Features of depression
We’re looking at four studies of depression today. First, Nagrodzki, Passamonti, Schweizer, Stretton, Knights, Henson & Wolpe (2025) published “Behavioral and Brain Differences in the Processing of Negative Emotion in Previously Depressed Individuals: An exploratory analysis of population-based data” in Emotion. Here’s the edited abstract:
Depressed individuals show significant biases in the processing of emotional stimuli, focusing attention on negative facial expressions (termed “attentional negativity bias”). Some of these biases persist in previously depressed individuals, but their mechanisms remain largely unknown. Here, in a population-based study in which participants (n = 134, 68 females; 21–92 years) were recruited as part of the Cambridge Centre for Ageing and Neuroscience in 2010–2014, we explored (a) the cognitive process underlying attentional negativity bias; (b) whether this process is associated with a self-reported history of depression; and (c) the neural correlates of this process. Participants completed an implicit emotion processing task, while functional MRI was acquired. Drift-diffusion modeling was used to calculate each participant’s tendency for sustained task-irrelevant attention on negative (angry) compared to neutral faces. In the cohort, 14% of participants reported a history of depression. Drift-diffusion modeling showed reduced drift rate for angry compared to neutral faces. The magnitude of this reduction was associated with self-reported depression history. Across the whole group, drift rate for angry faces was associated with increased brain activity when processing angry versus neutral faces in areas of bilateral insula/inferior frontal gyrus and bilateral parietal cortex. Our results suggest that attentional negativity bias is explained by slower task-relevant drift rate for negative (angry) stimuli. This slower drift rate is associated with the difference in brain activity when processing these stimuli, possibly reflecting increased emotional engagement. Such altered processing may persist even after a depressive episode, but this finding should be validated in clinical samples.
I thought this one is interesting in identifying the attentional negativity bias in depressed people. I like the idea of increased emotional engagement with angry stimuli leading to persistent focus on them. Next, Collins et al. (2025) published “Semantic Signals in Self-Reference: The detection and prediction of depressive symptoms from the daily diary entries of a sample with major depressive disorder” in Journal of Psychopathology and Clinical Science. The edited abstract and impact statement follow:
Individuals with major depressive disorder (MDD) experience fewer positive and more negative emotions and use fewer positive words to describe themselves. Natural language processing techniques have been used to predict depression, with pronoun and emotion usage being identified as important features. However, it is unclear how depressed individuals use positive and negative words when writing about themselves. Individuals with MDD (N = 258) completed ecological momentary assessments three times a day (including the Patient Health Questionnaire-9 [PHQ-9] and a free-text diary entry) and weekly ecological momentary assessments (including a free-text response to a life events prompt) over a 90-day study period. Using natural language processing techniques, we generated 20 model features to detect and predict averages of and changes in weekly depression from diary entries. Four regression models detected and predicted total PHQ-9 and changes in PHQ-9, and two classification models detected and predicted moderate to severe depression. The models classified current (area under the receiver operating curve [AUC] = 0.68) and future depression (AUC = 0.63), and suggest that lower valence increased usage of “I”/“me”/“my,” and lower valence of passages with “I”/“me” as the subject, influenced model predictions toward more severe depression, supporting prior research. These findings highlight that depressed individuals use less positive and more negative words when referring to themselves. Treatments targeting positive affect and digital interventions with written components may be beneficial for targeting MDD.
The findings of the current study demonstrate that there are important differences in how depressed individuals use positive and negative writing in their diary entries. When writing about themselves specifically and not others, they tend to use fewer positive words and more negative words. This suggests that there may be a specific devaluation of positivity seen in how they view themselves but a normal valuation of positivity regarding others. Thus, interventions that are digital or include a writing component that focuses on increasing positive affect and targeting self-views may be beneficial for depressed individuals.
