Trait attributions and threat appraisals explain why an entity theory of personality predicts greater internalizing symptoms during adolescence.

Adolescents who hold an entity theory of personality - the belief that people cannot change - are more likely to report internalizing symptoms during the socially stressful transition to high school. It has been puzzling, however, why a cognitive belief about the potential for change predicts symptoms of an affective disorder. The present research integrated three models - implicit theories, hopelessness theories of depression, and the biopsychosocial model of challenge and threat - to shed light on this issue. Study 1 replicated the link between an entity theory and internalizing symptoms by synthesizing multiple datasets (N = 6,910). Study 2 examined potential mechanisms underlying this link using 8-month longitudinal data and 10-day diary reports during the stressful first year of high school (N = 533, 3,199 daily reports). The results showed that an entity theory of personality predicted increases in internalizing symptoms through tendencies to make fixed trait causal attributions about the self and maladaptive (i.e., "threat") stress appraisals. The findings support an integrative model whereby situation-general beliefs accumulate negative consequences for psychopathology via situation-specific attributions and appraisals.

Efficacy of attention bias modification training for depressed adults: a randomized clinical trial.

BACKGROUND: This study examined the efficacy of attention bias modification training (ABMT) for the treatment of depression. METHODS: In this randomized clinical trial, 145 adults (77% female, 62% white) with at least moderate depression severity [i.e. self-reported Quick Inventory of Depressive Symptomatology (QIDS-SR) ⩾13] and a negative attention bias were randomized to active ABMT, sham ABMT, or assessments only. The training consisted of two in-clinic and three (brief) at-home ABMT sessions per week for 4 weeks (2224 training trials total). The pre-registered primary outcome was change in QIDS-SR. Secondary outcomes were the 17-item Hamilton Depression Rating Scale (HRSD) and anhedonic depression and anxious arousal from the Mood and Anxiety Symptom Questionnaire (MASQ). Primary and secondary outcomes were administered at baseline and four weekly assessments during ABMT. RESULTS: Intent-to-treat analyses indicated that, relative to assessment-only, active ABMT significantly reduced QIDS-SR and HRSD scores by an additional 0.62 ± 0.23 (p = 0.008, d = -0.57) and 0.74 ± 0.31 (p = 0.021, d = -0.49) points per week. Similar results were observed for active v. sham ABMT: a greater symptom reduction of 0.44 ± 0.24 QIDS-SR (p = 0.067, d = -0.41) and 0.69 ± 0.32 HRSD (p = 0.033, d = -0.42) points per week. Sham ABMT did not significantly differ from the assessment-only condition. No significant differences were observed for the MASQ scales. CONCLUSION: Depressed individuals with at least modest negative attentional bias benefitted from active ABMT.

Network analyses reveal which symptoms improve (or not) following an Internet intervention (Deprexis) for depression.

BACKGROUND: Depression is a heterogeneous collection of symptoms. Prior meta-analyses using symptom sum scores have shown the Internet intervention, Deprexis, to be an efficacious treatment for depression. However, no prior research has investigated how Deprexis (or any other Internet intervention for depression) impacts specific symptoms of depression. The current study utilizes symptom-level analyses to examine which symptoms are directly, indirectly, or minimally influenced by treatment. METHODS: Network analysis and mean-level approaches examined which symptoms, assessed by the Quick Inventory of Depression Symptoms, were affected by an 8-week course of Deprexis compared with a waitlist in a nationally recruited sample from the United States (N = 295). RESULTS: Deprexis directly improved the symptoms of sadness and indecision. Changes in these symptoms, in turn, was associated with a change in early insomnia, middle insomnia, self-dislike, fatigue, anhedonia, suicidality, slowness, and agitation. All of these symptoms (except for agitation and early insomnia) show decreases with Deprexis compared with a waitlist after correcting for multiple comparisons. Six additional symptoms, particularly the somatic symptoms, were not impacted by Deprexis compared with a waitlist. CONCLUSIONS: In this sample, the efficacy of Deprexis was due to its direct impact on sadness and indecision. Examining the treatment-related change in specific symptoms may facilitate a more nuanced understanding of how a treatment works compared with examining symptom sum scores. Symptom-level approaches may also identify symptoms that do not improve and provide important direction for future treatment development.

Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: A data-driven approach.

BACKGROUND: Individual differences in reward-related processes, such as reward responsivity and approach motivation, appear to play a role in the nature and course of depression. Prior work suggests that cognitive biases for valenced information may contribute to these reward processes. Yet there is little work examining how biased attention, processing, and memory for positively and negatively valenced information may be associated with reward-related processes in samples with depression symptoms. METHODS: We used a data-driven, machine learning (elastic net) approach to identify the best predictors of self-reported reward-related processes using multiple tasks of attention, processing, and memory for valenced information measured across behavioral, eye tracking, psychophysiological, and computational modeling approaches (n = 202). Participants were adults (ages 18-35) who ranged in depression symptom severity from mild to severe. RESULTS: Models predicted between 5.0-12.2% and 9.7-28.0% of held-out test sample variance in approach motivation and reward responsivity, respectively. Low self-referential processing of positively valenced information was the most robust, albeit modest, predictor of low approach motivation and reward responsivity. CONCLUSIONS: Self-referential processing of positive information is the strongest predictor of reward responsivity and approach motivation in a sample ranging from mild to severe depression symptom severity. Experiments are now needed to clarify the causal relationship between self-referential processing of positively valenced information and reward processes in depression.

Getting Fewer "Likes" Than Others on Social Media Elicits Emotional Distress Among Victimized Adolescents.

Three studies examined the effects of receiving fewer signs of positive feedback than others on social media. In Study 1, adolescents (N = 613, Mage  = 14.3 years) who were randomly assigned to receive few (vs. many) likes during a standardized social media interaction felt more strongly rejected, and reported more negative affect and more negative thoughts about themselves. In Study 2 (N = 145), negative responses to receiving fewer likes were associated with greater depressive symptoms reported day-to-day and at the end of the school year. Study 3 (N = 579) replicated Study 1's main effect of receiving fewer likes and showed that adolescents who already experienced peer victimization at school were the most vulnerable. The findings raise the possibility that technology which makes it easier for adolescents to compare their social status online-even when there is no chance to share explicitly negative comments-could be a risk factor that accelerates the onset of internalizing symptoms among vulnerable youth.

A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression.

BACKGROUND: Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment. METHOD: An elastic net and random forest were trained to predict depression symptoms and related disability after an 8-week course of an Internet intervention, Deprexis, involving adults (N = 283) from across the USA. Candidate predictors included psychopathology, demographics, treatment expectancies, treatment usage, and environmental context obtained from population databases. Model performance was evaluated using predictive R2$\lpar R_{{\rm pred}}^2\rpar\comma $ the expected variance explained in a new sample, estimated by 10 repetitions of 10-fold cross-validation. RESULTS: An ensemble model was created by averaging the predictions of the elastic net and random forest. Model performance was compared with a benchmark linear autoregressive model that predicted each outcome using only its baseline. The ensemble predicted more variance in post-treatment depression (8.0% gain, 95% CI 0.8-15; total $R_{{\rm pred}}^2 \; $= 0.25), disability (5.0% gain, 95% CI -0.3 to 10; total $R_{{\rm pred}}^2 \; $= 0.25), and well-being (11.6% gain, 95% CI 4.9-19; total $R_{{\rm pred}}^2 \; $= 0.29) than the benchmark model. Important predictors included comorbid psychopathology, particularly total psychopathology and dysthymia, low symptom-related disability, treatment credibility, lower access to therapists, and time spent using certain Deprexis modules. CONCLUSION: A number of variables predict symptom improvement following an Internet intervention, but each of these variables makes relatively small contributions. Machine learning ensembles may be a promising statistical approach for identifying the cumulative contribution of many weak predictors to psychosocial depression treatment response.

