Leads the identification, development, and evaluation of measures, including implementation of the OMNI ADRD Measures Evaluation Framework.
Core Lead:
Marty Sliwinski, PhD
Purpose
Leads development and refinement of the OMNI ADRD Measures Evaluation Framework for assessing tools across contexts and purposes.
Outputs
A structured framework with clear criteria, scoring rubrics, and guidance for application across measurement domains.
Why this matters
There is no consistent standard for evaluating many emerging digital measures. This framework provides a transparent and systematic approach to guide selection and use.
WG Lead: Louisa Thompson, PhD
John Felt, PhD
Jee-Eun Kang, PhD
Riki Slayday
Timothy Brearly, PsyD
Jessie Alwerdt, PhD
Ashley Tate, PhD
Elizabeth Muñoz, PhD
Molly Lawrence
Niliette Bravo
Purpose
Evaluates and advances the use of digital cognitive assessments in AD/ADRD prevention research.
Outputs
A structured catalog of digital cognitive measures, recommendations for their appropriate use across research contexts, and adaptations of the OMNI Measures Evaluation Framework that address digital-specific considerations such as practice effects, device variability, measurement invariance, and interoperability.
Why this matters
Digital cognitive assessments offer scalable, flexible approaches for measuring cognition, but their performance can vary across devices, populations, and study designs. Providing standardized evaluation criteria and practical guidance helps researchers select and implement digital measures that are fit for purpose and produce reliable, interpretable results.
WG Lead: Marty Sliwinski, PhD
WG Lead: Kate Papp, PhD
Mindy Katz, MPH
Timothy Brearly, PsyD
Elizabeth Muñoz, PhD
Seo-Eun Choi, PhD
Louisa Thompson, PhD
Nelson Roque, PhD
Ganesh Babulal, PhD, OTD
Purpose
Evaluates wearable, mobile, and sensor-based approaches for continuous measurement of behavior and function.
Outputs
Catalog of passive monitoring tools and guidance on their appropriate use in prevention research.
Why this matters
Passive data streams offer scalable, low-burden ways to track change, but their validity and interpretation are not always clear. This work helps define when and how these tools should be used.
WG Lead: Ganesh Babulal, PhD, OTD
Purpose
Evaluates self-reported cognitive measures, including global measures, daily reports, and EMA-based approaches.
Outputs
Catalog of subjective measures and guidance on their appropriate use for risk assessment and monitoring.
Why this matters
Subjective experience often changes before objective performance. Understanding how to measure and interpret these reports improves early detection and monitoring.
WG Lead: Laura Rabin, PhD
Andrew Saykin, PsyD
Rebecca Amariglio, PhD
David Almeida, PhD
Purpose
Evaluates sensory, motor, and functional performance measures for AD/ADRD prevention research.
Outputs
Catalog of sensory and motor measures and guidance on applying the OMNI ADRD Measures Evaluation Framework to these types of measures.
Why this matters
Sensory and motor changes often precede cognitive decline and are valuable early indicators for prevention research. Consistent evaluation standards ensure measures can be compared across studies.
WG Lead: Aaron Seitz, PhD
Ganesh Babulal, PhD, OTD
Nelson Roque, PhD
