Schematic overview of the Cued Emotional Conflict Task (CECT).

<p>First, a cue is presented in the center of the screen (“actual” or “opposite”), followed by a face with an emotional expression (happy or sad). The face shown in the illustration is not from the KDEF database. The individual of the photograph has given written informed consent, as outlined in the PLOS consent form, to publication of his photograph.</p

Mean RT for opposite trials (opposite/sad and opposite/happy) following tDCS and sham stimulation.

<p>Mean RT for opposite trials (opposite/sad and opposite/happy) following tDCS and sham stimulation.</p

Target locked grandmean waveforms at electrode FCz for the opposite trials(opposite/sad and opposite/happy) following tDCS and sham stimulation.

<p>Target locked grandmean waveforms at electrode FCz for the opposite trials(opposite/sad and opposite/happy) following tDCS and sham stimulation.</p

Trichotillomania: Psychopathological correlates and associations with health-related quality of life in a large sample

BACKGROUND.: Relatively few studies have assessed the prevalence, correlates, and independent impact on quality of life (QoL) of trichotillomania (TTM) in large samples. METHODS.: Consecutive participants (N = 7639) were recruited from a cross-sectional web-based study. Sociodemographic data were collected and several validated self-reported mental health measures were completed (Minnesota Impulsive Disorders Interview, Hypomania checklist, Fagerström Test for Nicotine Dependence, Alcohol Use Disorders Identification Test, Early Trauma Inventory Self Report-Short Form, and the Symptom Checklist-90-Revised Inventory). Health-related QoL was assessed with the World Health Organization QoL abbreviated scale (WHOQOL-Bref). Multivariable models adjusted associations to potential confounders. RESULTS.: The sample was predominantly composed of young females (71.3%; mean age: 27.2 ± 7.9 years). The prevalence of probable TTM was 1.4% (95% confidence intervals [CI]: 1.2-1.7), and was more common among females. Participants with probable TTM had a greater likelihood of having co-occurring probable depression (adjusted odds ratio [ORadj] = 1.744; 95% CI: 1.187-2.560), tobacco (ORadj = 2.250; 95% CI: 1.191-4.250), and alcohol (ORadj = 1.751; 95% CI: 1.169-2.621) use disorders. Probable TTM was also independently associated with suicidal ideation (ORadj = 1.917; 95% CI: 1.224-3.003) and exposure to childhood sexual abuse (ORadj = 1.221; 95% CI: 1.098-1.358). In addition, a positive screen for TTM had more impaired physical and mental QoL. CONCLUSIONS.: TTM was associated with a positive screen for several psychiatric comorbidities as well as impaired physical and psychological QoL. Efforts towards the recognition and treatment of TTM across psycho-dermatology services are warranted

Additional file 1 of Effectiveness and acceptability of noninvasive brain and nerve stimulation techniques for migraine prophylaxis: a network meta-analysis of randomized controlled trials

Additional file 1

Additional file 2 of Effectiveness and acceptability of noninvasive brain and nerve stimulation techniques for migraine prophylaxis: a network meta-analysis of randomized controlled trials

Additional file 2

Additional file 1 of The beneficial effect on cognition of noninvasive brain stimulation intervention in patients with dementia: a network meta-analysis of randomized controlled trials

Additional file 1: eTable 1. PRISMA 2020 checklist of the current network meta-analysis. eTable 2. Keyword used in each database and search results. eTable 3. Excluded studies and reason. eTable 4. Characteristics of the included studies. eTable 5. A League table of the changes of quality of life. B: League table of the rate of any adverse event. C: League table of the rate of local discomfort. D:League table of the drop-out rate. eTable 6. A SUCRA of the changes of cognition function-overall. B: SUCRA of the changes of cognition function: measured with MMSE. C: SUCRA of the changes of cognition function: measured with ADAS-Cog. D: SUCRA of the changes of quality of life. E: SUCRA of the rate of any adverse event. F: SUCRA of the rate of local discomfort. G: SUCRA of the drop-out rate. eTable 7. Inconsistency of different intervention. eTable 8. Estimated between-studies standard deviation of different outcome. eTable 9. GRADE evaluation quality of evidence for primary outcome. eFigure1. Test for transitivity assumption of primary outcome: changes of cognition function-overall. eFigure2. A network structure of NMA of changes of quality of life. B network structure of NMA of safety profile in aspect of rate of any adverse event. C network structure of NMA of safety profile in aspect of rate of any local discomfort. D network structure of NMA of acceptability in aspect of drop-out rate. eFigure3. A forest plot of NMA of change of quality of life. B forest plot of NMA of safety profile in aspect of rate of any adverse event. C forest plot of NMA of safety profile in aspect of rate of any local discomfort. D forest plot of NMA of acceptability in aspect of drop-out rate. eFigure4. A overview of risk of bias. B detailed risk of bias in each study. eFigure5. A Funnel plot of changes of cognition function: overall. B Egger’s regression of changes of cognition function: overall. C Funnel plot of changes of cognition function: MMSE measurement. D Egger’s regression of changes of cognition function: MMSE measurement. E Funnel plot of changes of cognition function: ADAS-Cog measurement. F Egger’s regression of changes of cognition function: ADAS-Cog measurement. G Funnel plot of changes of quality of life. H Egger’s regression of changes of quality of life. I Funnel plot of safety profile in aspect of rate of any adverse event. J Egger’s regression of safety profile in aspect of rate of any adverse event. K Funnel plot of safety profile in aspect of rate of any local discomfort. L Egger’s regression of safety profile in aspect of rate of any local discomfort. M Funnel plot of acceptability in aspect of drop-out rate. N Egger’s regression of acceptability in aspect of drop-out rate

