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. 2018 Apr 10;9:105.
doi: 10.3389/fpsyt.2018.00105. eCollection 2018.

Language Patterns Discriminate Mild Depression From Normal Sadness and Euthymic State

Free PMC article

Language Patterns Discriminate Mild Depression From Normal Sadness and Euthymic State

Daria Smirnova et al. Front Psychiatry. .
Free PMC article


Objectives: 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.

Methods: 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).

Results: 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.

Conclusion: 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.

Keywords: euthymic state; language patterns; mild depression; negative pronouns; normal sadness; past tense verbs; personal pronouns; word use.


Figure 1
Figure 1
Discriminant model of the diagnostic types of mild depression, normal sadness, and euthymic state in healthy participants, based on linguistic variables (excluding sentence-type analysis).

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