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使用预防老年人事故、死亡和伤害算法评估社区居住老年人的跌倒风险

Assessment of Fall Risk in Community-Dwelling Older Adults Using the Stopping Elderly Accidents, Deaths, and Injuries Algorithm.

作者信息

Yang Kyeongra, Wingerden Anita Van, Galagoza Marta, Soldevilla Karla, Lim Ethan A, Wagner Mary L

机构信息

Entry to Baccalaureate Practice Division, Rutgers University, School of Nursing, Newark, New Jersey, USA.

Department of Rehabilitation & Movement Sciences, Rutgers University, School of Health Professions, Newark, New Jersey, USA.

出版信息

Nurs Open. 2025 Sep;12(9):e70299. doi: 10.1002/nop2.70299.

Abstract

AIM

To identify individuals at risk of falls and the factors contributing to their risk, we screened community-dwelling older adults using the Centers for Disease Control and Prevention's Stopping Elderly Accidents, Deaths, and Injuries (STEADI) Assessments.

DESIGN

A descriptive correlational study design.

METHODS

Fall risk screenings with community-dwelling older adults aged 65 or older were conducted during a virtual interprofessional education event (IPE) for fall risk screening. The screening included demographic questions, perception of fall risks, medication questions and physical assessments (Timed Up and Go test, Single Leg test, 30-Second Sit to Stand) using the STEADI algorithm. Screening data were collected via Qualtrics, and descriptive data analyses were performed using SPSS.

RESULTS

In total, 114 community volunteers aged 65 or older were screened for fall risk. Using the STEADI Fall Risk questionnaire, 84 participants (73.7%) exhibited at least one clinically proven risk factor for falls, with 39 (34.2%) having four or more risk factors. The physical assessments identified 37 participants (32.5%) with functional leg weakness, 47 (41.2%) had poor mobility and 32 (28.1%) had poor balance. As a result, the modified STEADI algorithm identified 68 (59.6%) with fall risk and the most frequently discussed SMART objectives were related to physical assessment data issues (34.5%).

PATIENT OR PUBLIC CONTRIBUTION

Our study confirmed the effectiveness of a multifaceted STEADI assessment in identifying community individuals at risk for falls who may not be detected through the normal standard of care. Educating nurses on performing comprehensive fall risk assessments and creating corresponding action plans with SMART objectives is essential to ensure thorough screening and care of their patients. A collaborative, interprofessional education programme can help train health professional students to gain valuable skills in conducting comprehensive fall risk screenings and developing objectives for future care plans based on those findings.

摘要

目的

为了识别有跌倒风险的个体及其风险因素,我们使用美国疾病控制与预防中心的“预防老年人事故、死亡和伤害”(STEADI)评估工具,对社区居住的老年人进行了筛查。

设计

描述性相关性研究设计。

方法

在一次关于跌倒风险筛查的虚拟跨专业教育活动(IPE)期间,对65岁及以上居住在社区的老年人进行了跌倒风险筛查。筛查包括人口统计学问题、对跌倒风险的认知、用药问题以及使用STEADI算法进行的身体评估(计时起立行走测试、单腿测试、30秒坐立测试)。筛查数据通过Qualtrics收集,并使用SPSS进行描述性数据分析。

结果

总共对114名65岁及以上的社区志愿者进行了跌倒风险筛查。使用STEADI跌倒风险问卷,84名参与者(73.7%)表现出至少一种经临床证实的跌倒风险因素,其中39名(34.2%)有四个或更多风险因素。身体评估发现37名参与者(32.5%)存在功能性腿部无力,47名(41.2%)行动能力差,32名(28.1%)平衡能力差。因此,改良后的STEADI算法识别出68名(59.6%)有跌倒风险,讨论最多的SMART目标与身体评估数据问题有关(34.5%)。

患者或公众贡献

我们的研究证实了多方面的STEADI评估在识别社区中可能无法通过正常护理标准检测到的跌倒风险个体方面的有效性。培训护士进行全面的跌倒风险评估并制定具有SMART目标的相应行动计划,对于确保对患者进行全面筛查和护理至关重要。一个协作性的跨专业教育计划可以帮助培训健康专业学生获得进行全面跌倒风险筛查以及根据这些结果为未来护理计划制定目标的宝贵技能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd08/12413634/91a9bae5d1b2/NOP2-12-e70299-g001.jpg

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