# Stricker Learning Span: A Computer Adaptive Word List Memory Test Optimized for Remote Assessment

> **NIH NIH R21** · MAYO CLINIC ROCHESTER · 2021 · $437,250

## Abstract

PROJECT SUMMARY/ABSTRACT
Due to COVID-19, remote cognitive assessment has transitioned from an important research aim to an
immediate and urgent research and clinical need. This need has underscored the lack of well-validated,
sensitive, reliable, and well-normed tests available for remote assessment. Word list memory performance
changes early in the preclinical phase of Alzheimer’s disease (AD), up to 20 years prior to onset of mild
cognitive impairment (MCI). Although delayed word list recall is viewed as the most sensitive memory measure
in studies of MCI and AD dementia, traditional word list memory test paradigms require interactive
administration with an examiner. Further, recency effects may influence the sensitivity of delayed word list
recall: correct recall of words at the end of the list during immediate recall trials may represent attentional
span/working memory for some individuals. When these words are subsequently not recalled at delay, they are
considered forgotten, but an alternate view is that the words were never fully encoded during repeated learning
trials. In line with this, the central deficit in AD may be one of learning. To help address the critical need for a
sensitive and brief remote learning measure, we have developed a new word list learning paradigm. The
Stricker Learning Span (SLS) aims to achieve the known sensitivity of word list memory tests to the earliest
preclinical AD changes while allowing reliable remote self-administration on a smartphone or alternative device
(e.g., PC, tablet) through a web-based platform. This flexible approach is necessary to reach the most users
and eliminate potential health disparities. We have transformed the traditional manner of administering a word
list memory test in several important ways, resulting in a novel paradigm that takes full advantage of computer-
based administration through use of a computer adaptive testing procedure focused on learning, visual
presentation of the word list, 4-choice recognition to assess words learned, and a complete data capture
approach to allow future studies focused on process-based measures and application of machine learning
techniques. This study will leverage the resources of the ongoing population-based Mayo Clinic Study of
Aging, which already incorporates in-clinic and remote computerized cognitive assessment. Specifics aims
include to (1) determine the acceptability and efficiency of the unsupervised SLS, (2) demonstrate the
construct validity of the SLS by examining association with a traditional word list memory measure, (3)
determine the criterion validity of the SLS through sensitivity to preclinical AD (cross-sectional effect sizes
between cognitively unimpaired amyloid PET positive and negative groups) and associations with continuous
AD neuroimaging biomarkers (tau PET, hippocampal volume) in all participants with neuroimaging data, and
(4) determine 7.5 month test-retest reliability for the SLS. Sensitive, remotely administer...

## Key facts

- **NIH application ID:** 10295468
- **Project number:** 1R21AG073967-01
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Nikki H Stricker
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $437,250
- **Award type:** 1
- **Project period:** 2021-08-15 → 2024-05-01

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10295468

## Citation

> US National Institutes of Health, RePORTER application 10295468, Stricker Learning Span: A Computer Adaptive Word List Memory Test Optimized for Remote Assessment (1R21AG073967-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10295468. Licensed CC0.

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