Bulimia nervosa (BN), a mental disorder that causes significant impairment, can be treated with psychological, pharmacological, nutrition-based and self-help interventions. We conducted a pre-registered meta-analysis of randomized-controlled trials (RCTs) to assess the efficacy of these interventions in up to 19 different interventions.

Database search terms were combined for BN and RCTs from database inception to March 2017. Abstinence from binge eating episodes, compensatory behaviors, the absence of a BN diagnosis and reduction of symptom severity were considered as primary outcome variables, reduction of self-reported eating pathology and depression served as secondary outcome variables. Retrieved RCTs were meta-analyzed using fixed and random effects models.

RCT (79 trials; 5775 participants) effects post-treatment revealed moderate to large intervention effects for psychotherapy [mostly cognitive-behavioral therapy (CBT)] for primary outcome variables. Slightly reduced effects were obtained for self-help and moderate effects for pharmacotherapy. Similarly, psychotherapy yielded large to very large effects in regard to secondary outcome variables, while moderate to large effects were observed for self-help, Pharmacotherapy and combined therapies. Meta-analyses for the pre to post changes within group confirmed these findings. Additionally, follow-up analyses revealed the sustainability of psychotherapies in terms of large effects in primary outcome criteria, while these effects were moderate for self-help, pharmacotherapy, and combined therapies.

Most psychological and pharmacological interventions revealed to be effective in BN treatment. Taking effect size, sustainability of the intervention, as well as the consistency of findings and available evidence into consideration, CBT can be recommended as the best intervention for the initial treatment of BN.

Peripheral low-grade inflammation in depression is increasingly seen as a therapeutic target. We aimed to establish the prevalence of low-grade inflammation in depression, using different C-reactive protein (CRP) levels, through a systematic literature review and meta-analysis.

We searched the PubMed database from its inception to July 2018, and selected studies that assessed depression using a validated tool/scale, and allowed the calculation of the proportion of patients with low-grade inflammation (CRP >3 mg/L) or elevated CRP (>1 mg/L).

After quality assessment, 37 studies comprising 13 541 depressed patients and 155 728 controls were included. Based on the meta-analysis of 30 studies, the prevalence of low-grade inflammation (CRP >3 mg/L) in depression was 27% (95% CI 21–34%); this prevalence was not associated with sample source (inpatient, outpatient or population-based), antidepressant treatment, participant age, BMI or ethnicity. Based on the meta-analysis of 17 studies of depression and matched healthy controls, the odds ratio for low-grade inflammation in depression was 1.46 (95% CI 1.22–1.75). The prevalence of elevated CRP (>1 mg/L) in depression was 58% (95% CI 47–69%), and the meta-analytic odds ratio for elevated CRP in depression compared with controls was 1.47 (95% CI 1.18–1.82).

About a quarter of patients with depression show evidence of low-grade inflammation, and over half of patients show mildly elevated CRP levels. There are significant differences in the prevalence of low-grade inflammation between patients and matched healthy controls. These findings suggest that inflammation could be relevant to a large number of patients with depression.

Affective attitudes and behaviours manifested within the family environment have been characterised as expressed emotion (EE). High EE environments have been robustly shown to put psychosis patients at a greater risk of relapse compared with low EE exposure. Positive EE dimensions (warmth; positive remarks) have received far less attention than negative EE dimensions such that EE has become synonymous with a negative family atmosphere; the predictive value of positive EE dimensions is largely ignored. A systematic review examining the relationship between positive family EE and outcomes in psychosis is needed.

A systematic search was conducted. Studies reporting bias and study quality were assessed.

A total of 2368 studies were identified. Of these, 27 met eligibility criteria reporting outcomes including relapse, symptomatology, social functioning and life satisfaction. Relapse was the most commonly measured outcome. Stronger evidence emerged for the association between EE warmth and outcomes compared with EE positive remarks, with effects mostly evident in the early phase of psychosis. Evidence for protective effects of warmth on relapse was found up to 9 months follow-up. No effects were evident between positive remarks and relapse. Studies assessing symptom outcomes showed inconsistent findings. Evidence for an association with social functioning was evident, primarily in at risk mental states. Warmth and positive remarks predicted life satisfaction.

