Delay discounting—the extent to which individuals show a preference for smaller immediate rewards over larger delayed rewards—has been proposed as a transdiagnostic neurocognitive process across mental health conditions, but its examination in relation to posttraumatic stress disorder (PTSD) is comparatively recent. To assess the aggregated evidence for elevated delay discounting in relation to posttraumatic stress, we conducted a meta-analysis on existing empirical literature. Bibliographic searches identified 209 candidate articles, of which 13 articles with 14 independent effect sizes were eligible for meta-analysis, reflecting a combined sample size of N = 6897. Individual study designs included case-control (e.g. examination of differences in delay discounting between individuals with and without PTSD) and continuous association studies (e.g. relationship between posttraumatic stress symptom severity and delay discounting). In a combined analysis of all studies, the overall relationship was a small but statistically significant positive association between posttraumatic stress and delay discounting (r = .135, p < .0001). The same relationship was statistically significant for continuous association studies (r = .092, p = .027) and case-control designs (r = .179, p < .001). Evidence of publication bias was minimal. The included studies were limited in that many did not concurrently incorporate other psychiatric conditions in the analyses, leaving the specificity of the relationship to posttraumatic stress less clear. Nonetheless, these findings are broadly consistent with previous meta-analyses of delayed reward discounting in relation to other mental health conditions and provide further evidence for the transdiagnostic utility of this construct.

The reading the mind in the eyes test (RMET) – which assesses the theory of mind component of social cognition – is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91–20.60) in patients and 25.53 (95% CI 25.19–25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score – RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.

Quality of life (QoL) is a major patient reported outcome used to measure the psychological treatments success in people with schizophrenia-spectrum disorders. To date, the specific impact of different interventions on QoL remains undefined. A meta-analysis of Randomized Controlled Trials (RCTs) was carried out for this purpose. We searched Proquest, PUBMED/MEDLINE, PsycINFO, WOS, Scopus, the Cochrane Library for RCTs published until January 2023. We used multilevel meta-analysis to examine differences between intervention effectiveness of experimental and control conditions whilst accounting for data dependencies. By means of subgroup analyses, we investigated influences of intervention types (i.e. psychoeducation v. CBT v. cognitive v. combination of several types v. other, such as psychodynamic, systemic, etc.) and continuous moderators were examined with precision-weighted meta-regressions. The generalizability of results across moderators, their combinations, and analytical approaches was investigated with multiverse meta-analyses. We examined data of 60 independent studies, reporting intervention effects for objective and subjective QoL (k = 19 and 70 effect sizes based on N = 1024 and 6254 participants, respectively). Overall, psychological interventions seemed to be more effective for objective than for subjective QoL. However, specific intervention results were differentiated, suggesting largest effects of psychoeducation on objective and combined interventions on subjective QoL. Our findings suggest that QoL is a valid outcome criterion for testing intervention effectiveness, as it is sensitive to change. Additionally, psychological interventions can improve patients' QoL, though the effects are small. Further testing of less widely used interventions and a shift toward the multidimensional nature of QoL is still necessary.

Suicide is the leading cause of unnatural death among people with a diagnosis of schizophrenia. Alcohol use is a prevalent comorbid feature of schizophrenia and a modifiable risk factor for suicide. We conducted a prospectively registered (PROSPERO, CRD42022358214) systematic review and meta-analysis to quantify the relationship between alcohol use and suicide-related outcomes in schizophrenia.

We searched Medline, Embase, and PsycINFO for cross-sectional, case–control and longitudinal studies using exhaustive terms from database inception to December 2022 inclusive. Computation of odds ratios (ORs) and hazard ratios (HRs) were performed using a random-effects model with DerSimonian–Laird estimation. We also evaluated publication bias, study quality, and performed subgroup analysis and meta-regression. Fifty studies, comprising 65 samples, met eligibility criteria. Overall, alcohol use was associated with suicide (OR 1.38, 95% CI 1.21–1.58; HR = 1.32, 95% CI 1.00–1.74), attempted suicide (OR 1.69, 95% CI 1.45–1.98), and suicidal ideation (OR 1.69, 95% CI 1.22–2.34). While there was no evidence of publication bias, between-sample heterogeneity was moderate in analyses of attempted suicide (I2 = 39.6%, p = 0.01) and suicidal ideation (I2 = 56.0%, p = 0.01). Summary effects were significant in all subgroups except for longitudinal studies of attempted suicide (OR 1.60, 95% CI 0.86–3.00) and studies of suicidal ideation using gender combined samples (OR 1.63, 95% CI 0.99–2.67). Alcohol use is significantly associated with suicide-related outcomes in schizophrenia. Clinicians should routinely inquire about alcohol use in mental health services to focus preventative treatment efforts.

