Causes and consequences of suboptimal cognitive effort in the MACS

项目摘要 根据来自大型联盟研究的估计，艾滋病毒相关的神经认知障碍（HAND） 在任何时候都影响22-84%的感染者。绝大多数HAND诊断是轻度的， 在最近的研究诊断标准中被称为无症状神经认知障碍（ANI）。 根据CHARTER研究的数据，多达70%的HAND患者患有ANI。然而 一些人认为ANI被过度诊断，引用的事实是，当诊断标准被应用于其他疾病时， 健康的未感染个体，假阳性诊断率非常高。另一个可能的原因是 高估ANI的患病率是次优的努力。也就是说，参加研究的个人， 得出的患病率可能不会对神经认知测试做出足够的努力，从而夸大了 估计轻度HAND患病率。来自多中心艾滋病队列研究（MACS）的初步数据， 最大的艾滋病毒研究，包括神经认知措施，表明超过50%的MACS参与者， 最近完成的综合神经认知测试报告了次优努力。最常见的原因 疲劳/疲倦，注意力不集中/分心，以及“其他”。此外，还有一个序数 努力水平和HAND严重程度之间的关系，表明那些努力最少的人有最高的 ANI诊断率。初步数据还允许识别次优努力的预测因素， 包括低教育和失业。这些初步发现对未来极为重要 手的研究。他们认为，不仅是由于研究工作不力， 参与者，但也有具体的原因，和预测，次优的努力，可以是 已解决。在拟议的研究中，我们将进一步探讨在MACS次优努力。结果可能导致 调整HAND患病率估计值，并建立优化研究工作的方法。

Project Summary Based on estimates derived from large consortium studies, HIV-associated neurocognitive disorders (HAND) affects between 22-84% of infected individuals at any one time. The vast majority of HAND diagnoses are mild, and are termed Asymptomatic Neurocognitive Impairment (ANI) in the most recent research diagnostic criteria. As many as 70% of those diagnosed with HAND have ANI, according to data from the CHARTER study. Yet some argue that ANI is over diagnosed, citing the fact that when the diagnostic criteria are applied to otherwise healthy, uninfected individuals, there is a very high rate of false-positive diagnoses. Another likely reason for the overestimated prevalence of ANI is suboptimal effort. That is, individuals enrolled in research studies from which prevalence rates are derived may not put forth sufficient effort on neurocognitive testing, thereby inflating estimates of mild HAND prevalence. Preliminary data from the Multicenter AIDS Cohort Study (MACS), the largest HIV study incorporating neurocognitive measures, indicates that over 50% of MACS participants who recently completed comprehensive neurocognitive testing reported suboptimal effort. The most common reasons being fatigued/tired, having poor concentration/distraction, and “other”. Furthermore, there was an ordinal relationship between effort level and HAND severity, indicating that those with the poorest effort have the highest rates of ANI diagnosis. The preliminary data also allowed for identification of predictors of suboptimal effort, including low education and unemployment. These preliminary findings are extremely important for the future study of HAND. They suggest not only that rates of HAND are inflated due to poor effort among research participants, but also that there are specific causes for, and predictors of, suboptimal effort that can be addressed. In the proposed study, we will further explore suboptimal effort in the MACS. The results may lead to adjustments in HAND prevalence estimates and establishing methods for optimizing effort in research studies.