Evidence on neonatal withdrawal syndrome following antidepressant intrauterine exposure is limited, particularly for antidepressants other than selective serotonin reuptake inhibitor (SSRIs).

In our case/non-case pharmacovigilance study, based on VigiBase®, the WHO database of suspected adverse drug reactions, we estimated reporting odds ratio (ROR) and the Bayesian information component (IC) with 95% confidence/credibility intervals (CI) as measures of disproportionate reporting of antidepressant-related neonatal withdrawal syndrome. Antidepressants were first compared to all other medications, then to methadone, and finally within each class of antidepressants: SSRIs, tricyclics (TCA) and other antidepressants. Antidepressants were ranked in terms of clinical priority, based on semiquantitative score ratings. Serious v. non-serious reports were compared.

A total of 406 reports of neonatal withdrawal syndrome in 379 neonates related to 15 antidepressants were included. Disproportionate reporting was detected for antidepressants as a group as compared to all other drugs (ROR: 6.18, 95% CI 5.45–7.01, IC: 2.07, 95% CI 1.92–2.21). Signals were found for TCAs (10.55, 95% CI 8.02–13.88), followed by other antidepressants (ROR: 5.90, 95% CI 4.74–7.36) and SSRIs (ROR: 4.68, 95% CI 4.04–5.42). Significant disproportionality emerged for all individual antidepressants except for bupropion, whereas no disproportionality for any antidepressant was detected v. methadone. Eleven antidepressants had a moderate clinical priority score and four had a weak one. Most frequent symptoms included respiratory symptoms (n = 106), irritability/agitation (n = 75), tremor (n = 52) and feeding problems (n = 40).

Most antidepressants are associated with moderate signals of disproportionate reporting for neonatal withdrawal syndrome, which should be considered when prescribing an antidepressant during pregnancy, irrespective of class.

Psychosocial stressors characterized by social threat, such as interpersonal loss and social rejection, are associated with depression in adolescents. Few studies, however, have examined whether social threat affects fronto-cingulate-limbic systems implicated in adolescent depression.

We assessed lifetime stressor severity across several domains using the Stress and Adversity Inventory (STRAIN) in 57 depressed adolescents (16.15 ± 1.32 years, 34 females), and examined whether the severity of social threat and non-social threat stressors was associated with gray matter volumes (GMVs) in the anterior cingulate cortex (ACC), amygdala, hippocampus, and nucleus accumbens (NAcc). We also examined how lifetime social threat severity and GMVs in these regions related to depressive symptoms at baseline and over 9 months.

General stressor severity was related to greater depression severity at baseline and over 9 months. Moreover, greater severity of social threat (but not non-social threat) stressors was associated with smaller bilateral amygdala and NAcc GMVs, and smaller bilateral surface areas of caudal and rostral ACC (all pFDR ⩽ 0.048). However, neither social threat nor non-social threat stressor severity was related to hippocampal GMVs (all pFDR ⩾ 0.318). All fronto-cingulate-limbic structures that were associated with the severity of social threat were negatively associated with greater depression severity over 9 months (all pFDR ⩽ 0.014). Post-hoc analyses suggested that gray matter morphometry of bilateral amygdala, NAcc, and rostral and caudal ACC mediated the association between social threat and depression severity in adolescents over 9 months (all pFDR < 0.048).

Social threat specifically affects fronto-cingulate-limbic pathways that contribute to the maintenance of depression in adolescents.

Sexual minority men (SMM) experience higher suicidal ideation and suicide attempts than the general population. We examined the associations of adverse childhood experiences (ACES) and protective and compensatory childhood experiences (PACES) with suicidal ideation and suicide attempts in adulthood via thwarted belongingness and perceived burdensomeness among SMM.

