BACKGROUND:School absence is associated with mental health problems in adolescents, but most studies are cross-sectional. Longitudinal studies where school absence precedes mental health problems are needed to infer whether school absence is associated with later mental health problems. We aimed to investigate the association between school absence among 14- to 15-year-olds and later mental health problems at ages 16-17 in England. METHODS:A retrospective cohort study using an existing linkage between the Millennium Cohort Study (MCS) and the National Pupil Database (NPD), representing 8438 adolescents. We explored different absence thresholds and used logistic regression to examine associations between school absence and later mental health problems. RESULTS:A threshold of >10% of half-day school sessions missed identified 18% of adolescents who reported mental health problems at follow-up. At this threshold, high school absence was associated with increased odds of later mental health problems after adjusting for covariates (girls = 1.44, 95% CI 1.05-1.98; boys OR = 1.49, 95% CI 1.04-2.13). The strength of associations between absence and later mental health problems increased with longer durations of absence. CONCLUSION:We found a longitudinal association between high levels of school absence (>10% of sessions) and later mental health problems in a nationally representative sample of adolescents in England. High levels of school absence can be used as an early marker of increased risk of mental health problems in the general population. School absence may contribute to the development of later mental health problems in adolescents.

Introduction Schools worldwide balance whole-class teaching with additional provision for children with special educational needs or disability (SEND). Robust evidence on equity and effectiveness of SEND provision is essential to address growing demand and rising costs globally. Objectives To synthesise findings from the Health Outcomes for young People throughout Education (HOPE) evaluation of variation in SEND provision and its impact on health and education outcomes in English primary schools. We integrated findings from 14 sub-studies using administrative data in the Education and Child Health Insights from Linked Data (ECHILD) database and 10 mixed methods sub-studies. Methods Analyses of ECHILD data followed children from birth to age 11 years. We examined how variation in SEND provision was associated with health conditions, and school, social and organisational factors. Using target trial emulation, we estimated the impact of SEND provision on hospital admissions, school absences and attainment. We surveyed and interviewed young people, parents, and professionals and reviewed information about services to understand SEND processes and contexts. Results Of 3.8 million children born 2004 to 2013, 30% had SEND provision recorded by age 11. Health conditions were only partially associated with SEND provision, which was also related to male gender, social disadvantage, low attainment and type of school. SEND provision modestly reduced rates of unauthorised absences in subgroups of children but showed no measurable benefit on hospital admissions or school attainment. Mixed methods studies highlighted benefits of early, responsive support, challenges posed by limited capacity, harms caused by delayed or inadequate provision, and need for parent advocacy to access SEND provision. Discussion Weak evidence of benefits of SEND provision in causal analyses likely reflects unmeasured confounding, lack of measures of provision received and insensitive outcomes in ECHILD data. SEND policies need robust evidence from analyses across jurisdictions using administrative data, enhanced with better measures, experimental methods and contextual evaluation.

