Self-processing in relation to emotion and reward processing in depression.

BACKGROUND: Depression is characterised by a heightened self-focus, which is believed to be associated with differences in emotion and reward processing. However, the precise relationship between these cognitive domains is not well understood. We examined the role of self-reference in emotion and reward processing, separately and in combination, in relation to depression. METHODS: Adults experiencing varying levels of depression (n = 144) completed self-report depression measures (PHQ-9, BDI-II). We measured self, emotion and reward processing, separately and in combination, using three cognitive tasks. RESULTS: When self-processing was measured independently of emotion and reward, in a simple associative learning task, there was little association with depression. However, when self and emotion processing occurred in combination in a self-esteem go/no-go task, depression was associated with an increased positive other bias [b = 3.51, 95% confidence interval (CI) 1.24-5.79]. When the self was processed in relation to emotion and reward, in a social evaluation learning task, depression was associated with reduced positive self-biases (b = 0.11, 95% CI 0.05-0.17). CONCLUSIONS: Depression was associated with enhanced positive implicit associations with others, and reduced positive learning about the self, culminating in reduced self-favouring biases. However, when self, emotion and reward processing occurred independently there was little evidence of an association with depression. Treatments targeting reduced positive self-biases may provide more sensitive targets for therapeutic intervention and potential biomarkers of treatment responses, allowing the development of more effective interventions.

Trajectories of depression and generalised anxiety symptoms over the course of cognitive behaviour therapy in primary care: an observational, retrospective cohort.

BACKGROUND: Cognitive-behavioural therapy (CBT) has been shown to be an effective treatment for depression and anxiety. However, most research has focused on the sum scores of symptoms. Relatively little is known about how individual symptoms respond. METHODS: Longitudinal models were used to explore how depression and generalised anxiety symptoms behave over the course of CBT in a retrospective, observational cohort of patients from primary care settings (n = 5306). Logistic mixed models were used to examine the probability of being symptom-free across CBT appointments, using the 9-item Patient Health Questionnaire and the 7-item Generalised Anxiety Disorder scale as measures. RESULTS: All symptoms improve across CBT treatment. The results suggest that low mood/hopelessness and guilt/worthlessness improved quickest relative to other depressive symptoms, with sleeping problems, appetite changes, and psychomotor retardation/agitation improving relatively slower. Uncontrollable worry and too much worry were the anxiety symptoms that improved fastest; irritability and restlessness improved the slowest. CONCLUSIONS: This research suggests there is a benefit to examining symptoms rather than sum scores alone. Investigations of symptoms provide the potential for precision psychiatry and may explain some of the heterogeneity observed in clinical outcomes when only sum scores are considered.

Inhibitory control of positive and negative information and adolescent depressive symptoms: a population-based cohort study.

BACKGROUND: Large population-based cohort studies of neuropsychological factors that characterise or precede depressive symptoms are rare. Most studies use small case-control or cross-sectional designs, which may cause selection bias and cannot test temporality. In a large UK population-based cohort, we investigated cross-sectional and longitudinal associations between inhibitory control of positive and negative information and adolescent depressive symptoms. METHODS: Cohort study of 2328 UK adolescents who completed an affective go/no-go task at age 18. Depressive symptoms were assessed with the Clinical Interview Schedule Revised (CIS-R) and short Mood and Feeling Questionnaire (sMFQ) at age 18, and with the sMFQ 1 year later (age 19). Analyses were multilevel and traditional linear regressions, before and after adjusting for confounders. RESULTS: Cross-sectionally, we found little evidence that adolescents with more depressive symptoms made more inhibitory control errors [after adjustments, errors increased by 0.04% per 1 s.d. increase in sMFQ score (95% confidence interval 0.02-0.06)], but this association was not observed for the CIS-R. There was no evidence for an influence of valence. Longitudinally, there was no evidence that reduced inhibitory control was associated with future depressive symptoms. CONCLUSIONS: Inhibitory control of positive and negative information does not appear to be a marker of current or future depressive symptoms in adolescents and would not be a useful target in interventions to prevent adolescent depression. Our lack of convincing evidence for associations with depressive symptoms suggests that the affective go/no-go task is not a promising candidate for future neuroimaging studies of adolescent depression.

