Hill Edward, Alty Jane, Bartlett Larissa, Goldberg Lyn, Park Mira, Yeom Soonja, Vickers James
Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia.
Information and Communication Technology, University of Tasmania, Hobart, Tasmania, Australia.
Cortex. 2021 Dec;145:264-272. doi: 10.1016/j.cortex.2021.09.018. Epub 2021 Oct 23.
Previous research suggests oral and written language can act as barometers of an individual's cognitive function, potentially providing a screening tool for the earliest stages of Alzheimer's disease (AD) and other forms of dementia. Idea density is a measure of the rate at which ideas, or elementary predications, are expressed and may provide an ideal measure for early detection of deficits in language. Previous research has shown that when no restrictions are set on the topic of the idea, a decrease in propositional idea density (PID) is associated with an increased risk of developing AD. However, this has been limited by moderate sample sizes and manual transcribing. Technological advancement has enabled the automated calculation of PID from tools such as the Computerized Propositional Idea Density Rater (CPIDR). We delivered an online autobiographical writing task to older adult Australians from ISLAND (Island Study Linking Ageing and Neurodegenerative Disease). Linear regression models were fitted in R. We analysed text files (range 10-1180 words) using CPIDRv5 provided by 3316 (n = 853 males [25.7%], n = 2463 females [74.3%]) ISLAND participants. Over 358,957 words written in 3316 written autobiographical responses were analysed. Mean PID was higher in females (53.5 [±3.69]) than males (52.6 [±4.50]). Both advancing age and being male were significantly associated with a decrease in PID (p < .001). Automated methods of language analysis hold great promise for the early detection of subtle deficits in language capacity. Although our effect sizes were small, PID may be a sensitive measure of deficits in language in ageing individuals and is able to be collected at scale using online methods of data capture.
先前的研究表明,口头和书面语言可作为个体认知功能的晴雨表,有可能为阿尔茨海默病(AD)及其他形式痴呆症的早期阶段提供一种筛查工具。观点密度是对观点或基本断言的表达速率的一种衡量,可能为语言缺陷的早期检测提供理想指标。先前的研究表明,当对观点主题不设限制时,命题观点密度(PID)的降低与患AD风险的增加相关。然而,这受到样本量适中及人工转录的限制。技术进步已使通过诸如计算机化命题观点密度评分器(CPIDR)等工具自动计算PID成为可能。我们向来自ISLAND(衰老与神经退行性疾病关联岛研究)的澳大利亚老年成年人提供了一项在线自传写作任务。在R语言中拟合线性回归模型。我们使用由3316名(n = 853名男性[25.7%],n = 2463名女性[74.3%])ISLAND参与者提供的CPIDRv5分析了文本文件(字数范围为10 - 1180个单词)。对3316份书面自传回复中超过358,957个单词进行了分析。女性的平均PID(53.5[±3.69])高于男性(52.6[±4.50])。年龄增长和男性身份均与PID降低显著相关(p <.001)。语言分析的自动化方法在早期检测语言能力的细微缺陷方面具有巨大潜力。尽管我们的效应量较小,但PID可能是衰老个体语言缺陷的敏感指标,并且能够通过在线数据采集方法大规模收集。