↓ Skip to main content

Language Patterns Discriminate Mild Depression From Normal Sadness and Euthymic State

Overview of attention for article published in Frontiers in Psychiatry, April 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
6 news outlets
twitter
4 X users

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
95 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Language Patterns Discriminate Mild Depression From Normal Sadness and Euthymic State
Published in
Frontiers in Psychiatry, April 2018
DOI 10.3389/fpsyt.2018.00105
Pubmed ID
Authors

Daria Smirnova, Paul Cumming, Elena Sloeva, Natalia Kuvshinova, Dmitry Romanov, Gennadii Nosachev

Abstract

Deviations from typical word use have been previously reported in clinical depression, but language patterns of mild depression (MD), as distinct from normal sadness (NS) and euthymic state, are unknown. In this study, we aimed to apply the linguistic approach as an additional diagnostic key for understanding clinical variability along the continuum of affective states. We studied 402 written reports from 124 Russian-speaking patients and 77 healthy controls (HC), including 35 cases of NS, using hand-coding procedures. The focus of our psycholinguistic methods was on lexico-semantic [e.g., rhetorical figures (metaphors, similes)], syntactic [e.g., predominant sentence type (single-clause and multi-clause)], and lexico-grammatical [e.g., pronouns (indefinite, personal)] variables. Statistical evaluations included Cohen's kappa for inter-rater reliability measures, a non-parametric approach (Mann-Whitney U-test and Pearson chi-square test), one-way ANOVA for between-group differences, Spearman's and point-biserial correlations to analyze relationships between linguistic and gender variables, discriminant analysis (Wilks' λ) of linguistic variables in relation to the affective diagnostic types, all using SPSS-22 (significant, p < 0.05). In MD, as compared with healthy individuals, written responses were longer, demonstrated descriptive rather than analytic style, showed signs of spoken and figurative language, single-clause sentences domination over multi-clause, atypical word order, increased use of personal and indefinite pronouns, and verb use in continuous/imperfective and past tenses. In NS, as compared with HC, we found greater use of lexical repetitions, omission of words, and verbs in continuous and present tenses. MD was significantly differentiated from NS and euthymic state by linguistic variables [98.6%; Wilks' λ(40) = 0.009; p < 0.001; r = 0.992]. The highest predictors in discrimination between MD, NS, and euthymic state groups were the variables of word order (typical/atypical) (r = -0.405), ellipses (omission of words) (r = 0.583), colloquialisms (informal words/phrases) (r = 0.534), verb tense (past/present/future) (r = -0.460), verbs form (continuous/perfect) (r = 0.345), amount of reflexive (e.g., myself)/personal (r = 0.344), and negative (e.g., nobody)/indefinite (r = 0.451) pronouns. The most significant between-group differences were observed in MD as compared with both NS and euthymic state. MD is characterized by patterns of atypical language use distinguishing depression from NS and euthymic state, which points to a potential role of linguistic indicators in diagnosing affective states.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 16%
Student > Ph. D. Student 13 14%
Student > Master 10 11%
Researcher 9 9%
Student > Doctoral Student 6 6%
Other 16 17%
Unknown 26 27%
Readers by discipline Count As %
Psychology 20 21%
Medicine and Dentistry 11 12%
Computer Science 6 6%
Arts and Humanities 4 4%
Linguistics 4 4%
Other 19 20%
Unknown 31 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 June 2020.
All research outputs
#690,626
of 23,041,514 outputs
Outputs from Frontiers in Psychiatry
#350
of 10,167 outputs
Outputs of similar age
#17,432
of 329,244 outputs
Outputs of similar age from Frontiers in Psychiatry
#18
of 160 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,167 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,244 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 160 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.