Calvin Howard, Amy Johnson, Joseph Peedicail, Marcus C Ng
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Here, we evaluate the Rapid Online Cognitive Assessment (RoCA), a remote and self-administered digital cognitive screening examination.</p><p><strong>Objective: </strong>The objective of this study was to validate the ability of RoCA to reliably evaluate patient input, identify patients with cognitive impairment relative to the established tests, and evaluate its potential as a screening tool.</p><p><strong>Methods: </strong>RoCA uses a convolutional neural network to evaluate a patient's ability to perform common cognitive screening tasks: wireframe diagram copying and clock drawing tests. To evaluate RoCA, we compared its evaluations with those of established paper-based tests. This open-label study consists of 46 patients (age range 33-82 years) who were enrolled from neurology clinics. Patients completed the RoCA screening examination and either Addenbrooke's Cognitive Examination-3 (ACE-3, n=35) or Montreal Cognitive Assessment (MoCA, n=11). We evaluated 3 primary metrics of RoCA's performance: (1) ability to correctly evaluate patient inputs, (2) ability to identify patients with cognitive impairment compared to ACE-3 and MoCA, and (3) performance as a screening tool.</p><p><strong>Results: </strong>RoCA classifies patients similarly to gold standard paper-based tests, with a receiver operating characteristic area under the curve of 0.81 (95% CI 0.67-0.91; P<.001). RoCA achieved sensitivity of 0.94 (95% CI 0.80-1.0; P<.001). This was robust to multiple control analyses. Approximately 83% (16/19) of the patient respondents reported RoCA as highly intuitive, with 95% (18/19) perceiving it as adding value to their care.</p><p><strong>Conclusions: </strong>RoCA may act as a simple and highly scalable digital cognitive screening examination. 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引用次数: 0
摘要
背景:痴呆症患病率的上升需要一种可扩展的认知筛查解决方案。基于纸张的认知筛查检查得到了很好的验证,但可扩展性很低。如果数字认知筛查检查可以复制纸质筛查,它可能会提高可扩展性,同时潜在地保持这些经过良好验证的纸质测试的性能。在这里,我们评估快速在线认知评估(RoCA),一种远程和自我管理的数字认知筛查检查。目的:本研究的目的是验证RoCA可靠评估患者输入的能力,识别相对于既定测试的认知障碍患者,并评估其作为筛查工具的潜力。方法:RoCA使用卷积神经网络来评估患者执行常见认知筛查任务的能力:线框图复制和时钟绘制测试。为了评估RoCA,我们将其评估与现有的纸质测试进行了比较。这项开放标签研究包括来自神经病学诊所的46名患者(年龄范围33-82岁)。患者完成RoCA筛查检查和阿登布鲁克认知检查-3 (ACE-3, n=35)或蒙特利尔认知评估(MoCA, n=11)。我们评估了RoCA表现的3个主要指标:(1)正确评估患者输入的能力,(2)与ACE-3和MoCA相比识别认知障碍患者的能力,以及(3)作为筛查工具的表现。结果:RoCA对患者的分类与金标准纸质试验相似,曲线下的受试者工作特征面积为0.81 (95% CI 0.67-0.91;结论:RoCA可作为一种简单且高度可扩展的数字认知筛查检查。然而,由于本研究的局限性,需要进一步的工作来评估RoCA在患者群体中的推广能力,以完全远程的方式评估其表现,并分析数字素养的影响。
The Rapid Online Cognitive Assessment for the Detection of Neurocognitive Disorder: Open-Label Study.
Background: The rising prevalence of dementia necessitates a scalable solution to cognitive screening. Paper-based cognitive screening examinations are well-validated but minimally scalable. If a digital cognitive screening examination could replicate paper-based screening, it may improve scalability while potentially maintaining the performance of these well-validated paper-based tests. Here, we evaluate the Rapid Online Cognitive Assessment (RoCA), a remote and self-administered digital cognitive screening examination.
Objective: The objective of this study was to validate the ability of RoCA to reliably evaluate patient input, identify patients with cognitive impairment relative to the established tests, and evaluate its potential as a screening tool.
Methods: RoCA uses a convolutional neural network to evaluate a patient's ability to perform common cognitive screening tasks: wireframe diagram copying and clock drawing tests. To evaluate RoCA, we compared its evaluations with those of established paper-based tests. This open-label study consists of 46 patients (age range 33-82 years) who were enrolled from neurology clinics. Patients completed the RoCA screening examination and either Addenbrooke's Cognitive Examination-3 (ACE-3, n=35) or Montreal Cognitive Assessment (MoCA, n=11). We evaluated 3 primary metrics of RoCA's performance: (1) ability to correctly evaluate patient inputs, (2) ability to identify patients with cognitive impairment compared to ACE-3 and MoCA, and (3) performance as a screening tool.
Results: RoCA classifies patients similarly to gold standard paper-based tests, with a receiver operating characteristic area under the curve of 0.81 (95% CI 0.67-0.91; P<.001). RoCA achieved sensitivity of 0.94 (95% CI 0.80-1.0; P<.001). This was robust to multiple control analyses. Approximately 83% (16/19) of the patient respondents reported RoCA as highly intuitive, with 95% (18/19) perceiving it as adding value to their care.
Conclusions: RoCA may act as a simple and highly scalable digital cognitive screening examination. However, due to the limitations of this study, further work is required to evaluate the ability of RoCA to be generalizable across patient populations, assess its performance in an entirely remote manner, and analyze the effect of digital literacy.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.