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A new study led by linguists from the Department of English, Linguistics, and Theatre Studies (ELTS) at the NUS Faculty of Arts and Social Sciences (FASS) has unveiled early signs of dementia through the analysis of natural speech patterns among senior Singaporeans.

The study, conducted in collaboration with researchers from the NUS Yong Loo Lin School of Medicine (NUS Medicine), compared the spontaneous speech of cognitively healthy individuals with those exhibiting mild cognitive impairment (MCI) to identify linguistic markers of dementia. Notably, individuals with memory-related MCI demonstrated reduced speech output and produced fewer, yet more abstract nouns-a pattern consistent with patients diagnosed with Alzheimer's disease.

Professor Bao Zhiming, Principal Investigator of the study, highlighted Singapore's linguistic diversity as a unique environment for such research endeavors.

"Previous studies had analysed targeted and smaller volumes of language data through word-based fluency tests, structured interviews and picture narrations. Our study has never been done before as it focused on unstructured and spontaneous speech that is easy to collect and analys," Zhiming said, as per Science Daily.

Emeritus Professor Kua Ee Heok, psychiatrist at NUS Medicine, emphasized the urgency of innovative strategies to address Singapore's aging population and rising dementia rates. The study, part of the broader Community Health Intergenerational (CHI) Study, aimed to identify at-risk seniors and implement interventions for healthy aging.

Published in the journal Alzheimer's & Dementia: Diagnosis, Assessment, and Disease Monitoring, the study analyzed natural speech data from 148 elderly Singaporeans, half of whom were cognitively healthy and the other half diagnosed with MCI.

Participants engaged in a 20-minute English speech task covering various topics, with recordings yielding over 267,310 words transcribed and analyzed for noun and verb usage. Notably, individuals with amnestic MCI exhibited reduced speech output and abstract noun production compared to those with non-amnestic MCI and healthy controls, highlighting the potential of linguistic analysis in early dementia detection.

Dr. Luwen Cao, from the NUS Department of ELTS, emphasized the study's significance in providing a non-invasive and cost-effective tool for early dementia detection, complementing traditional diagnostic methods.

"Our findings are a significant breakthrough as traditional diagnoses of dementia are done following a battery of neuropsychological and neurological tests. The study of natural speech to detect linguistic signs of early cognitive decline is a reliable, non-invasive and cost-effective tool that could possibly help medical practitioners in the early diagnosis, intervention and management of the progressive disease," Cao said.

Moving forward, the research team aims to collaborate with neurologists to develop language-based intervention strategies for individuals with amnestic MCI, ultimately contributing to healthier aging in Singapore and enhancing the quality of life for older adults.