Antidepressants reduce depressive symptoms in patients with coronary heart disease, but they may be associated with increased mortality. This study aimed to examine whether the use of tricyclic antidepressants (TCA) or selective serotonin reuptake inhibitors (SSRI) is associated with mortality in patients with coronary heart disease, and to determine whether this association is mediated by autonomic function.

A total of 956 patients with coronary heart disease were followed for a mean duration of 7.2 years. Autonomic function was assessed as heart rate variability, and plasma and 24-h urinary norepinephrine.

Of 956 patients, 44 (4.6%) used TCA, 89 (9.3%) used SSRI, and 823 (86.1%) did not use antidepressants. At baseline, TCA users exhibited lower heart rate variability and higher norepinephrine levels compared with SSRI users and antidepressant non-users. At the end of the observational period, 52.3% of the TCA users had died compared with 38.2% in the SSRI group and 37.3% in the control group. The adjusted hazard ratio (HR) for TCA use compared with non-use was 1.74 [95% confidence interval (CI) 1.12–2.69, p = 0.01]. Further adjustment for measures of autonomic function reduced the association between TCA use and mortality (HR = 1.27, 95% CI 0.67–2.43, p = 0.47). SSRI use was not associated with mortality (HR = 1.15, 95% CI 0.81–1.64, p = 0.44).

The use of TCA was associated with increased mortality. This association was at least partially mediated by differences in autonomic function. Our findings suggest that TCA should be avoided in patients with coronary heart disease.

The prevalence of serious psychological distress (SPD) was elevated during the COVID-19 pandemic in the USA, but the relationships of SPD during the pandemic with pre-pandemic SPD, pre-pandemic socioeconomic status, and pandemic-related social stressors remain unexamined.

A probability-based sample (N = 1751) of the US population age 20 and over was followed prospectively from February 2019 (T1), with subsequent interviews in May 2020 (T2) and August 2020 (T3). Multinomial logistic regression was used to assess prospective relationships between T1 SPD with experiences of disruption of employment, health care, and childcare at T2. Binary logistic regression was then used to assess relationships of T1 SPD, and socioeconomic status and T2 pandemic-related stressors with T3 SPD.

At T1, SPD was associated with age, race/ethnicity, and household income. SPD at T1 predicted disruption of employment (OR 4.5, 95% CI 1.4–3.8) and health care (OR 3.2, 95% CI 1.4–7.1) at T2. SPD at T1 (OR 10.2, 95% CI 4.5–23.3), low household income at T1 (OR 2.6, 95% CI 1.1–6.4), disruption of employment at T2 (OR 3.2, 95% CI 1.4–7.6), and disruption of healthcare at T2 (OR 3.3, 95% CI 1.5–7.2) were all significantly associated with elevated risk for SPD at T3.

Elevated risk for SPD during the COVID-19 pandemic is related to multiple psychological and social pathways that are likely to interact over the life course. Policies and interventions that target individuals with pre-existing mental health conditions as well as those experiencing persistent unemployment should be high priorities in the mental health response to the pandemic.

The vulnerability hypothesis suggests that impairments after remission of depressive episodes reflect a pre-existing vulnerability, while the scar hypothesis proposes that depression leaves residual impairments that confer risk of subsequent episodes. We prospectively examined vulnerability and scar effects in mental and physical functioning in a representative Dutch population sample.

Three waves were used from the Netherlands Mental Health Survey and Incidence Study-2, a population-based study with a 6-years follow-up. Mental and physical functioning were assessed with the Medical Outcomes Study Short Form (SF-36). Major depressive disorder (MDD) was assessed with the Composite International Diagnostic Interview 3.0. Vulnerability effects were examined by comparing healthy controls (n = 2826) with individuals who developed a first-onset depressive episode during first follow-up but did not have a lifetime diagnosis of MDD at baseline (n = 181). Scarring effects were examined by comparing pre- and post-morbid functioning in individuals who developed a depressive episode after baseline that was remitted at the third wave (n = 108).