How much change is enough? Evidence from a longitudinal study on depression in UK primary care.

BACKGROUND: The Patient Health Questionnaire (PHQ-9), the Beck Depression Inventory (BDI-II) and the Generalised Anxiety Disorder Assessment (GAD-7) are widely used in the evaluation of interventions for depression and anxiety. The smallest reduction in depressive symptoms that matter to patients is known as the Minimum Clinically Important Difference (MCID). Little empirical study of the MCID for these scales exists. METHODS: A prospective cohort of 400 patients in UK primary care were interviewed on four occasions, 2 weeks apart. At each time point, participants completed all three questionnaires and a 'global rating of change' scale (GRS). MCID estimation relied on estimated changes in symptoms according to reported improvement on the GRS scale, stratified by baseline severity on the Clinical Interview Schedule (CIS-R). RESULTS: For moderate baseline severity, those who reported improvement on the GRS had a reduction of 21% (95% confidence interval (CI) -26.7 to -14.9) on the PHQ-9; 23% (95% CI -27.8 to -18.0) on the BDI-II and 26.8% (95% CI -33.5 to -20.1) on the GAD-7. The corresponding threshold scores below which participants were more likely to report improvement were -1.7, -3.5 and -1.5 points on the PHQ-9, BDI-II and GAD-7, respectively. Patients with milder symptoms require much larger reductions as percentage of their baseline to endorse improvement. CONCLUSIONS: An MCID representing 20% reduction of scores in these scales, is a useful guide for patients with moderately severe symptoms. If treatment had the same effect on patients irrespective of baseline severity, those with low symptoms are unlikely to notice a benefit. FUNDING: Funding. National Institute for Health Research.

Emotional recognition training modifies neural response to emotional faces but does not improve mood in healthy volunteers with high levels of depressive symptoms.

BACKGROUND: There is demand for new, effective and scalable treatments for depression, and development of new forms of cognitive bias modification (CBM) of negative emotional processing biases has been suggested as possible interventions to meet this need. METHODS: We report two double blind RCTs, in which volunteers with high levels of depressive symptoms (Beck Depression Inventory ii (BDI-ii) > 14) completed a brief course of emotion recognition training (a novel form of CBM using faces) or sham training. In Study 1 (N = 36), participants completed a post-training emotion recognition task whilst undergoing functional magnetic resonance imaging to investigate neural correlates of CBM. In Study 2 (N = 190), measures of mood were assessed post-training, and at 2-week and 6-week follow-up. RESULTS: In both studies, CBM resulted in an initial change in emotion recognition bias, which (in Study 2) persisted for 6 weeks after the end of training. In Study 1, CBM resulted in increases neural activation to happy faces, with this effect driven by an increase in neural activity in the medial prefrontal cortex and bilateral amygdala. In Study 2, CBM did not lead to a reduction in depressive symptoms on the BDI-ii, or on related measures of mood, motivation and persistence, or depressive interpretation bias at either 2 or 6-week follow-ups. CONCLUSIONS: CBM of emotion recognition has effects on neural activity that are similar in some respects to those induced by Selective Serotonin Reuptake Inhibitors (SSRI) administration (Study 1), but we find no evidence that this had any later effect on self-reported mood in an analogue sample of non-clinical volunteers with low mood (Study 2).

Logical and Methodological Issues Affecting Genetic Studies of Humans Reported in Top Neuroscience Journals.