Data are from the UNITE study, a national longitudinal cohort study of HIV-negative SMM from the 50 U.S. states and Puerto Rico. Between 2017 and 2019, participants (N = 6303) completed web-based assessments at baseline and 12-month follow-up. ACES and PACES occurring before the age of 18, and current symptoms of thwarted belongingness and perceived burdensomeness were assessed at baseline. Past-week suicidal ideation and past-year suicide attempt were assessed at follow-up.

424 (6.7%) participants reported past-week suicidal ideation and 123 (2.0%) reported a past-year suicide attempt. The results of our multivariate model suggest that each additional adverse childhood experience was prospectively associated with 14% higher odds of past-week suicidal ideation (AOR = 1.14, 95% CI 1.09–1.19) and 19% higher odds of past-year suicide attempt (AOR = 1.19, 95% CI 1.11–1.29). Each additional protective childhood experience was prospectively associated with 15% lower odds of past-week suicidal ideation (AOR = 0.85, 95% CI 0.81–0.90) and 11% lower odds of past-year suicide attempt (AOR = 0.89, 95% CI 0.82–0.98). Perceived burdensomeness partially mediated these prospective associations.

To reduce suicide, screening and treating perceived burdensomeness among SMM with high ACES may be warranted. PACES may decrease perceived burdensomeness and associated suicide risk.

Depression is an important, potentially modifiable dementia risk factor. However, it is not known whether effective treatment of depression through psychological therapies is associated with reduced dementia incidence. The aim of this study was to investigate associations between reduction in depressive symptoms following psychological therapy and the subsequent incidence of dementia.

National psychological therapy data were linked with hospital records of dementia diagnosis for 119808 people aged 65+. Participants received a course of psychological therapy treatment in Improving Access to Psychological Therapies (IAPT) services between 2012 and 2019. Cox proportional hazards models were run to test associations between improvement in depression following psychological therapy and incidence of dementia diagnosis up to eight years later.

Improvements in depression following treatment were associated with reduced rates of dementia diagnosis up to 8 years later (HR = 0.88, 95% CI 0.83–0.94), after adjustment for key covariates. Strongest effects were observed for vascular dementia (HR = 0.86, 95% CI 0.77–0.97) compared with Alzheimer's disease (HR = 0.91, 95% CI 0.83–1.00).

Reliable improvement in depression across psychological therapy was associated with reduced incidence of future dementia. Results are consistent with at least two possibilities. Firstly, psychological interventions to improve symptoms of depression may have the potential to contribute to dementia risk reduction efforts. Secondly, psychological therapies may be less effective in people with underlying dementia pathology or they may be more likely to drop out of therapy (reverse causality). Tackling the under-representation of older people in psychological therapies and optimizing therapy outcomes is an important goal for future research.

While suicide rates have recently declined for White individuals, rates among Black and Hispanic individuals have increased. Yet, little is known about racial/ethnic differences in precursors to suicide, including suicidal ideation (SI) and suicide attempts (SA).

Data from 2009–2020 National Survey of Drug Use and Health (NSDUH) consisted of non-institutionalized US civilians aged ⩾18 (n = 426 008). We compared proportions of White, Black, and Hispanics among adults reporting no past-year suicidal thoughts/behavior, SI, and SA. Multivariable-adjusted analyses were used to evaluate the independence of observed racial/ethnic differences in past-year SI, SA, and mental health service use.

In the entire sample, 20 791 (4.9%) reported past-year SI only and 3661 (0.9%) reported a SA. Compared to White individuals, Black and Hispanic individuals were significantly less likely to report past-year SI [OR 0.73 (95% CI 0.69–0.77); OR 0.75 (95% CI 0.71–0.79), respectively], but more likely to report a past-year SA [OR 1.45 (95% CI 1.28–1.64); OR 1.19 (95% CI 1.04–1.37), respectively] even after multivariable adjustment. Black and Hispanic individuals were significantly less likely to use mental health services, but the lack of significant interactions between race/ethnicity and SI/SA in association with service use suggests differences in service use do not account for differences in SI or SA.

