Concurrent Validity
Reviewed byRemya Krishnan
Definition
Concurrent validity is a type of criterion validity that evaluates how well a new measurement instrument agrees with an established gold standard when both are administered at the same point in time. If the new measure produces scores that correlate strongly with the reference standard, researchers can be more confident that it captures the same underlying construct. Concurrent validity is distinct from predictive validity, which assesses agreement between a measure and a criterion assessed at a future time point.
Explore the concept
Can the screener stand in?
Pick a reference and a time for the comparison, apply the screener's cutoff to 200 clinic patients, and see why a high correlation is not the same as agreement.
Ten items for generalized anxiety disorder
Reference standard for the same diagnosis
Both measures in one session
Concurrent validity evidence
The big idea: Concurrent validity is criterion validity: a new measure is compared with a credible reference standard for the same construct, measured at the same time, using statistics that fit the data. It can justify substituting the new measure for the reference, but a high correlation alone does not show that the two agree.
The screener study is the article's example: a ten item screener for generalized anxiety disorder and the SCID 5 interview given to 200 primary care adults on the same day, sensitivity 0.88 and specificity 0.79 at a cutoff. The strips show these proportions per 100 people in each group (88 of 100 and 79 of 100), because the article does not give how many of the 200 had the diagnosis. The 12 people in the agreement view are illustrative scores on a shared 0 to 40 scale; r, the bias (mean difference) and the limits of agreement (bias ± 1.96 SD of the differences) are computed live from them.
Why it matters
Researchers frequently need shorter, cheaper, or less invasive instruments that perform as well as existing gold standards. A screening questionnaire that can substitute for a lengthy diagnostic interview saves both time and resources. Concurrent validity evidence is what justifies that substitution. Without it, there is no empirical basis for claiming that the new tool can stand in for the reference standard.
How it works
Researchers administer the new instrument and the reference standard to the same group of participants during a single testing session or within a narrow time window. They then quantify how closely the two measures correspond, typically using Pearson's r for continuous scores or Cohen's kappa for agreement between categorical classifications. A strong positive correlation (often r greater than 0.70) suggests acceptable concurrent validity. Researchers may also examine sensitivity and specificity if the new measure produces binary classifications. A strong correlation does not by itself show that the two measures agree: a new measure can correlate highly with the reference standard while reading consistently higher or lower.[3] When both measures use the same units, Bland Altman plots show the level of agreement across the range of scores, revealing any systematic difference and whether discrepancies are larger at certain values.[3]
When to use it
Use concurrent validity testing when you are developing or adapting a measurement instrument and a credible reference standard exists. It is especially relevant when the new measure offers practical advantages: lower cost, reduced participant burden, faster administration, or applicability in settings where the gold standard is impractical. Concurrent validity is also appropriate when translating an instrument into a new language or adapting it for a different cultural context and you want to compare the adapted version with the original.
Key takeaways
- Researchers frequently need shorter, cheaper, or less invasive instruments that perform as well as existing gold standards.
- They then quantify how closely the two measures correspond, typically using Pearson's r for continuous scores or Cohen's kappa for agreement between categorical classifications.
- Use concurrent validity testing when you are developing or adapting a measurement instrument and a credible reference standard exists.
- One frequent error is confusing concurrent validity with convergent validity.
Common mistakes
- One frequent error is confusing concurrent validity with convergent validity. Convergent validity is evidence for construct validity: the new measure correlates as theory predicts with other measures of the same or related constructs, none of which needs to be a gold standard. Concurrent validity is a form of criterion validity: it compares a new measure with a reference standard for the same construct, measured at the same time.
- Another mistake is using an inadequate reference standard: if the gold standard itself has questionable validity, the comparison tells you little.
- Researchers also sometimes conclude that high concurrent validity means the new instrument is "valid" in all respects, ignoring other dimensions such as content validity or construct validity.
- Finally, sample size matters; a small sample can produce misleadingly high or low correlation coefficients with wide confidence intervals.
Example
A team of psychologists develops a ten item screener for generalized anxiety disorder and wants to validate it against the Structured Clinical Interview for DSM 5 (SCID 5). They recruit 200 adults from a primary care clinic. Each participant completes the screener and then undergoes the SCID 5 interview on the same day. When a cutoff score is applied, the screener identifies SCID 5 diagnoses of generalized anxiety disorder with sensitivity of 0.88 and specificity of 0.79. These results support concurrent validity and suggest the screener can serve as a practical first stage assessment in busy clinical settings.
Test your understanding
5 questions that adapt as you go: answer two in a row correctly and they get harder.
Question 1 of 5
Scenario:
A team validates a new fatigue questionnaire against an older fatigue questionnaire, completed in the same session. The two correlate strongly, but the older questionnaire's own validity has never been tested.
Question:
What is the main problem with this study?
Hardness: Interpret
Sources
- [1]DeVellis RF, Thorpe CT. Scale Development: Theory and Applications. 5th ed. SAGE Publications, 2022. ISBN 9781544379340
- [2]Field A. Discovering Statistics Using IBM SPSS Statistics. 6th ed. SAGE Publications, 2024. ISBN 9781529630008
- [3]Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307-310. doi:10.1016/S0140-6736(86)90837-8
Cite this term
Paperguide. (2026, October 14). Concurrent Validity. In Paperguide Research Glossary. https://paperguide.ai/research-glossary/concurrent-validity/(Paperguide, 2026)