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5 Intraindividual Variability in Processing Speed on Digital Cognitive Assessments Differs by Amyloidosis Status in Cognitively Normal Older Adults
- Alyssa De Vito, Zachary Kunicki, Karysa Britton, Priscilla Villa, Jennifer Strenger, Karra Harrington, Nelson Roque, Martin J. Sliwinski, Louisa I. Thompson
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 217-218
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Objective:
Intraindividual variability (IIV) is defined as fluctuations in an individual’s cognitive performance over time1. IIV has been identified as a marker of neurobiological disturbance making it a useful method for detecting changes in cognition among cognitively healthy individuals as well as those with prodromal syndromes2. IIV on laboratory-based computerized tasks has been linked with cognitive decline and conversion to mild cognitive impairment (MCI) and/or dementia (Haynes et al., 2017). Associations between IIV and AD risk factors including apolipoprotein (APOE) ε4 carrier status, neurodegeneration seen on brain imaging, and amyloid (Aß) Positron emission tomography (PET) scan status have also been observed1. Recent studies have demonstrated that evaluating IIV on smartphone-based digital cognitive assessments is feasible, has the capacity to differentiate between cognitively normal (CN) and MCI individuals, and may reduce barriers to cognitive assessment3. This study sought to evaluate whether such differences could be detected in CN participants with and without elevated AD risk.
Participants and Methods:Participants (n=57) were cognitively normal older adults who previously received an Aß PET scan through the Butler Hospital Memory and Aging Program. The sample consisted of primarily non-Hispanic (n=49, 86.0%), White (n=52, 91.2%), college-educated (M=16.65 years), females (n=39, 68.4%). The average age of the sample was 68 years old. Approximately 42% of the sample (n=24) received a positive PET scan result. Participants completed brief cognitive assessments (i.e., 3-4 minutes) three times per day for eight days (i.e., 24 sessions) using the Mobile Monitoring of Cognitive Change (M2C2) application, a mobile app-based cognitive testing platform developed as part of the National Institute of Aging’s Mobile Toolbox initiative (Sliwinski et al., 2018). Participants completed visual working memory, processing speed, and episodic memory tasks on the M2C2 platform. Intraindividual standard deviations (ISDs) across trials were computed for each person at each time point (Hultsch et al., 2000). Higher ISD values indicate more variability in performance. Linear mixed effects models were utilized to examine whether differences in IIV existed based on PET scan status while controlling for age, sex at birth, and years of education.
Results:n interaction between PET status and time was observed on the processing speed task such that Aß- individuals were less variable over the eight assessment days compared to Aß + individuals (B= -5.79, SE=2.67, p=.04). No main or interaction effects were observed on the visual working memory task or episodic memory task.
Conclusions:Our finding that Aß- individuals demonstrate less variability over time on a measure of processing speed is consistent with prior work. No associations were found between IIV in other cognitive domains and PET status. As noted by Allaire and Marsiske (2005), IIV is not a consistent phenomenon across different cognitive domains. Therefore, identifying which tests are the most sensitive to early change is crucial. Additional studies in larger, more diverse samples are needed prior to widespread clinical use for early detection of AD.
48 Psychometric properties of DCTclock™ with commonly used neuropsychological tests and their combined ability to predict Beta-Amyloid Positron Emission Tomography Status
- Sheina Emrani, Jennifer Strenger, Zachary Kunicki, Alyssa De Vito, Stephen Salloway, Louisa Thompson
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 255-256
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Objective:
Sensitive and non-invasive methods of screening for early-stage Alzheimer’s disease (AD) are urgently needed. The digital clock drawing test (DCTclockTM) is an established and well-researched neuropsychological tool that can aid in early detection of dementia. Other simple, yet sensitive, neuropsychological measures able to detect early stages of AD include Trail Making Tests (TMT). We investigated the psychometric properties of DCTclockTM with TMT-A and TMT-B. We then sought to understand the degree to which neuropsychological tools (i.e., DCTclockTM, TMT-A, and B) versus the Montreal Cognitive Assessment (MoCA) predict beta-amyloid (Aß) positron emission tomography (PET) status (positive or negative) in cognitively normal individuals.
Participants and Methods:Participants included a sample of cognitively normal older adults (n= 59, M age = 69.2, F = 64%) recruited from the Butler Memory and Aging Program. The Linus Health DCTclockTM uses a digital pen to capture traditional clock drawing test performance and advanced analytics to evaluate the drawing process for indicators of cognitive difficulty. DCTclockTM may have overlapping cognitive properties with TMT measures, like efficiency, processing speed, and spatial reasoning. We compared latency measures (i.e., process efficiency, clock face speed, average latency, and processing speed) and spatial reasoning of the DCTclockTM to z-scores of TMT-A and TMT-B to detect any overlapping psychometric properties. Verbal fluency was included for discriminant validity. We then ran logistic regressions on a subset of the sample to compare neuropsychological tests (DCTclockTM total score [score that captures overall performance], TMT-A/B, and verbal fluency) to the MoCA, a commonly used cognitive screening tool, in determining PET status.
Results:Highly correlated (r > .7) DCTclockTM variables were excluded. We found statistically significant correlations between some DCTclockTM measures and TMT-A/B, like DCTclockTM drawing process efficiency and TMT-A and TMT-B (r= .45, p< .001, r=.29, p< .026, respectively), and DCTclockTM average latency and TMT-A and TMT-B (r=.3, p< .024, r= .26, p< .044, respectively). No statistically significant associations were found between any DCTclockTM measures and verbal fluency, or between DCTclockTM spatial reasoning and TMT-A/B. We then investigated the effect of these neuropsychological tests (DCTclockTM total score, TMT-A/B, verbal fluency) and age on the likelihood of PET positivity (subset of sample, total PET, n=31). The model was statistically significant (x2 (5) = 15.35, p< .01). The model explained 53% (Nagelkerke R2) of the variance in PET status and correctly classified 74.2% of cases. DCTclockTM was the only significant predictor (p< .02), after controlling for TMT-A, TMT-B, verbal fluency, and age. Comparatively, there was no effect of MoCA and age (total PET, n= 29) on the likelihood of PET positivity.
Conclusions:Overall, these results suggest psychometric convergence on elements of DCTclockTM and TMT-A/B, while there was no association in spatial operations between DCTclockTM and TMT measures. Further, when compared to the MoCA, DCTclockTM and these commonly used neuropsychological tests (verbal fluency and TMT-A/B) were better predictors of PET status, primarily driven by the DCTclockTM. Digitized neuropsychological tools may provide additional metrics not captured by pen-and-paper tests that can detect AD-associated pathology.