Using Network Analysis to Identify Central Symptoms of Adolescent Depression.

Experiencing depression symptoms, even at mild to moderate levels, is associated with maladaptive outcomes for adolescents. We used network analysis to evaluate which symptoms (and associations between symptoms) are most central to adolescent depression. Participants were part of a large, diverse community sample (N = 1,409) of adolescents between 13 and 19 years of age. Network analysis was used to identify the most central symptoms (nodes) and associations between symptoms (edges) assessed by the Children's Depression Inventory. We also evaluated these centrality indicators for network robustness using stability and accuracy tests, associated symptom centrality with mean levels of symptoms, and examined potential differences between the structure and connectivity of depression networks in boys and girls. The most central symptoms in the network were self-hatred, loneliness, sadness, and pessimism. The strongest associations between symptoms were sadness-crying, anhedonia-school dislike, sadness-loneliness, school work difficulty-school performance decrement, self-hatred-negative body image, sleep disturbance-fatigue, and self-deprecation-self-blame. The network was robust to stability and accuracy tests. Notably, symptom centrality and mean levels of symptoms were not associated. Boys and girls' networks did not differ in levels of connectivity, though the link between body image and self-hatred was stronger in girls than boys. Self-hatred, loneliness, sadness, and pessimism were the most central symptoms in adolescent depression networks, suggesting that these symptoms (and associations between symptoms) should be prioritized in theoretical models of adolescent depression and could also serve as important treatment targets for adolescent depression interventions.

Effect of cognitive bias modification-memory on depressive symptoms and autobiographical memory bias: two independent studies in high-ruminating and dysphoric samples.

Memory bias is a risk factor for depression. In two independent studies, the efficacy of one CBM-Memory session on negative memory bias and depressive symptoms was tested in vulnerable samples. We compared positive to neutral (control) CBM-Memory trainings in highly-ruminating individuals (N = 101) and individuals with elevated depressive symptoms (N = 100). In both studies, participants studied positive, neutral, and negative Swahili words paired with their translations. In five study-test blocks, they were then prompted to retrieve either only the positive or neutral translations. Immediately following the training and one week later, we tested cued recall of all translations and autobiographical memory bias; and also measured mood, depressive symptoms, and rumination. Retrieval practice resulted in training-congruent recall both immediately after and one week after the training. Overall, there was no differential decrease in symptoms or difference in autobiographical memory bias between the training conditions. In the dysphoric but not in the high-ruminating sample, the positive training resulted in positive autobiographical bias only in dysphoric individuals with positive pre-existing bias. We conclude that one session of positive retrieval-based CBM-Memory may not be enough to yield symptom change and affect autobiographical memory bias in vulnerable individuals.

Serotonin Transporter Genetic Variation is Differentially Associated with Reflexive- and Reflective-Optimal Learning.

Learning to respond optimally under a broad array of environmental conditions is a critical brain function that requires engaging the cognitive systems that are optimal for solving the task at hand. Serotonin is implicated in learning and decision-making, but the specific functions of serotonin in system-level cognitive control remain unclear. Across 3 studies, we examined the influence of a polymorphism within the promoter region of the serotonin transporter gene (5-HTTLPR polymorphism in SLC6A4) on participants' ability to engage the task appropriate cognitive system when the reflexive (Experiments 1 and 2) or the reflective (Experiment 3) system was optimal. Critically, we utilized a learning task for which all aspects remain fixed with only the nature of the optimal cognitive processing system varying across experiments. Using large community samples, Experiments 1 and 2 (screened for psychiatric diagnosis) found that 5-HTTLPR S/LG allele homozygotes, with putatively lower serotonin transport functionality, outperformed LA allele homozygotes in a reflexive-optimal learning task. Experiment 3 used a large community sample, also screened for psychiatric diagnosis, and found that 5-HTTLPR LA homozygotes, with putatively higher serotonin transport functionality, outperformed S/LG allele homozygotes in a reflective-optimal learning task.

