Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study
Background and Objective: Within-person variability in cognitive performance has emerged as a promising indicator of cognitive health with potential to distinguish normative and pathological cognitive aging. We use a smartphone-based digital health approach with ecological momentary assessments (EMA...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:2ca958f948ea4ddabc14d3868b1fc8632021-12-03T04:58:32ZVariability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study2673-253X10.3389/fdgth.2021.758031https://doaj.org/article/2ca958f948ea4ddabc14d3868b1fc8632021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fdgth.2021.758031/fullhttps://doaj.org/toc/2673-253XBackground and Objective: Within-person variability in cognitive performance has emerged as a promising indicator of cognitive health with potential to distinguish normative and pathological cognitive aging. We use a smartphone-based digital health approach with ecological momentary assessments (EMA) to examine differences in variability in performance among older adults with mild cognitive impairment (MCI) and those who were cognitively unimpaired (CU).Method: A sample of 311 systematically recruited, community-dwelling older adults from the Einstein Aging Study (Mean age = 77.46 years, SD = 4.86, Range = 70–90; 67% Female; 45% Non-Hispanic White, 40% Non-Hispanic Black) completed neuropsychological testing, neurological assessments, and self-reported questionnaires. One hundred individuals met Jak/Bondi criteria for MCI. All participants performed mobile cognitive tests of processing speed, visual short-term memory binding, and spatial working memory on a smartphone device up to six times daily for 16 days, yielding up to 96 assessments per person. We employed heterogeneous variance multilevel models using log-linear prediction of residual variance to simultaneously assess cognitive status differences in mean performance, within-day variability, and day-to-day variability. We further tested whether these differences were robust to the influence of environmental contexts under which assessments were performed.Results: Individuals with MCI exhibited greater within-day variability than those who were CU on ambulatory assessments that measure processing speed (p < 0.001) and visual short-term memory binding (p < 0.001) performance but not spatial working memory. Cognitive status differences in day-to-day variability were present only for the measure of processing speed. Associations between cognitive status and within-day variability in performance were robust to adjustment for sociodemographic and contextual variables.Conclusion: Our smartphone-based digital health approach facilitates the ambulatory assessment of cognitive performance in older adults and the capacity to differentiate individuals with MCI from those who were CU. Results suggest variability in mobile cognitive performance is sensitive to MCI and exhibits dissociative patterns by timescale and cognitive domain. Variability in processing speed and visual short-term memory binding performance may provide specific detection of MCI. The 16-day smartphone-based EMA measurement burst offers novel opportunity to leverage digital technology to measure performance variability across frequent assessments for studying cognitive health and identifying early clinical manifestations of cognitive impairment.Eric S. CerinoEric S. CerinoMindy J. KatzCuiling WangCuiling WangJiyue QinQi GaoJinshil HyunJonathan G. HakunJonathan G. HakunNelson A. RoqueCarol A. DerbyRichard B. LiptonRichard B. LiptonMartin J. SliwinskiFrontiers Media S.A.articlecognitive performance variabilitycognitive healthmild cognitive impairment–MCImobile cognitive assessmenttechnologyecological momentary assessment (EMA)MedicineRPublic aspects of medicineRA1-1270Electronic computers. Computer scienceQA75.5-76.95ENFrontiers in Digital Health, Vol 3 (2021) |
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| collection |
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| topic |
cognitive performance variability cognitive health mild cognitive impairment–MCI mobile cognitive assessment technology ecological momentary assessment (EMA) Medicine R Public aspects of medicine RA1-1270 Electronic computers. Computer science QA75.5-76.95 |
| spellingShingle |
cognitive performance variability cognitive health mild cognitive impairment–MCI mobile cognitive assessment technology ecological momentary assessment (EMA) Medicine R Public aspects of medicine RA1-1270 Electronic computers. Computer science QA75.5-76.95 Eric S. Cerino Eric S. Cerino Mindy J. Katz Cuiling Wang Cuiling Wang Jiyue Qin Qi Gao Jinshil Hyun Jonathan G. Hakun Jonathan G. Hakun Nelson A. Roque Carol A. Derby Richard B. Lipton Richard B. Lipton Martin J. Sliwinski Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study |
| description |
Background and Objective: Within-person variability in cognitive performance has emerged as a promising indicator of cognitive health with potential to distinguish normative and pathological cognitive aging. We use a smartphone-based digital health approach with ecological momentary assessments (EMA) to examine differences in variability in performance among older adults with mild cognitive impairment (MCI) and those who were cognitively unimpaired (CU).Method: A sample of 311 systematically recruited, community-dwelling older adults from the Einstein Aging Study (Mean age = 77.46 years, SD = 4.86, Range = 70–90; 67% Female; 45% Non-Hispanic White, 40% Non-Hispanic Black) completed neuropsychological testing, neurological assessments, and self-reported questionnaires. One hundred individuals met Jak/Bondi criteria for MCI. All participants performed mobile cognitive tests of processing speed, visual short-term memory binding, and spatial working memory on a smartphone device up to six times daily for 16 days, yielding up to 96 assessments per person. We employed heterogeneous variance multilevel models using log-linear prediction of residual variance to simultaneously assess cognitive status differences in mean performance, within-day variability, and day-to-day variability. We further tested whether these differences were robust to the influence of environmental contexts under which assessments were performed.Results: Individuals with MCI exhibited greater within-day variability than those who were CU on ambulatory assessments that measure processing speed (p < 0.001) and visual short-term memory binding (p < 0.001) performance but not spatial working memory. Cognitive status differences in day-to-day variability were present only for the measure of processing speed. Associations between cognitive status and within-day variability in performance were robust to adjustment for sociodemographic and contextual variables.Conclusion: Our smartphone-based digital health approach facilitates the ambulatory assessment of cognitive performance in older adults and the capacity to differentiate individuals with MCI from those who were CU. Results suggest variability in mobile cognitive performance is sensitive to MCI and exhibits dissociative patterns by timescale and cognitive domain. Variability in processing speed and visual short-term memory binding performance may provide specific detection of MCI. The 16-day smartphone-based EMA measurement burst offers novel opportunity to leverage digital technology to measure performance variability across frequent assessments for studying cognitive health and identifying early clinical manifestations of cognitive impairment. |
| format |
article |
| author |
Eric S. Cerino Eric S. Cerino Mindy J. Katz Cuiling Wang Cuiling Wang Jiyue Qin Qi Gao Jinshil Hyun Jonathan G. Hakun Jonathan G. Hakun Nelson A. Roque Carol A. Derby Richard B. Lipton Richard B. Lipton Martin J. Sliwinski |
| author_facet |
Eric S. Cerino Eric S. Cerino Mindy J. Katz Cuiling Wang Cuiling Wang Jiyue Qin Qi Gao Jinshil Hyun Jonathan G. Hakun Jonathan G. Hakun Nelson A. Roque Carol A. Derby Richard B. Lipton Richard B. Lipton Martin J. Sliwinski |
| author_sort |
Eric S. Cerino |
| title |
Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study |
| title_short |
Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study |
| title_full |
Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study |
| title_fullStr |
Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study |
| title_full_unstemmed |
Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study |
| title_sort |
variability in cognitive performance on mobile devices is sensitive to mild cognitive impairment: results from the einstein aging study |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/2ca958f948ea4ddabc14d3868b1fc863 |
| work_keys_str_mv |
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