The positive aspects of EE require further investigation with longitudinal research designs. Clinical interventions should focus not only on reducing negative aspects of EE but also foster warmth within families in the context of psychosis.

Reappraisal, an adaptive emotion regulation strategy, is associated with frontal engagement. In internalizing psychopathologies (IPs) such as anxiety and depression frontal activity is atypically reduced suggesting impaired regulation capacity. Yet, successful reappraisal is often demonstrated at the behavioral level. A data-driven approach was used to clarify brain and behavioral relationships in IPs.

During functional magnetic resonance imaging, anxious [general anxiety disorder (n = 43), social anxiety disorder (n = 72)] and depressed (n = 47) patients reappraised negative images to reduce negative affect (‘ReappNeg’) and viewed negative images (‘LookNeg’). After each trial, the affective state was reported. A cut-point (i.e. values <0 based on ΔReappNeg-LookNeg) demarcated successful reappraisers. Neural activity for ReappNeg-LookNeg, derived from 37 regions of interest, was submitted to Principal Component Analysis (PCA) to identify unique components of reappraisal-related brain response. PCA factors, symptom severity, and self-reported habitual reappraisal were submitted to discriminant function analysis and linear regression to examine whether these data predicted successful reappraisal (yes/no) and variance in reappraisal ability.

Most patients (63%) were successful reappraisers according to the behavioral criterion (values<0; ΔReappNeg-LookNeg). Discriminant function analysis was not significant for PCA factors, symptoms, or habitual reappraisal. For regression, more activation in a factor with high loadings for frontal regions predicted better reappraisal facility. Results were not significant for other variables.

At the individual level, more activation in a ‘frontal’ factor corresponded with better reappraisal facility. However, neither brain nor behavioral variables classified successful reappraisal (yes/no). Findings suggest individual differences in regions strongly implicated in reappraisal play a role in on-line reappraisal capability.

Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment.

An elastic net and random forest were trained to predict depression symptoms and related disability after an 8-week course of an Internet intervention, Deprexis, involving adults (N = 283) from across the USA. Candidate predictors included psychopathology, demographics, treatment expectancies, treatment usage, and environmental context obtained from population databases. Model performance was evaluated using predictive R2$\lpar R_{{\rm pred}}^2\rpar\comma $ the expected variance explained in a new sample, estimated by 10 repetitions of 10-fold cross-validation.

An ensemble model was created by averaging the predictions of the elastic net and random forest. Model performance was compared with a benchmark linear autoregressive model that predicted each outcome using only its baseline. The ensemble predicted more variance in post-treatment depression (8.0% gain, 95% CI 0.8–15; total $R_{{\rm pred}}^2 \; $= 0.25), disability (5.0% gain, 95% CI −0.3 to 10; total $R_{{\rm pred}}^2 \; $= 0.25), and well-being (11.6% gain, 95% CI 4.9–19; total $R_{{\rm pred}}^2 \; $= 0.29) than the benchmark model. Important predictors included comorbid psychopathology, particularly total psychopathology and dysthymia, low symptom-related disability, treatment credibility, lower access to therapists, and time spent using certain Deprexis modules.

A number of variables predict symptom improvement following an Internet intervention, but each of these variables makes relatively small contributions. Machine learning ensembles may be a promising statistical approach for identifying the cumulative contribution of many weak predictors to psychosocial depression treatment response.

Though meta-analyses of neuropsychological and social cognitive deficits in behavioral variant frontotemporal dementia (bvFTD) have been conducted, no study has comprehensively characterized and compared the neuropsychological, social cognitive, and olfactory profiles in the behavioral and language variants of FTD.