Genetics and neuroscience are two areas of science that pose particular methodological problems because they involve detecting weak signals (i.e., small effects) in noisy data. In recent years, increasing numbers of studies have attempted to bridge these disciplines by looking for genetic factors associated with individual differences in behavior, cognition, and brain structure or function. However, different methodological approaches to guarding against false positives have evolved in the two disciplines. To explore methodological issues affecting neurogenetic studies, we conducted an in-depth analysis of 30 consecutive articles in 12 top neuroscience journals that reported on genetic associations in nonclinical human samples. It was often difficult to estimate effect sizes in neuroimaging paradigms. Where effect sizes could be calculated, the studies reporting the largest effect sizes tended to have two features: (i) they had the smallest samples and were generally underpowered to detect genetic effects, and (ii) they did not fully correct for multiple comparisons. Furthermore, only a minority of studies used statistical methods for multiple comparisons that took into account correlations between phenotypes or genotypes, and only nine studies included a replication sample or explicitly set out to replicate a prior finding. Finally, presentation of methodological information was not standardized and was often distributed across Methods sections and Supplementary Material, making it challenging to assemble basic information from many studies. Space limits imposed by journals could mean that highly complex statistical methods were described in only a superficial fashion. In summary, methods that have become standard in the genetics literature-stringent statistical standards, use of large samples, and replication of findings-are not always adopted when behavioral, cognitive, or neuroimaging phenotypes are used, leading to an increased risk of false-positive findings. Studies need to correct not just for the number of phenotypes collected but also for the number of genotypes examined, genetic models tested, and subsamples investigated. The field would benefit from more widespread use of methods that take into account correlations between the factors corrected for, such as spectral decomposition, or permutation approaches. Replication should become standard practice; this, together with the need for larger sample sizes, will entail greater emphasis on collaboration between research groups. We conclude with some specific suggestions for standardized reporting in this area.

Power failure: why small sample size undermines the reliability of neuroscience.

A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood that a statistically significant result reflects a true effect. Here, we show that the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.

Exposure to childhood adversity and deficits in emotion recognition: results from a large, population-based sample.

BACKGROUND: Emotion recognition skills are essential for social communication. Deficits in these skills have been implicated in mental disorders. Prior studies of clinical and high-risk samples have consistently shown that children exposed to adversity are more likely than their unexposed peers to have emotion recognition skills deficits. However, only one population-based study has examined this association. METHODS: We analyzed data from children participating in the Avon Longitudinal Study of Parents and Children, a prospective birth cohort (n = 6,506). We examined the association between eight adversities, assessed repeatedly from birth to age 8 (caregiver physical or emotional abuse; sexual or physical abuse; maternal psychopathology; one adult in the household; family instability; financial stress; parent legal problems; neighborhood disadvantage) and the ability to recognize facial displays of emotion measured using the faces subtest of the Diagnostic Assessment of Non-Verbal Accuracy (DANVA) at age 8.5 years. In addition to examining the role of exposure (vs. nonexposure) to each type of adversity, we also evaluated the role of the timing, duration, and recency of each adversity using a Least Angle Regression variable selection procedure. RESULTS: Over three-quarters of the sample experienced at least one adversity. We found no evidence to support an association between emotion recognition deficits and previous exposure to adversity, either in terms of total lifetime exposure, timing, duration, or recency, or when stratifying by sex. CONCLUSIONS: Results from the largest population-based sample suggest that even extreme forms of adversity are unrelated to emotion recognition deficits as measured by the DANVA, suggesting the possible immutability of emotion recognition in the general population. These findings emphasize the importance of population-based studies to generate generalizable results.

Peer victimization during adolescence and risk for anxiety disorders in adulthood: a prospective cohort study.

BACKGROUND: Peer victimization is ubiquitous across schools and cultures, and has been suggested as one developmental pathway to anxiety disorders. However, there is a dearth of prospective studies examining this relationship. The purpose of this cohort study was to examine the association between peer victimization during adolescence and subsequent anxiety diagnoses in adulthood. A secondary aim was to investigate whether victimization increases risk for severe anxiety presentations involving diagnostic comorbidity. METHODS: The sample comprised 6,208 adolescents from the Avon Longitudinal Study of Parents and Children who were interviewed about experiences of peer victimization at age 13. Maternal report of her child's victimization was also assessed. Anxiety disorders at age 18 were assessed with the Clinical Interview Schedule-Revised. Multivariable logistic regression was used to examine the association between victimization and anxiety diagnoses adjusted for potentially confounding individual and family factors. Sensitivity analyses explored whether the association was independent of diagnostic comorbidity with depression. RESULTS: Frequently victimized adolescents were two to three times more likely to develop an anxiety disorder than nonvictimized adolescents (OR = 2.49, 95% CI: 1.62-3.85). The association remained after adjustment for potentially confounding individual and family factors, and was not attributable to diagnostic overlap with depression. Frequently victimized adolescents were also more likely to develop multiple internalizing diagnoses in adulthood. CONCLUSIONS: Victimized adolescents are at increased risk of anxiety disorders in later life. Interventions to reduce peer victimization and provide support for victims may be an effective strategy for reducing the burden associated with these disorders.

Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive-behavioural therapy versus counselling for depression.

BACKGROUND: Various effective psychotherapies exist for the treatment of depression; however, only approximately half of patients recover after treatment. In efforts to improve clinical outcomes, research has focused on personalised psychotherapy - an attempt to match patients to treatments they are most likely to respond to. AIM: The present research aimed to evaluate the benefit of a data-driven model to support clinical decision-making in differential treatment allocation to cognitive-behavioural therapy versus counselling for depression. METHOD: The present analysis used electronic healthcare records from primary care psychological therapy services for patients receiving cognitive-behavioural therapy (n = 14 544) and counselling for depression (n = 4725). A linear regression with baseline sociodemographic and clinical characteristics was used to differentially predict post-treatment Patient Health Questionnaire (PHQ-9) scores between the two treatments. The benefit of differential prescription was evaluated in a held-out validation sample. RESULTS: On average, patients who received their model-indicated optimal treatment saw a greater improvement (by 1.78 PHQ-9 points). This translated into 4-10% more patients achieving clinically meaningful changes. However, for individual patients, the estimated differences in benefits of treatments were small and rarely met the threshold for minimal clinically important differences. CONCLUSION: Precision prescription of psychotherapy based on sociodemographic and clinical characteristics is unlikely to produce large benefits for individual patients. However, the benefits may be meaningful from an aggregate public health perspective when applied at scale.

Relationship between change in social evaluation learning and mood in early antidepressant treatment: A prospective cohort study in primary care.

BACKGROUND: Antidepressants are proposed to work by increasing sensitivity to positive versus negative information. Increasing positive affective learning within social contexts may help remediate negative self-schema. We investigated the association between change in biased learning of social evaluations about the self and others, and mood during early antidepressant treatment. METHOD: Prospective cohort assessing patients recruited from primary care in South West England at four timepoints over the first 8 weeks of antidepressant treatment (n = 29). At each timepoint, participants completed self-report measures of depression (Beck Depression Inventory II (BDI-II) and Patient Health Questionnaire 9 (PHQ-9)), anxiety (Generalised Anxiety Disorder Questionnaire 7 (GAD-7)), and a computerised task measuring learning of social evaluations about the self, a friend and a stranger. RESULTS: We did not find evidence that learning about the self was associated with a reduction in PHQ-9 (b = 0.08, 95% CI: -0.05, 0.20, p = 0.239) or BDI-II scores (b = 0.10, 95% CI: -0.18, 0.38, p = 0.469). We found some weak evidence that increased positive learning about the friend was associated with a reduction in BDI-II scores (b = 0.30, 95% CI: -0.02, 0.62, p = 0.069). However, exploratory analyses indicated stronger evidence that increased positive learning about the self (b = 0.18, 95% CI: 0.07, 0.28, p = 0.002) and a friend (b = 0.22, 95% CI: 0.10, 0.35, p = 0.001) was associated with reductions in anxiety. CONCLUSIONS: Change in social evaluation learning was associated with a reduction in anxiety but not depression. Antidepressants may treat anxiety symptoms by remediating negative affective biases towards socially threatening information directed towards the self and close others. However, our findings are based on exploratory analyses within a small sample without a control group and are therefore at risk of type 1 errors and order effects. Further research with larger samples is required.

Factors associated with differential response to online cognitive behavioural therapy.

