First‐person Pronoun Use in Spoken Language as a Predictor of Future Depressive Symptoms: Preliminary Evidence from a Clinical Sample of Depressed Patients

Zimmermann, Johannes; Brockmeyer, Timo; Hunn, Matthias; Schauenburg, Henning; Wolf, Markus

doi:10.1002/cpp.2006

Cited by 86 publications

(82 citation statements)

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“…Of note, earlier findings of a higher use of overall negative emotion words could not be replicated in the current study [34], [35]. A possible explanation is the diverse assessment of depression.…”

Section: Prediction Of Depressive Symptoms Through Word Usecontrasting

confidence: 94%

How Did You like 2017? Detection of Language Markers of Depression and Narcissism in Personal Narratives

Rathner

Djamali²,

Terhorst

et al. 2018

Interspeech 2018

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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.

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Section: Prediction Of Depressive Symptoms Through Word Usecontrasting

confidence: 94%

How Did You like 2017? Detection of Language Markers of Depression and Narcissism in Personal Narratives

Rathner

Djamali²,

Terhorst

et al. 2018

Interspeech 2018

View full text Add to dashboard Cite

show abstract

“…Future studies are needed not only to confirm whether or not changes in self-evaluation influences outcome in different types of psychotherapy but also to better understand the related processes and helpful techniques that will eventually result in higher self-esteem. A recent empirical finding that may be of relevance here, is that heightened self-focused attention as evidenced in patients' language was associated with slower recovery from depression (Zimmermann, Brockmeyer, Hunn, Schauenburg, & Wolf, 2016). Based on the previous finding that cognitive errors of depressed patients are associated with the interpersonal patterns between patients and therapists, future studies should also include the therapeutic alliance as potential mediating variable.…”

Section: Prediction Of Outcome At Follow-upmentioning

confidence: 95%

Change in self‐esteem predicts depressive symptoms at follow‐up after intensive multimodal psychotherapy for major depression

Dinger

Ehrenthal

Nikendei

et al. 2017

Clin Psychology and Psychoth

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Self-esteem is related to depressive symptoms and interpersonal problems. Improvement of self-esteem during psychotherapy correlates with improvements of symptoms and interpersonal problems. Change of self-esteem during psychotherapy predicts depressive symptoms 6 months after termination of therapy. When treating depressed patients, psychotherapists should work towards an improvement of self-esteem in order to prevent relapse.

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“…Linguistic research has found a positive association between past-focused language and depressive symptoms (Habermas, Ott, Schubert, Schneider, & Pate, 2008;Rodriguez et al, 2010). Zimmermann, Brockmeyer, Hunn, Schauenburg, and Wolf (2017) found that first-person singular (FPS) pronoun use in semi-structured diagnostic interviews (e.g., "I was offended by his behaviour") was positively related to BDI score at both termination and follow-up. Van Staden (2006) noted that poor outcome cases evidenced significantly more negative words, such as never and not, in the initial sessions in comparison with cases that experienced positive change.…”

Section: Psychology Psychotherapy and The Study Of Languagementioning

confidence: 99%

Exploratory study of automated linguistic analysis for progress monitoring and outcome assessment

Huston

Meier

Faith

et al. 2019

Couns and Psychother Res

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Objective The most successful approach to dealing with treatment failure employs progress monitoring and outcome assessment (PMOA) measures that enable clinicians to identify clients who are failing to progress. On the basis of previous research indicating that word use relates to individuals’ psychological characteristics as well as clinical outcomes, we investigated automated linguistic analysis of client speech as an alternative PMOA approach. Methods We employed the Linguistic Inquiry and Word Count (LIWC) program to study the language of a subset of 12 clients from the York I Depression Study. Automated analyses examined transcripts of 24 individual psychotherapy sessions, one early in treatment (T1) and one late in treatment (T2), split between six good and six poor outcome cases. Results Good outcomes were associated with more positive emotion words and fewer past focus words and negation words at T1. Logistic regression models predicted good versus poor treatment outcome for 70–82% of transcripts. However, analyses failed to support the hypothesis that language use patterns changed from T1 to T2 during the course of therapy. Conclusions Clinicians have been slow to adopt PMOA measures as part of routine practice, partially as a result of additional paperwork and time burdens. Automated analysis of client language provides one alternative method for decreasing client and therapist workload. This study's results, while mixed, provide evidence that additional research should be conducted to investigate the potential for LIWC and other automated measures to provide PMOA data for clinical feedback.

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First‐person Pronoun Use in Spoken Language as a Predictor of Future Depressive Symptoms: Preliminary Evidence from a Clinical Sample of Depressed Patients

Cited by 86 publications

References 50 publications

How Did You like 2017? Detection of Language Markers of Depression and Narcissism in Personal Narratives

How Did You like 2017? Detection of Language Markers of Depression and Narcissism in Personal Narratives

Change in self‐esteem predicts depressive symptoms at follow‐up after intensive multimodal psychotherapy for major depression

Exploratory study of automated linguistic analysis for progress monitoring and outcome assessment

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