Black and Hispanic individuals are significantly less likely than White individuals to report SI but more likely to report SAs, suggesting differences in suicidal behavior across race/ethnicity that may be impacted by socio-culturally acceptable expressions of distress and structural racism in the healthcare system.

Empirical evidence suggests that people use cannabis to ameliorate anxiety and depressive symptoms, yet cannabis also acutely worsens psychosis and affective symptoms. However, the temporal relationship between cannabis use, anxiety and depressive symptoms and psychotic experiences (PE) in longitudinal studies is unclear. This may be informed by examination of mutually mediating roles of cannabis, anxiety and depressive symptoms in the emergence of PE.

Data were derived from the second longitudinal Netherlands Mental Health Survey and Incidence Study. Mediation analysis was performed to examine the relationship between cannabis use, anxiety/depressive symptoms and PE, using KHB logit in STATA while adjusting for age, sex and education status.

Cannabis use was found to mediate the relationship between preceding anxiety, depressive symptoms and later PE incidence, but the indirect contribution of cannabis use was small (for anxiety: % of total effect attributable to cannabis use = 1.00%; for depression: % of total effect attributable to cannabis use = 1.4%). Interestingly, anxiety and depressive symptoms were found to mediate the relationship between preceding cannabis use and later PE incidence to a greater degree (% of total effect attributable to anxiety = 17%; % of total effect attributable to depression = 37%).

This first longitudinal cohort study examining the mediational relationship between cannabis use, anxiety/depressive symptoms and PE, shows that there is a bidirectional relationship between cannabis use, anxiety/depressive symptoms and PE. However, the contribution of anxiety/depressive symptoms as a mediator was greater than that of cannabis.

The association between anxious mood and aberrant fear learning mechanisms has not been fully elucidated. Studying how fear conditioning and extinction constructs relate to anxiety symptoms and reactivity to stressful and benign moments in everyday life provides a powerful addition to experimental paradigms.

Fifty-one young adults completed laboratory-based differential conditioning and extinction tasks with (CS + ) and without (CS-) an aversive unconditional stimulus (US). Electrodermal skin conductance responses were measured during each phase, followed by ecological momentary assessment (EMA) tapping anxiety and stressors six times daily for seven days (2, 142 moments).

Conditioned electrodermal reactivity to the CS + and overgeneralisation to the CS- were associated with greater change in anxiety (measured via EMA), across non-stressful situations, remaining the same across stressful situations. Likewise, during extinction when the CS + is now safe, more electrodermal reactivity to the CS + was associated with more anxiety change across non-stressful situations and remained the same across stressful situations. Also, during extinction when threat is absent, more electrodermal reactivity at the late stage of the CS- was associated with less momentary anxiety change in response to stressful situations; more electrodermal activity at the late stage of the CS + was associated with more anxiety change across non-stressful situations and remained the same across stressful situations.

Sampling ‘in vivo’ emotion and stress experiences, study findings revealed links between conditioned electrodermal reactivity and overgeneralisation to safe stimuli and heightened anxious reactivity during non-stressful (i.e. safe) moments in daily life, coupled with less change in response to actual stressors.

Insomnia symptoms are common during the postpartum period, yet interventions remain scarce. This trial aimed to simultaneously examine the efficacy of cognitive behavioural therapy (CBT) and light dark therapy (LDT), targeting different mechanisms, against treatment-as-usual (TAU), in reducing maternal postpartum insomnia symptoms.

This three-arm randomised controlled trial recruited from the general community in Australia. Nulliparous females 4–12 months postpartum with self-reported insomnia symptoms [Insomnia Severity Index (ISI) scores >7] were included; severe medical/psychiatric conditions were excluded. Participants were randomised 1:1:1 to CBT, LDT, or TAU stratified by ISI (< or ⩾14) and infant age (< or ⩾8 months). Participants and principal investigators were unblinded. Six-week interventions were delivered via digital materials and telephone. The primary outcome was insomnia symptoms (ISI), assessed pre-, midpoint-, post- (primary endpoint), and one-month post-intervention. Analyses were intention-to-treat using latent growth models.