Self-referential schemas and attentional bias predict severity and naturalistic course of depression symptoms.

Attentional bias and self-referential schemas have been observed in numerous cross-sectional studies of depressed adults and are theorised to maintain negative mood. However, few longitudinal studies have examined whether maladaptive cognition predicts the course of depressive symptoms. Fifty-seven adults with elevated depression symptoms were assessed for negative attentional bias using a dot-probe task with eye-tracking and self-referential schemas using a self-referent encoding task. Participants subsequently completed five weekly depression symptom assessments. Participants with more negative self-referential schemas had higher baseline depression symptoms (r = .55). However, participants who spent more time attending to negative words showed greater symptom worsening over time (r = .42). The findings for negative self-referential schemas replicate past research, while the findings for negative attention bias represent the first evidence showing that attentional biases predict naturalistic symptom course. This work suggests that negative attention biases maintain depression symptoms and represent an important treatment target for neurocognitive therapeutics.

Neural mechanisms of the cognitive model of depression.

In the 40 years since Aaron Beck first proposed his cognitive model of depression, the elements of this model--biased attention, biased processing, biased thoughts and rumination, biased memory, and dysfunctional attitudes and schemas--have been consistently linked with the onset and maintenance of depression. Although numerous studies have examined the neural mechanisms that underlie the cognitive aspects of depression, their findings have not been integrated with Beck's cognitive model. In this Review, we identify the functional and structural neurobiological architecture of Beck's cognitive model of depression. Although the mechanisms underlying each element of the model differ, in general the negative cognitive biases in depression are facilitated by increased influence from subcortical emotion processing regions combined with attenuated top-down cognitive control.

Attentional biases to emotional stimuli: Key components of the RDoC constructs of sustained threat and loss.

Biased attention to emotional stimuli plays a key role in the RDoC constructs of Sustained Threat and Loss. In this article, we review approaches to assessing these biases, their links with psychopathology, and the underlying neural influences. We then review evidence from twin and candidate gene studies regarding genetic influences on attentional biases. We also discuss the impact of developmental and environmental influences and end with a number of suggestions for future research in this area.

DRD4 long allele carriers show heightened attention to high-priority items relative to low-priority items.

Humans with seven or more repeats in exon III of the DRD4 gene (long DRD4 carriers) sometimes demonstrate impaired attention, as seen in attention-deficit hyperactivity disorder, and at other times demonstrate heightened attention, as seen in addictive behavior. Although the clinical effects of DRD4 are the focus of much work, this gene may not necessarily serve as a "risk" gene for attentional deficits, but as a plasticity gene where attention is heightened for priority items in the environment and impaired for minor items. Here we examine the role of DRD4 in two tasks that benefit from selective attention to high-priority information. We examine a category learning task where performance is supported by focusing on features and updating verbal rules. Here, selective attention to the most salient features is associated with good performance. In addition, we examine the Operation Span (OSPAN) task, a working memory capacity task that relies on selective attention to update and maintain items in memory while also performing a secondary task. Long DRD4 carriers show superior performance relative to short DRD4 homozygotes (six or less tandem repeats) in both the category learning and OSPAN tasks. These results suggest that DRD4 may serve as a "plasticity" gene where individuals with the long allele show heightened selective attention to high-priority items in the environment, which can be beneficial in the appropriate context.

Influence of depressive symptoms on speech perception in adverse listening conditions.

