View in EDS HTML Full Text PDF Full Text

The language of paranoia: linguistic analysis of SMI speech with considerations of race and sex.

Saved in:
Bibliographic Details
Title: The language of paranoia: linguistic analysis of SMI speech with considerations of race and sex.
Authors: Warren, Kiara K. (AUTHOR), Cox, Christopher R. (AUTHOR), Cohen, Alex S. (AUTHOR)
Source: Journal of Mental Health. Dec2025, Vol. 34 Issue 6, p662-669. 8p.
Subjects: Speech evaluation, Language & languages, Paranoia, Research funding, T-test (Statistics), Mental illness, Sex distribution, Interviewing, Descriptive statistics, Chi-squared test, Linguistics, Race, Research methodology, Data analysis software, Psychosocial factors
Abstract: Background: Linguistic analysis, notably using conceptually derived linguistic categories, has been used to quantify various aspects of serious mental illness. It has the potential for understanding paranoia, defined in terms of perceived and intentional threats from others. However, paranoia and the language expressing it potentially varies due to demographic factors, notably race and sex. Aims: This study aims to expand upon prior findings linking linguistic expression and serious mental illness symptoms by focusing on paranoia and evaluating potential moderating roles of race and sex in two archived studies using two separate speaking tasks. Methods: We hypothesized that a limited feature set of linguistic categories derived from these speaking tasks would accurately classify clinical ratings of paranoia using regularized regression. It was further hypothesized that these relationships would vary as a function of Black versus White and male versus female identities. Results: Unexpectedly, there were no differences in model accuracy as a function of race and sex, suggesting no overt bias or differential functioning from demographics in our models. Conclusions: Results highlight the strengths and limitations of using linguistic analysis to understand paranoia. Exploring variation amongst paranoia scoring could improve model accuracy across different demographic groups. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Mental Health is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 190283421
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The language of paranoia: linguistic analysis of SMI speech with considerations of race and sex.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Warren%2C+Kiara+K%2E%22">Warren, Kiara K.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cox%2C+Christopher+R%2E%22">Cox, Christopher R.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cohen%2C+Alex+S%2E%22">Cohen, Alex S.</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Mental+Health%22">Journal of Mental Health</searchLink>. Dec2025, Vol. 34 Issue 6, p662-669. 8p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Speech+evaluation%22">Speech evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Language+%26+languages%22">Language & languages</searchLink><br /><searchLink fieldCode="DE" term="%22Paranoia%22">Paranoia</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22T-test+%28Statistics%29%22">T-test (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+illness%22">Mental illness</searchLink><br /><searchLink fieldCode="DE" term="%22Sex+distribution%22">Sex distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Interviewing%22">Interviewing</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Linguistics%22">Linguistics</searchLink><br /><searchLink fieldCode="DE" term="%22Race%22">Race</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Psychosocial+factors%22">Psychosocial factors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Linguistic analysis, notably using conceptually derived linguistic categories, has been used to quantify various aspects of serious mental illness. It has the potential for understanding paranoia, defined in terms of perceived and intentional threats from others. However, paranoia and the language expressing it potentially varies due to demographic factors, notably race and sex. Aims: This study aims to expand upon prior findings linking linguistic expression and serious mental illness symptoms by focusing on paranoia and evaluating potential moderating roles of race and sex in two archived studies using two separate speaking tasks. Methods: We hypothesized that a limited feature set of linguistic categories derived from these speaking tasks would accurately classify clinical ratings of paranoia using regularized regression. It was further hypothesized that these relationships would vary as a function of Black versus White and male versus female identities. Results: Unexpectedly, there were no differences in model accuracy as a function of race and sex, suggesting no overt bias or differential functioning from demographics in our models. Conclusions: Results highlight the strengths and limitations of using linguistic analysis to understand paranoia. Exploring variation amongst paranoia scoring could improve model accuracy across different demographic groups. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Mental Health is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=190283421
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/09638237.2025.2512313
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 8
        StartPage: 662
    Subjects:
      – SubjectFull: Speech evaluation
        Type: general
      – SubjectFull: Language & languages
        Type: general
      – SubjectFull: Paranoia
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: T-test (Statistics)
        Type: general
      – SubjectFull: Mental illness
        Type: general
      – SubjectFull: Sex distribution
        Type: general
      – SubjectFull: Interviewing
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Chi-squared test
        Type: general
      – SubjectFull: Linguistics
        Type: general
      – SubjectFull: Race
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Psychosocial factors
        Type: general
    Titles:
      – TitleFull: The language of paranoia: linguistic analysis of SMI speech with considerations of race and sex.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Warren, Kiara K.
      – PersonEntity:
          Name:
            NameFull: Cox, Christopher R.
      – PersonEntity:
          Name:
            NameFull: Cohen, Alex S.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 09638237
          Numbering:
            – Type: volume
              Value: 34
            – Type: issue
              Value: 6
          Titles:
            – TitleFull: Journal of Mental Health
              Type: main
ResultId 1