Language analyses reveals crucial information about an individual's current state of mind. Maladaptive psychological functioning appears in cognition, emotional experience and behaviour. In the time of the internet of things, a vast number of text and speech is available; subsequently, the interest in the automated detection of psychological functioning via language is rising. The current study indicates that depression and narcissism can be predicted through word use in personal narratives. Both conditions are characterised by an altered word count regarding anxiety and we (LIWC-based). While depressive individuals use less social words and more anxietyrelated words, narcissists do the opposite. This might reflect the verbal correlate of the cognitive triad in depression. In contrast, narcissists' word use mirrors their excommunicated anxiety of being an undesired self and their inability to reach long-term goals due to a lack of impulse control. The automated recognition of mental state through word use could improve early detection of mental disease, monitoring of disease course, delivery of tailored interventions and evaluation of therapy outcome.

Background Studies show that 16% to 77% of psychotherapy patients abandon therapy within the first sessions. The aim of this study is to examine how patient personality variables, specifically the patients' structural integration and the personality traits dependency and self‐criticism, are associated with symptomatic change and therapy dropout. Method We analysed data from 96 patients (age: M = 30.56, SD = 11.39; 78.5% women; 44.6% students, 28.3% employees). A hierarchical logistic regression analysis was carried out to determine whether patients' structural integration (assessed via the OPD‐SQ) and their level of dependency and self‐criticism (DEQ) can predict therapy dropout. In addition, a multiple regression was used to analyse how these variables affect symptomatic change (OQ‐45.2 symptom subscale). Results The interaction of structural integration level and dependency best predicts therapy dropout. For the prediction of symptomatic change, both structural integration and dependency were significant. However, their interaction showed no significant results. Discussion The patient's structural integration was associated to both symptomatic change and dropout. Therapists' training should include techniques addressing patients' structural integration and degree of dependency to prevent patient dropout from therapy.

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