114 participants (CBT = 39, LDT = 36, TAU = 39; Mage = 32.20 ± 4.62 years) were randomised. There were significantly greater reductions in ISI scores in CBT and LDT (effect sizes −2.01 and −1.52 respectively, p < 0.001) from baseline to post-intervention compared to TAU; improvements were maintained at follow-up. Similar effects were observed for self-reported sleep disturbance. There were greater reductions in fatigue in CBT (effect size = 0.85, p < 0.001) but not LDT (p = 0.11) compared to TAU. Changes in sleepiness, depression, and anxiety were non-significant compared to TAU (all p > 0.08). Four participants (11%) in the LDT group reported headaches, dizziness, or nausea; no others reported adverse events.

Therapist-assisted CBT and LDT were feasible during the first postpartum year; data at post-intervention and 1-month follow-up support their safety and efficacy in reducing postpartum insomnia symptoms.

Altered white matter brain connectivity has been linked to depression. The aim of this study was to investigate the association of markers of white matter connectivity with prevalence, incidence and course of depressive symptoms.

Markers of white matter connectivity (node degree, clustering coefficient, local efficiency, characteristic path length, and global efficiency) were assessed at baseline by 3 T MRI in the population-based Maastricht Study (n = 4866; mean ± standard deviation age 59.6 ± 8.5 years, 49.0% women; 17 406 person-years of follow-up). Depressive symptoms (9-item Patient Health Questionnaire; PHQ-9) were assessed at baseline and annually over seven years of follow-up. Major depressive disorder (MDD) was assessed with the Mini-International Neuropsychiatric Interview at baseline only. We used negative binominal, logistic and Cox regression analyses, and adjusted for demographic, cardiovascular, and lifestyle risk factors.

A lower global average node degree at baseline was associated with the prevalence and persistence of clinically relevant depressive symptoms [PHQ-9 ⩾ 10; OR (95% confidence interval) per standard deviation = 1.21 (1.05–1.39) and OR = 1.21 (1.02–1.44), respectively], after full adjustment. On the contrary, no associations were found of global average node degree with the MDD at baseline [OR 1.12 (0.94–1.32) nor incidence or remission of clinically relevant depressive symptoms [HR = 1.05 (0.95–1.17) and OR 1.08 (0.83–1.41), respectively]. Other connectivity measures of white matter organization were not associated with depression.

Our findings suggest that fewer white matter connections may contribute to prevalent depressive symptoms and its persistence but not to incident depression. Future studies are needed to replicate our findings.

People with severe mental illness (SMI) have more physical health conditions than the general population, resulting in higher rates of hospitalisations and mortality. In this study, we aimed to determine the rate of emergency and planned physical health hospitalisations in those with SMI, compared to matched comparators, and to investigate how these rates differ by SMI diagnosis.

We used Clinical Practice Research DataLink Gold and Aurum databases to identify 20,668 patients in England diagnosed with SMI between January 2000 and March 2016, with linked hospital records in Hospital Episode Statistics. Patients were matched with up to four patients without SMI. Primary outcomes were emergency and planned physical health admissions. Avoidable (ambulatory care sensitive) admissions and emergency admissions for accidents, injuries and substance misuse were secondary outcomes. We performed negative binomial regression, adjusted for clinical and demographic variables, stratified by SMI diagnosis.

Emergency physical health (aIRR:2.33; 95% CI 2.22–2.46) and avoidable (aIRR:2.88; 95% CI 2.60–3.19) admissions were higher in patients with SMI than comparators. Emergency admission rates did not differ by SMI diagnosis. Planned physical health admissions were lower in schizophrenia (aIRR:0.80; 95% CI 0.72–0.90) and higher in bipolar disorder (aIRR:1.33; 95% CI 1.24–1.43). Accident, injury and substance misuse emergency admissions were particularly high in the year after SMI diagnosis (aIRR: 6.18; 95% CI 5.46–6.98).