Background:Little is known about the provision of diagnoses to young people with mental health disorders. We investigated diagnosis provision by NHS mental health services, focusing on 17-year-olds in South London between 2009-2024, and compared with estimated disorder prevalence. Methods:To examine diagnosis provision in the population, we extracted diagnosis data from records of the NHS mental healthcare provider serving South London, using the Maudsley Biomedical Research Centre Clinical Record Interactive Search application; we then compared these data with the corresponding population size, obtained from the Office for National Statistics. To assess diagnosis provision in those with mental health disorders, we compared diagnosis data with the number of young people estimated to have met criteria for a disorder, derived from epidemiological interview data collected in the Environmental Risk (E-Risk) Longitudinal Twin Study and weighted according to characteristics of 17-year-old South Londoners. To assess diagnosis provision in those with mental health disorders within health services, we compared diagnosis data with the number estimated to have met criteria for a disorder and used any health service for their mental health, again derived from weighted E-Risk Study data. Findings:Of 17-year-olds from South London in 2009-2024, 4.0% (n=8,958/223,404) had a diagnosis in mental health records during the previous year. This diagnosis provision covered <1 in 16 of those estimated to have had a mental health disorder, and <1 in 4 of those estimated to have also used health services. Diagnosis provision was lower in girls than boys and in young people with Black/Asian/Mixed/Other ethnicity than those with White ethnicity, in those estimated to have had a mental health disorder and used health services. Interpretation:These findings demonstrate gaps and biases in mental health diagnosis provision for young people, including within health services, and reveal the imperative need to strengthen young people's mental healthcare. Funding:National Institute for Health Research, Medical Research Council, National Institute of Child Health and Development, Jacobs Foundation, National Society for Prevention of Cruelty to Children, Economic and Social Research Council, Prudence Trust, Wellcome Trust. RESEARCH IN CONTEXT:Evidence before this study: Epidemiological research has found that less than half of young people with a mental health disorder report seeing a health professional for their symptoms and only a quarter to a third have seen a mental health specialist, and these findings are fairly consistent across high-income countries where this research has been conducted. For young people who see health professionals, there are likely to be barriers to the recognition and treatment of mental health disorders. We focused on the recognition of mental health disorders in young people, which is operationalised in clinical practice as provision of diagnoses. To identify studies examining mental health diagnosis provision in young people accessing health services, we searched MEDLINE with the terms "diagnos*" AND ("mental" OR "psychiatr*" OR [various terms for individual disorders]) AND ("young" OR "youth*" OR "child*" OR "adolescen*" OR "paedatric*" OR "pedatric*" OR "juvenile") AND ("clinical" OR "healthcare" OR "health care" OR "service*"). This search was supplemented by reviewing reference lists and forward citations of relevant articles. We identified several studies that found diagnosis provision varied by sociodemographic characteristics and has increased over the past two decades in young people across multiple countries for several disorders, including depression, anxiety disorders, eating disorders, autism, and attention-deficit/hyperactivity disorder (ADHD). Only a small number of studies investigated diagnosis provision within young people who met criteria for a disorder. In the Avon Longitudinal Study of Parents and Children in the UK, of 18-year-olds who met criteria for depression, only 7.0% had a diagnosis of depression documented in their primary care records. In the Child and Adolescent Twin Study in Sweden, of 9-year-olds who met criteria for ADHD, only 18.5% of boys and 12.1% of girls had a diagnosis of ADHD noted in their health records. Within an Irish child and adolescent mental health service, of 12-15-year-olds who met criteria for depressive disorder, only 28.4% received a depressive disorder diagnosis after their usual clinical assessment. These studies suggest large gaps in diagnosis provision, including within health services, and highlight possible bias by sociodemographic characteristics. A better understanding of this topic is needed to enable more effective service planning, commissioning, and policymaking.Added value of this study: This study investigated mental health diagnosis provision in 17-year-olds from South London. We examined diagnosis provision for several mental health disorders in NHS mental healthcare records. We compared these data with population and epidemiological data to calculate diagnosis provision rates in the general population, in those estimated to have met criteria for a disorder, and in those estimated to have also seen a health professional. We found that diagnosis provision substantially increased during our study period of 2009-2024, demonstrating an increase in the number of young people whose mental health needs were recognised in specialist services. However, we estimated that diagnoses were only provided to a small proportion of young people with a mental health disorder, including those within health services. Estimated diagnosis gaps were largest for those with generalised anxiety disorder and multiple disorders. We also found evidence of biases in diagnosis provision, based on gender, neighbourhood deprivation, and ethnicity.Implications of all the available evidence: Barriers to mental healthcare access for young people should be reduced by policymakers and commissioners, including through investment in adequately staffed services with skilled clinicians, enabling more young people with mental health disorders to receive cost-effective evidence-based healthcare that has long-term benefits. Greater awareness among clinicians of the under-diagnosis and bias in diagnosis of young people's mental health disorders, alongside strategies to address these problems, could improve young people's mental healthcare. Innovative scalable interventions that can reach many more young people need to be developed, evaluated, and implemented by researchers. Prevention strategies are also required, including addressing risk factors for young people's mental health disorders, and intervening early for those with symptoms before disorders develop, to reduce the future burden of mental health disorders in young people.

