Christian Mychajliw, Heiko Holz, Nathalie Minuth, Kristina Dawidowsky, Gerhard Wilhelm Eschweiler, Florian Gerhard Metzger, Franz Wortha
{"title":"健康老年参与者和认知障碍老年参与者在平板电脑上完成触摸式连续反应时间任务的表现差异:实验研究。","authors":"Christian Mychajliw, Heiko Holz, Nathalie Minuth, Kristina Dawidowsky, Gerhard Wilhelm Eschweiler, Florian Gerhard Metzger, Franz Wortha","doi":"10.2196/48265","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Digital neuropsychological tools for diagnosing neurodegenerative diseases in the older population are becoming more relevant and widely adopted because of their diagnostic capabilities. In this context, explicit memory is mainly examined. The assessment of implicit memory occurs to a lesser extent. A common measure for this assessment is the serial reaction time task (SRTT).</p><p><strong>Objective: </strong>This study aims to develop and empirically test a digital tablet-based SRTT in older participants with cognitive impairment (CoI) and healthy control (HC) participants. On the basis of the parameters of response accuracy, reaction time, and learning curve, we measure implicit learning and compare the HC and CoI groups.</p><p><strong>Methods: </strong>A total of 45 individuals (n=27, 60% HCs and n=18, 40% participants with CoI-diagnosed by an interdisciplinary team) completed a tablet-based SRTT. They were presented with 4 blocks of stimuli in sequence and a fifth block that consisted of stimuli appearing in random order. Statistical and machine learning modeling approaches were used to investigate how healthy individuals and individuals with CoI differed in their task performance and implicit learning.</p><p><strong>Results: </strong>Linear mixed-effects models showed that individuals with CoI had significantly higher error rates (b=-3.64, SE 0.86; z=-4.25; P<.001); higher reaction times (F<sub>1,41</sub>=22.32; P<.001); and lower implicit learning, measured via the response increase between sequence blocks and the random block (β=-0.34; SE 0.12; t=-2.81; P=.007). Furthermore, machine learning models based on these findings were able to reliably and accurately predict whether an individual was in the HC or CoI group, with an average prediction accuracy of 77.13% (95% CI 74.67%-81.33%).</p><p><strong>Conclusions: </strong>Our results showed that the HC and CoI groups differed substantially in their performance in the SRTT. This highlights the promising potential of implicit learning paradigms in the detection of CoI. The short testing paradigm based on these results is easy to use in clinical practice.</p>","PeriodicalId":36245,"journal":{"name":"JMIR Aging","volume":"7 ","pages":"e48265"},"PeriodicalIF":5.0000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10995790/pdf/","citationCount":"0","resultStr":"{\"title\":\"Performance Differences of a Touch-Based Serial Reaction Time Task in Healthy Older Participants and Older Participants With Cognitive Impairment on a Tablet: Experimental Study.\",\"authors\":\"Christian Mychajliw, Heiko Holz, Nathalie Minuth, Kristina Dawidowsky, Gerhard Wilhelm Eschweiler, Florian Gerhard Metzger, Franz Wortha\",\"doi\":\"10.2196/48265\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Digital neuropsychological tools for diagnosing neurodegenerative diseases in the older population are becoming more relevant and widely adopted because of their diagnostic capabilities. In this context, explicit memory is mainly examined. The assessment of implicit memory occurs to a lesser extent. A common measure for this assessment is the serial reaction time task (SRTT).</p><p><strong>Objective: </strong>This study aims to develop and empirically test a digital tablet-based SRTT in older participants with cognitive impairment (CoI) and healthy control (HC) participants. On the basis of the parameters of response accuracy, reaction time, and learning curve, we measure implicit learning and compare the HC and CoI groups.</p><p><strong>Methods: </strong>A total of 45 individuals (n=27, 60% HCs and n=18, 40% participants with CoI-diagnosed by an interdisciplinary team) completed a tablet-based SRTT. They were presented with 4 blocks of stimuli in sequence and a fifth block that consisted of stimuli appearing in random order. Statistical and machine learning modeling approaches were used to investigate how healthy individuals and individuals with CoI differed in their task performance and implicit learning.