We found twice the incidence of emergency physical health admissions in patients with SMI compared to those without SMI. Avoidable admissions were particularly elevated, suggesting interventions in community settings could reduce hospitalisations. Importantly, we found underutilisation of planned inpatient care in patients with schizophrenia. Interventions are required to ensure appropriate healthcare use, and optimal diagnosis and treatment of physical health conditions in people with SMI, to reduce the mortality gap due to physical illness.

The benefits of peer support interventions (PSIs) for individuals with mental illness are not well known. The aim of this systematic review and meta-analysis was to assess the effectiveness of PSIs for individuals with mental illness for clinical, personal, and functional recovery outcomes.

Searches were conducted in PubMed, Embase, and PsycINFO (December 18, 2020). Included were randomized controlled trials (RCTs) comparing peer-delivered PSIs to control conditions. The quality of records was assessed using the Cochrane Collaboration Risk of Bias tool. Data were pooled for each outcome, using random-effects models.

After screening 3455 records, 30 RCTs were included in the systematic review and 28 were meta-analyzed (4152 individuals). Compared to control conditions, peer support was associated with small but significant post-test effect sizes for clinical recovery, g = 0.19, 95% CI (0.11–0.27), I2 = 10%, 95% CI (0–44), and personal recovery, g = 0.15, 95% CI (0.04–0.27), I2 = 43%, 95% CI (1–67), but not for functional recovery, g = 0.08, 95% CI (−0.02 to 0.18), I2 = 36%, 95% CI (0–61). Our findings should be considered with caution due to the modest quality of the included studies.

PSIs may be effective for the clinical and personal recovery of mental illness. Effects are modest, though consistent, suggesting potential efficacy for PSI across a wide range of mental disorders and intervention types.

The term ‘pandemic paranoia’ has been coined to refer to heightened levels of mistrust and suspicion towards other people specifically due to the COVID-19 pandemic. In this study, we examine the international prevalence of pandemic paranoia in the general population and its associated sociodemographic profile.

A representative international sample of general population adults (N = 2510) from five sites (USA N = 535, Germany N = 516, UK N = 512, Australia N = 502 and Hong Kong N = 445) were recruited using stratified quota sampling (for age, sex, educational attainment) and completed the Pandemic Paranoia Scale (PPS).

The overall prevalence rate of pandemic paranoia was 19%, and was highest in Australia and lowest in Germany. On the subscales of the PPS, prevalence was 11% for persecutory threat, 29% for paranoid conspiracy and 37% for interpersonal mistrust. Site and general paranoia significantly predicted pandemic paranoia. Sociodemographic variables (lower age, higher population size and income, being male, employed and no migrant status) explained additional variance and significantly improved prediction of pandemic paranoia.

Pandemic paranoia was relatively common in a representative sample of the general population across five international sites. Sociodemographic variables explained a small but significant amount of the variance in pandemic paranoia.

Major depressive disorder (MDD) has been associated with alterations in brain white matter (WM) microstructure. However, diffusion tensor imaging studies in biological relatives have presented contradicting results on WM alterations and their potential as biomarkers for vulnerability or resilience. To shed more light on associations between WM microstructure and resilience to familial risk, analyses including both healthy and depressed relatives of MDD patients are needed.

In a 2 (MDD v. healthy controls, HC) × 2 (familial risk yes v. no) design, we investigated fractional anisotropy (FA) via tract-based spatial statistics in a large well-characterised adult sample (N = 528), with additional controls for childhood maltreatment, a potentially confounding proxy for environmental risk.

