Promotion of good mental health, prevention, and early intervention before/at the onset of mental disorders improve outcomes. However, the range and peak ages at onset for mental disorders are not fully established. To provide robust, global epidemiological estimates of age at onset for mental disorders, we conducted a PRISMA/MOOSE-compliant systematic review with meta-analysis of birth cohort/cross-sectional/cohort studies, representative of the general population, reporting age at onset for any ICD/DSM-mental disorders, identified in PubMed/Web of Science (up to 16/05/2020) (PROSPERO:CRD42019143015). Co-primary outcomes were the proportion of individuals with onset of mental disorders before age 14, 18, 25, and peak age at onset, for any mental disorder and across International Classification of Diseases 11 diagnostic blocks. Median age at onset of specific disorders was additionally investigated. Across 192 studies (n = 708,561) included, the proportion of individuals with onset of any mental disorders before the ages of 14, 18, 25 were 34.6%, 48.4%, 62.5%, and peak age was 14.5 years (k = 14, median = 18, interquartile range (IQR) = 11–34). For diagnostic blocks, the proportion of individuals with onset of disorder before the age of 14, 18, 25 and peak age were as follows: neurodevelopmental disorders: 61.5%, 83.2%, 95.8%, 5.5 years (k = 21, median=12, IQR = 7–16), anxiety/fear-related disorders: 38.1%, 51.8%, 73.3%, 5.5 years (k = 73, median = 17, IQR = 9–25), obsessive-compulsive/related disorders: 24.6%, 45.1%, 64.0%, 14.5 years (k = 20, median = 19, IQR = 14–29), feeding/eating disorders/problems: 15.8%, 48.1%, 82.4%, 15.5 years (k = 11, median = 18, IQR = 15–23), conditions specifically associated with stress disorders: 16.9%, 27.6%, 43.1%, 15.5 years (k = 16, median = 30, IQR = 17–48), substance use disorders/addictive behaviours: 2.9%, 15.2%, 48.8%, 19.5 years (k = 58, median = 25, IQR = 20–41), schizophrenia-spectrum disorders/primary psychotic states: 3%, 12.3%, 47.8%, 20.5 years (k = 36, median = 25, IQR = 20–34), personality disorders/related traits: 1.9%, 9.6%, 47.7%, 20.5 years (k = 6, median = 25, IQR = 20–33), and mood disorders: 2.5%, 11.5%, 34.5%, 20.5 years (k = 79, median = 31, IQR = 21–46). No significant difference emerged by sex, or definition of age of onset. Median age at onset for specific mental disorders mapped on a time continuum, from phobias/separation anxiety/autism spectrum disorder/attention deficit hyperactivity disorder/social anxiety (8-13 years) to anorexia nervosa/bulimia nervosa/obsessive-compulsive/binge eating/cannabis use disorders (17-22 years), followed by schizophrenia, personality, panic and alcohol use disorders (25-27 years), and finally post-traumatic/depressive/generalized anxiety/bipolar/acute and transient psychotic disorders (30-35 years), with overlap among groups and no significant clustering. These results inform the timing of good mental health promotion/preventive/early intervention, updating the current mental health system structured around a child/adult service schism at age 18.

ContextDuring the past 2 decades, a major transition in the clinical characterization of psychotic disorders has occurred. The construct of a clinical high-risk (HR) state for psychosis has evolved to capture the prepsychotic phase, describing people presenting with potentially prodromal symptoms. The importance of this HR state has been increasingly recognized to such an extent that a new syndrome is being considered as a diagnostic category in the DSM-5.ObjectiveTo reframe the HR state in a comprehensive state-of-the-art review on the progress that has been made while also recognizing the challenges that remain.Data SourcesAvailable HR research of the past 20 years from PubMed, books, meetings, abstracts, and international conferences.Study Selection and Data ExtractionCritical review of HR studies addressing historical development, inclusion criteria, epidemiologic research, transition criteria, outcomes, clinical and functional characteristics, neurocognition, neuroimaging, predictors of psychosis development, treatment trials, socioeconomic aspects, nosography, and future challenges in the field.Data SynthesisRelevant articles retrieved in the literature search were discussed by a large group of leading worldwide experts in the field. The core results are presented after consensus and are summarized in illustrative tables and figures.ConclusionsThe relatively new field of HR research in psychosis is exciting. It has the potential to shed light on the development of major psychotic disorders and to alter their course. It also provides a rationale for service provision to those in need of help who could not previously access it and the possibility of changing trajectories for those with vulnerability to psychotic illnesses.

Although prodromal symptoms of psychosis have long been recognized,² the clinical management of psychotic disorders conventionally begins at the first episode of frank psychosis, and, until recently, the period immediately preceding the first episode received relatively little attention. For the past 15 years, there has been increasing academic and clinical interest in people presenting with potentially prodromal symptoms.³ This clinical syndrome has been termed an at risk mental state,⁴ and operationalized criteria—the ultra high risk (UHR)⁵ or clinical high risk (HR)⁶ criteria—have been developed to identify the syndrome.⁴ The criteria apply to young help-seeking patients and require 1 of 3 presentations:“attenuated” psychotic symptoms, full-blown psychotic symptoms that are brief and self-limiting, or a significant decrease in functioning in the context of a genetic risk for schizophrenia.⁷ Additional prodromal criteria emerging from the basic symptoms (BS) literature⁸ include subjective disturbances of cognitive processing and the perception of the self and the world.⁹ Belonging to one of these prodromal groups, which we hereafter term the clinical high risk syndrome, is associated with impairments in neuropsychologic performance¹⁰ and alterations in the structure^11-13 (for meta-analyses, see Fusar-Poli et al^14,15), function^16-18 (for meta-analyses, see Smieskova et al¹⁹ and Fusar-Poli et al²⁰), connectivity,²¹ and neurochemistry^22-24 of the brain.

Background: Most of our social interactions involve perception of emotional information from the faces of other people. Furthermore, such emotional processes are thought to be aberrant in a range of clinical disorders, including psychosis and depression. However, the exact neurofunctional maps underlying emotional facial processing are not well defined. Methods: Two independent researchers conducted separate comprehensive PubMed (1990 to May 2008) searches to find all functional magnetic resonance imaging (fMRI) studies using a variant of the emotional faces paradigm in healthy participants. The search terms were: “fMRI AND happy faces,” “fMRI AND sad faces,” “fMRI AND fearful faces,” “fMRI AND angry faces,” “fMRI AND disgusted faces” and “fMRI AND neutral faces.” We extracted spatial coordinates and inserted them in an electronic database. We performed activation likelihood estimation analysis for voxel-based meta-analyses. Results: Of the originally identified studies, 105 met our inclusion criteria. The overall database consisted of 1785 brain coordinates that yielded an overall sample of 1600 healthy participants. Quantitative voxel-based meta-analysis of brain activation provided neurofunctional maps for 1) main effect of human faces; 2) main effect of emotional valence; and 3) modulatory effect of age, sex, explicit versus implicit processing and magnetic field strength. Processing of emotional faces was associated with increased activation in a number of visual, limbic, temporoparietal and prefrontal areas; the putamen; and the cerebellum. Happy, fearful and sad faces specifically activated the amygdala, whereas angry or disgusted faces had no effect on this brain region. Furthermore, amygdala sensitivity was greater for fearful than for happy or sad faces. Insular activation was selectively reported during processing of disgusted and angry faces. However, insular sensitivity was greater for disgusted than for angry faces. Conversely, neural response in the visual cortex and cerebellum was observable across all emotional conditions. Limitations: Although the activation likelihood estimation approach is currently one of the most powerful and reliable meta-analytical methods in neuroimaging research, it is insensitive to effect sizes. Conclusion: Our study has detailed neurofunctional maps to use as normative references in future fMRI studies of emotional facial processing in psychiatric populations. We found selective differences between neural networks underlying the basic emotions in limbic and insular brain regions.

Objective Evidence syntheses such as systematic reviews and meta-analyses provide a rigorous and transparent knowledge base for translating clinical research into decisions, and thus they represent the basic unit of knowledge in medicine. Umbrella reviews are reviews of previously published systematic reviews or meta-analyses. Therefore, they represent one of the highest levels of evidence synthesis currently available, and are becoming increasingly influential in biomedical literature. However, practical guidance on how to conduct umbrella reviews is relatively limited. Methods We present a critical educational review of published umbrella reviews, focusing on the essential practical steps required to produce robust umbrella reviews in the medical field. Results The current manuscript discusses 10 key points to consider for conducting robust umbrella reviews. The points are: ensure that the umbrella review is really needed, prespecify the protocol, clearly define the variables of interest, estimate a common effect size, report the heterogeneity and potential biases, perform a stratification of the evidence, conduct sensitivity analyses, report transparent results, use appropriate software and acknowledge the limitations. We illustrate these points through recent examples from umbrella reviews and suggest specific practical recommendations. Conclusions The current manuscript provides a practical guidance for conducting umbrella reviews in medical areas. Researchers, clinicians and policy makers might use the key points illustrated here to inform the planning, conduction and reporting of umbrella reviews in medicine.

Existing treatments for schizophrenia can improve positive symptoms, but it is unclear if they have any impact on negative symptoms. This meta-analysis was conducted to assess the efficacy of available treatments for negative symptoms in schizophrenia. All randomized-controlled trials of interventions for negative symptoms in schizophrenia until December 2013 were retrieved; 168 unique and independent placebo-controlled trials were used. Negative symptom scores at baseline and follow-up, duration of illness, doses of medication, type of interventions, and sample demographics were extracted. Heterogeneity was addressed with the I² and Q statistic. Standardized mean difference in values of the Negative Symptom Rating Scale used in each study was calculated as the main outcome measure. 6503 patients in the treatment arm and 5815 patients in the placebo arm were included. No evidence of publication biases found. Most treatments reduced negative symptoms at follow-up relative to placebo: second-generation antipsychotics: −0.579 (−0.755 to −0.404); antidepressants: −0.349 (−0.551 to −0.146); combinations of pharmacological agents: −0.518 (−0.757 to −0.279); glutamatergic medications: −0.289 (−0.478 to −0.1); psychological interventions: −0.396 (−0.563 to −0.229). No significant effect was found for first-generation antipsychotics: −0.531 (−1.104 to 0.041) and brain stimulation: −0.228 (−0.775 to 0.319). Effects of most treatments were not clinically meaningful as measured on Clinical Global Impression Severity Scale. Although some statistically significant effects on negative symptoms were evident, none reached the threshold for clinically significant improvement.