</p><p><strong>Results: </strong>Linear mixed-effects models showed that individuals with CoI had significantly higher error rates (b=-3.64, SE 0.86; z=-4.25; P<.001); higher reaction times (F<sub>1,41</sub>=22.32; P<.001); and lower implicit learning, measured via the response increase between sequence blocks and the random block (β=-0.34; SE 0.12; t=-2.81; P=.007). Furthermore, machine learning models based on these findings were able to reliably and accurately predict whether an individual was in the HC or CoI group, with an average prediction accuracy of 77.13% (95% CI 74.67%-81.33%).</p><p><strong>Conclusions: </strong>Our results showed that the HC and CoI groups differed substantially in their performance in the SRTT. This highlights the promising potential of implicit learning paradigms in the detection of CoI. The short testing paradigm based on these results is easy to use in clinical practice.</p>\",\"PeriodicalId\":36245,\"journal\":{\"name\":\"JMIR Aging\",\"volume\":\"7 \",\"pages\":\"e48265\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10995790/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2196/48265\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/48265","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:用于诊断老年人群神经退行性疾病的数字神经心理学工具因其诊断功能而变得越来越重要,并被广泛采用。在这种情况下,主要检查的是显性记忆。对内隐记忆的评估则较少。评估内隐记忆的常用方法是连续反应时间任务(SRTT):本研究旨在开发一种基于数字平板电脑的 SRTT,并对患有认知障碍(CoI)的老年参与者和健康对照(HC)参与者进行实证测试。在反应准确性、反应时间和学习曲线等参数的基础上,我们测量了内隐学习,并对 HC 组和 CoI 组进行了比较:共有 45 人完成了基于平板电脑的 SRTT。他们依次接受了 4 个区块的刺激,第五个区块由随机顺序出现的刺激组成。研究人员采用统计和机器学习建模方法,调查了健康人和共济失调患者在任务表现和内隐学习方面的差异:线性混合效应模型显示,CoI患者的错误率明显更高(b=-3.64,SE 0.86;z=-4.25;P1,41=22.32;PC结论:我们的研究结果表明,HC 组和 CoI 组在 SRTT 中的表现有很大差异。这凸显了内隐学习范式在检测 CoI 方面的巨大潜力。基于这些结果的简短测试范式易于在临床实践中使用。
Performance Differences of a Touch-Based Serial Reaction Time Task in Healthy Older Participants and Older Participants With Cognitive Impairment on a Tablet: Experimental Study.
Background: Digital neuropsychological tools for diagnosing neurodegenerative diseases in the older population are becoming more relevant and widely adopted because of their diagnostic capabilities. In this context, explicit memory is mainly examined. The assessment of implicit memory occurs to a lesser extent. A common measure for this assessment is the serial reaction time task (SRTT).
Objective: This study aims to develop and empirically test a digital tablet-based SRTT in older participants with cognitive impairment (CoI) and healthy control (HC) participants. On the basis of the parameters of response accuracy, reaction time, and learning curve, we measure implicit learning and compare the HC and CoI groups.
Methods: A total of 45 individuals (n=27, 60% HCs and n=18, 40% participants with CoI-diagnosed by an interdisciplinary team) completed a tablet-based SRTT. They were presented with 4 blocks of stimuli in sequence and a fifth block that consisted of stimuli appearing in random order. Statistical and machine learning modeling approaches were used to investigate how healthy individuals and individuals with CoI differed in their task performance and implicit learning.
Results: Linear mixed-effects models showed that individuals with CoI had significantly higher error rates (b=-3.64, SE 0.86; z=-4.25; P<.001); higher reaction times (F1,41=22.32; P<.001); and lower implicit learning, measured via the response increase between sequence blocks and the random block (β=-0.34; SE 0.12; t=-2.81; P=.007). Furthermore, machine learning models based on these findings were able to reliably and accurately predict whether an individual was in the HC or CoI group, with an average prediction accuracy of 77.13% (95% CI 74.67%-81.33%).
Conclusions: Our results showed that the HC and CoI groups differed substantially in their performance in the SRTT. This highlights the promising potential of implicit learning paradigms in the detection of CoI. The short testing paradigm based on these results is easy to use in clinical practice.