Our search yielded 470 publications meeting inclusion criteria representing 11 782 FTD patients and 19 451 controls. For each domain, we calculated Hedges’ g effect sizes, which represent the mean difference between the patient and control group divided by the pooled standard deviation. The heterogeneity of these effects was assessed with Cochran's Q-statistic using a random-effects model. Meta-regressions were employed to analyze the influence of demographic and disease characteristics.

Though semantic variant primary progressive aphasia patients showed the greatest impairment across all task types, the three groups showed similar cognitive effect sizes once contributions from the language subdomain were excluded from analysis. Contrary to expectation, the magnitude of deficits in executive functioning, social cognition and olfaction were comparable between the three subgroups. Among indices, a metric of executive errors distinguished the behavioral variant of FTD from the language phenotypes.

These data indicate that social cognitive and traditional executive functioning measures may not capture differences between FTD syndromes. These results have important implications for the interpretation of neuropsychological assessments, particularly when applied to the differential diagnosis of FTD. It is hoped that these findings will guide clinical and research assessments and spur new studies focused on improving the measurement of FTD syndromes.

Schizophrenia is associated with significant cognitive impairment. However, the pathophysiological mechanisms underlying cognitive dysfunction in schizophrenia remain unclear. Brain-derived neurotrophic factor (BDNF) and C-reactive protein (CRP) are among the most commonly investigated peripheral markers of cognition in schizophrenia.

A systematic review in PubMed and Scopus databases was performed until 31 January 2019 to assess the relationship between cognitive impairment, CRP and BDNF levels in schizophrenia. A random-effects meta-analysis was conducted.

Current meta-analysis included 21 studies including 2449 patients with schizophrenia-spectrum disorders. Overall, both BDNF [r = 0.12, confidence interval (CI) 0.04–0.19] and CRP (r = −0.13, CI 0.08–0.18) levels were very modestly but significantly related to cognitive functioning in schizophrenia (r = 0.12, CI 0.04–0.19). In meta-analyses of cognitive domains, BDNF levels were significantly associated with verbal memory (r = 0.16, CI 0.09–0.23), working memory (r = 0.14, CI 0.06–0.22), processing speed (r = 0.18, CI 0.10–0.26) and verbal fluency (r = 0.09, CI 0–0.18) performances. Elevated CRP levels were related to all cognitive domains (r = −0.09 to −0.13) except for fluency. Subgroup analyses suggested that the relationship between cognitive and BDNF levels were more pronounced in chronic samples.

Current findings suggest that cognitive impairment in schizophrenia is significantly related to elevated CRP and reduced BDNF levels in schizophrenia, particularly in chronic samples. However, small effect sizes of these correlations suggest that inflammation and decreased BDNF levels do not play a major role in cognitive dysfunction in most patients with schizophrenia. Further studies are needed to investigate the potential intermediating and confounding factors which can influence the level of relationship between inflammation, neurotrophic factors and cognition in schizophrenia.

Although being married with children is associated with a reduced rate of alcohol use disorder (AUD), is this finding independent of a marital effect, different in mothers and fathers and potentially causal in effect.

Using Cox proportional hazards, we examined, in 1 252 237 married individuals, the association between a resident younger and older child and risk for AUD registration in national medical, criminal, and pharmacy registers. Using logistic regression, we analyzed, in 600 219 parents, within-person models comparing risk for AUD prior to first pregnancy v. with young children. We examined whether risk for AUD in 1302 parents after a first spousal AUD registration was reduced by having a young resident child.

Compared with childless married individuals, resident younger children were associated with a reduced risk for AUD in mothers [hazard ratio (HR) 0.36, 95% confidence interval 0.31–0.41] and fathers (HR 0.66, 0.60–0.73). The reduced risk was attenuated but still significant for older children. Within-person models confirmed the protective effect of young children in mothers [odds ratio (OR) 0.49, 0.30–0.80] but yielded inconclusive results in fathers (OR 0.85, 0.58–1.25). After a first spousal registration for AUD, a resident young child was associated with a substantial reduction in risk for mothers and a weaker marginal effect in fathers.

