Biobehavioral Nursing and Health Systems, School of Nursing, Box 357266, University of Washington, Seattle, WA 98195, USA.
Int J Med Inform. 2013 Jul;82(7):565-79. doi: 10.1016/j.ijmedinf.2013.03.007. Epub 2013 Apr 30.
There is a critical need for public health interventions to support the independence of older adults as the world's population ages. Health smart homes (HSH) and home-based consumer health (HCH) technologies may play a role in these interventions.
We conducted a systematic review of HSH and HCH literature from indexed repositories for health care and technology disciplines (e.g., MEDLINE, CINAHL, and IEEE Xplore) and classified included studies according to an evidence-based public health (EBPH) typology.
One thousand, six hundred and thirty-nine candidate articles were identified. Thirty-one studies from the years 1998-2011 were included. Twenty-one included studies were classified as emerging, 10 as promising and 3 as effective (first tier).
The majority of included studies were published in the period beginning in the year 2005. All 3 effective (first tier) studies and 9 of 10 of promising studies were published during this period. Almost all studies included an activity sensing component and most of them used passive infrared motion sensors. The three effective (first tier) studies all used a multicomponent technology approach that included activity sensing, reminders and other technologies tailored to individual preferences. Future research should explore the use of technology for self-management of health by older adults; social support; and self-reported health measures incorporated into personal health records, electronic medical records, and community health registries.
随着世界人口老龄化,公共卫生干预措施迫切需要支持老年人的独立性。健康智能家居(HSH)和家庭为基础的消费者健康(HCH)技术可能在这些干预措施中发挥作用。
我们从医疗保健和技术学科的索引库(例如 MEDLINE、CINAHL 和 IEEE Xplore)中对 HSH 和 HCH 文献进行了系统回顾,并根据循证公共卫生(EBPH)分类法对纳入的研究进行了分类。
确定了 1639 篇候选文章。纳入了 1998 年至 2011 年的 31 项研究。21 项纳入的研究被归类为新兴,10 项为有前途,3 项为有效(第一级)。
纳入的研究大多发表在 2005 年开始的时期。所有 3 项有效(第一级)研究和 10 项有前途的研究中的 9 项都发表在这一时期。几乎所有的研究都包含了活动感应组件,其中大多数使用被动红外运动传感器。这三项有效(第一级)的研究都使用了多组件技术方法,包括活动感应、提醒和其他针对个人喜好定制的技术。未来的研究应该探索利用技术来实现老年人的健康自我管理;社会支持;以及个人健康记录、电子病历和社区健康登记中纳入的自我报告健康指标。