Evaluation of variation in special educational needs provision and its impact on health and education using administrative records for England: umbrella protocol for a mixed-methods research programme.

INTRODUCTION: One-third of children in England have special educational needs (SEN) provision recorded during their school career. The proportion of children with SEN provision varies between schools and demographic groups, which may reflect variation in need, inequitable provision and/or systemic factors. There is scant evidence on whether SEN provision improves health and education outcomes. METHODS: The Health Outcomes of young People in Education (HOPE) research programme uses administrative data from the Education and Child Health Insights from Linked Data-ECHILD-which contains data from all state schools, and contacts with National Health Service hospitals in England, to explore variation in SEN provision and its impact on health and education outcomes. This umbrella protocol sets out analyses across four work packages (WP). WP1 defined a range of 'health phenotypes', that is health conditions expected to need SEN provision in primary school. Next, we describe health and education outcomes (WP1) and individual, school-level and area-level factors affecting variation in SEN provision across different phenotypes (WP2). WP3 assesses the impact of SEN provision on health and education outcomes for specific health phenotypes using a range of causal inference methods to account for confounding factors and possible selection bias. In WP4 we review local policies and synthesise findings from surveys, interviews and focus groups of service users and providers to understand factors associated with variation in and experiences of identification, assessment and provision for SEN. Triangulation of findings on outcomes, variation and impact of SEN provision for different health phenotypes in ECHILD, with experiences of SEN provision will inform interpretation of findings for policy, practice and families and methods for future evaluation. ETHICS AND DISSEMINATION: Research ethics committees have approved the use of the ECHILD database and, separately, the survey, interviews and focus groups of young people, parents and service providers. These stakeholders will contribute to the design, interpretation and communication of findings.

Resting heart rate and antisocial behaviour: a Mendelian randomisation study.

Observational studies frequently report phenotypic associations between low resting heart rate (RHR) and higher levels of antisocial behaviour (ASB), although it remains unclear whether this relationship reflects causality. To triangulate evidence, we conducted two-sample univariable Mendelian randomisation (MR), multivariable MR and linkage disequilibrium score regression (LDSC) analyses. Genetic data were accessed from published genome-wide association studies (GWAS) for RHR (n = 458,835) and ASB (n = 85,359) for the univariable analyses, along with a third GWAS for heart rate variability (HRV; n = 53,174) for all other analyses. Genome-wide significant (p < 5 × 10-8) single-nucleotide polymorphisms associated with RHR (n = 278) were selected as instrumental variables and the outcome was a composite measure of ASB. No causal association was observed between RHR and ASB (BIVW = - 0.0004, p = 0.841). The multivariable MR analyses including RHR and HRV also suggested no causal associations (BIVW = 0.016, p = 0.914) and no genetic correlations between the heart rate measures and ASB were observed using LDSC (rg = 0.057, p = 0.169). Sensitivity analyses suggested that our results are not likely to be affected by heterogeneity, pleiotropic effects, or reverse causation. These findings suggest that individual differences in autonomic nervous system functioning indexed by RHR are not likely to directly contribute to the development of ASB. Therefore, previously observed associations between RHR and ASB may arise from confounding, reverse causation, and/or additional study characteristics. Further causally informative longitudinal research is required to confirm our findings, and caution should be applied when using measures of RHR in interventions targeting ASB.

Personalised interventions for subgroups of children with conduct problems.