This time, we see a negativity bias in that depressed people use fewer positive and more negative words when writing about themselves. So, now we have a bias toward focusing on angry stimuli and one that produces more negative words in writing. Liu, Ying, Feng, Shi & Joormann (2025) published “Emotion Regulation, Depressive Symptoms, and Sleep Problems in Adolescents: A four-wave random-intercept cross-lagged panel model. Journal of Psychopathology and Clinical Science. Here again, the edited abstract and impact statement follow:
Depressive symptoms and sleep problems are detrimental for adolescents, with emotion regulation related to both problems. The present study explores emotion regulation as a potential mediator of the reciprocal associations between depressive symptoms and sleep problems and examines gender differences. A total of 1,535 adolescents (47.4% girls; baseline Mage = 13.19 years) were included in this four-wave longitudinal study with 6-month intervals. We used random-intercept cross-lagged panel models to examine our research questions. The results indicated that increases in sleep problems significantly predicted more depressive symptoms 6 months later but not vice versa. Emotion regulation mediated the reciprocal associations between depressive symptoms and sleep problems. Multigroup analyses on the associations among depressive symptoms, sleep problems, and emotion regulation showed that sleep problems predicted depressive symptoms, but not vice versa, in both girls and boys. However, emotion regulation was a mediator only in girls but not boys. These findings support the critical role of sleep problems in the development of depressive symptoms, underscoring the necessity for early and targeted sleep interventions. Emotion regulation was shown to mediate the reciprocal associations between depressive symptoms and sleep problems in girls only highlighting the need for more focus on gender differences and a need for gender-sensitive intervention strategies.
This study suggests that sleep problems can predict depressive symptoms but not vice versa. Emotion regulation emerges as a key factor mediating the reciprocal associations between sleep problems and depressive symptoms, particularly in adolescent girls, underscoring the need for targeted interventions addressing sleep and emotion regulation to support adolescent mental health.
This time we see that, in teens at least, sleep problems predict depressive symptoms, with, in girls especially, emotion regulation mediating the relationship between poor sleep and depression. Next, we look at self-esteem. Haehner, Driver, Hopwood, Luhmann, Fliedner & Bleidorn (2025) published “The Dynamics of Self-Esteem and Depressive Symptoms across Days, Months, and Years” in Journal of Personality and Social Psychology. Abstract
Self-esteem and depressive symptoms are important predictors of a range of societally relevant outcomes and are theorized to influence each other reciprocally over time. However, existing research offers only a limited understanding of how their dynamics unfold across different timescales. Using three data sets with different temporal resolutions, we aimed to advance our understanding of the temporal unfolding of the reciprocal dynamics between self-esteem and depressive symptoms. Across these data sets, participants (Ntotal = 6,210) rated their self-esteem and depressive symptoms between 6 and 14 times across days, months, and years, respectively. Using continuous time dynamic models, we found limited evidence for significant within-person cross-lagged effects between self-esteem and depressive symptoms. Only in the yearly data set, a cross-lagged effect from depressive symptoms to self-esteem emerged quite consistently. However, in all data sets, cross-lagged effects were small in size (−0.04 ≤ β ≤ −0.01). These findings suggest that the reciprocal dynamics between self-esteem and depressive symptoms may be less robust than commonly thought. Furthermore, exploratory analyses indicated that these effects depended on people’s overall levels of depressive symptoms, suggesting that theoretical frameworks that highlight transactions between self-esteem and depression may not generalize across all levels of depressive symptoms. Finally, self-esteem and depressive symptoms were strongly correlated within measurements, similarly stable over time, and changed similarly in response to negative life events, provoking questions as to their conceptual distinctiveness and measurement approaches.
I thought it interesting that, in a huge sample, the cross-lagged effect of depressive symptoms on self-esteem is quite small. I find even more interesting the idea that measures of self-esteem and depression seem not to reflect conceptual distinctions. Taken together, these articles illustrate the bias of depressed individuals toward angry stimuli, negative self-reference, low self-esteem, a history of sleep problems and, in teenaged females, poor emotional regulation.