Childhood bullying is a public health priority. We evaluated the effectiveness and costs of KiVa, a whole-school anti-bullying program that targets the peer context.

A two-arm pragmatic multicenter cluster randomized controlled trial with embedded economic evaluation. Schools were randomized to KiVa-intervention or usual practice (UP), stratified on school size and Free School Meals eligibility. KiVa was delivered by trained teachers across one school year. Follow-up was at 12 months post randomization. Primary outcome: student-reported bullying-victimization; secondary outcomes: self-reported bullying-perpetration, participant roles in bullying, empathy and teacher-reported Strengths and Difficulties Questionnaire. Outcomes were analyzed using multilevel linear and logistic regression models.

Between 8/11/2019–12/02/2021, 118 primary schools were recruited in four trial sites, 11 111 students in primary analysis (KiVa-intervention: n = 5944; 49.6% female; UP: n = 5167, 49.0% female). At baseline, 21.6% of students reported being bullied in the UP group and 20.3% in the KiVa-intervention group, reducing to 20.7% in the UP group and 17.7% in the KiVa-intervention group at follow-up (odds ratio 0.87; 95% confidence interval 0.78 to 0.97, p value = 0.009). Students in the KiVa group had significantly higher empathy and reduced peer problems. We found no differences in bullying perpetration, school wellbeing, emotional or behavioral problems. A priori subgroup analyses revealed no differences in effectiveness by socioeconomic gradient, or by gender. KiVa costs £20.78 more per pupil than usual practice in the first year, and £1.65 more per pupil in subsequent years.

The KiVa anti-bullying program is effective at reducing bullying victimization with small-moderate effects of public health importance.

The study was funded by the UK National Institute for Health and Care Research (NIHR) Public Health Research program (17-92-11). Intervention costs were funded by the Rayne Foundation, GwE North Wales Regional School Improvement Service, Children's Services, Devon County Council and HSBC Global Services (UK) Ltd.

We examined whether cannabis use contributes to the increased risk of psychotic disorder for non-western minorities in Europe.

We used data from the EU-GEI study (collected at sites in Spain, Italy, France, the United Kingdom, and the Netherlands) on 825 first-episode patients and 1026 controls. We estimated the odds ratio (OR) of psychotic disorder for several groups of migrants compared with the local reference population, without and with adjustment for measures of cannabis use.

The OR of psychotic disorder for non-western minorities, adjusted for age, sex, and recruitment area, was 1.80 (95% CI 1.39–2.33). Further adjustment of this OR for frequency of cannabis use had a minimal effect: OR = 1.81 (95% CI 1.38–2.37). The same applied to adjustment for frequency of use of high-potency cannabis. Likewise, adjustments of ORs for most sub-groups of non-western countries had a minimal effect. There were two exceptions. For the Black Caribbean group in London, after adjustment for frequency of use of high-potency cannabis the OR decreased from 2.45 (95% CI 1.25–4.79) to 1.61 (95% CI 0.74–3.51). Similarly, the OR for Surinamese and Dutch Antillean individuals in Amsterdam decreased after adjustment for daily use: from 2.57 (95% CI 1.07–6.15) to 1.67 (95% CI 0.62–4.53).

The contribution of cannabis use to the excess risk of psychotic disorder for non-western minorities was small. However, some evidence of an effect was found for people of Black Caribbean heritage in London and for those of Surinamese and Dutch Antillean heritage in Amsterdam.

Children and adolescents with a history of adverse childhood experiences (ACEs) are more likely than their peers to develop mental health difficulties, but not enough is known about their help-seeking behaviours and preferences. We aimed to determine whether ACEs are associated with access to and perceived unmet need for mental health services and support amongst secondary school students.

We used multi-level logistic regression with data from the 2020 OxWell Student Survey to assess whether ACEs were associated with (1) prior access to mental health support and (2) perceived unmet need for mental health services in a community sample of English secondary school students. We assessed ACEs as a cumulative score from the Center for Youth Wellness Adverse Childhood Experiences Questionnaire: Teen Self-Report version and accounted for current mental health difficulties as measured by the 25-item Revised Children’s Anxiety and Depression Scale (RCADS).