Both mental (B = −5.4, s.e. = 0.9, p < 0.001) and physical functioning (B = −8.2, s.e. = 1.1, p < 0.001) at baseline were lower in individuals who developed a first depressive episode after baseline compared with healthy controls. This effect was most pronounced in people who developed a severe episode. No firm evidence of scarring in mental or physical functioning was found. In unadjusted analyses, physical functioning was still lowered post-morbidly (B = −5.1, s.e. = 2.1, p = 0.014), but this effect disappeared in adjusted analyses.

Functional impairments after remission of depression seem to reflect a pre-existing vulnerability rather than a scar.

Although the DSM-5 was adopted in 2013, the validity of the new substance use disorder (SUD) diagnosis and craving criterion has not been investigated systematically across substances.

Adults (N = 588) who engaged in binge drinking or illicit drug use and endorsed at least one DSM-5 SUD criterion were included. DSM-5 SUD criteria were assessed for alcohol, tobacco, cannabis, cocaine, heroin, and opioids. Craving was considered positive if “wanted to use so badly that could not think of anything else” (severe craving) or “felt a very strong desire or urge to use” (moderate craving) was endorsed. Baseline information on substance-related variables and psychopathology was collected, and electronic daily assessment queried substance use for the following 90 days. For each substance, logistic regression estimated the association between craving and validators, i.e. variables expected to be related to craving/SUD, and whether association with the validators differed for DSM-5 SUD diagnosed with craving as a criterion v. without.

Across substances, craving was associated with most baseline validators (p values<0.05); neither moderate nor severe craving consistently showed greater associations. Baseline craving predicted subsequent use [odds ratios (OR): 4.2 (alcohol) – 234.3 (heroin); p's ⩽ 0.0001], with stronger associations for moderate than severe craving (p's < 0.05). Baseline DSM-5 SUD showed stronger associations with subsequent use when diagnosed with craving than without (p's < 0.05).

The DSM-5 craving criterion as operationalized in this study is valid. Including craving improves the validity of DSM-5 SUD diagnoses, and clinical relevance, since craving may cause impaired control over use and development and maintenance of SUD.

Worrying has been suggested to prevent emotional and elaborative processing of fears. In cognitive-behavioral therapy (CBT), generalized anxiety disorder (GAD) patients are exposed to their fears during the method of directed threat imagery by inducing emotional reactivity. However, studies investigating neural correlates of directed threat imagery and emotional reactivity in GAD patients are lacking. The present functional magnetic resonance imaging (fMRI) study aimed at delineating neural correlates of directed threat imagery in GAD patients.

Nineteen GAD patients and 19 healthy controls (HC) were exposed to narrative scripts of either disorder-related or neutral content and were encouraged to imagine it as vividly as possible.

Rating results showed that GAD patients experienced disorder-related scripts as more anxiety inducing and arousing than HC. These results were also reflected in fMRI data: Disorder-related v. neutral scripts elicited elevated activity in the amygdala, dorsomedial prefrontal cortex, ventrolateral prefrontal cortex and the thalamus as well as reduced activity in the ventromedial prefrontal cortex/subgenual anterior cingulate cortex in GAD patients relative to HC.

The present study presents the first behavioral and neural evidence for emotional reactivity during directed threat imagery in GAD. The brain activity pattern suggests an involvement of a fear processing network as a neural correlate of initial exposure during directed imagery in CBT in GAD.

Social anxiety disorder (SAD) is characterized by anxiety regarding social situations, avoidance of external social stimuli, and negative self-beliefs. Virtual reality self-training (VRS) at home may be a good interim modality for reducing social fears before formal treatment. This study aimed to find neurobiological evidence for the therapeutic effect of VRS.

Fifty-two patients with SAD were randomly assigned to a VRS or waiting list (WL) group. The VRS group received an eight-session VRS program for 2 weeks, whereas the WL group received no intervention. Clinical assessments and functional magnetic resonance imaging scanning with the distress and speech evaluation tasks were repeatedly performed at baseline and after 3 weeks.

