{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T17:01:32Z","timestamp":1791478892890,"version":"4.3.4"},"reference-count":46,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T00:00:00Z","timestamp":1759881600000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["P01 AG03991"],"award-info":[{"award-number":["P01 AG03991"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["P01 AG026276"],"award-info":[{"award-number":["P01 AG026276"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["P30 AG066444"],"award-info":[{"award-number":["P30 AG066444"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alzheimer's &amp;amp; Dementia"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION<\/jats:title>\n                    <jats:p>Sleep disturbances are associated with Alzheimer's disease (AD) pathology and cognitive symptoms, but few studies have longitudinally assessed sleep, AD biomarkers, and cognition. Understanding how sleep changes over time in older adults with and without AD pathology is crucial for appropriately designing longitudinal studies of aging and AD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>Sleep was measured over \u22483.5 years in older adults using self\u2010reported questionnaires and an at\u2010home single\u2010channel electroencephalography (scEEG) device. Participants also underwent amyloid imaging and cognitive testing. Longitudinal change of multiple sleep parameters was determined and sample sizes estimated for future clinical trials using sleep as an outcome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>In both amyloid groups, EEG spectral power measures demonstrated minimal longitudinal change, whereas self\u2010reported and sleep parameters such as sleep efficiency demonstrated greater variability over time.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>This study characterized how sleep parameters change in older adults with and without AD pathology, offering important guidance for future longitudinal studies targeting sleep and neurodegeneration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Low variability in electroencephalography (EEG) spectral power metrics, including delta, theta, and alpha power.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Greater variability in self\u2010report sleep metrics, including self\u2010reported time to fall asleep and EEG\u2010derived metrics such as sleep duration and N2 sleep.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Understanding the variability in sleep measures over time will offer important guidance for designing future longitudinal studies targeting sleep and neurodegeneration.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.70761","type":"journal-article","created":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T09:54:50Z","timestamp":1759917290000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Variability of longitudinal sleep monitoring in amyloid\u2010negative and amyloid\u2010positive cognitively unimpaired and mildly impaired older adults"],"prefix":"10.1002","volume":"21","author":[{"given":"Taylor J.","family":"Pedersen","sequence":"first","affiliation":[{"name":"Department of Psychological &amp; 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