Introduction Amid growing global concern about child and adolescent mental health problems and their long-term consequences, research in this area is increasingly critical. Population-representative datasets are valuable resources for addressing these challenges. The Mental Health of Children and Young People (MHCYP) 2017 survey was designed to meet this need in England. Methods The 2017 survey included 9117 children and young people aged 2 to 19 years. Information was collected from parents or carers (hereafter referred to as 'parents'), and for those aged 11 years or over, directly from the young people themselves, as well as from teachers. The baseline assessment used the standardised Development and Wellbeing Assessment (DAWBA), based on ICD-10 and DSM-5 diagnostic criteria. The subsequent waves in 2020, 2021, 2022 and 2023, measured mental health difficulties using the Strengths and Difficulties Questionnaire (SDQ). Results The MHCYP 2017 survey and its follow-up waves provide population-representative data on children and adolescents in England, encompassing a range of mental health disorders and difficulties---from eating disorders and attention and hyperactivity disorder to depression and anxiety, with longitudinal data on mental health, social situation and activities during the Covid-19 pandemic. It builds on earlier UK representative surveys conducted in 1999 and 2004. Conclusion Together with the 1999 and 2004 surveys, this dataset offers a unique opportunity to investigate trends in mental health disorders among young people, assess associated difficulties and comorbidities, and explore links with socio-economic factors. The MHCYP 2017 survey and follow-ups offer valuable cross-sectional data for understanding child and adolescent mental health trends in the UK, with longitudinal data from four subsequent surveys conducted between 2020 and 2023.

Background:Children and young people with pre-existing mental health and neurodevelopmental conditions may have experienced heterogeneous mental health impacts during the COVID-19 pandemic, but what facts may explain these variations are still unclear. We aimed to examine variations in the longitudinal trajectories of emotional and behavioural symptoms before and during the COVID-19 pandemic in the United Kingdom (UK). Methods:We used a novel nested clinical cohort study, linking the Maudsley Child and Young People Health and Experience Research (CYPHER) survey and electronic health records (EHRs) data of mental health service users (aged 5-17 years old) in South London and Maudsley NHS Foundation Trust, UK, on 1 June 2020 (n = 388). Composite emotional and behavioural scores, including internalising and externalising symptoms, were assessed in June-September 2020 and February-March 2021 by the Maudsley CYPHER survey and the Strengths and Difficulties Questionnaire from EHRs was used to supplement data pre-pandemic (2019-March 2020) and during the pandemic (2020 and 2021). Sociodemographic characteristics and diagnoses were extracted from EHRs. Relative symptom trajectories were modelled with predictors using linear mixed models. Results:Relative emotional and behavioural symptoms were not significantly different from pre-pandemic to 2021, but variations were found across predictors. Those who were female (vs. male; b = 0.19, 95% CI 0.02 to 0.36), lived in deprived neighbourhoods (vs. non-deprived; b = 0.19, 95% CI 0.03 to 0.36), and had a diagnosis of autism (vs. emotional disorder; b = 0.33, 95% CI 0.13 to 0.53) had relatively higher emotional symptoms pre- and during pandemic. Those who were Black (vs. White; b = -0.48, 95% CI -0.82 to -0.14) or who did not state their ethnicity (b = -0.47, 95% CI -0.82 to -0.12) had relatively higher decreases in emotional symptoms between pre-pandemic and 2020. Those who had a diagnosis of intellectual disability (vs. without) had greater relative decrease in emotional symptoms between pre-pandemic and 2020 (b = -0.94, 95% CI -1.60 to -0.28) and 2021 (b = -2.02, 95% CI -2.46 to -1.58). Those who were younger (vs. older; b = -0.03, 95% CI -0.06 to -0.01) and had a diagnosis of autism (vs. emotional disorder; b = 0.40, 95% CI 0.20 to 0.60) or attention-deficit hyperactivity disorder (vs. emotional disorder; b = 0.43, 95% CI 0.19 to 0.66) had relatively higher behavioural symptoms pre- and during pandemic. Conclusion:Emotional and behavioural symptoms were high and relatively stable across pre- and during pandemic timepoints. Relatively worse emotional and behavioural symptoms were observed in children and young people who were younger, female, lived in deprived neighbourhoods, and had a diagnosis of a neurodevelopmental condition. However, some effects might reflect distinctive features between groups rather than pandemic-specific differences. Future research should examine longer-term mental health impacts of the pandemic across clinical groups and potential mechanisms of change.

