{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T15:40:27Z","timestamp":1791906027059,"version":"4.3.4"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T00:00:00Z","timestamp":1741046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"National Institute on Aging of the National Institutes of Health","award":["R03AG069793"],"award-info":[{"award-number":["R03AG069793"]}]},{"name":"National Institute on Aging of the National Institutes of Health","award":["P30AG073105"],"award-info":[{"award-number":["P30AG073105"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Falls and fall-related injuries are significant public health issues for adults 65 years of age and older. The annual direct medical costs in the United States as a result of falls are estimated to exceed $50 billion, and this estimate does not include the indirect costs of disability, dependence, and decreased quality of life. This project targets community-dwelling older adults (OA) with mild cognitive impairment (MCI) who are socially vulnerable and thus at high risk for falling.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We have developed an innovative technology-supported nursing-driven intervention called Sense4Safety to (a) identify escalating risk for falls real time through in-home passive sensor monitoring (including depth sensors); (b) employ machine learning to inform individualized alerts for fall risk; and (c) link \u201cat risk\u201d socially vulnerable OA with a coach who guides them in implementing evidence-based individualized plans to reduce fall risk. The purpose of this study was to assess the feasibility and acceptability of the Sense4Safety intervention through participant interviews.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We recruited a cohort of 11 low-income OA with MCI who received the intervention for 3 months. Our study findings indicate the overall feasibility of the intervention with most participants (n\u2005=\u20059; 82%) having confidence in the passive monitoring system to effectively predict fall risk and generate actionable and tailored information that informs educational and exercise components.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Passive sensing technologies can introduce acceptable platforms for fall prevention for community-dwelling OA with MCI.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/gerona\/glaf043","type":"journal-article","created":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T00:24:48Z","timestamp":1741134288000},"source":"Crossref","is-referenced-by-count":8,"title":["Feasibility and Acceptability of a Technology-Mediated Fall Risk Prevention Intervention for Older Adults With Mild Cognitive 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