Analyses revealed a significant main effect of diagnosis on FA in the forceps minor and the left superior longitudinal fasciculus (ptfce−FWE = 0.009). Furthermore, a significant interaction of diagnosis with familial risk emerged (ptfce−FWE = 0.036) Post-hoc pairwise comparisons showed significantly higher FA, mainly in the forceps minor and right inferior fronto-occipital fasciculus, in HC with as compared to HC without familial risk (ptfce−FWE < 0.001), whereas familial risk played no role in MDD patients (ptfce−FWE = 0.797). Adding childhood maltreatment as a covariate, the interaction effect remained stable.

We found widespread increased FA in HC with familial risk for MDD as compared to a HC low-risk sample. The significant effect of risk on FA was present only in HC, but not in the MDD sample. These alterations might reflect compensatory neural mechanisms in healthy adults at risk for MDD potentially associated with resilience.

Ambulatory monitoring is gaining popularity in mental and somatic health care to capture an individual's wellbeing or treatment course in daily-life. Experience sampling method collects subjective time-series data of patients' experiences, behavior, and context. At the same time, digital devices allow for less intrusive collection of more objective time-series data with higher sampling frequencies and for prolonged sampling periods. We refer to these data as parallel data. Combining these two data types holds the promise to revolutionize health care. However, existing ambulatory monitoring guidelines are too specific to each data type, and lack overall directions on how to effectively combine them.

Literature and expert opinions were integrated to formulate relevant guiding principles.

Experience sampling and parallel data must be approached as one holistic time series right from the start, at the study design stage. The fluctuation pattern and volatility of the different variables of interest must be well understood to ensure that these data are compatible. Data have to be collected and operationalized in a manner that the minimal common denominator is able to answer the research question with regard to temporal and disease severity resolution. Furthermore, recommendations are provided for device selection, data management, and analysis. Open science practices are also highlighted throughout. Finally, we provide a practical checklist with the delineated considerations and an open-source example demonstrating how to apply it.

The provided considerations aim to structure and support researchers as they undertake the new challenges presented by this exciting multidisciplinary research field.

Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers.

In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively.

A combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction.

A combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.

Despite a well-established link between childhood traumatic brain injury (TBI) and elevated secondary attention-deficit/hyperactivity disorder (s-ADHD) symptomology, the neurostructural correlates of these symptoms are largely unknown. Based on the influential ‘triple-network model’ of ADHD, this prospective longitudinal investigation aimed to (i) assess the effect of childhood TBI on brain morphometry of higher-order cognitive networks proposed to play a key role in ADHD pathophysiology, including the default-mode network (DMN), salience network (SN) and central executive network (CEN); and (ii) assess the independent prognostic value of DMN, SN and CEN morphometry in predicting s-ADHD symptom severity after childhood TBI.

The study sample comprised 155 participants, including 112 children with medically confirmed mild-severe TBI ascertained from consecutive hospital admissions, and 43 typically developing (TD) children matched for age, sex and socio-economic status. High-resolution structural brain magnetic resonance imaging (MRI) sequences were acquired sub-acutely in a subset of 103 children with TBI and 34 TD children. Parents completed well-validated measures of ADHD symptom severity at 12-months post injury.

Relative to TD children and those with milder levels of TBI severity (mild, complicated mild, moderate), children with severe TBI showed altered brain morphometry within large-scale, higher-order cognitive networks, including significantly diminished grey matter volumes within the DMN, SN and CEN. When compared with the TD group, the TBI group showed significantly higher ADHD symptomatology and higher rates of clinically elevated symptoms. In multivariable models adjusted for other well-established risk factors, altered DMN morphometry independently predicted higher s-ADHD symptomatology at 12-months post-injury, whilst SN and CEN morphometry were not significant independent predictors.

Our prospective study findings suggest that neurostructural alterations within higher-order cognitive circuitry may represent a prospective risk factor for s-ADHD symptomatology at 12-months post-injury in children with TBI. High-resolution structural brain MRI has potential to provide early prognostic biomarkers that may help early identification of high-risk children with TBI who are likely to benefit from early surveillance and preventive measures to optimise long-term neuropsychiatric outcomes.