When thoroughly assessed, the prevalence of attention-deficit hyperactivity disorder (ADHD) in children/adolescents is estimated at 5%. There is no evidence that ADHD is over-diagnosed in the UK. Indeed, available data point to under-diagnosis, even though rigorous updated post-COVID-19 pandemic data are not available. Some cases may be misdiagnosed due to low-quality assessment, poor adherence to national guidance or inappropriate differential diagnosis. Beyond the controversy around over- or under-diagnosis and over-medicalisation of ordinary behaviours or emotions, the main issue is that UK clinical services cannot adequately support individuals with ADHD who need help. There is a risk that the narrative claiming 'ADHD is over-diagnosed' could be used to deny people with properly-diagnosed ADHD the care they deserve.

The COVID-19 pandemic may have amplified existing inequalities and disproportionately impacted the mental health of children and young people (CYP) with pre-existing mental health and neurodevelopmental conditions. Evidence suggests the mental health impact on this clinical group was heterogeneous, but the role of ethnicity and socioeconomic position on longitudinal mental health outcomes is unclear. This systematic review investigates the longitudinal association between ethnic and socioeconomic inequalities and the mental health outcomes of CYP with pre-existing conditions during the pandemic. OVID Medline, EMBASE, APA PsycInfo, and Global Health databases were searched between January 2020 and November 2025 (PROSPERO CRD42024611865). Eligible papers included longitudinal studies that assessed mental health outcomes at multiple timepoints before and/or during the pandemic in CYP with pre-existing conditions and examined the effect of ethnicity and socioeconomic position on outcomes. Included studies were narratively synthesised. Ten studies (N = 3,887) were included. We found evidence that CYP from lower income brackets and who experienced financial hardship reported greater levels of internalising, neurodevelopmental, post-traumatic stress, and obsessive-compulsive symptoms. Weak associations were found between ethnicity and internalising symptoms. However, the findings were inconsistent across mental health outcomes, timepoints, and ethnic and socioeconomic position groups. There is some evidence for the association between lower socioeconomic position and increased mental health outcomes in CYP with pre-existing conditions during the pandemic. Further robust longitudinal research is warranted to examine the long-term consequences of the pandemic to better understand how ethnic and socioeconomic inequalities contribute to mental health outcomes.

As digital mental health research and technology continue to grow, a systematic approach to quickly and safely translating digital innovation into Child and Adolescent Mental Health Services (CAMHS) is needed. Here, we provide an overview of the CAMHS Digital Lab, a service in London, United Kingdom, which integrates operational, clinical and research expertise to support digital discovery and translate research into practice. The service is organized into four workstreams: Population and clinical analytics; Data science and discovery; Digital therapeutics and assessment; and Education, outreach and training. This service provides a model for integrating digital innovation into mental health services which could be adopted elsewhere.

Understanding predictors of offending is essential for developing effective crime prevention. Educational attainment is a readily available metric for pupils in many countries, with performance on standardised tests often systematically collected throughout school. If changing attainment is associated with offending risk, it could present a signal to check in with pupils and offer appropriate support. We analysed an existing linkage between the National Pupil Database and the Police National Computer in England. In a cohort of 4.3 million pupils born between the academic years 1990/91 and 1996/97, we modelled trajectories of standardised attainment on statutory tests at ages 7, 11 and 16 years. We then investigated the association between these attainment trajectories and subsequent first offence convictions or cautions during young adulthood. Among pupils showing relative declines in attainment over their school career, 1 in 3 were convicted or cautioned for a first offence before the end of school, and 1 in 10 were convicted or cautioned for a first offence during young adulthood. Additionally, among pupils who performed at below average levels towards the beginning of school, their odds of offending during young adulthood were 53

The Twins Early Development Study (TEDS) is a longitudinal population study of over 10,000 twin pairs born in England and Wales between 1994 and 1996. As the twins enter their thirties, a primary focus of TEDS is to better understand the development of common physical and mental health problems and the relationship with the different social milestones of adulthood (e.g., employment, partnerships, and/or parenthood). With over 30 years of prospectively collected questionnaire and genetic data, the study is uniquely placed to answer questions about the health challenges facing young adults today. Incorporating linked medical records with the existing research data will provide a different data perspective on our twin's health status and outcomes and support more equitable research by helping to address both response and attrition bias. This article provides an overview of the protocol to link TEDS participants to electronic health records collected by the UK National Health Service (NHS). It will outline the linkage process, characterize the available linked study sample and NHS datasets, and describe the legal basis for this work.