Our analysis included 2018 students across 64 schools, of whom 29.9% (598/2002) reported prior access to mental health support. Of those not reporting prior access, 34.1% (469/1377) reported a perceived unmet need for services. In the unadjusted models, cumulative ACE scores were significantly positively associated with both prior access to mental health support (odds ratio (OR) = 1.36; 95% confidence interval (CI): 1.29–1.43) and perceived unmet need for mental health services (OR = 1.47; 95% CI: 1.37–1.59), meaning that students who had experienced adversity had a greater chance of having previously accessed support as well as perceiving an unmet need for services. After adjusting for mental health difficulties and other sociodemographic variables, cumulative ACE scores were positively associated with prior access (adjusted OR (aOR) = 1.25; 95% CI: 1.17–1.34 with a significant interaction between RCADS and ACE scores, aOR = 0.88; 95% CI: 0.84–0.93) as well as perceived unmet need (aOR = 1.32; 95% CI: 1.21–1.43 with a significant interaction between RCADS and ACE scores, aOR = 0.85; 95% CI: 0.78–0.91).

Although it is encouraging that adolescents with experience of adversity are more likely than their peers with similar levels of depression and anxiety symptoms to have accessed mental health support, there remains a concern that those who have not accessed support are more likely to perceive an as-yet unmet need for it. Mental health support must be available, accessible and acceptable to all who need it, especially for those groups that traditionally have not accessed services, including the more marginalised and vulnerable populations.

The UK Soft Drinks Industry Levy (SDIL) (announced in March 2016; implemented in April 2018) aims to incentivise reformulation of soft drinks to reduce added sugar levels. The SDIL has been applauded as a policy success, and it has survived calls from parliamentarians for it to be repealed. We aimed to explore parliamentary reaction to the SDIL following its announcement until two years post-implementation in order to understand how health policy can become established and resilient to opposition.

Searches of Hansard for parliamentary debate transcripts that discussed the SDIL retrieved 186 transcripts, with 160 included after screening. Five stages of Applied Thematic Analysis were conducted: familiarisation and creation of initial codebooks; independent second coding; codebook finalisation through team consensus; final coding of the dataset to the complete codebook; and theme finalisation through team consensus.

The United Kingdom Parliament

N/A

Between the announcement (16/03/2016) – royal assent (26/04/2017), two themes were identified 1: SDIL welcomed cross-party 2: SDIL a good start but not enough. Between royal assent – implementation (5/04/2018), one theme was identified 3: The SDIL worked – what next? The final theme identified from implementation until 16/03/2020 was 4: Moving on from the SDIL.

After the announcement, the SDIL had cross-party support and was recognised to have encouraged reformulation prior to implementation. Lessons for governments indicate that the combination of cross-party support and a policy’s documented success in achieving its aim can help cement the resilience of it to opposition and threats of repeal.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.

Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.

Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.

Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Gene x environment (G×E) interactions, i.e. genetic modulation of the sensitivity to environmental factors and/or environmental control of the gene expression, have not been reliably established regarding aetiology of psychotic disorders. Moreover, recent studies have shown associations between the polygenic risk scores for schizophrenia (PRS-SZ) and some risk factors of psychotic disorders, challenging the traditional gene v. environment dichotomy. In the present article, we studied the role of GxE interaction between psychosocial stressors (childhood trauma, stressful life-events, self-reported discrimination experiences and low social capital) and the PRS-SZ on subclinical psychosis in a population-based sample.

Data were drawn from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, in which subjects without psychotic disorders were included in six countries. The sample was restricted to European descendant subjects (n = 706). Subclinical dimensions of psychosis (positive, negative, and depressive) were measured by the Community Assessment of Psychic Experiences (CAPE) scale. Associations between the PRS-SZ and the psychosocial stressors were tested. For each dimension, the interactions between genes and environment were assessed using linear models and comparing explained variances of ‘Genetic’ models (solely fitted with PRS-SZ), ‘Environmental’ models (solely fitted with each environmental stressor), ‘Independent’ models (with PRS-SZ and each environmental factor), and ‘Interaction’ models (Independent models plus an interaction term between the PRS-SZ and each environmental factor). Likelihood ration tests (LRT) compared the fit of the different models.

