Key Takeaways
- Concurrent validity is a type of criterion validity that measures how well a test correlates with a previously validated measure for the same construct, administered at the same time.
- It demonstrates a test’s accuracy by comparing it to an established benchmark, ensuring the test effectively measures what it claims to measure in the present moment.
- Concurrent validity has a broad range of applications, ranging from measures of well-being to IQ and educational assessment tests.
What Is Concurrent Validity?
Concurrent validity is a type of criterion validity that measures the degree to which a new test or measurement tool correlates with a well-established measure (criterion) of the same construct, when both are administered at the same time.
In other words, it assesses how well the new test can predict or agree with the results of the existing, validated measure in the present moment.
If a new assessment for depression correlates highly with scores on the Beck Depression Inventory (a validated measure for depression) when administered to the same individuals, it would support the new assessment’s concurrent validity.
This is because the new assessment successfully distinguishes between individuals with varying levels of depression, as measured by an established criterion.
How to measure concurrent validity
In general, any correlation between two related measures taken at the same point in time can be used to demonstrate concurrent validity.
To measure concurrent validity, follow these steps:
Identify a well-established, validated measure (criterion) that assesses the same construct as the new measure you want to validate.
This criterion measure should have demonstrated reliability and validity, serving as a benchmark for comparison.
For example, if you’re validating a new test for depression, you might use the Beck Depression Inventory as your criterion measure.
Administer both the new measure and the established criterion measure to a sample of participants at the same time or within a short time frame.
Ensure an adequate sample size to obtain a reliable estimate of the correlation coefficient. A larger sample size will generally lead to a more precise and stable estimate of the relationship.
Ensure that the administration of both measures is independent to avoid criterion contamination.
Prevent the scores on one measure from influencing the scores on the other.
Differences in administration conditions can introduce unwanted variability and reduce the observed concurrent validity.
For instance, if teachers are aware of students’ scores on an aptitude test, this knowledge might unintentionally bias their ratings of those students’ academic performance.
Collect the data from both measures for each participant.
Calculate the correlation coefficient between the scores on the new measure and the scores on the established criterion measure.
Common correlation coefficients include Pearson’s r for continuous data and Spearman’s rho for ordinal data.
Interpret the correlation coefficient:
- A strong positive correlation (e.g., r > 0.7) indicates high concurrent validity, meaning the new measure is assessing the same construct as the established criterion.
- A moderate positive correlation (e.g., 0.4 < r < 0.7) suggests acceptable concurrent validity.
- A weak or no correlation (e.g., r < 0.4) indicates poor concurrent validity, suggesting the new measure may not be assessing the same construct as the established criterion.
Remember that concurrent validity is just one type of validity evidence, and it’s essential to gather other types of validity evidence (e.g., content validity, predictive validity) to comprehensively evaluate the validity of a new measure.
Examples of concurrent validity
Depression Questionnaires
Depression is a common mental health issue that affects many people, so it is important to assess its severity accurately.
One way of doing this is through the use of depression questionnaires. In this context, concurrent validity involves comparing scores on the questionnaire with scores from other measures that should be related, such as clinician-rated symptom scales or diagnostic interviews based on DSM criteria.
This allows researchers to determine whether higher scores on the questionnaire correlate with higher scores on these other measures and vice versa, providing evidence of concurrent validity for the questionnaire (Bowers, 2004).
IQ Tests
IQ tests are widely used to measure intelligence, but they must first demonstrate concurrent validity before they can be relied upon as accurate.
Numerous circumstances affect the accuracy of IQ tests over time. For example, researchers have established that the average IQ score of test takers increases by three points every decade.
Since IQ is designed to be a fundamentally curved scale, using concurrent validity as a way of confirming new means is essential to its usability. There are many ways that researchers can ensure the concurrent validity of IQ tests.
For example, researchers can measure whether students’ scores on an IQ test are positively correlated with their grades in school. Otherwise, they may test if the calculated IQ scores of their assessment correlate with the calculated IQ scores of others (Hays et al., 2002).
