Detecting dementia using linguistic analysis: Terry Pratchett's Discworld tells a more personal story

Dementia, characterised by cognitive decline, significantly impacts language abilities. While the risk of dementia increases with age, it often manifests years before clinical diagnosis. Identifying early warning signs is crucial for timely intervention. Previous research has demonstrated that changes in language, such as reduced vocabulary diversity and simpler sentence structures, may be observed in individuals with dementia. This study investigates the potential of linguistic analysis to detect early signs of cognitive decline by examining the writing of Sir Terry Pratchett, a renowned author diagnosed with Posterior Cortical Atrophy (PCA), a form of dementia caused by Alzheimer’s disease. This study analysed 33 Discworld novels by Terry Pratchett, comparing linguistic features (e.g., vocabulary size, lexical diversity, word class distribution) before and after a potential turning point identified through analysis of adjective type-token ratios (TTR). A significant decrease in lexical diversity (TTR) was observed for nouns and adjectives in later works. Total word count increased, while lexical diversity decreased, suggesting a shift towards simpler language. This shift coincided with a decrease in adjective TTR below a defined threshold, occurring approximately ten years before Pratchett's formal diagnosis. These findings suggest that subtle changes in linguistic patterns, such as decreased lexical diversity, may precede clinical diagnosis of dementia by a considerable margin. This research highlights the potential of linguistic analysis as a valuable tool for early detection of cognitive decline. Further research is needed to validate these findings in larger cohorts and explore the specific linguistic markers associated with different types of dementia.