Technology-based fall risk assessments for older adults in low-income settings
基于技术的低收入老年人跌倒风险评估
基本信息
- 批准号:10093556
- 负责人:
- 金额:$ 7.45万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-30 至 2022-06-30
- 项目状态:已结题
- 来源:
- 关键词:AccelerometerAge-YearsAmericanBiolectric ImpedanceBody CompositionBody fatBody mass indexBody measure procedureCensusesChronicCognitive deficitsCommunitiesCross-Sectional StudiesDataDevelopmentDevicesElderlyEnrollmentEquilibriumExclusion CriteriaFloridaFrightHealth TechnologyHome environmentImpaired cognitionInterventionKnowledgeLinkLongevityLow incomeMeasurementMeasuresMedicalObesityOverweightPacemakersParticipantPatient Self-ReportPerformancePhysical activityPhysiologicalPilot ProjectsPovertyProceduresQuality of lifeQuestionnairesRehabilitation therapyReportingResearchRisk AssessmentSafetySamplingSeveritiesShortness of BreathSkeletal MuscleSocial isolationSystemTechnologyTestingTimeWell in selfWomanactigraphybalance testingbasedesigndisabilityfall riskfallsfear of fallingfunctional disabilityimprovedimproved functioningmedical implantmonitoring devicemuscle formnovelphysical inactivityportabilityprogramsrecruitresidenceskills
项目摘要
PROJECT SUMMARY/ABSTRACT
In the US, older adults (OAs) who live in low-income communities are less likely to engage in physical activity
(PA). Lack of PA is related to chronic conditions and poor quality of life. Limited data suggest that OAs who
report fear of falling (FOF) and overestimate their fall risk are less likely to participate in PA; and the
association between FOF and PA intensity differs by fear severity. One-third of OAs have maladaptive fall risk
appraisal (FRA), a condition in which there is a discrepancy between levels of FOF) and balance performance.
Maladaptive FRA may impede low-income OAs participation in PA and can result in social isolation. Measuring
FRA in OAs can be challenging due to self-report bias and cognitive deficit. Thus, we developed a fall risk
appraisal matrix, a graphical grid categorizing levels of FOF and balance performance into four groups
(rational/ incongruent/ irrational/ congruent). Additionally, body composition (e.g., obesity, low skeletal muscle
mass) has been associated with FOF and functional impairment. However, research has not examined the
association among body composition, FRA, and PA using Assistive Health Technology (AHT), which is the
application of organization knowledge, skills, procedures, and systems in order to improve functioning. We
propose to explore the associations among body composition, FRA, and PA using AHT including bioelectric
impedance analysis (BIA), BTracK Balance System (BBS), and accelerometer-based physical activity devices.
These devices are portable, non-invasive, safe, valid, reliable and allow for home testing. We employ a cross-
sectional study. Aim 1 is to examine the feasibility of recruitment (e.g., how many OAs need to be screened to
recruit the sample?) and acceptability of technologies and procedures for use among OAs in low-income
settings. Aim 2 is to examine the associations among fall risk appraisal, body composition, and physical
activity. Participants (N=120) will be enrolled if they are: 1) ≥ 60 years of age, 2) low-income (using poverty
thresholds from the US Census Bureau), 3) no marked cognitive impairment, and 4) live in their own homes or
apartments. Exclusion criteria: 1) a medical condition precluding balance test (e.g., unable to stand on the
balance plate) and/or PA (e.g., shortness of breath when performing PA); or 2) currently receiving treatment
from a rehabilitation facility, or 3) medical implants (e.g., pacemakers). Data will be collected at OAs’ place of
residence. OAs will be assessed FOF, balance performance, and body composition using a questionnaire,
BBS, and BIA, respectively. OAs will wear an accelerometer-based physical activity device (ActiGraph GT9X
Link) for 7 days. Accurate FRA is essential in implementing physical activity programs. This study will provide
data for the development of a technology-based intervention that facilitates a shift from maladaptive to adaptive
FRA, and improving participation in PA, thus enhancing healthy longevity among OAs in low-income settings.