Individuals with mood disorders are predisposed to metabolic dysfunction, while those with metabolic dysregulation such as diabetes and obesity experience more severe depressive symptoms. Both metabolic dysfunction and mood disorders are independently associated with cognitive deficits. Therefore, given their close association, this study aimed to explore the association between metabolic dysfunction in individuals with mood disorders in relation to cognitive outcomes. A comprehensive search comprised of these three domains was carried out; a random-effects meta-analysis pooling mean cognitive outcomes was conducted (PROSPERO ID: CRD42022295765). Sixty-three studies were included in this review; 26 were synthesized in a quantitative meta-analysis. Comorbid metabolic dysregulation was associated with significantly lower global cognition among individuals with mood disorders. These trends were significant within each mood disorder subgroup, including major depressive disorder, bipolar disorder, and self-report depression/depressive symptoms. Type 2 diabetes was associated with the lowest cognitive performance in individuals with mood disorders, followed by peripheral insulin resistance, body mass index ⩾25 kg/m2, and metabolic syndrome. Significant reduction in scores was also observed among individual cognitive domains (in descending order) of working memory, attention, executive function, processing speed, verbal memory, and visual memory. These findings demonstrate the detrimental effects of comorbid metabolic dysfunction in individuals with mood disorders. Further research is required to understand the underlying mechanisms connecting mood disorders, metabolism, and cognition.

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples – the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

Reward processing dysfunctions are considered a candidate mechanism underlying anhedonia and apathy in depression. Neuroimaging studies have documented that neurofunctional alterations in mesocorticolimbic circuits may neurally mediate these dysfunctions. However, common and distinct neurofunctional alterations during motivational and hedonic evaluation of monetary and natural rewards in depression have not been systematically examined. Here, we capitalized on pre-registered neuroimaging meta-analyses to (1) establish general reward-related neural alterations in depression, (2) determine common and distinct alterations during the receipt and anticipation of monetary v. natural rewards, and, (3) characterize the differences on the behavioral, network, and molecular level. The pre-registered meta-analysis (https://osf.io/ay3r9) included 633 depressed patients and 644 healthy controls and revealed generally decreased subgenual anterior cingulate cortex and striatal reactivity toward rewards in depression. Subsequent comparative analyses indicated that monetary rewards led to decreased hedonic reactivity in the right ventral caudate while natural rewards led to decreased reactivity in the bilateral putamen in depressed individuals. These regions exhibited distinguishable profiles on the behavioral, network, and molecular level. Further analyses demonstrated that the right thalamus and left putamen showed decreased activation during the anticipation of monetary reward. The present results indicate that distinguishable neurofunctional alterations may neurally mediate reward-processing alterations in depression, in particular, with respect to monetary and natural rewards. Given that natural rewards prevail in everyday life, our findings suggest that reward-type specific interventions are warranted and challenge the generalizability of experimental tasks employing monetary incentives to capture reward dysregulations in everyday life.

Cannabis use is consistently associated with both increased incidence of frank psychotic disorders and acute exacerbations of psychotic symptoms in healthy individuals and people with psychosis spectrum disorders. Although there is uncertainty around causality, cannabis use may be one of a few modifiable risk factors for conversion to psychotic disorders in individuals with Clinical High Risk for Psychosis (CHR-P) syndromes, characterized by functionally impairing and distressing subthreshold psychotic symptoms. To date, few recommendations beyond abstinence to reduce adverse psychiatric events associated with cannabis use have been made. This narrative review synthesizes existing scientific literature on cannabis' acute psychotomimetic effects and epidemiological associations with psychotic disorders in both CHR-P and healthy individuals to bridge the gap between scientific knowledge and practical mental health intervention. There is compelling evidence for cannabis acutely exacerbating psychotic symptoms in CHR-P, but its impact on conversion to psychotic disorder is unclear. Current evidence supports a harm reduction approach in reducing frequency of acute psychotic-like experiences, though whether such interventions decrease CHR-P individuals' risk of conversion to psychotic disorder remains unknown. Specific recommendations include reducing frequency of use, lowering delta-9-tetrahydrocannabinol content in favor of cannabidiol-only products, avoiding products with inconsistent potency like edibles, enhancing patient-provider communication about cannabis use and psychotic-like experiences, and utilizing a collaborative and individualized therapeutic approach. Despite uncertainty surrounding cannabis' causal association with psychotic disorders, cautious attempts to reduce acute psychosis risk may benefit CHR-P individuals uninterested in abstinence. Further research is needed to clarify practices associated with minimization of cannabis-related psychosis risk.

Debate is ongoing on the efficacy of cognitive behavior therapy (CBT) for myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS). With an individual patient data (IPD) meta-analysis we investigated whether the effect of CBT varied by patient characteristics. These included post-exertional malaise (PEM), a central feature of ME/CFS according to many. We searched for randomized controlled trials similar with respect to comparison condition, outcomes and treatment-protocol. Moderation on fatigue severity (Checklist Individual Strength, subscale fatigue severity), functional impairment (Sickness Impact Profile-8) and physical functioning (Short Form-36, subscale physical functioning) was investigated using linear mixed model analyses and interaction tests. PROSPERO (CRD42022358245). Data from eight trials (n = 1298 patients) were pooled. CBT showed beneficial effects on fatigue severity (β = −11.46, 95% CI −15.13 to −7.79); p < 0.001, functional impairment (β = −448.40, 95% CI −625.58 to −271.23); p < 0.001; and physical functioning (β = 9.64, 95% CI 3.30 to 15.98); p < 0.001. The effect of CBT on fatigue severity varied by age (pinteraction = 0.003), functional impairment (pinteraction = 0.045) and physical activity pattern (pinteraction = 0.027). Patients who were younger, reported less functional impairments and had a fluctuating activity pattern benefitted more. The effect on physical functioning varied by self-efficacy (pinteraction = 0.025), with patients with higher self-efficacy benefitting most. No other moderators were found. It can be concluded from this study that CBT for ME/CFS can lead to significant reductions of fatigue, functional impairment, and physical limitations. There is no indication patients meeting different case definitions or reporting additional symptoms benefit less from CBT. Our findings do not support recent guidelines in which evidence from studies not mandating PEM was downgraded.

Duration of untreated psychosis (DUP) has been associated with poor mental health outcomes. We aimed to meta-analytically estimate the mean and median DUP worldwide, evaluating also the influence of several moderating factors. This PRISMA/MOOSE-compliant meta-analysis searched for non-overlapping individual studies from inception until 9/12/2022, reporting mean ± s.d. or median DUP in patients with first episode psychosis (FEP), without language restrictions. We conducted random-effect meta-analyses, stratified analyses, heterogeneity analyses, meta-regression analyses, and quality assessment (PROSPERO:CRD42020163640). From 12 461 citations, 369 studies were included. The mean DUP was 42.6 weeks (95% confidence interval (CI) 40.6–44.6, k = 283, n = 41 320), varying significantly across continents (p < 0.001). DUP was (in descending order) 70.0 weeks (95% CI 51.6–88.4, k = 11, n = 1508) in Africa; 48.8 weeks (95% CI 43.8–53.9, k = 73, n = 12 223) in Asia; 48.7 weeks (95% CI 43.0–54.4, k = 36, n = 5838) in North America; 38.6 weeks (95% CI 36.0–41.3, k = 145, n = 19 389) in Europe; 34.9 weeks (95% CI 23.0–46.9, k = 11, n = 1159) in South America and 28.0 weeks (95% CI 20.9–35.0, k = 6, n = 1203) in Australasia. There were differences depending on the income of countries: DUP was 48.4 weeks (95% CI 43.0–48.4, k = 58, n = 5635) in middle-low income countries and 41.2 weeks (95% CI 39.0–43.4, k = 222, n = 35 685) in high income countries. Longer DUP was significantly associated with older age (β = 0.836, p < 0.001), older publication year (β = 0.404, p = 0.038) and higher proportion of non-White FEP patients (β = 0.232, p < 0.001). Median DUP was 14 weeks (Interquartile range = 8.8–28.0, k = 206, n = 37 215). In conclusion, DUP is high throughout the world, with marked variation. Efforts to identify and intervene sooner in patients with FEP, and to promote global mental health and access to early intervention services (EIS) are critical, especially in developing countries.

Globally, mental disorders account for almost 20% of disease burden and there is growing evidence that mental disorders are socially determined. Tackling the United Nations Sustainable Development Goals (UN SDGs), which address social determinants of mental disorders, may be an effective way to reduce the global burden of mental disorders. We conducted a systematic review of reviews to examine the evidence base for interventions that map onto the UN SDGs and seek to improve mental health through targeting known social determinants of mental disorders. We included 101 reviews in the final review, covering demographic, economic, environmental events, neighborhood, and sociocultural domains. This review presents interventions with the strongest evidence base for the prevention of mental disorders and highlights synergies where addressing the UN SDGs can be beneficial for mental health.

The prevalence of self-harm has increased substantially in recent decades. Despite the development of guidelines for better management and prevention of self-harm, service users report that quality of care remains variable. A previous systematic review of research published to June 2006 documented largely negative experiences of clinical services among patients who self-harm. This systematic review summarized the literature published since then to July 2022 to examine contemporary attitudes toward and experience of clinical and non-clinical services among individuals who self-harm and their relatives. We systematically searched for literature using seven databases. Quality of studies was assessed using the Mixed-Methods Appraisal Tool and findings were summarized using a narrative synthesis. We identified 29 studies that met our inclusion criteria, all of which were from high- or middle-income countries and were generally of high methodological quality. Our narrative synthesis identified negative attitudes toward clinical management and organizational barriers across services. Generally, more positive attitudes were found toward non-clinical services providing therapeutic contact, such as voluntary sector organizations and social services, than clinical services, such as emergency departments and inpatient units. Views suggested that negative experiences of service provision may perpetuate a cycle of self-harm. Our review suggests that in recent years there has been little improvement in attitudes toward and experiences of services for patients who self-harm. These findings should be used to reform clinical guidelines and staff training across clinical services to promote patient-centered and compassionate care and deliver more effective, acceptable and accessible services.

The network theory of psychological disorders posits that systems of symptoms cause, or are associated with, the expression of other symptoms. Substantial literature on symptom networks has been published to date, although no systematic review has been conducted exclusively on symptom networks of schizophrenia, schizoaffective disorder, and schizophreniform (people diagnosed with schizophrenia; PDS). This study aims to compare statistics of the symptom network publications on PDS in the last 21 years and identify congruences and discrepancies in the literature. More specifically, we will focus on centrality statistics. Thirty-two studies met the inclusion criteria. The results suggest that cognition, and social, and occupational functioning are central to the network of symptoms. Positive symptoms, particularly delusions were central among participants in many studies that did not include cognitive assessment. Nodes representing cognition were most central in those studies that did. Nodes representing negative symptoms were not as central as items measuring positive symptoms. Some studies that included measures of mood and affect found items or subscales measuring depression were central nodes in the networks. Cognition, and social, and occupational functioning appear to be core symptoms of schizophrenia as they are more central in the networks, compared to variables assessing positive symptoms. This seems consistent despite heterogeneity in the design of the studies.

Precision psychiatry is an emerging field that aims to provide individualized approaches to mental health care. An important strategy to achieve this precision is to reduce uncertainty about prognosis and treatment response. Multivariate analysis and machine learning are used to create outcome prediction models based on clinical data such as demographics, symptom assessments, genetic information, and brain imaging. While much emphasis has been placed on technical innovation, the complex and varied nature of mental health presents significant challenges to the successful implementation of these models. From this perspective, I review ten challenges in the field of precision psychiatry, including the need for studies on real-world populations and realistic clinical outcome definitions, and consideration of treatment-related factors such as placebo effects and non-adherence to prescriptions. Fairness, prospective validation in comparison to current practice and implementation studies of prediction models are other key issues that are currently understudied. A shift is proposed from retrospective studies based on linear and static concepts of disease towards prospective research that considers the importance of contextual factors and the dynamic and complex nature of mental health.

Decision-making capacity (DMC) among psychiatric inpatients is a pivotal clinical concern. A review by Okai et al. (2007) suggested that most psychiatric inpatients have DMC for treatment, and its assessment is reliable. Nevertheless, the high heterogeneity and mixed results from other studies mean there is considerable uncertainty around this topic. This study aimed to update Okai's research by conducting a systematic review with meta-analysis to address heterogeneity. We performed a systematic search across four databases, yielding 5351 results. We extracted data from 20 eligible studies on adult psychiatric inpatients, covering DMC assessments from 2006 to May 2022. A meta-analysis was conducted on 11 papers, and a quality assessment was performed. The study protocol was registered on PROSPERO (ID: CRD42022330074). The proportion of patients with DMC for treatment varied widely based on treatment setting, the specific decision and assessment methods. Reliable capacity assessment was feasible. The Mini-Mental State Examination (MMSE), Global Assessment of Function (GAF), and Brief Psychiatric Rating Scale (BPRS) predicted clinical judgments of capacity. Schizophrenia and bipolar mania were linked to the highest incapacity rates, while depression and anxiety symptoms were associated with better capacity and insight. Unemployment was the only sociodemographic factor correlated with incapacity. Assessing mental capacity is replicable, with most psychiatric inpatients able to make treatment decisions. However, this capacity varies with admission stage, formal status (involuntary or voluntary), and information provided. The severity of psychopathology is linked to mental capacity, though detailed psychopathological data are limited.