It is widely acknowledged that individuals with elevated depressive symptoms exhibit deficits in inter-personal communication. Research has primarily focused on speech production in individuals with elevated depressive symptoms. Little is known about speech perception in individuals with elevated depressive symptoms, especially in challenging listening conditions. Here, we examined speech perception in young adults with low- or high-depressive (HD) symptoms in the presence of a range of maskers. Maskers were selected to reflect various levels of informational masking (IM), which refers to cognitive interference due to signal and masker similarity, and energetic masking (EM), which refers to peripheral interference due to signal degradation by the masker. Speech intelligibility data revealed that individuals with HD symptoms did not differ from those with low-depressive symptoms during EM, but they exhibited a selective deficit during IM. Since IM is a common occurrence in real-world social settings, this listening deficit may exacerbate communicative difficulties.

5-HTTLPR, HTR1A, and HTR2A cumulative genetic score interacts with mood reactivity to predict mood-congruent gaze bias.

Genetic variation within the serotonin system has been associated with biased attention for affective stimuli and, less consistently, with vulnerability for major depressive disorder. In particular, 5-HTTLPR, HTR1A (rs6295), and HTR2A (rs6311) polymorphisms have been linked with biased cognition. The present study developed a serotonergic cumulative genetic score (CGS) that quantified the number of risk alleles associated with these candidate polymorphisms to yield a single CGS. The CGS was then used to model genetic influence on the relationship between reactivity to a negative mood induction and negatively biased cognition. A passive-viewing eye-tracking task was administered to 170 healthy volunteers to assess sustained attention for positive, dysphoric, neutral, and threatening scenes. Participants were then induced into a sad mood and readministered the passive-viewing task. Change in gaze bias, as a function of reactivity to mood induction, was the primary measure of cognitive vulnerability. Results suggest that, although none of the individual genes interacted with mood reactivity to predict change in gaze bias, individuals with higher serotonin CGS were significantly more likely to look toward dysphoric images and away from positive images as mood reactivity increased. These findings suggest that a CGS approach may better capture genetic influences on cognitive vulnerability and reaffirm the need to examine multilocus approaches in genomic research.

Training attention improves decision making in individuals with elevated self-reported depressive symptoms.

Depression is often characterized by attentional biases toward negative items and away from positive items, which likely affects reward and punishment processing. Recent work has reported that training attention away from negative stimuli reduced this bias and reduced depressive symptoms. However, the effect of attention training on subsequent learning has yet to be explored. In the present study, participants were required to learn to maximize reward during decision making. Undergraduates with elevated self-reported depressive symptoms received attention training toward positive stimuli prior to performing the decision-making task (n = 20; active training). The active-training group was compared to two other groups: undergraduates with elevated self-reported depressive symptoms who received placebo training (n = 22; placebo training) and a control group with low levels of depressive symptoms (n = 33; nondepressive control). The placebo-training depressive group performed worse and switched between options more than did the nondepressive controls on the reward maximization task. However, depressives that received active training performed as well as the nondepressive controls. Computational modeling indicated that the placebo-trained group learned more from negative than from positive prediction errors, leading to more frequent switching. The nondepressive control and active-training depressive groups showed similar learning from positive and negative prediction errors, leading to less-frequent switching and better performance. Our results indicate that individuals with elevated depressive symptoms are impaired at reward maximization, but that the deficit can be improved with attention training toward positive stimuli.

Childhood abuse and vulnerability to depression: cognitive scars in otherwise healthy young adults.

Models of depression vulnerability posit that negative early experiences, such as exposure to childhood abuse (CA), increase vulnerability to depression later in life. Though most victims of CA do not go on to develop depression, the question remains as to whether these individuals retain cognitive 'scars' that may contribute to depression vulnerability. The present study examined the relationship between self-reported, retrospective CA and cognitive vulnerability to depression in a carefully selected sample of young adults without current or past psychopathology. We measured cognitive vulnerability with both a self-report questionnaire, the Dysfunctional Attitudes Scale (DAS), and a measure of information processing bias, the Scrambled Sentences Test (SST). Self-reported severity of CA was associated with increased cognitive vulnerability to depression on both the DAS and SST. Vulnerability to depression as measured by the SST, but not by the DAS, prospectively predicted increases in depressive symptoms over a 6-month period. Scores on the SST also interacted with CA to predict increases in depressive symptoms. These findings demonstrate the pernicious effects of CA even in those without current or past psychopathology.

