Teaching open and reproducible scholarship: a critical review of the evidence base for current pedagogical methods and their outcomes.

In recent years, the scientific community has called for improvements in the credibility, robustness and reproducibility of research, characterized by increased interest and promotion of open and transparent research practices. While progress has been positive, there is a lack of consideration about how this approach can be embedded into undergraduate and postgraduate research training. Specifically, a critical overview of the literature which investigates how integrating open and reproducible science may influence student outcomes is needed. In this paper, we provide the first critical review of literature surrounding the integration of open and reproducible scholarship into teaching and learning and its associated outcomes in students. Our review highlighted how embedding open and reproducible scholarship appears to be associated with (i) students' scientific literacies (i.e. students' understanding of open research, consumption of science and the development of transferable skills); (ii) student engagement (i.e. motivation and engagement with learning, collaboration and engagement in open research) and (iii) students' attitudes towards science (i.e. trust in science and confidence in research findings). However, our review also identified a need for more robust and rigorous methods within pedagogical research, including more interventional and experimental evaluations of teaching practice. We discuss implications for teaching and learning scholarship.

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.

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.

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.

Under-triage: A New Trigger to Drive Quality Improvement in the Emergency Department.

The emergency department (ED) is a care setting with a high risk for medical error. In collaboration with our nursing colleagues, we identified a new trigger, under-triage, and demonstrated how its implementation could detect and reduce medical errors in the ED. Methods: We defined under-triage as patient visits with an Emergency Severity Index (ESI) score of 4 or 5 (ie, low acuity), and the patient was admitted to the hospital during the same visit. We defined mistriage, or medical error, when nurse-physician dyad reviewers determined that a different ESI level should have been assigned based on the information available at triage. A multidisciplinary team used nominal group technique to build consensus on key drivers and outcome metrics for this new trigger. We randomly selected 267 charts for review utilizing the under-triage trigger. Results: Of the 125,457 patients triaged as level 4 or 5 in 2019 and 2020, 1.1% (n = 1,423) were under-triaged. Of the 267 charts reviewed, 127 were categorized as mistriage, making the under-triage's positive predictive value trigger 48%. Reviews took 2-10 minutes per chart. We identified 10 categories of under-triage. Nine themes emerged, with four specific and measurable action items mapped to process and outcome metrics. Conclusions: We identify a new, feasible ED trigger, under-triage, that identifies medical error with a high positive predictive value. We identify process and outcome metrics and interventions to improve triage for future patients.

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.

Is depression associated with reduced optimistic belief updating?

When asked to evaluate their probability of experiencing a negative life event, healthy individuals update their beliefs more following good news than bad. This is referred to as optimistic belief updating. By contrast, individuals with depression update their beliefs by a similar amount, showing reduced optimism. We conducted the first independent replication of this effect and extended this work to examine whether reduced optimistic belief updating in depression also occurs for positive life events. Replicating previous research, healthy and depression groups differed in belief updating for negative events (ß = 0.71, 95% CI: 0.24, 1.18). Whereas healthy participants updated their beliefs more following good news than bad, individuals experiencing depression lacked this bias. However, our findings for positive events were inconclusive. While we did not find statistical evidence that patterns of belief updating between groups varied by valence (ß = -0.51, 95% CI: -1.16, 0.15), mean update scores suggested that both groups showed largely similar updating for positive life events. Our results add confidence to previous findings that depression is characterized by negative future expectations maintained by reduced updating in response to good news. However, further research is required to understand the specificity of this to negative events, and into refining methods for quantifying belief updating in clinical and non-clinical research.

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).

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.

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.

Effects of go/no-go training on food-related action tendencies, liking and choice.

Inhibitory control training effects on behaviour (e.g. 'healthier' food choices) can be driven by changes in affective evaluations of trained stimuli, and theoretical models indicate that changes in action tendencies may be a complementary mechanism. In this preregistered study, we investigated the effects of food-specific go/no-go training on action tendencies, liking and impulsive choices in healthy participants. In the training task, energy-dense foods were assigned to one of three conditions: 100% inhibition (no-go), 0% inhibition (go) or 50% inhibition (control). Automatic action tendencies and liking were measured pre- and post-training for each condition. We found that training did not lead to changes in approach bias towards trained foods (go and no-go relative to control), but we warrant caution in interpreting this finding as there are important limitations to consider for the employed approach-avoidance task. There was only anecdotal evidence for an effect on food liking, but there was evidence for contingency learning during training, and participants were on average less likely to choose a no-go food compared to a control food after training. We discuss these findings from both a methodological and theoretical standpoint and propose that the mechanisms of action behind training effects be investigated further.

