Language Patterns Discriminate Mild Depression From Normal Sadness and Euthymic State
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Résumé
Objectives. Deviations from typical word use have been previously reported in clinical depression, but language patterns of mild depression, as distinct from normal sadness 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, including 35 cases of normal sadness, 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, multi-clause)), and lexico-grammatical (e.g. pronouns (indefinite, personal)) variables. Statistical evaluations included Cohen’s Kappa for inter-rater reliability measures, a nonparametric approach (Mann-Whitney U-test, 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 (λ–Wilks) of linguistic variables in relation to the affective diagnostic types, all using SPSS-22 (significant, p<0.05). Results. In mild depression, as compared to 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 normal sadness, as compared to healthy controls, we found greater use of lexical repetitions, omission of words, verbs in continuous and present tenses. Mild depression was significantly differentiated from normal sadness and euthymic state by linguistic variables (98.6%; λ–Wilks(40)=0.009; p<0.001; r=0.992). The highest predictors in discrimination between mild depression, normal sadness 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 mild depression as compared to both normal sadness and euthymic state. Conclusion. Mild depression is characterized by patterns of atypical language use distinguishing depression from normal sadness and euthymic state, which points to a potential role of linguistic indicators in diagnosing affective states.
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| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
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| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
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