The role of controlled attention on recall in major depression.

Information processing biases are hallmark features of major depressive disorder (MDD). Depressed individuals display biased memory and attention for negative material. Given that memory is highly dependent on attention for initial encoding, understanding the interplay of these processes may provide important insight into mechanisms that produce memory biases in depression. In particular, attentional control-the ability to selectively attend to task-relevant information by both inhibiting the processing of irrelevant information and disengaging attention from irrelevant material-may be one area of impairment in MDD. In the current study, clinically depressed (MDD: n = 15) and never depressed (non-MDD: n = 22) participants' line of visual gaze was assessed while participants viewed positive and negative word pairs. For each word pair, participants were instructed to attend to one word (target) and ignore one word (distracter). Free recall of study stimuli was then assessed. Depressed individuals displayed greater recall of negatively valenced target words following the task. Although there were no group differences in attentional control in the context of negative words, attention to negative targets mediated the relationship between depression status and recall of negative words. Results suggest a stronger link between attention and memory for negative material in MDD.

Association between serotonin cumulative genetic score and the Behavioral Approach System (BAS): Moderation by early life environment.

The present study investigates if genetic variation in the serotonergic system interacts with early adversity to predict changes in the Behavioral Approach System (BAS), a system that taps into reward processing. In a sample of community adults (N= 236) the influence of single serotonergic candidate polymorphisms on BAS was analyzed, we also examined the aggregate contribution of these genetic variants by creating a Cumulative Genetic Score (CGS). A CGS quantifies an individual's cumulative risk by aggregating the number of risk alleles across the candidate polymorphisms. After individual gene analysis, three candidate genes rs7305115 (TPH2), rs6311 (HTR2A), and rs6295 (HTR1A) were combined into the CGS. There were no significant interactions between individual candidate polymorphisms and childhood adversity, but the CGS interacted with childhood adversity to explain a significant amount of variance (11.6%) in the BAS. Findings suggest that genetic variations in the serotonergic system in combination with childhood adversity contribute to individual differences in reward sensitivity.

Perceptual Observer Modeling Reveals Likely Mechanisms of Face Expression Recognition Deficits in Depression.

BACKGROUND: Deficits in face emotion recognition are well documented in depression, but the underlying mechanisms are poorly understood. Psychophysical observer models provide a way to precisely characterize such mechanisms. Using model-based analyses, we tested 2 hypotheses about how depression may reduce sensitivity to detect face emotion: 1) via a change in selectivity for visual information diagnostic of emotion or 2) via a change in signal-to-noise ratio in the system performing emotion detection. METHODS: Sixty adults, one half meeting criteria for major depressive disorder and the other half healthy control participants, identified sadness and happiness in noisy face stimuli, and their responses were used to estimate templates encoding the visual information used for emotion identification. We analyzed these templates using traditional and model-based analyses; in the latter, the match between templates and stimuli, representing sensory evidence for the information encoded in the template, was compared against behavioral data. RESULTS: Estimated happiness templates produced sensory evidence that was less strongly correlated with response times in participants with depression than in control participants, suggesting that depression was associated with a reduced signal-to-noise ratio in the detection of happiness. The opposite results were found for the detection of sadness. We found little evidence that depression was accompanied by changes in selectivity (i.e., information used to detect emotion), but depression was associated with a stronger influence of face identity on selectivity. CONCLUSIONS: Depression is more strongly associated with changes in signal-to-noise ratio during emotion recognition, suggesting that deficits in emotion detection are driven primarily by deprecated signal quality rather than suboptimal sampling of information used to detect emotion.