Background The longitudinal relationship between school absence and mental health has important policy implications; if school absence predicts later mental health problems, it could be used to identify young people at increased risk and enable further assessment, prevention, and early intervention. Methods We analysed an existing data linkage between the National Pupil Database and healthcare records representing a sample of 47,926 young people aged 11-15 in the UK. We used logistic regression to examine the longitudinal association between persistent school absence (defined by the Government Department for Education in England as missing more than 10% of available school sessions) and later contact with secondary care mental health services. We also compared the sensitivity and positive predictive value of the >10% absence threshold to alternative thresholds for predicting adverse mental health outcomes. Results At the currently applied threshold of >10%, persistent school absence was associated with 2.77 (95% CI 2.33-3.30, girls) and 1.58 (95% CI 1.29-1.95, boys) times the odds of accepted referral to secondary care mental health services in the following year, after adjustment for sociodemographic and educational factors. The absolute risk difference for girls was 4.7% (95% CI 3.9-5.4) and for boys, 2.8% (95% CI 2.1-3.4). Compared to other thresholds, the >10% absence threshold provided a good balance between sensitivity (40.5%), positive predictive value (5.5%), and identifying a manageable proportion of young people as high risk (18%). Conclusion The longitudinal relationship between school absence and later secondary care mental health service contact suggests that school absence may be a useful marker for educators to identify children in need of support. The >10% absence threshold used in education policy in England may also serve as a useful marker of later mental health risk in other national policy contexts.

Evidence of disparities in special educational needs and disability (SEND) provision at local authority (LA) level in England is needed to guide policies for equitable provision. We described LA-level variation in recorded SEND provision using linked health-education records. We used linked hospital-primary school records (ECHILD - Education and Child Health Insights from Linked Data) to create a cohort of 3 729 265 children born in England between 2003/04-2012/13. LA of pupil's residential address and SEND provision [SEND support or Educational Health and Care Plan (EHCP)] were defined at Year 1 (5/6 years old). We compared single-level and multilevel logistic models, adjusting for individual-level sociodemographic, health indicators, and school governance, and stratifying by gestational age. In further multilevel models, we added LA characteristics. After accounting for individual-level characteristics, there was between 2.0% (SEND support compared with no SEND provision) and 5.8% (EHCPs compared with SEND support) residual unexplained variation between LAs across gestational age groups. Adding LA-level income deprivation reduced the between-LA variance for EHCPs by 14%-24% across gestational age groups; less so for other LA characteristics. Under 6% of the differences in school-recorded SEND provision in Year 1 between 2009/10 and 2018/19 was associated with the LA context. We need to carefully disentangle structural factors at the school and individual level to understand inequities in recorded SEND provision.

Anxiety and depression are increasingly prevalent among young people and significantly impact their lives. However, research on the referral pathways into Child and Adolescent Mental Health Services (CAMHS) for young people with these disorders, and how these pathways vary according to socio-demographic characteristics, remains limited. Moreover, few studies have examined whether educational factors are associated with these referral pathways. Therefore, this study aimed to examine the relationships of sociodemographic and educational characteristics with CAMHS referral pathways for anxiety disorders and depression. We used routinely collected educational data linked with CAMHS records from South London and Maudsley NHS Foundation Trust, focusing on young people aged 12–17 years with clinical diagnoses of anxiety disorders and depression (N = 4,169). Using multinominal logistic regression, we identified that referral pathways to CAMHS are associated with various sociodemographic and educational factors. Specifically, youth with lower educational attainment, school exclusion, or SEN status, were more likely to be referred to CAMHS through education. This suggests that educational services may be a key referral pathway for young people in need of mental health support for anxiety and/or depression and referring to CAMHS. However, Black young people, those who speak English as an additional language (EAL), individuals eligible for free school meals (FSM), and young people under the care of local authorities were more likely to be referred via social care or youth justice services. Also, older young people, females and those under the care of local authority showed a higher likelihood of being referred via emergency services rather than primary care. These findings highlight that efforts to identify problems earlier through primary care or education services could benefit for those young people who are more frequently referred via emergency or social care/youth justice routes. Further research is needed to examine the potential under-utilisation of certain referral pathways by specific groups, in order to improve accessibility and ensure that more young people can access effective mental health care.

