Optimizing a technology-based body and mind intervention to prevent falls and reduce health disparities in low-income populations

项目摘要/摘要 跌倒和害怕跌倒(FOF)是不同种族人群受伤、残疾和住院的主要原因 低收入老年人(LOA)。缺乏动力、资源有限、受教育程度低和不便依然存在 参与跌倒预防计划的障碍。超过一半的老年人有适应不良的跌倒风险 评估(FRA)，即感觉到的跌倒风险(FOF水平)和 生理性跌倒风险(平衡能力)，可能阻碍体力活动(PA)。帮助解决 不适应的FRA；我们开发了一个跌倒风险评估矩阵，一个对FOF(Mind)级别进行分类的图形网格 和平衡水平(身体)分为四个象限：1)有理FRA(低FOF和正常平衡)，2) 不一致的FRA(尽管平衡差，但FOF低)，3)不合理的FRA(尽管平衡正常，但FOF高)，以及4) 一致的FRA(高FOF和较差的平衡)。我们开发了一个新颖的，为期8周的基于技术的，个性化的， 家庭物理反馈锻炼计划(PEER)，其包括：a)使用实时的物理反馈 便携创新技术-BTrackS平衡系统：BBS；b)基于一种新的认知重组 摔倒风险评估矩阵；以及c)注重平衡和力量训练的同伴主导运动。我们的R03 研究结果支持使用BBS技术筛查适应不良的LOA的可行性和可接受性 强调减少久坐时间和增加适度到剧烈体力活动的重要性 (MVPA)帮助从适应不良向自适应FRA转变的时间。关键的是，我们发现我们的贷款中没有一个 在我们的研究之前，有没有人评估过他们的跌倒风险和FOF，他们的数据显示， FOF和对衰老的负面自我认知。在我们发表的先导研究中，我们发现基于技术的 同伴干预显著改善了动态平衡，降低了跌倒风险，并促进了 不适应适应性变化；然而，我们有限的LOA样本(占总数的40%)阻止了强烈的 关于这一组的有效性的结论。我们使用一项群集化随机对照试验， 将在佛罗里达州奥兰多的低收入独立生活社区/单位通过我们的 与社区和公共卫生组织建立伙伴关系。我们将在基线(T1)和 评估项目完成后(T2)、3个月(T3)和6个月(T4)的结果。低收入者 老年人(n=340)将被纳入，如果他们是≥60岁，认知完好无损，并且能够在没有 援助。我们的目标是1)检验基于技术的同伴干预对跌倒风险的影响，动态 平衡和基于加速度计的体力活动；2)检查干预对跌倒风险的影响 评估转移和对衰老的负面自我认知；以及3)探索参与者对 干预以及获取和采用以技术为基础的同行干预的潜在障碍。本研究 通过优化技术驱动的量身定制的方法来解决公共卫生问题，该方法可以 在拥有无限用户的低资源环境中运行，以防止跌倒并减少健康差距。

PROJECT SUMMARY/ABSTRACT Falls and fear of falling (FOF) are the leading cause of injury, disability, and hospitalization in racially diverse low-income older adults (LOA). Lack of motivation, limited resources, low education, and inconvenience remain barriers to participate in fall prevention programs. More than half of older adults have maladaptive fall risk appraisal (FRA), a condition in which there is a discrepancy between perceived fall risk (levels of FOF) and physiological fall risk (balance performance) which may impede physical activity (PA). To help address maladaptive FRA; we developed a fall risk appraisal matrix, a graphical grid categorizing levels of FOF (Mind) and levels of balance (Body) into four quadrants: 1) rational FRA (low FOF and normal balance), 2) incongruent FRA (low FOF despite poor balance), 3) irrational FRA (high FOF despite normal balance), and 4) congruent FRA (high FOF and poor balance). We developed a novel, 8-week technology-based, individualized, in-home Physio-fEedback Exercise pRogram (PEER), which includes a) physio-feedback using a real-time portable innovative technology—the BTrackS Balance System: BBS; b) cognitive reframing based on a novel fall risk appraisal matrix; and c) peer-led exercise by focusing on balance and strength training. Our R03 findings support the feasibility and acceptability of using BBS technology on screening LOA with maladaptive FRA, highlight the importance of reducing sedentary time and increasing moderate to vigorous physical activity (MVPA) time to help shift from maladaptive to adaptive FRA. Critically, we found that none of our LOA had ever had their fall risk and FOF assessed before our study and their data reveal a strong relationship between FOF and negative self-perceptions of aging. In our published pilot study, we found that the technology-based PEER intervention had significant improvements in dynamic balance, reduced fall risk, and facilitated maladaptive to adaptive shifting; however, our limited sample of LOA (40% of total) prevents strong conclusions about effectiveness in this group. We use a clustered randomized controlled trial, and the intervention will be offered at the low-income independent living communities/units in Orlando, FL through our partnership with community-based & public health organizations. We will collect data at baseline (T1) and measure outcomes after program completion (T2), follow up at 3-months (T3), and 6-months (T4). Low-income older adults (n=340) will be enrolled if they are ≥60 years old, cognitive intact, and able to stand without assistance. We aim to 1) examine the effects of the technology-based PEER intervention on fall risk, dynamic balance, and accelerometer-based physical activity; 2) examine the effects of the intervention on fall risk appraisal shifting and negative self-perceptions of aging; and 3) explore participants’ experiences with the intervention and potential barriers to access and adoption of technology-based PEER intervention. This study addresses the public health problem with the optimization of a technology - driven tailored approach that can operate in low-resource environments with unlimited users to prevent falls and reduce health disparities.