In married individuals, resident children are associated with a reduction in basal risk for AUD which is stronger in mothers than fathers and with younger v. older children. This effect is also evident during high-risk periods. In mothers, our results are consistent with a largely causal effect.

Although bipolar disorder (BD) is a fundamentally cyclical illness, a divided model of BD that emphasizes polarity over cyclicity has dominated modern psychiatric diagnostic systems since their advent in the 1980s. However, there has been a gradual return to conceptualizations of BD which focus on longitudinal course in the research community due to emerging supportive data. Advances in longitudinal statistical methods promise to further progress the field.

The current study employed hidden Markov modeling to uncover empirically derived manic and depressive states from longitudinal data [i.e. Young Mania Rating Scale and Montgomery–Asberg Depression Rating Scale responses across five occasions from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study], estimate participants’ probabilities of transitioning between these states over time (n = 3918), and evaluate whether clinical variables (e.g. rapid cycling and substance dependence) predict participants’ state transitions (n = 3229).

Analyses identified three empirically derived mood states (‘euthymic,’ ‘depressed,’ and ‘mixed’). Relative to the euthymic and depressed states, the mixed state was less commonly experienced, more temporally unstable, and uniquely associated with rapid cycling, substance use, and psychosis. Individuals assigned to the mixed state at baseline were relatively less likely to be diagnosed with BD-II (v. BD-I), more likely to present with a mixed or (hypo)manic episode, and reported experiencing irritable and elevated mood more frequently.

The results from the current study represent an important step in defining, and characterizing the longitudinal course of, empirically derived mood states that can be used to form the foundation of objective, empirical attempts to define meaningful subtypes of affective illness defined by clinical course.

Non-psychotic affective symptoms are important components of psychotic syndromes. They are frequent and are now thought to influence the emergence of paranoia and hallucinations. Evidence supporting this model of psychosis comes from recent cross-fertilising epidemiological and intervention studies. Epidemiological studies identify plausible targets for intervention but must be interpreted cautiously. Nevertheless, causal inference can be strengthened substantially using modern statistical methods.

Directed Acyclic Graphs were used in a dynamic Bayesian network approach to learn the overall dependence structure of chosen variables. DAG-based inference identifies the most likely directional links between multiple variables, thereby locating them in a putative causal cascade. We used initial and 18-month follow-up data from the 2000 British National Psychiatric Morbidity survey (N = 8580 and N = 2406).

We analysed persecutory ideation, hallucinations, a range of affective symptoms and the effects of cannabis and problematic alcohol use. Worry was central to the links between symptoms, with plausible direct effects on insomnia, depressed mood and generalised anxiety, and recent cannabis use. Worry linked the other affective phenomena with paranoia. Hallucinations were connected only to worry and persecutory ideation. General anxiety, worry, sleep problems, and persecutory ideation were strongly self-predicting. Worry and persecutory ideation were connected over the 18-month interval in an apparent feedback loop.

These results have implications for understanding dynamic processes in psychosis and for targeting psychological interventions. The reciprocal influence of worry and paranoia implies that treating either symptom is likely to ameliorate the other.

There is strong evidence that people born in winter and in spring have a small increased risk of schizophrenia. As this ‘season of birth’ effect underpins some of the most influential hypotheses concerning potentially modifiable risk exposures, it is important to exclude other possible explanations for the phenomenon.

Here we sought to determine whether the season of birth effect reflects gene-environment confounding rather than a pathogenic process indexing environmental exposure. We directly measured, in 136 538 participants from the UK Biobank (UKBB), the burdens of common schizophrenia risk alleles and of copy number variants known to increase the risk for the disorder, and tested whether these were correlated with a season of birth.

Neither genetic measure was associated with season or month of birth within the UKBB sample.

As our study was highly powered to detect small effects, we conclude that the season of birth effect in schizophrenia reflects a true pathogenic effect of environmental exposure.