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).

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.

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.

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).

Are affective factors related to individual differences in facial expression recognition?

Evidence that affective factors (e.g. anxiety, depression, affect) are significantly related to individual differences in emotion recognition is mixed. Palermo et al. (Palermo et al. 2018 J. Exp. Psychol. Hum. Percept. Perform. 44, 503-517) reported that individuals who scored lower in anxiety performed significantly better on two measures of facial-expression recognition (emotion-matching and emotion-labelling tasks), but not a third measure (the multimodal emotion recognition test). By contrast, facial-expression recognition was not significantly correlated with measures of depression, positive or negative affect, empathy, or autistic-like traits. Because the range of affective factors considered in this study and its use of multiple expression-recognition tasks mean that it is a relatively comprehensive investigation of the role of affective factors in facial expression recognition, we carried out a direct replication. In common with Palermo et al. (Palermo et al. 2018 J. Exp. Psychol. Hum. Percept. Perform. 44, 503-517), scores on the DASS anxiety subscale negatively predicted performance on the emotion recognition tasks across multiple analyses, although these correlations were only consistently significant for performance on the emotion-labelling task. However, and by contrast with Palermo et al. (Palermo et al. 2018 J. Exp. Psychol. Hum. Percept. Perform. 44, 503-517), other affective factors (e.g. those related to empathy) often also significantly predicted emotion-recognition performance. Collectively, these results support the proposal that affective factors predict individual differences in emotion recognition, but that these correlations are not necessarily specific to measures of general anxiety, such as the DASS anxiety subscale.

Effect of acute citalopram on self-referential emotional processing and social cognition in healthy volunteers.

BACKGROUND: Depression is characterised by negative views of the self. Antidepressant treatment may remediate negative self-schema through increasing processing of positive information about the self. Changes in affective processing during social interactions may increase expression of prosocial behaviours, improving interpersonal communications. AIMS: To examine whether acute administration of citalopram is associated with an increase in positive affective learning biases about the self and prosocial behaviour. METHOD: Healthy volunteers (n = 41) were randomised to either an acute 20 mg dose of citalopram or matched placebo in a between-subjects double-blind design. Participants completed computer-based cognitive tasks designed to measure referential affective processing, social cognition and expression of prosocial behaviours. RESULTS: Participants administered citalopram made more cooperative choices than those administered placebo in a prisoner's dilemma task (ß = 20%, 95% CI: 2%, 37%). Exploratory analyses indicated that participants administered citalopram showed a positive bias when learning social evaluations about a friend (ß = 4.06, 95% CI: 0.88, 7.24), but not about the self or a stranger. Similarly, exploratory analyses found evidence of increased recall of positive words and reduced recall of negative words about others (ß = 2.41, 95% CI: 0.89, 3.93), but not the self, in the citalopram group. CONCLUSIONS: Participants administered citalopram showed greater prosocial behaviours, increased positive recall and increased positive learning of social evaluations towards others. The increase in positive affective bias and prosocial behaviours towards others may, at least partially, be a mechanism of antidepressant effect. However, we found no evidence that citalopram influenced self-referential processing.

The clinical effectiveness of sertraline in primary care and the role of depression severity and duration (PANDA): a pragmatic, double-blind, placebo-controlled randomised trial.

