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

Several theories suggest that self‐focused attention plays an important role in the maintenance of depression. However, previous studies have predominantly relied on self‐report and laboratory‐based measures such as sentence completion tasks to assess individual differences in self‐focus. We present a prospective, longitudinal study based on a sample of 29 inpatients with clinical depression, investigating whether an implicit, behavioural measure of self‐focused attention, i.e., the relative frequency of first‐person singular pronouns in naturally spoken language, predicts depressive symptoms at follow‐up over and above initial depression. We did not find a significant cross‐sectional association between depressive symptoms and first‐person singular pronoun use. However, first‐person singular pronoun use significantly predicted depressive symptoms approximately 8 months later, even after controlling for depressive symptoms at baseline or discharge. Exploratory analyses revealed that this effect was mainly driven by the use of objective and possessive self‐references such as ‘me’ or ‘my’. Our findings are in line with theories that highlight individual differences in self‐focused attention as a predictor of the course of depression. Moreover, our findings extend previous work in this field by adopting an unobtrusive approach of non‐reactive assessment, capturing naturally occurring differences in self‐focused attention. We discuss possible clinical applications of language‐based assessments and interventions with regard to self‐focus. Copyright © 2016 John Wiley & Sons, Ltd. Key Practitioner Message Naturally occurring individual differences in first‐person singular pronoun use provide an unobtrusive way to assess patients' automatic self‐focused attention. Frequent use of first‐person singular pronouns predicts an unfavourable course of depression. Self‐focused language might offer innovative ways of tracking and targeting therapeutic change.