The post-VRS assessment showed significantly decreased anxiety and avoidance scores, distress index, and negative evaluation index for ‘self’, but no change in the negative evaluation index for ‘other’. Patients showed significant responses to the distress task in various regions, including both sides of the prefrontal regions, occipital regions, insula, and thalamus, and to the speech evaluation task in the bilateral anterior cingulate cortex. Among these, significant neuronal changes after VRS were observed only in the right lingual gyrus and left thalamus.

VRS-induced improvements in the ability to pay attention to social stimuli without avoidance and even positively modulate emotional cues are based on functional changes in the visual cortices and thalamus. Based on these short-term neuronal changes, VRS can be a first intervention option for individuals with SAD who avoid society or are reluctant to receive formal treatment.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors.

Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change.

Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status.

We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

Freeman et al. (2020a, Psychological Medicine, 21, 1–13) argue that there is widespread support for coronavirus conspiracy theories in England. We hypothesise that their estimates of prevalence are inflated due to a flawed research design. When asking respondents to their survey to agree or disagree with pro-conspiracy statements, they used a biased set of response options: four agree options and only one disagree option (and no ‘don't know’ option). We also hypothesise that due to these flawed measures, the Freeman et al. approach under-estimates the strength of the correlation between conspiracy beliefs and compliance. Finally, we hypothesise that, due to reliance on bivariate correlations, Freeman et al. over-estimate the causal connection between conspiracy beliefs and compliance.

In a pre-registered study, we conduct an experiment embedded in a survey of a representative sample of 2057 adults in England (fieldwork: 16−19 July 2020).

Measured using our advocated ‘best practice’ approach (balanced response options, with a don't know option), prevalence of support for coronavirus conspiracies is only around five-eighths (62.3%) of that indicated by the Freeman et al. approach. We report mixed results on our correlation and causation hypotheses.

To avoid over-estimating prevalence of support for coronavirus conspiracies, we advocate using a balanced rather than imbalanced set of response options, and including a don't know option.

Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Therefore, individualized predictions of worry propensity could be highly relevant in clinical practice, with respect to the assessment of worry symptom severity at the individual level.

We applied a multivariate machine learning approach to predict dispositional worry based on microstructural integrity of white matter (WM) tracts.

We demonstrated that the machine learning model was able to decode individual dispositional worry scores from microstructural properties in widely distributed WM tracts (mean absolute error = 10.46, p < 0.001; root mean squared error = 12.82, p < 0.001; prediction R2 = 0.17, p < 0.001). WM tracts that contributed to worry prediction included the posterior limb of internal capsule, anterior corona radiate, and cerebral peduncle, as well as the corticolimbic pathways (e.g. uncinate fasciculus, cingulum, and fornix) already known to be critical for emotion processing and regulation.

The current work thus elucidates potential neuromarkers for clinical assessment of worry symptoms across a wide range of psychiatric disorders. In addition, the identification of widely distributed pathways underlying worry propensity serves to better improve the understanding of the neurobiological mechanisms associated with worry.

Disorders involving compulsivity, fear, and anxiety are linked to beliefs that the world is less predictable. We lack a mechanistic explanation for how such beliefs arise. Here, we test a hypothesis that in people with compulsivity, fear, and anxiety, learning a probabilistic mapping between actions and environmental states is compromised.

In Study 1 (n = 174), we designed a novel online task that isolated state transition learning from other facets of learning and planning. To determine whether this impairment is due to learning that is too fast or too slow, we estimated state transition learning rates by fitting computational models to two independent datasets, which tested learning in environments in which state transitions were either stable (Study 2: n = 1413) or changing (Study 3: n = 192).

Study 1 established that individuals with higher levels of compulsivity are more likely to demonstrate an impairment in state transition learning. Preliminary evidence here linked this impairment to a common factor comprising compulsivity and fear. Studies 2 and 3 showed that compulsivity is associated with learning that is too fast when it should be slow (i.e. when state transition are stable) and too slow when it should be fast (i.e. when state transitions change).

Together, these findings indicate that compulsivity is associated with a dysregulation of state transition learning, wherein the rate of learning is not well adapted to the task environment. Thus, dysregulated state transition learning might provide a key target for therapeutic intervention in compulsivity.