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The California Cognitive Assessment Battery (CCAB)
David Woods1, Peter Pebler1, David K Johnson2
1NeuroBehavioral Systems Inc., Berkeley, CA, United States.
Frontiers in Human Neuroscience
|January 26, 2024
Summary
The California Cognitive Assessment Battery (CCAB) offers scalable, lab-quality neuropsychological assessments remotely. It shows promise in reducing disparities and bias in diagnosing cognitive impairment, even post-COVID-19.
Area of Science:
- Neuroscience
- Medical Technology
- Psychology
Background:
- Neuropsychological assessments are crucial for diagnosing cognitive impairments.
- Access to traditional testing is limited by cost, location, and mobility.
- Telemedical solutions are needed to bridge the gap in neuropsychological evaluation.
Purpose of the Study:
- To introduce the California Cognitive Assessment Battery (CCAB), a telemedical tool for neuropsychological assessment.
- To evaluate the usability and psychometric properties of the CCAB in older adults.
- To investigate the impact of COVID-19 on cognitive performance and the effectiveness of scoring models in classifying Mild Cognitive Impairment (MCI).
Main Methods:
- Developed the CCAB with 32 subtests (15 non-verbal, 17 verbal) for telemedical use on tablet computers.
- Utilized naturalistic text-to-speech and consensus automatic speech recognition for verbal components.
- Employed a web-based application (The Examiner) for supervised self-administration and real-time monitoring by examiners.
- Collected normative data from 415 older adults (ages 50-89) and analyzed performance differences related to COVID-19 status and demographic factors.
Main Results:
- CCAB demonstrated usability in older adults, with comparable psychometric properties to in-lab testing.
- Preliminary analysis indicated impaired performance in COVID-19 positive individuals, but this was mitigated by comprehensive demographic factoring.
- A comprehensive scoring model significantly improved variance accounted for and reduced racial bias in MCI classification compared to simpler models.
Conclusions:
- The CCAB is a viable tool for scalable, laboratory-quality neurodiagnostic assessments, particularly for underserved populations.
- The CCAB's scoring models can improve the accuracy and reduce bias in diagnosing conditions like MCI.
- The CCAB technology holds promise for expanding access to essential cognitive evaluations.
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