Quality of Life Research
One example of concurrent validity could involve a self-report measure of quality of life, the Satisfaction with Life Domains Scale for Cancer (SLDS-C), being verified by its score correlation of 0.76 with another cancer-specific quality of life measure, the Functional Assessment of Cancer Therapy Scale-General (FACT-G).
These two scales both measure functional well-being, emotional well-being, and physical well-being.
Because there is a strong correlation between these subscales, researchers can better assume that those with higher life satisfaction are predicted to express more positive affect and have higher levels of health status (Baker et al., 2007).
What are the limitations of concurrent validity?
- Concurrent validity heavily depends on the quality and relevance of the chosen criterion variable. A weak or irrelevant criterion will compromise the validity of the test.
- It offers a snapshot of the relationship between the test and the criterion at a specific time, potentially overlooking the dynamic nature of some variables.
- Convergent validity is sometimes used interchangeably with concurrent validity, causing confusion. Additional research might be needed to clarify their relationship in different situations.
FAQs
Is concurrent validity internal or external?
Concurrent validity is a type of external validity, which focuses on relationships external to the test, such as the association between test scores and external criteria.
In contrast, internal validity focuses on relationships internal to the test, such as the relations among the items that make up the test.
For instance, internal validity would investigate whether responses to different items within a depression assessment are consistent with one another, suggesting that the items are all measuring the same underlying construct of depression.
Is concurrent and convergent validity the same?
Concurrent validity refers to the degree to which a test or measurement tool correlates with another, previously validated measure of the same construct, when both measures are taken at the same time.
In other words, it assesses how well a new test compares to an existing, well-established test.
Convergent validity is a subtype of construct validity. It refers to the degree to which two measures of constructs that theoretically should be related are, in fact, related.
Convergent validity is assessed by comparing the new test to other measures that are theoretically related to the construct being measured.
How can concurrency validity be improved?
The degree of concurrent validity in a study can be improved by implementing a number of best practices.
Firstly, researchers can ensure that the data used for concurrent review is complete and up to date.
Secondly, researchers can use design techniques that reduce the chance of conflicting updates from different sources.
Thirdly, researchers can consider implementing automated conflict resolution protocols if appropriate.
Fourthly, they can create standard operating procedures that are consistently followed and regularly reviewed to minimize errors in concurrent reviews.
Finally, documenting the results of each concurrent review can help identify areas where improvements could be made or conflicts avoided in future reviews.
By adhering to these principles, organizations can ensure that their concurrent reviews are conducted accurately and reliably (Lin & Yao, 2014).
What is the relationship between concurrent validity and construct validity?
Concurrent validity is one aspect of the broader concept of construct validity.
It serves as one piece of evidence supporting construct validity, especially when combined with other forms of evidence like content validity, predictive validity, convergent validity, and discriminant validity.
Construct validity seeks to confirm that a test genuinely measures the intended theoretical construct.
References
American Psychological Association. (n.D.) Concurrent Validity. American Psychological Association Dictionary.
Baker, F., Denniston, M., Hann, D., Gesme, D., Reding, D. J., Flynn, T., & Kennedy, J. S. (2007). Factor structure and concurrent validity of the Satisfaction with Life Domains Scale for Cancer (SLDS-C). Journal of Psychosocial Oncology, 25(2), 1–17.
Bowers, A. (2004). Concurrent Validity Study of the Clinical Assessment of Depression with the Beck Depression Inventory. University of Kentucky.
Gregory, R. J. (2000). Psychological testing, history, principles, and applications (4th ed.). Allyn & Bacon.
Hays, J. R., Reas, D. L., & Shaw, J. B. (2002). Concurrent validity of the Wechsler abbreviated scale of intelligence and the Kaufman brief intelligence test among psychiatric inpatients. Psychological reports, 90(2), 355-359.
Drake, R. D., Rao, G. G., McIntire, D. D., Miller, D. S., & Schorge, J. O. (2005). The Incidence of GTD in Hispanic Women: A 20-Year Experience at Parkland Memorial Hospital. Obstetrics & Gynecology, 105(4), 119S.
Lin, W. & Yao, G. Concurrent Validity. In Michalos, A. C. (Ed.). (2014). Encyclopedia of quality of life and well-being research (pp. 311-1). Springer Netherlands.
