April Thames
University of California-Los Angeles, CA·Psychology
Neuropsychological tests are the standard way clinicians measure memory, attention, language and other thinking abilities, and the results guide diagnoses and treatment decisions. But the reference norms those tests rely on were built from samples that underrepresent much of the US population, so scores can be misread for people whose language, culture or life circumstances differ from the original samples.
- Fields
Psychology
Neuroscience
Public Health & Epidemiology
- Topics
neuropsychological assessment
neuropsychology
cognitive testing
- Grants
- 1 known grant, through Dec 2028
What they work on
- Expand the National Neuropsychology Network with a new Texas clinical research site and enroll over 10,000 additional participants, with emphasis on Black or African American participants and bilingual or monolingual Spanish speakers.
- Test measurement invariance, whether neuropsychological tests measure the same abilities the same way, across groups defined by individual, cultural and linguistic differences, using item-level data deposited in the NIMH Data Archive.
- Build regression-based predictions of neuropsychological performance from demographic variables and social determinants of health, as an alternative to race- and ethnicity-stratified normative scores.
- Develop more efficient adaptive tests and batteries using computerized adaptive testing models that shorten administration without losing diagnostic information.
- Synchronize electronic medical record data with the network database to automate retrieval of common data elements and set standards for the elements most important to neuropsychological assessment.
More about the research
This project builds a national data resource to put neuropsychological assessment on firmer, fairer footing.
Why it matters
Misinterpreted neuropsychological test scores have had adverse consequences for people from racial, ethnic and linguistic groups underrepresented in the samples used to build test norms. Prediction models based on demographics and social determinants of health, rather than race-stratified norms, could make clinical interpretation fairer, while shorter adaptive tests could cut assessment time for patients and clinics. The openly shared data archive supports analyses well beyond this network.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Alexander Young
University of California-Los Angeles, CA·Psychology
Assess the commercial translation potential of an interactive patient data tracking platform for mental health through customer discovery and firsthand investigation of the industry ecosystem.
Sarah Mattson Weller
San Diego State University, CA·Psychology
Measure how accurately the FASD-Tree, a web tool recording physical and behavioral features, and BRAIN-online, a web-based cognitive test, classify children aged 6–17 with FASD, alone and combined, by sensitivity and specificity.
Eleonora Rossi
University of Florida, FL·Psychology
Test whether the composition and structure of heritage Spanish speakers' personal social networks, mapped through network interviews, predict their written and oral fluency in Spanish and English.
The school
University of California-Los Angeles: 84 labs on PI Pages, $1.9B a year on research, 803 research doctorates a year.
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