BACKGROUND: Conduct problems are a range of disruptive behaviours in childhood that are associated with long-term adverse outcomes in adolescence and adulthood, including antisocial behaviour, substance misuse, and poor academic achievement. Children with conduct problems can vary according to age of onset, comorbidities, and environmental factors, and it has been suggested that certain groups of children may have different treatment outcomes. Therefore, it is important to assess the extent to which personalised interventions for different groups of children with conduct problems may affect outcomes. To our knowledge, this is the first review to systematically identify and appraise the effectiveness of personalised interventions, adapted, or developed, for prespecified subgroups of children with conduct problems. OBJECTIVES: To assess whether personalised interventions, adapted or developed for subgroups of children with conduct problems are effective in improving outcomes. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search was 1 February 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs), in any setting, in children (aged two to 12 years) with conduct problems and within a prespecified subgroup, comparing a personalised intervention with a non-personalised intervention, waitlist control, or treatment as usual. Personalised interventions included adaptations to standard practice, such as parent-training programmes; other recommended interventions for children with conduct problems; or interventions developed specifically to target subgroups of children with conduct problems. We excluded non-personalised and non-psychological interventions (e.g. pharmacological or dietary intervention). Prespecified subgroups of children with conduct problems, however defined, were eligible for inclusion. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcomes were 1. child conduct problems or disruptive behaviour and 2. ADVERSE EVENTS: Our secondary outcomes were 3. personalised treatment outcomes relevant to each subgroup, 4. parenting skills and knowledge, 5. family functioning, engagement and decreased dropout, and 6. educational outcomes. We used GRADE to assess the certainty of the evidence. MAIN RESULTS: We identified 13 RCTs (858 participants). Seven studies were conducted in the USA, five in Australia, and one in Germany. Eleven studies reported their source of funding, with five studies receiving grants from the National Institute of Mental Health. In total, 15 different funders supported the studies included in the review. We separated subgroups of children with conduct problems into three broad categories: children with co-occurring conditions (e.g. emotional difficulties), parent characteristics (e.g. conflict between parents), or familial/environmental circumstances (e.g. rural families). All studies delivered a personalised intervention that was adapted or developed for a prespecified subgroup of children with conduct problems. We rated all trials at unclear or high risk of bias in most domains. Below, we report the results of improvement in child conduct problems and disruptive behaviour, personalised treatment outcomes, and parenting skills and knowledge for our main comparison: personalised versus non-personalised interventions. Improvement in child conduct problems and disruptive behaviour Compared with a non-personalised intervention, a personalised intervention may result in a slight improvement in child conduct problems or disruptive behaviour measured using the Eyberg Child Behavior Inventory (ECBI) Problem subscale in the short term (mean difference (MD) -3.04, 95% confidence interval (CI) -6.06 to -0.02; 6 studies, 278 participants; P = 0.05), but may have little to no effect on improving child conduct problems or disruptive behaviour measured by the ECBI Intensity subscale (MD -6.25, 95% CI -16.66 to 4.15; 6 studies, 278 participants; P = 0.24), or the Externalising subscale of the Child Behaviour Checklist (CBCL) (MD -2.19, 95% CI -6.97 to 2.59; 3 studies, 189 participants, P = 0.37) in the short term. We graded the certainty of evidence as very low for all three outcomes, meaning any estimate of effect is very uncertain.  Personalised treatment outcomes, relevant to each subgroup Although six studies reported personalised treatment outcomes, relevant to each subgroup, we were unable to pool the data due to differences between the measures used in the studies and the heterogeneity this would produce in analysis. The results for this outcome were inconclusive. Parenting skills and knowledge Although seven studies reported parenting skills and knowledge, we were unable to pool the data due to differences between the measures used in the studies and the heterogeneity this would produce in analysis. The results for this outcome were inconclusive.  Adverse events None of the trials reported monitoring adverse events. Summary of results In summary, there is limited evidence that personalised intervention improves child conduct problems, personalised treatment outcomes, relevant to each subgroup, or parenting skills and knowledge compared with a non-personalised intervention. AUTHORS' CONCLUSIONS: There is limited evidence for the effectiveness of personalised interventions for subgroups of children with conduct problems. The certainty of evidence for all outcomes was very low, meaning that we have very little confidence in the estimated effects and the true effects may be different to our findings, which will limit the relevance of our findings to clinical decisions. To overcome the limitations of the evidence, large-scale RCTs are needed to determine whether personalised interventions, adapted or developed, for subgroups of children with conduct problems are effective in improving outcomes. Consensus on the most appropriate measures to use in these studies is needed in order to facilitate cross-study comparisons. Persistent conduct problems predict a range of adverse long-term outcomes, so future research should investigate the medium- and long-term effects of personalised treatments. Studies are needed in low- and middle-income countries as well as studies recruiting children aged between nine and 12 years, as they were under-represented in the studies.

Childhood Maltreatment and Mental Health Problems: A Systematic Review and Meta-Analysis of Quasi-Experimental Studies.