Caregivers’ expressed emotion (EE) when speaking about their children has been shown to predict their children’s future mental health. However, these measures are rarely used in clinical settings or large cohort studies because manually rating EE is resource intensive. Here, we describe the development of an automated EE analysis tool. We assessed its predictive validity for mental health outcomes, as well as provide an initial evaluation of possible socioeconomic bias encoded in the automated tool. Data were provided by the UK-based Environmental Risk (E-Risk) Longitudinal Twin Study. We analysed ratings of negativity from ‘Five-Minute Speech Samples’ provided by mothers when children were aged 10. From a subset of 240 speech samples, text was extracted using automatic speech recognition, then acoustic and textual features were extracted utilising automated speech and language processing tools. Finally, machine learning models were trained to code maternal speech into negativity classifications (low vs elevated). The accuracy of automated negativity classifications compared to human-rated negativity classifications was tested across socio-economic strata divided into tertiles (low/medium/high). The associations between automated and human-rated negativity classifications and children’s age-18 mental health outcomes were also examined. Automated models of age-10 maternal EE showed medium levels of accuracy (0.65-0.67), with the highest-performing acoustic-textual fusion model demonstrating accuracy of 0.65, an F1-score of 0.63, and a harmonic mean of 0.64. Training models on manually-transcribed text did not enhance model performance. Scores generated by the highest-performing automated model had a similar magnitude of association with age-18 mental health outcomes to human-rated classifications. Automated negativity classifications were significantly more accurate amongst parents with mid-level socio-economic status than low or high socioeconomic status (χ2(2)=7.925, p=0.019). These preliminary findings indicate that automated methods of coding maternal EE from speech samples show promise for applications to large-scale epidemiological studies, but require increased accuracy before use in clinical settings. Moreover, replication is needed as well as detailed investigations into the impact of socio-economic status on automated speech coding accuracy.

Background: There is growing evidence that air pollution may impact mental health, however this is the first study to investigate its role in child and adolescent community mental health service use. Methods: This retrospective cohort study used electronic health records from a large South London mental healthcare provider to establish a cohort of young people first in contact with community mental health services between 2008 and 2012, who were then followed for up to 9 years. Baseline (3-month) residential nitrogen dioxide (NO2), particulate matter (PM)10 and PM2.5 exposure was estimated using the KCL urban model. Contacts over 1-, 5-, and 9-year periods were analysed in relation to air pollution using negative binomial regression. The potential effect-modifying role of high vs low greenspace exposure (residential normalised difference vegetation index) and age-, gender-, ethnicity- and disorder-specific differences were investigated using subgroup analyses. Findings: The sample consisted of 11,773 children and adolescents (3-17 years) who had first face-to-face contact with mental health services between 2008 and 2012. Consistent positive associations were observed between air pollution exposure and number of community mental health service (CMHS) contacts. For example, by Year 9 a clear dose-response pattern was evident between NO2 exposure and CMHS contacts, with an adjusted incidence rate ratio of 1.17 (95% CI=1.09 to 1.26) for service users in the highest quartile of exposure compared to the lowest quartile. Population Attributable Fractions (PAFs) suggested that bringing UK air quality in line with WHO recommendations could reduce CMHS contacts by 3-6%. Associations were most pronounced for boys and children (3-12 years) and were substantially attenuated in those living near high levels of greenspace. Interpretation: Residential air pollution exposure was associated with increased community mental health service contacts in children and adolescents, attenuated by high greenspace exposure, suggesting that policy changes acting on air quality and green infrastructure in urban settings could improve population-level mental health and reduce current strain on child and adolescent mental health services.

