be used to investigate the relationships between the measure and other variables that should theoretically be related or unrelated to the construct of interest. This can provide evidence of the measure’s ability to predict or be predicted by relevant criteria, supporting its construct validity.
Threats to construct validity
Several factors can threaten the construct validity of a measure:
Poor operationalization
If the operational definition or measurement of a construct is inadequate or fails to capture the full essence of the theoretical construct, it can undermine construct validity. This can occur when the measure is too narrow or fails to include important facets of the construct.
Experimenter expectancies
Researchers’ expectations or biases about the nature or relationships of the construct can influence the way they design or interpret the measure, potentially introducing construct validity threats.
Subject bias
Participants’ responses or behaviors on the measure may be influenced by factors such as social desirability, demand characteristics, or misunderstanding of the instructions, which can distort the relationship between the measure and the intended construct.
What is construct validity in psychology?
In psychology, construct validity is particularly important because many of the variables under investigation are abstract and not directly observable. Psychologists often deal with complex constructs like intelligence, personality traits, or mental health conditions.