OBJECTIVE: Childhood maltreatment is associated with mental health problems, but the extent to which this relationship is causal remains unclear. To strengthen causal inference, the authors conducted a systematic review and meta-analysis of quasi-experimental studies examining the relationship between childhood maltreatment and mental health problems. METHODS: A search of PubMed, PsycINFO, and Embase was conducted for peer-reviewed, English-language articles from database inception until January 1, 2022. Studies were included if they examined the association between childhood maltreatment and mental health problems using a quasi-experimental method (e.g., twin/sibling differences design, children of twins design, adoption design, fixed-effects design, random-intercept cross-lagged panel model, natural experiment, propensity score matching, or inverse probability weighting). RESULTS: Thirty-four quasi-experimental studies were identified, comprising 54,646 independent participants. Before quasi-experimental adjustment for confounding, childhood maltreatment was moderately associated with mental health problems (Cohen's d=0.56, 95% CI=0.41, 0.71). After quasi-experimental adjustment, a small association between childhood maltreatment and mental health problems remained (Cohen's d=0.31, 95% CI=0.24, 0.37). This adjusted association between childhood maltreatment and mental health was consistent across different quasi-experimental methods, and generalized across different psychiatric disorders. CONCLUSIONS: These findings are consistent with a small, causal contribution of childhood maltreatment to mental health problems. Furthermore, the findings suggest that part of the overall risk of mental health problems in individuals exposed to maltreatment is due to wider genetic and environmental risk factors. Therefore, preventing childhood maltreatment and addressing wider psychiatric risk factors in individuals exposed to maltreatment could help to prevent psychopathology.

Risk factors for disruptive behaviours: protocol for a systematic review and meta-analysis of quasi-experimental evidence.

INTRODUCTION: Disruptive behaviour disorders, including oppositional defiant disorder and conduct disorder, are a common set of diagnoses in childhood and adolescence, with global estimates of 5.7%, 3.6% and 2.1% for any disruptive disorder, oppositional defiant disorder and conduct disorder, respectively. There are high economic and social costs associated with disruptive behaviours and the prevalence of these disorders has increased in recent years. As such, disruptive behaviours represent an escalating major public health concern and it is important to understand what factors may influence the risk of these behaviours. Such research would inform interventions that aim to prevent the development of disruptive behaviours. The current review will identify the most stringent evidence of putative risk factors for disruptive behaviour from quasi-experimental studies, which enable stronger causal inference. METHODS AND ANALYSIS: The review will be carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. An electronic search of references published between 1 January 1980 and 1 March 2020 will be conducted using Medline, Embase, PsycINFO and Web of Science. Initial abstract and title screening, full-text screening and data extraction will be completed independently by two reviewers using Evidence for Policy and Practice Information (EPPI)-Reviewer 4 software. Quasi-experimental studies in the English language examining the association between any putative risk factor and a clearly defined measure of disruptive behaviour (eg, a validated questionnaire measure) will be included. We will conduct meta-analyses if we can pool a minimum of three similar studies with the same or similar exposures and outcomes. ETHICS AND DISSEMINATION: The proposed review does not require ethical approval. The results will help to identify risk factors for which there is strong evidence of causal effects on disruptive behaviours and also highlight potential risk factors that require further research. The findings will be disseminated via publication in a peer-reviewed scientific journal and through presentations at international meetings and conferences. PROSPERO REGISTRATION NUMBER: CRD42020169313.

Acute anxiety and social inference: An experimental manipulation with 7.5% carbon dioxide inhalation.

BACKGROUND: Positive self-bias is thought to be protective for mental health. We previously found that the degree of positive bias when learning self-referential social evaluation decreases with increasing social anxiety. It is unclear whether this reduction is driven by differences in state or trait anxiety, as both are elevated in social anxiety; therefore, we examined the effects on the state of anxiety induced by the 7.5% carbon dioxide (CO2) inhalation model of generalised anxiety disorder (GAD) on social evaluation learning. METHODS: For our study, 48 (24 of female gender) healthy volunteers took two inhalations (medical air and 7.5% CO2, counterbalanced) whilst learning social rules (self-like, self-dislike, other-like and other-dislike) in an instrumental social evaluation learning task. We analysed the outcomes (number of positive responses and errors to criterion) using the random effects Poisson regression. RESULTS: Participants made fewer and more positive responses when breathing 7.5% CO2 in the other-like and other-dislike rules, respectively (gas × condition × rule interaction p = 0.03). Individuals made fewer errors learning self-like than self-dislike, and this positive self-bias was unaffected by CO2. Breathing 7.5% CO2 increased errors, but only in the other-referential rules (gas × condition × rule interaction p = 0.003). CONCLUSIONS: Positive self-bias (i.e. fewer errors learning self-like than self-dislike) seemed robust to changes in state anxiety. In contrast, learning other-referential evaluation was impaired as state anxiety increased. This suggested that the previously observed variations in self-bias arise due to trait, rather than state, characteristics.