There were no genes-environment associations. PRS-SZ was associated with positive dimensions (β = 0.092, R2 = 7.50%), and most psychosocial stressors were associated with all three subclinical psychotic dimensions (except social capital and positive dimension). Concerning the positive dimension, Independent models fitted better than Environmental and Genetic models. No significant GxE interaction was observed for any dimension.

This study in subjects without psychotic disorders suggests that (i) the aetiological continuum hypothesis could concern particularly the positive dimension of subclinical psychosis, (ii) genetic and environmental factors have independent effects on the level of this positive dimension, (iii) and that interactions between genetic and individual environmental factors could not be identified in this sample.

23% of people experiencing a first episode of psychosis (FEP) develop treatment resistant schizophrenia (TRS). At present, there are no established methods to accurately identify who will develop TRS from baseline.

In this study we used patient data from three UK early intervention services (EIS) to investigate the predictive potential of routinely recorded sociodemographic, lifestyle and biological data at FEP baseline for the risk of TRS up to six years later.

We developed two risk prediction algorithms to predict the risk of TRS at 2-8 years from FEP onset using commonly recorded information at baseline. Using the forced-entry method, we created a model including age, sex, ethnicity, triglycerides, alkaline phosphatase levels and lymphocyte counts. We also produced a machine-learning-based model, including an additional four variables. The models were developed using data from two and externally validated in another UK psychosis EIS.

The development samples included 785 patients, and 1,110 were included in the validation sample. The models discriminated TRS well at internal validation (forced-entry: C 0.70, 95%CI 0.63-0.76; LASSO: C 0.69, 95%CI 0.63-0.77). At external validation, discrimination performance attenuated (forced-entry: C 0.63, 0.58-0.69; LASSO: C 0.64, 0.58-0.69) but recovered for the forced entry model after recalibration and revision of the lymphocyte predictor (C: 0.67, 0.62-0.73).

The use of commonly recorded clinical information including biomarkers taken at FEP onset could help to predict TRS. These measures should be considered in future studies modelling psychiatric outcomes.

No significant relationships.

The comorbidity between cardiometabolic and psychotic disorders develops early. This is a crucial window of opportunity to reduce excess morbidity and mortality. Recently, a cardiometabolic risk prediction algorithm for young people with psychosis, the psychosis metabolic risk calculator (PsyMetRiC) was developed and externally validated in the UK. However, its international transportability is unknown.

We performed the first international validation study of PsyMetRiC in Lausanne, Switzerland, and examined whether additional variables (clinical and/or genetic) may improve the predictive performance of the algorithm

We included people aged 16-35y with psychosis from the PsyMetab cohort, who did not have MetS at baseline, and who had 1-6y follow-up data. The PsyMetRiC partial (age, sex, ethnicity, body mass index, smoking status, and prescription of a metabolically-active antipsychotic) and full (also including high-density lipoprotein and triglycerides) algorithms were applied. Predictive performance was assessed using measures of discrimination (C-statistic) and calibration (calibration plots). Recalibration steps included refitting the intercept and/or slope if necessary. Additional variables (e.g. speed of weight gain, polygenic risk scores) were added to the model and predictive performance was reassessed.

We included 545 participants. The discrimination performance of both PsyMetRiC algorithms was good (C>0.75), and calibration plots showed good agreement between observed and predicted risk. Additional analyses to be conducted.

PsyMetRiC is likely to be generalizable for use in Switzerland, suggesting that PsyMetRiC may also be suitable for use in other European populations. While additional international validations are required, these findings are an encouraging step toward an international cardiometabolic risk prediction algorithm for young people with psychosis.

No significant relationships.