PURPOSE: Patients differ in their response to treatments. There is obvious clinical utility in establishing patient characteristics that are associated with differential treatment responses (i.e., are effect modifiers or moderators of treatment response). Factors that moderate response to cognitive behavioural therapy (CBT) remain unclear. This study investigates whether factors prognostic of general depression outcome generally are also moderators of response to online CBT in a sample of depressed patients recruited through U.K. general practices. METHODS: Secondary analysis of a randomised controlled trial, internet-based psychotherapy for depression. A total of 297 patients referred from 55 U.K. general practices and suffering from depression were randomly allocated to receive either online CBT or waiting list control. Treatment effect was measured by comparing depression score at 4 months between randomization groups. Treatment effect modification was assessed using regression analyses focusing on interactions between treatment effect and putative moderator variables. RESULTS: Pretreatment severity and marital status moderated treatment response. More severe patients, and patients who were separated, widowed, or divorced, benefited most from the intervention. Weak evidence suggested that treatment effectiveness diminished with increasing recent adverse life events. No evidence was found to suggest that educational attainment, age, and history of depression-moderated treatment response. CONCLUSIONS: Secondary analyses of trials comparing two or more treatments allow factors that may moderate treatment response to be distinguished from more general prognostic indicators, although caution is needed in interpreting such exploratory analyses.

Understanding emotion: lessons from anxiety.

We agree that conceptualisation is key in understanding the brain basis of emotion. We argue that by conflating facial emotion recognition with subjective emotion experience, Lindquist et al. understate the importance of biological predisposition in emotion. We use examples from the anxiety disorders to illustrate the distinction between these two phenomena, emphasising the importance of both emotional hardware and contextual learning.

Beyond online participant crowdsourcing: The benefits and opportunities of big team addiction science.

Participant crowdsourcing platforms (e.g., MTurk, Prolific) offer numerous advantages to addiction science, permitting access to hard-to-reach populations and enhancing the feasibility of complex experimental, longitudinal, and intervention studies. Yet these are met with equal concerns about participant nonnaivety, motivation, and careless responding, which if not considered can greatly compromise data quality. In this article, we discuss an alternative crowdsourcing avenue that overcomes these issues whilst presenting its own unique advantages-crowdsourcing researchers through big team science. First, we review several contemporary efforts within psychology (e.g., ManyLabs, Psychological Science Accelerator) and the benefits these would yield if they were more widely implemented in addiction science. We then outline our own consortium-based approach to empirical dissertations: a grassroots initiative that trains students in reproducible big team addiction science. In doing so, we discuss potential challenges and their remedies, as well as providing resources to help addiction researchers develop these initiatives. Through researcher crowdsourcing, together we can answer fundamental scientific questions about substance use and addiction, build a literature that is representative of a diverse population of researchers and participants, and ultimately achieve our goal of promoting better global health. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Depression screening using a non-verbal self-association task: A machine-learning based pilot study.

BACKGROUND: Effective screening is important to combat the raising burden of depression and opens a critical time window for early intervention. Clinical use of non-verbal depression screening is nascent, yet a promising and viable candidate to supplement verbal screening. Differential self- and emotion-processing in depression patients were previously reported by non-verbal behavioural assessments, corroborated by neuroimaging findings of distinct neuroanatomical markers. Thus non-verbal validated brain-behaviour based self-emotion-related assessment data reflect physiological differences and may support individual level screening of depression. METHODS: In this pilot study (n = 84) we collected two longitudinal sessions of behavioural assessment data in a laboratory setting. Depression was assessed using Beck Depression Inventory II (BDI-II), to explore optimal screening methods with machine-learning, and to establish the validity of adapting a novel behavioural assessment focusing on self and emotions for depression screening. RESULTS: The best machine-learning model achieved high performance in depression screening, 10-Fold cross-validation (CV) Area Under the receiver operating characteristic Curve (AUC) of 0.90 and balanced accuracy of 0.81, using a Gradient Boosting algorithm. Prospective prediction using a model trained with session 1 data to predict session 2 depression status achieved a 10-Fold CV AUC of 0.77 and balanced accuracy of 0.66. We also identified interpretable behavioural signatures for depression patients based on the best model. CONCLUSION: The study supports the utility of using behavioural data as a viable and cost-effective solution for depression screening, with a potential wide range of applications in clinical settings.

A Reduced Self-Positive Belief Underpins Greater Sensitivity to Negative Evaluation in Socially Anxious Individuals.

