背景:故事回忆是一种简单而敏感的认知测试,通常用于测量早期阿尔茨海默病(AD)中情景记忆功能的变化。数字技术和自然语言处理方法的最新进展使该测试成为自动管理和评分的候选。更高频率的疾病监测需要多个并行测试刺激。
目的:本研究旨在开发和验证远程和全自动故事回忆任务,适合纵向评估,在有或没有轻度认知障碍(MCI)或轻度AD的老年人群体中。
方法:“早期阿尔茨海默病的淀粉样蛋白预测”(AMYPRED)研究招募了英国(AMYPRED-UK:NCT04828122)和美国(AMYPRED-US:NCT04928976)的参与者。参与者被要求在7到8天内在他们的智能设备上远程完成可选的每日自我管理评估。评估包括立即和延迟召回自动故事召回任务(ASRT)中的3个故事,具有多个平行刺激(18个短篇故事和18个长篇故事)的测试,平衡了关键的语言和话语指标。口头回答被记录并从参与者的个人设备安全地传输,并使用源文本和复述之间的文本相似性度量自动转录和评分,以得出广义匹配分数。使用逻辑和线性混合模型检查了依从性和任务绩效的组差异,分别。相关分析检查了ASRT的并行形式可靠性和认知测试的收敛有效性(逻辑记忆测试和具有语义处理的临床前阿尔茨海默认知组合)。使用远程管理的问卷获得可接受性和可用性数据。
结果:在AMYPRED研究中招募的200名参与者中,151(75.5%)-78认知未受损(CU)和73MCI或轻度AD-从事可选的远程评估。对每日评估的坚持是中等的,并没有随着时间的推移而下降,但在CU参与者中更高(每天73/106,68.9%的MCI或轻度AD参与者和78/94,83%的CU参与者完成ASRT)。参与者报告了有利的任务可用性:不常见的技术问题,易于使用的应用程序,以及对任务的广泛兴趣。任务绩效在一周内略有改善,并且更适合立即召回。MCI或轻度AD参与者的广义匹配得分较低(Cohend=1.54)。对于立即召回(平均rho0.73,范围0.56-0.88)和延迟召回(平均rho=0.73,范围=0.54-0.86),ASRT故事的并行形式可靠性中等到强。在已建立的认知测试中,ASRT表现出中等的收敛效度。
结论:无监督,自我管理的ASRT任务对MCI和轻度AD的认知障碍敏感。该任务显示出良好的可用性,高并行形式可靠性,和具有既定认知测验的高收敛效度。远程,低成本,低负担,自动评分语音评估可以支持诊断筛查,卫生保健,和治疗监测。
BACKGROUND: Story recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring.
OBJECTIVE: This study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD.
METHODS: The \"Amyloid Prediction in Early Stage Alzheimer\'s disease\" (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants\' personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent
validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer\'s Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire.
RESULTS: Of the 200 participants recruited in the AMYPRED studies, 151 (75.5%)-78 cognitively unimpaired (CU) and 73 MCI or mild AD-engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent
validity with established cognitive tests.
CONCLUSIONS: The unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent
validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring.