Humanitarian crises and armed conflicts lead to a greater prevalence of poor population mental health. Following the 1 February 2021 military coup in Burma, the country's civilians have faced humanitarian crises that have probably caused rising rates of mental disorders. However, a dearth of data has prevented researchers from assessing the extent of the problem empirically.

To better understand prevalence of depressive and anxiety disorders among the Burmese adult population after the February 2021 military coup.

We fielded an online non-probability survey of 7720 Burmese adults aged 18 and older during October 2021 and asked mental health and demographic questions. We used the Patient Health Questionnaire-4 to measure probable depression and anxiety in respondents. We also estimated logistic regressions to assess variations in probable depression and anxiety across demographic subgroups and by level of trust in various media sources, including those operated by the Burmese military establishment.

We found consistently high rates of probable anxiety and depression combined (60.71%), probable depression (61%) and probable anxiety (58%) in the sample overall, as well as across demographic subgroups. Respondents who ‘mostly’ or ‘completely’ trusted military-affiliated media sources (about 3% of the sample) were significantly less likely than respondents who did not trust these sources to report symptoms of anxiety and depression (AOR = 0.574; 95% CI 0.370–0.889), depression (AOR = 0.590; 95% CI 0.383–0.908) or anxiety (AOR = 0.609; 95% CI 0.390–0.951).

The widespread symptoms of anxiety and depression we observed demonstrate the need for both continuous surveillance of the current situation and humanitarian interventions to address mental health needs in Burma.

‘Mental Health Answers’ [Salud Mental Responde] is a Crisis Telephone Line that was developed during the first months of the COVID-19 pandemic in the Autonomous City of Buenos Aires, Argentina. It is also a Point of Entry to Mental Health services, providing assisted referrals to the appropriate level of care. The aim of this paper is to evaluate the profile of the callers to the line during the first three waves of COVID-19.

Retrospective case analysis of calls made to the telephone line throughout the different COVID-19 waves under study. For this analysis, the time frame for the first three waves was as follows. First wave: from 1 August to 30 of November 2020; second wave: 15 of March to 30 of July 2021; third wave: from 20 of December 2021 to 25 January 2022.

The first wave lasted 122 days. 4,601 calls were recorded, 27 calls were discarded for missing data. Women's mean age 51.79, SD 17.3, n = 3355. Men's mean age 43.29, SD 15.52, n = 1219. Significant differences were found in age, being men younger (T=−15.764, p < 0.000). Women made the majority of calls (72.9%). Fear and anxiety represented 45.1% of calls, depression 27.3% and psychosis 9%.

The second wave lasted 138 days and there were 4051 calls. Again, most of calls were made by women (71.5%). There were significant differences in age, being men younger (T = 14.450, p < 0.000). Women's mean age 46.68, SD = 18.72, n = 2872; men's mean age 38.05, SD = 16.34, n = 1138. The three most common detected problems were fear and anxiety 53.3%, depression 14.9% and psychosis 18.3%.

The third wave lasted 36 days; it had 1117 calls. Most calls made by women, 70.5%. Men were younger and this difference was significant (women's mean age 46.09, men's mean age 42.54; T = 3.233, p = 0.001). Problems detected, fear and anxiety 37.6%, depression 4.5% and psychosis 32.7%.

There was a change in the caller profile throughout the studied period, the callers from the first wave were older than the ones from the second and third waves. There was a change in the motivation to call, the most noticeable changes the drop in the number of calls related to depression (from 27.3% to 4.5%) and the increase in calls related to psychotic problems (from 9% to 32.7%). This last change might be related to the shift in the use of the Phoneline, from a Crisis Line to a Point of Entry to Mental Health Services.

Early-onset psychosis (EOP) refers to the development of a first episode of psychosis before 18 years of age. Individuals at clinical high risk for psychosis (CHR-P) include adolescents and young adults, although most evidence has focused on adults. Negative symptoms are important prognostic indicators in psychosis. However, research focusing on children and adolescents is limited.

To provide meta-analytical evidence and a comprehensive review of the status and advances in the diagnosis, prognosis and treatment of negative symptoms in children and adolescents with EOP and at CHR-P.

PRISMA/MOOSE-compliant systematic review (PROSPERO: CRD42022360925) from inception to 18 August 2022, in any language, to identify individual studies conducted in EOP/CHR-P children and adolescents (mean age <18 years) providing findings on negative symptoms. Findings were systematically appraised. Random-effects meta-analyses were performed on the prevalence of negative symptoms, carrying out sensitivity analyses, heterogeneity analyses, publication bias assessment and quality assessment using the Newcastle–Ottawa Scale.

Of 3289 articles, 133 were included (n = 6776 EOP, mean age 15.3 years (s.d. = 1.6), males = 56.1%; n = 2138 CHR-P, mean age 16.1 years (s.d. = 1.0), males = 48.6%). There were negative symptoms in 60.8% (95% CI 46.4%–75.2%) of the children and adolescents with EOP and 79.6% (95% CI 66.3–92.9%) of those at CHR-P. Prevalence and severity of negative symptoms were associated with poor clinical, functional and intervention outcomes in both groups. Different interventions were piloted, with variable results requiring further replication.

Negative symptoms are common in children and adolescents at early stages of psychosis, particularly in those at CHR-P, and are associated with poor outcomes. Future intervention research is required so that evidence-based treatments will become available.

Childhood adversity and cannabis use are considered independent risk factors for psychosis, but whether different patterns of cannabis use may be acting as mediator between adversity and psychotic disorders has not yet been explored. The aim of this study is to examine whether cannabis use mediates the relationship between childhood adversity and psychosis.

Data were utilised on 881 first-episode psychosis patients and 1231 controls from the European network of national schizophrenia networks studying Gene–Environment Interactions (EU-GEI) study. Detailed history of cannabis use was collected with the Cannabis Experience Questionnaire. The Childhood Experience of Care and Abuse Questionnaire was used to assess exposure to household discord, sexual, physical or emotional abuse and bullying in two periods: early (0–11 years), and late (12–17 years). A path decomposition method was used to analyse whether the association between childhood adversity and psychosis was mediated by (1) lifetime cannabis use, (2) cannabis potency and (3) frequency of use.

The association between household discord and psychosis was partially mediated by lifetime use of cannabis (indirect effect coef. 0.078, s.e. 0.022, 17%), its potency (indirect effect coef. 0.059, s.e. 0.018, 14%) and by frequency (indirect effect coef. 0.117, s.e. 0.038, 29%). Similar findings were obtained when analyses were restricted to early exposure to household discord.

Harmful patterns of cannabis use mediated the association between specific childhood adversities, like household discord, with later psychosis. Children exposed to particularly challenging environments in their household could benefit from psychosocial interventions aimed at preventing cannabis misuse.

While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis.

We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case–control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.

We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case–control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case–control status.

Controls (86.1%) and FEPp (75.63%) were most likely to report ‘because of friends’ as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: ‘to feel better’ as their RFUC (χ2 = 50.97; p < 0.001). RFUC ‘to feel better’ was associated with being a FEPp (OR 1.74; 95% CI 1.03–2.95) while RFUC ‘with friends’ was associated with being a control (OR 0.56; 95% CI 0.37–0.83). The path model indicated an association between RFUC ‘to feel better’ with heavy cannabis use and with FEPp-control status.

Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use ‘to feel better’. People who reported their reason for first using cannabis to ‘feel better’ were more likely to progress to heavy use and develop a psychotic disorder than those reporting ‘because of friends’.

Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case–control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD).

Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons.

In case–control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case–case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54–0.92] and PRS-D (OR = 1.31, 95% CI 1.06–1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23–3.74).

Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases.

A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to the number of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing polygenic vulnerability. Here, we investigated, in the largest sample of first-episode psychosis (FEP) cases to date, whether childhood adversity and high polygenic risk scores for schizophrenia (SZ-PRS) combine synergistically to increase the risk of psychosis, over and above the effect of each alone.

We assigned a schizophrenia-polygenic risk score (SZ-PRS), calculated from the Psychiatric Genomics Consortium (PGC2), to all participants in a sample of 384 FEP patients and 690 controls from the case–control component of the EU-GEI study. Only participants of European ancestry were included in the study. A history of childhood adversity was collected using the Childhood Trauma Questionnaire (CTQ). Synergistic effects were estimated using the interaction contrast ratio (ICR) [odds ratio (OR)exposure and PRS − ORexposure − ORPRS + 1] with adjustment for potential confounders.

There was some evidence that the combined effect of childhood adversities and polygenic risk was greater than the sum of each alone, as indicated by an ICR greater than zero [i.e. ICR 1.28, 95% confidence interval (CI) −1.29 to 3.85]. Examining subtypes of childhood adversities, the strongest synergetic effect was observed for physical abuse (ICR 6.25, 95% CI −6.25 to 20.88).

Our findings suggest possible synergistic effects of genetic liability and childhood adversity experiences in the onset of FEP, but larger samples are needed to increase precision of estimates.

There has been a recent trend in medical research towards a more collaborative relationship between statisticians and clinical investigators. This has led to an increased focus on the most efficient and effective ways to structure, conduct, and measure the impact of organizations that provide statistical services to clinical investigators. Several recent guidelines and recommendations on the conduct of statistical consulting services(SCSs) have been made in response to this need, focusing on larger SCSs consisting primarily of faculty and staff statisticians. However, the application of these recommendations to consulting services primarily staffed by graduate students, which have the dual role of providing a professional service and training, remains unclear.

Guidelines and recommendations, primarily from the Clinical and Translational Science (CTSA) consortium, were applied to a SCS staffed primarily by graduate students in an academic health center. A description of the organizational structure and outcomes after 3 years of operation is presented.

The guidelines recommended by the CTSA consortium and other groups were successfully incorporated into the graduate consulting laboratory. At almost one new project request per week, the consulting laboratory demonstrated a large bandwidth and had an excellent feedback from investigators.

Guidelines developed for larger statistical consulting organizations are able to be applied in student-led consultation organizations. Outcomes and recommendations from 3.5 years of operation are used to describe the successes and challenges we have encountered.

The ‘jumping to conclusions’ (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.

A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.

The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI −0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25–0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = −1.7, 95% CI −2.8 to −0.5, p = 0.006), but did not relate to delusions in patients.

Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.

Recent studies have led to suggest that the multifunctional protein clusterin could be envisaged as a potential diagnostic biomarker of addictive behaviours. However, this hypothesis has not been yet tested in nicotine addicts.

We have studied possible associations between clusterin levels in saliva from smokers under cessation treatment and variables related to tobacco consumption, dependence and addiction.

Eighty-one patients were included in an ambulatory smoking cessation programme that involved the use of pharmacological and behavioural therapy. The participants underwent psychological assessment of addiction and dependence (DAST-20, ASSIST, Fagerström tests) and provided saliva samples at the onset of the intervention and 6 months after smoking discontinuation to study the evolution of clusterin levels by enzyme-linked immunosorbent assays.

Clusterin concentration did not correlate with nicotine addiction/dependence scores but was significantly elevated in smokers with prolonged tobacco use and high intensity of tobacco consumption. Moreover, the levels of the protein significantly decreased 6 months after smoking cessation.

The results obtained provide strong evidence of a close association between tobacco use and salivary clusterin, a protein that emerges as a biomarker of tobacco toxicity with potential interest to monitor the beneficial effects of smoking cessation.

Jumping to conclusions (JTC), which is the proneness to require less information before forming beliefs or making a decision, has been related to formation and maintenance of delusions. Using data from the National Institute of Health Research Biomedical Research Centre Genetics and Psychosis (GAP) case–control study of first-episode psychosis (FEP), we set out to test whether the presence of JTC would predict poor clinical outcome at 4 years.

One-hundred and twenty-three FEP patients were assessed with the Positive and Negative Syndrome Scale (PANSS), Global Assessment of Functioning (GAF) and the probabilistic reasoning ‘Beads’ Task at the time of recruitment. The sample was split into two groups based on the presence of JTC bias. Follow-up data over an average of 4 years were obtained concerning clinical course and outcomes (remission, intervention of police, use of involuntary treatment – the Mental Health Act (MHA) – and inpatient days).

FEP who presented JTC at baseline were more likely during the follow-up period to be detained under the MHA [adjusted OR 15.62, 95% confidence interval (CI) 2.92–83.54, p = 0.001], require intervention by the police (adjusted OR 14.95, 95% CI 2.68–83.34, p = 0.002) and have longer admissions (adjusted IRR = 5.03, 95% CI 1.91–13.24, p = 0.001). These associations were not accounted for by socio-demographic variables, IQ and symptom dimensions.

JTC in FEP is associated with poorer outcome as indicated and defined by more compulsion police intervention and longer periods of admission. Our findings raise the question of whether the implementation of specific interventions to reduce JTC, such as Metacognition Training, may be a useful addition in early psychosis intervention programmes.