BACKGROUND: Depression is usually managed in primary care, but most antidepressant trials are of patients from secondary care mental health services, with eligibility criteria based on diagnosis and severity of depressive symptoms. Antidepressants are now used in a much wider group of people than in previous regulatory trials. We investigated the clinical effectiveness of sertraline in patients in primary care with depressive symptoms ranging from mild to severe and tested the role of severity and duration in treatment response. METHODS: The PANDA study was a pragmatic, multicentre, double-blind, placebo-controlled randomised trial of patients from 179 primary care surgeries in four UK cities (Bristol, Liverpool, London, and York). We included patients aged 18 to 74 years who had depressive symptoms of any severity or duration in the past 2 years, where there was clinical uncertainty about the benefit of an antidepressant. This strategy was designed to improve the generalisability of our sample to current use of antidepressants within primary care. Patients were randomly assigned (1:1) with a remote computer-generated code to sertraline or placebo, and were stratified by severity, duration, and site with random block length. Patients received one capsule (sertraline 50 mg or placebo orally) daily for one week then two capsules daily for up to 11 weeks, consistent with evidence on optimal dosages for efficacy and acceptability. The primary outcome was depressive symptoms 6 weeks after randomisation, measured by Patient Health Questionnaire, 9-item version (PHQ-9) scores. Secondary outcomes at 2, 6 and 12 weeks were depressive symptoms and remission (PHQ-9 and Beck Depression Inventory-II), generalised anxiety symptoms (Generalised Anxiety Disorder Assessment 7-item version), mental and physical health-related quality of life (12-item Short-Form Health Survey), and self-reported improvement. All analyses compared groups as randomised (intention-to-treat). The study is registered with EudraCT, 2013-003440-22 (protocol number 13/0413; version 6.1) and ISRCTN, ISRCTN84544741, and is closed to new participants. FINDINGS: Between Jan 1, 2015, and Aug 31, 2017, we recruited and randomly assigned 655 patients-326 (50%) to sertraline and 329 (50%) to placebo. Two patients in the sertraline group did not complete a substantial proportion of the baseline assessment and were excluded, leaving 653 patients in total. Due to attrition, primary outcome analyses were of 550 patients (266 in the sertraline group and 284 in the placebo group; 85% follow-up that did not differ by treatment allocation). We found no evidence that sertraline led to a clinically meaningful reduction in depressive symptoms at 6 weeks. The mean 6-week PHQ-9 score was 7·98 (SD 5·63) in the sertraline group and 8·76 (5·86) in the placebo group (adjusted proportional difference 0·95, 95% CI 0·85-1·07; p=0·41). However, for secondary outcomes, we found evidence that sertraline led to reduced anxiety symptoms, better mental (but not physical) health-related quality of life, and self-reported improvements in mental health. We observed weak evidence that depressive symptoms were reduced by sertraline at 12 weeks. We recorded seven adverse events-four for sertraline and three for placebo, and adverse events did not differ by treatment allocation. Three adverse events were classified as serious-two in the sertraline group and one in the placebo group. One serious adverse event in the sertraline group was classified as possibly related to study medication. INTERPRETATION: Sertraline is unlikely to reduce depressive symptoms within 6 weeks in primary care but we observed improvements in anxiety, quality of life, and self-rated mental health, which are likely to be clinically important. Our findings support the prescription of SSRI antidepressants in a wider group of participants than previously thought, including those with mild to moderate symptoms who do not meet diagnostic criteria for depression or generalised anxiety disorder. FUNDING: National Institute for Health Research.

Variation in recognition of happy and sad facial expressions and self-reported depressive symptom severity: A prospective cohort study.

OBJECTIVE: Cognitive theories suggest people with depression interpret self-referential social information negatively. However, it is unclear whether these biases precede or follow depression. We investigated whether facial expression recognition was associated with depressive symptoms cross-sectionally and longitudinally. METHODS: Prospective cohort study of people who had visited UK primary care in the past year reporting depressive symptoms (n = 509). Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9) at four time-points, 2 weeks apart. A computerised task assessed happy and sad facial expression recognition at three time-points (n = 505 at time 1). The unbiased hit rate measured ability to recognise emotions accounting for any general tendency to identify the emotion when it was not present. RESULTS: The sample included the full range of depressive symptom severity, with 45% meeting diagnostic criteria for depression. There was no evidence that happy or sad unbiased hit rates were associated with concurrent or subsequent depressive symptoms. There was weak evidence that, for every additional face incorrectly classified as happy, concurrent PHQ-9 scores reduced by 0.05 of a point (95% CI = -0.10 to 0.002, p = 0.06 after adjustment for confounders). This association was strongest for more ambiguous facial expressions (interaction term p<0.001). LIMITATIONS: This was an observational study with relatively short follow-up (6 weeks) and small changes in depressive symptoms and emotion recognition. Only 7% of invited patients consented to participate. CONCLUSIONS: Reduced misclassifications of ambiguous faces as happy could be a state marker of depression, but was not associated with subsequent depressive symptoms. Future research should focus on the interpretation of ambiguous social information.