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A Short Screening Measure of Contextual Vulnerability for Financial Exploitation

机译:金融剥削中情境脆弱性的短暂筛选措施

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摘要

Financial exploitation (FE) among older adults is an expensive personal and societal problem. Many professionals who work with older adults need fast and reliable measures to detect FE, including: APS workers, financial professionals, and healthcare providers. Very few standardized measures exist to assess an older adult’s risk for FE, and fewer still that do not require extensive training to administer. Lichtenberg et al. (in press) presented the Financial Exploitation Vulnerability Scale (FEVS), which assesses the context (i.e. financial, social, and psychological) in which an older adult is making a financial decision. This 17-item scale differentiates between older adults who’ve experienced FE and those who have not. It has excellent psychometric properties and clinical utility to detect FE beyond demographic and neuropsychological variables. We utilized exploratory factor analysis to examine the factor structure of the FEVS and reduce the number of items. Participant data (n=243) were drawn from two samples: a community-based sample and a group of individuals who were seeking financial coaching services following a financial scam or theft. Examination of the eigenvalues yielded a unidimensional scale. An iterative process was used to remove items that did not load on the single factor or with low corrected item total correlations. The final scale contained nine items and retained its ability to detect financial exploitation (AUC=0.778) and good internal consistency (a=0.845). This short form scale (FEVS-SF) is a brief, standardized screening measure to assess contextual vulnerability for FE that is accessible to professionals who work with older adults.
机译:老年人的财务剥削(FE)是一个昂贵的个人和社会问题。许多与老年人合作的专业人士需要快速且可靠的措施来检测FE,包括:APS工人,金融专业人士和医疗保健提供者。很少有标准化措施,以评估老年人的FE的风险,并且仍然不需要大量培训来管理。 Lichtenberg等。 (incress)介绍了财务开发漏洞规模(FEV),评估了一个老年人正在进行财务决定的上下文(即财务,社会和心理)。这个17项规模区分了那些经验丰富的Fe和那些没有的老年人的成年人之间的区别。它具有出色的心理测量性能和临床效用,可以检测超出人口统计和神经心理变量的Fe。我们利用探索性因子分析来检查FEV的因子结构并减少物品的数量。参与者数据(n = 243)从两个样本中绘制:基于社区的样本和一群正在寻求金融诈骗或盗窃之后的金融教练服务的个人。检查特征值产生单向规模。使用迭代过程来删除未在单个因子或低校正项总相关性上加载的项目。最终规模包含九个项目并保留其检测金融开发(AUC = 0.778)和良好内部一致性(A = 0.845)的能力。这种简短的形式刻度(FEVS-SF)是一个简短的标准化筛选措施,以评估与老年人合作的专业人士可访问的FE的上下文脆弱性。

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