项目摘要/摘要
在美国,生活在低收入社区的老年人(OA)不太可能从事体育活动
(帕)。缺乏PA与慢性病和生活质量差有关。有限的数据表明,美洲国家组织
报告害怕跌倒(FOF)和高估他们跌倒的风险不太可能参与PA;
FOF和PA强度之间的关联因恐惧严重程度而不同。三分之一的OAS有适应不良跌倒的风险
评估(FRA),即FOF水平和平衡绩效之间存在差异的情况。
不适应的FRA可能会阻碍低收入的美洲国家组织参与PA,并可能导致社会孤立。量测
由于自我报告偏差和认知缺陷,FRA在OAS中可能具有挑战性。因此,我们形成了一种跌倒风险
评估矩阵,一个图形网格,将FOF和Balance绩效级别分类为四组
(理性/不一致/不合理/一致)。此外,身体成分(例如,肥胖、低骨骼肌
肿块)与FOF和功能损害有关。然而,研究并没有检查
使用辅助健康技术(AHT)在身体成分、FRA和PA之间的关联,这是
组织知识、技能、程序和系统的应用,以改进运作。我们
建议使用包括生物电在内的AHT来探索身体成分、FRA和PA之间的关联
阻抗分析(BIA)、BTracK平衡系统(BBS)和基于加速度计的体力活动设备。
这些设备是便携的、非侵入性的、安全的、有效的、可靠的,并允许在家中测试。我们雇佣了一个十字架-
横断面研究。目标1是审查招聘的可行性(例如,需要对多少组织进行筛选
招募样本?)低收入国家组织使用的技术和程序的可接受性
设置。目标2是检查跌倒风险评估、身体成分和体能之间的联系。
活动。符合以下条件的参与者(N=120)将被纳入:1)60岁的≥,2)低收入(使用贫困
来自美国人口普查局的门槛),3)没有明显的认知障碍,4)住在自己的家里或
公寓。排除标准:1)身体状况不能进行平衡测试(例如,不能站在
平衡板)和/或PA(例如,进行PA时呼吸急促);或2)目前正在接受治疗
从康复机构,或3)医疗植入物(例如,起搏器)。数据将在美洲国家组织的
住处。OAS将使用问卷对FOF、平衡能力和身体成分进行评估,
BBS和BIA。OAS将佩戴基于加速度计的体力活动设备(Actigraph GT9X
链接),为期7天。准确的法兰克福机场是实施体力活动计划的关键。这项研究将提供
促进从适应不良向适应转变的以技术为基础的干预发展的数据
FRA,并改善对PA的参与,从而提高低收入环境下美洲国家组织的健康寿命。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Ladda Thiamwong其他文献
Ladda Thiamwong的其他文献
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{{ truncateString('Ladda Thiamwong', 18)}}的其他基金
Optimizing a technology-based body and mind intervention to prevent falls and reduce health disparities in low-income populations.
优化基于技术的身心干预措施,以防止跌倒并减少低收入人群的健康差距。
- 批准号:
10790425 - 财政年份:2022
- 资助金额:
$ 7.45万 - 项目类别:
Optimizing a technology-based body and mind intervention to prevent falls and reduce health disparities in low-income populations
优化基于技术的身心干预措施,以预防跌倒并减少低收入人群的健康差距
- 批准号:
10710190 - 财政年份:2022
- 资助金额:
$ 7.45万 - 项目类别:
Optimizing a technology-based body and mind intervention to prevent falls and reduce health disparities in low-income populations
优化基于技术的身心干预措施,以预防跌倒并减少低收入人群的健康差距
- 批准号:
10570625 - 财政年份:2022
- 资助金额:
$ 7.45万 - 项目类别:
Technology-based fall risk assessments for older adults in low-income settings
基于技术的低收入老年人跌倒风险评估
- 批准号:
10264885 - 财政年份:2020
- 资助金额:
$ 7.45万 - 项目类别:
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