Impact of data extraction errors in meta-analyses on the association between depression and peripheral inflammatory biomarkers: An umbrella review

Background- Accumulating evidence suggests that alterations in inflammatory biomarkers are important in depression. However, previous meta-analyses disagree on these associations, and errors in data extraction may account for these discrepancies. Methods- PubMed/MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from database inception to 14 January 2020. Meta-analyses of observational studies examining the association between depression and levels of tumor necrosis factor-α (TNF-α), interleukin 1-β (IL-1β), interleukin-6 (IL-6), and C-reactive protein (CRP) were eligible. Errors were classified as follows: incorrect sample sizes, incorrectly used standard deviation, incorrect participant inclusion, calculation error, or analysis with insufficient data. We determined their impact on the results after correction thereof. Results- Errors were noted in 14 of the 15 meta-analyses included. Across 521 primary studies, 118 (22.6%) showed the following errors: incorrect sample sizes (20 studies, 16.9%), incorrect use of standard deviation (35 studies, 29.7%), incorrect participant inclusion (7 studies, 5.9%), calculation errors (33 studies, 28.0%), and analysis with insufficient data (23 studies, 19.5%). After correcting these errors, 11 (29.7%) out of 37 pooled effect sizes changed by a magnitude of more than 0.1, ranging from 0.11 to 1.15. The updated meta-analyses showed that elevated levels of TNF- α, IL-6, CRP, but not IL-1β, are associated with depression. Conclusions- These findings show that data extraction errors in meta-analyses can impact findings. Efforts to reduce such errors are important in studies of the association between depression and peripheral inflammatory biomarkers, for which high heterogeneity and conflicting results have been continuously reported

A systematic review and meta-analysis of structural and functional brain alterations in individuals with genetic and clinical high-risk for psychosis and bipolar disorder

Neuroimaging findings in people at either genetic risk or at clinical high-risk for psychosis (CHR-P) or bipolar disorder (CHR-B) remain unclear. A meta-analytic review of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies in individuals with genetic risk or CHR-P or CHR-B and controls identified 94 datasets (N = 7942). Notwithstanding no significant findings were observed following adjustment for multiple comparisons, several findings were noted at a more liberal threshold. Subjects at genetic risk for schizophrenia or bipolar disorder or at CHR-P exhibited lower gray matter (GM) volumes in the gyrus rectus (Hedges' g = −0.19). Genetic risk for psychosis was associated with GM reductions in the right cerebellum and left amygdala. CHR-P was associated with decreased GM volumes in the frontal superior gyrus and hypoactivation in the right precuneus, the superior frontal gyrus and the right inferior frontal gyrus. Genetic and CHR-P were associated with small structural and functional alterations involving regions implicated in psychosis. Further neuroimaging studies in individuals with genetic or CHR-B are warranted

Evidence-Based Umbrella Review of 162 Peripheral Biomarkers for Major Mental Disorders

The literature on non-genetic peripheral biomarkers for major mental disorders is broad, with conflicting results. An umbrella review of meta-analyses of non-genetic peripheral biomarkers for Alzheimer’s disease, autism spectrum disorder, bipolar disorder (BD), major depressive disorder, and schizophrenia, including first-episode psychosis. We included meta-analyses that compared alterations in peripheral biomarkers between participants with mental disorders to controls (i.e., between-group meta-analyses) and that assessed biomarkers after treatment (i.e., within-group meta-analyses). Evidence for association was hierarchically graded using a priori defined criteria against several biases. The Assessment of Multiple Systematic Reviews (AMSTAR) instrument was used to investigate study quality. 1161 references were screened. 110 met inclusion criteria, relating to 359 meta-analytic estimates and 733,316 measurements, on 162 different biomarkers. Only two estimates met a priori defined criteria for convincing evidence (elevated awakening cortisol levels in euthymic BD participants relative to controls and decreased pyridoxal levels in participants with schizophrenia relative to controls). Of 42 estimates which met criteria for highly suggestive evidence only five biomarker aberrations occurred in more than one disorder. Only 15 meta-analyses had a power >0.8 to detect a small effect size, and most (81.9%) meta-analyses had high heterogeneity. Although some associations met criteria for either convincing or highly suggestive evidence, overall the vast literature of peripheral biomarkers for major mental disorders is affected by bias and is underpowered. No convincing evidence supported the existence of a trans-diagnostic biomarker. Adequately powered and methodologically sound future large collaborative studies are warranted