Positive self-beliefs are important for well-being, and are influenced by how others evaluate us during social interactions. Mechanistic accounts of self-beliefs have mostly relied on associative learning models. These account for choice behaviour but not for the explicit beliefs that trouble socially anxious patients. Neither do they speak to self-schemas, which underpin vulnerability according to psychological research. Here, we compared belief-based and associative computational models of social-evaluation, in individuals that varied in fear of negative evaluation (FNE), a core symptom of social anxiety. We used a novel analytic approach, 'clinically informed model-fitting', to determine the influence of FNE symptom scores on model parameters. We found that high-FNE participants learn more easily from negative feedback about themselves, manifesting in greater self-negative learning rates. Crucially, we provide evidence that this bias is underpinned by an overall reduced belief about self-positive attributes. The study population could be characterized equally well by belief-based or associative models, however large individual differences in model likelihood indicated that some individuals relied more on an associative (model-free), while others more on a belief-guided strategy. Our findings have therapeutic importance, as positive belief activation may be used to specifically modulate learning. AUTHOR SUMMARY: Understanding how we form and maintain positive self-beliefs is crucial to understanding how things go awry in disorders such as social anxiety. The loss of positive self-belief in social anxiety, especially in inter-personal contexts, is thought to be related to how we integrate evaluative information that we receive from others. We frame this social information integration as a learning problem and ask how people learn whether someone approves of them or not. We thus elucidate why the decrease in positive evaluations manifests only for the self, but not for an unknown other, given the same information. We investigated the mechanics of this learning using a novel computational modelling approach, comparing models that treat the learning process as series of stimulusresponse associations with models that treat learning as updating of beliefs about the self (or another). We show that both models characterise the process well and that individuals higher in symptoms of social anxiety learn more from negative information specifically about the self. Crucially, we provide evidence that this originates from a reduction in the amount of positive attributes that are activated when the individual is placed in a social evaluative context.

The early impact of COVID-19 on primary care psychological therapy services: A descriptive time series of electronic healthcare records.

BACKGROUND: There are growing concerns about the impact of the COVID-19 pandemic on mental health. With government-imposed restrictions as well as a general burden on healthcare systems, the pandemic has the potential to disrupt the access to, and delivery of, mental healthcare. METHODS: Electronic healthcare records from primary care psychological therapy services (Improving Access to Psychological Therapy) in England were used to examine changes in access to mental health services and service delivery during early stages of the COVID-19 pandemic. A descriptive time series was conducted using data from five NHS trusts to examine patterns in referrals to services (1st January 2019 to 24th May 2020) and appointments (1st January 2020 to 24th May 2020) taking place. FINDINGS: The number of patients accessing mental health services dropped by an average of 55% in the early weeks after the March 2020 lockdown was announced, reaching a maximum reduction of 74% in the initial 3 weeks after lockdown in the UK, which gradually recovered to a 28% reduction by May. We found some evidence suggesting changes in the sociodemographic and clinical characteristics of referrals. Despite a reduction in access, the impact on appointments appeared limited with service providers shifting to remote delivery of care. INTERPRETATION: Services appeared to adapt to provide continuity of care in mental healthcare. However, patients accessing services reduced, potentially placing a future burden on service. Despite the observational nature of the data, the present study can inform the planning of service provision and policy. FUNDING: AD and TS were funded by Innovate UK (KTP #11,105).

Effective dose 50 method as the minimal clinically important difference: Evidence from depression trials.

OBJECTIVE: Previous research on the minimal clinically important difference (MCID) for depression and anxiety is based on population averages. The present study aimed to identify the MCID across the spectrum of baseline severity. STUDY DESIGN AND SETTINGS: The present analysis used secondary data from 2 randomized controlled trials for depression (n = 1,122) to calibrate the Global Rating of Change with the PHQ-9 and GAD-7. The MCID was defined as a change in scores corresponding to a 50% probability of patients "feeling better", given their baseline severity, referred to as Effective Dose 50 (ED50). RESULTS: MCID estimates depended on baseline severity and ranged from no change for very mild up to 14 points (52%) on the PHQ-9 and up to 10 points (48%) on the GAD-7 for very high severity. The average MCID estimates were 3.7 points (23%) and 3.3 (28%) for the PHQ-9 and GAD-7 respectively. CONCLUSION: The ED50 method generates MCID estimates across the spectrum of baseline severity, offering greater precision but at the cost of greater complexity relative to population average estimates. This has important implications for evaluations of treatments and clinical practice where users can use these results to tailor the MCID to specific populations according to baseline severities.