{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T07:00:53Z","timestamp":1790060453294,"version":"4.0.1"},"reference-count":91,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nursing in Critical Care"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sleep and circadian disruption are common in critical illness, yet bedside assessment remains difficult. Wearables are unobtrusive and extend observation across 24\u2009h, but their measurement performance in critical illness requires appraisal.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>To map wearable sleep and circadian monitoring during intensive care, its measurement performance, clinical applications and nursing implications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Design<\/jats:title>\n                    <jats:p>A scoping review followed JBI and PRISMA\u2010ScR guidance. PubMed, Europe PMC and OpenAlex were searched from inception to 22 July 2026, with citation searching. Eligible primary reports used a body\u2010worn sensor during intensive care to estimate sleep or circadian\/rest\u2013activity outcomes at any age. Conventional polysomnography\/electroencephalography without an eligible wearable, non\u2010contact systems, staff studies and post\u2010ICU\u2010only monitoring were excluded. No risk\u2010of\u2010bias appraisal was undertaken.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Sixty\u2010one reports (43 adult; 18 paediatric\/neonatal; 1996\u20132026) were included. Actigraphy dominated; commercial trackers, smartwatches and one respiratory\u2010belt\/heart\u2010rate\u2010variability system were less common. Monitoring was feasible, but performance varied by device, patient state and age group: wake specificity was often poor in ventilated, sedated or immobile patients and agreement with patient or nurse reports was weak to modest. Records showed fragmented and daytime sleep, weak day\u2013night consolidation and attenuated circadian rhythmicity. Nursing bundles, massage, positioning, light and chronotype\u2010informed care changed selected outcomes, but effects were heterogeneous.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Wearables usefully describe rest\u2013activity patterns and support nursing assessment, but agreement with physiological sleep varied by device, patient state and age; movement\u2010derived estimates need clinical context and are not a stand\u2010alone sleep measure.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Relevance to Clinical Practice<\/jats:title>\n                    <jats:p>Nurses should combine wearable trends with patient report, sedation and mobility, delirium screening and care\u2010interaction records; escalation thresholds require prospective validation.<\/jats:p>\n                  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