Depression, Negative Emotionality, and Self-Referential Language: A Multi-Lab, Multi-Measure, and Multi-Language-Task Research Synthesis_Tackman et al_Preprint

Abstract

Depressive symptomatology is manifested in greater first-person singular pronoun use (i.e., I-talk), but when and for whom this effect is most apparent, and the extent to which it is specific to depression or part of a broader association between negative emotionality and I-talk, remains unclear. Using pooled data from N = 4,754 participants from 6 labs across 2 countries, we examined, in a preregistered analysis, how the depression–I-talk effect varied by (a) first-person singular pronoun type (i.e., subjective, objective, and possessive), (b) the communication context in which language was generated (i.e., personal, momentary thought, identity-related, and impersonal), and (c) gender. Overall, there was a small but reliable positive correlation between depression and I-talk (r = .10, 95% CI [.07, .13]). The effect was present for all first-person singular pronouns except the possessive type, in all communication contexts except the impersonal one, and for both females and males with little evidence of gender differences. Importantly, a similar pattern of results emerged for negative emotionality. Further, the depression–I-talk effect was substantially reduced when controlled for negative emotionality but this was not the case when the negative emotionality–I-talk effect was controlled for depression. These results suggest that the robust empirical link between depression and I-talk largely reflects a broader association between negative emotionality and I-talk. Self-referential language using first-person singular pronouns may therefore be better construed as a linguistic marker of general distress proneness or negative emotionality rather than as a specific marker of depression.

Tweeting about alcohol: Exploring differences in Twitter sentiment during the onset of the COVID-19 pandemic

“…The increased use of telecommuting, coupled with government-mandated lockdowns, meant that work-related stress was likely intermingled with stress related to personal, homebased concerns. The increased stress can manifest itself in an increased use of self-referential language (e.g., "I"), which research has shown may inhibit the ability of individuals to avoid negative emotionality and therefore may result in inappropriate or detrimental behaviors and associated health outcomes, including abuse of alcohol [42,43]. Increased stress can also lead to the sharing of alcohol-related events through social media outlets.…”

Applying Attention-Based Models for Detecting Cognitive Processes and Mental Health Conditions

“…Examples of recent efforts building technology toward this direction are the Woebot [24] and Wysa [25] dialog systems for health and therapy support for patients that have depression symptoms; Expressive Interviewing [26], which is a conversational agent aiming at support users to cope with COVID-19 issues. The underlying hypothesis of most these works relies on the notion of the language as a powerful indicator about our personality, social, or emotional status, and mental health [3,27]. Accordingly, the NLP community has focused on proposing several methods to identify different psychological traits from texts, and to examine the connection between language and mental health.…”

“…Accordingly, the NLP community has focused on proposing several methods to identify different psychological traits from texts, and to examine the connection between language and mental health. As a few examples of this type of research, we can mention dementia identification [28,29], depression detection [27,30,31], crisis counselling [32], suicide risks identification [31,33,34], mental illnesses classification [35,36], anxiety detection [37], personality traits identification [38,39], etc.…”

Capturing mood dynamics through adolescent smartphone social communication.

“…Lower positive sentiment and greater negative sentiment in social media posts (e.g., Facebook, Twitter) have been shown to reliably differentiate people with versus without depression (De Choudhury et al, 2013;Eichstaedt et al, 2018;Reece et al, 2017). Additionally, motivated by theories that depression results from an excessive self-focus after loss (Pyszczynski et al, 1987), research has shown that greater first-person singular pronoun use (e.g., I, me) in a variety of contexts (e.g., social media posts, speech, expressive writing essays) consistently associates with greater depression severity (Edwards & Holtzman, 2017;Tackman et al, 2019). More recently, borrowing methods from computer science, an open-vocabulary approach has emerged.…”