Academic Journal

Detecting dementia using lexical analysis: Terry Pratchett's discworld tells a more personal story

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Detecting dementia using lexical analysis: Terry Pratchett's discworld tells a more personal story
Συγγραφείς: Pattison, Melody, Begde, Ahmet, Wilcockson, Thomas D. W.
Στοιχεία εκδότη: MDPI
Έτος έκδοσης: 2026
Συλλογή: Cardiff University: ORCA (Online Research @ Cardiff)
Περιγραφή: Background/Objectives: 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), typically a form of dementia caused by Alzheimer’s disease. Methods: This study analysed 33 Discworld novels by Terry Pratchett, comparing linguistic features before and after a potential turning point identified through analysis of adjective type-token ratios (TTR). Results: A significant decrease in lexical diversity (TTR) was observed for nouns and adjectives in later works. Total wordcount 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. Conclusions: 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.
Τύπος εγγράφου: article in journal/newspaper
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
Relation: https://orca.cardiff.ac.uk/id/eprint/183960/1/brainsci-16-00094.pdf; Pattison, Melody https://orca.cardiff.ac.uk/view/cardiffauthors/A23826167.html orcid:0009-0009-8499-0497 orcid:0009-0009-8499-0497, Begde, Ahmet and Wilcockson, Thomas D. W. 2026. Detecting dementia using lexical analysis: Terry Pratchett's discworld tells a more personal story. Brain Sciences 16 (1) , 94. 10.3390/brainsci16010094 https://doi.org/10.3390/brainsci16010094 file https://orca.cardiff.ac.uk/id/eprint/183960/1/brainsci-16-00094.pdf
DOI: 10.3390/brainsci16010094
Διαθεσιμότητα: https://orca.cardiff.ac.uk/id/eprint/183960/
https://doi.org/10.3390/brainsci16010094
Rights: cc_by_4_0
Αριθμός Καταχώρησης: edsbas.CF22B60C
Βάση Δεδομένων: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://orca.cardiff.ac.uk/id/eprint/183960/#
    Name: EDS - BASE (ns324271)
    Category: fullText
    Text: View record from BASE
Header DbId: edsbas
DbLabel: BASE
An: edsbas.CF22B60C
RelevancyScore: 1011
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1010.63568115234
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Detecting dementia using lexical analysis: Terry Pratchett's discworld tells a more personal story
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Pattison%2C+Melody%22">Pattison, Melody</searchLink><br /><searchLink fieldCode="AR" term="%22Begde%2C+Ahmet%22">Begde, Ahmet</searchLink><br /><searchLink fieldCode="AR" term="%22Wilcockson%2C+Thomas+D%2E+W%2E%22">Wilcockson, Thomas D. W.</searchLink>
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: MDPI
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2026
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Cardiff University: ORCA (Online Research @ Cardiff)
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Background/Objectives: 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), typically a form of dementia caused by Alzheimer’s disease. Methods: This study analysed 33 Discworld novels by Terry Pratchett, comparing linguistic features before and after a potential turning point identified through analysis of adjective type-token ratios (TTR). Results: A significant decrease in lexical diversity (TTR) was observed for nouns and adjectives in later works. Total wordcount 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. Conclusions: 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.
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: article in journal/newspaper
– Name: Format
  Label: File Description
  Group: SrcInfo
  Data: application/pdf
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: https://orca.cardiff.ac.uk/id/eprint/183960/1/brainsci-16-00094.pdf; Pattison, Melody https://orca.cardiff.ac.uk/view/cardiffauthors/A23826167.html orcid:0009-0009-8499-0497 orcid:0009-0009-8499-0497, Begde, Ahmet and Wilcockson, Thomas D. W. 2026. Detecting dementia using lexical analysis: Terry Pratchett's discworld tells a more personal story. Brain Sciences 16 (1) , 94. 10.3390/brainsci16010094 https://doi.org/10.3390/brainsci16010094 file https://orca.cardiff.ac.uk/id/eprint/183960/1/brainsci-16-00094.pdf
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.3390/brainsci16010094
– Name: URL
  Label: Availability
  Group: URL
  Data: https://orca.cardiff.ac.uk/id/eprint/183960/<br />https://doi.org/10.3390/brainsci16010094
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: cc_by_4_0
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.CF22B60C
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.CF22B60C
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/brainsci16010094
    Languages:
      – Text: English
    Titles:
      – TitleFull: Detecting dementia using lexical analysis: Terry Pratchett's discworld tells a more personal story
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Pattison, Melody
      – PersonEntity:
          Name:
            NameFull: Begde, Ahmet
      – PersonEntity:
          Name:
            NameFull: Wilcockson, Thomas D. W.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
ResultId 1