With rising referrals to child and adolescent mental health services (CAMHS), patient- and caregiver-facing digital platforms could streamline service delivery and research. With South London and Maudsley NHS Foundation Trust and King’s College London, the CAMHS Digital Lab developed myHealthE, a digital platform for families to access advice and support from the point of referral to CAMHS in South London, submit routine outcome measures, and consent to be contacted about relevant research studies. This secondary analysis descriptively summarised data from n=10,151 families under CAMHS invited to register on myHealthE between 2021 and 2023. Referral details, demographic and clinical characteristics were derived via the Clinical Record Interactive Search. myHealthE engagement was measured using Google Analytics. Routine outcome measures (particularly the Strengths and Difficulties Questionnaire [SDQ]) were collected via myHealthE. Of the invited families, 87.1% registered on myHealthE, and 85.4% completed at least one SDQ via the platform during their care episode. Overall, families completed n=29,906 SDQs during their episode of CAMHS support, mostly via myHealthE (93.2%) rather than conventional pen-and-paper methods (6.8%). Families engaged with resources on myHealthE, with 7,900 views of ‘Your Referral’ and ‘Information While You Wait’ pages over six-months. The platform also increased capacity for research recruitment, with 65.5% of families who consented for research contact over a 12-month period doing so via myHealthE. myHealthE provides a valuable tool for patients, caregivers, clinicians and researchers. Such platforms can fulfil multiple functions. This is advantageous for both informing clinical service delivery, and for conducting research.

Background Children and young people (CYP) with neurodevelopmental diagnoses such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have high child and adolescent mental health service (CAMHS) needs. Mood instability is a common and impairing emotion dysregulation-related symptom linked to increased adult psychiatric service use; however, its role in CAMHS trajectories remains unclear. We aimed to examine whether baseline mood instability was significantly associated with time to discharge and annual CAMHS use in CYP with ASD and/or ADHD.Methods We applied natural language processing (NLP) to extract mentions of mood instability within 3 months of ASD or ADHD index diagnosis from electronic health records of 21 906 CYP referred to CAMHS between 2008 and 2022. We used accelerated failure time models and negative binomial regression to assess associations between baseline mood instability and time to discharge and annual CAMHS use, adjusting for clinical and sociodemographic confounders.Findings Mood instability was associated with increased annual CAMHS use across ASD (adjusted incidence rate ratio (aIRR) 1.24, 95% CI 1.08 to 1.42), ADHD (aIRR 1.47, 95% CI 1.30 to 1.67) and ASD+ADHD (aIRR 1.27, 95% CI 1.12 to 1.44) groups. While mood instability had no significant effect on discharge timelines in autistic children with or without ADHD, it was linked to reduced time to discharge in the ADHD group (aTR 0.76, 95% CI 0.69 to 0.84). Associations were most pronounced in those not receiving ADHD medication in the ADHD group (aIRR 1.67, 95% CI 1.47 to 1.89; aTR 0.70, 95% CI 0.61 to 0.79).Conclusions Mood instability was significantly associated with elevated CAMHS use in CYP with neurodevelopmental conditions, with differential effect across diagnostic groups. This may reflect both variations in clinical expression of mood instability and configuration of neurodevelopmental CAMHS provision.Clinicalimplications These findings suggest the importance of assessing emotion dysregulation in care planning and pathway allocation in neurodevelopmental CAMHS. NLP offers a time- and cost-efficient approach to surface and structure clinical data from electronic CAMHS records for scalable clinical research on complex constructs such as mood instability.

BACKGROUND:Mental health conditions account for 18% of years lived with disability worldwide. 1-in-6 adults are affected in England, with most mental health conditions beginning in childhood and adolescence. Mental distress and ill health are unequally distributed in the UK, with strong associations with wider determinants of health, and higher prevalence among systemically disadvantaged groups. Currently, there is a lack of evidence to inform effective and timely policymaking for primary prevention in the UK. METHODS:In recognition of these challenges, a national Population Mental Health (PMH) Consortium was established, as part of Population Health Improvement UK (PHIUK). PHIUK is a national research network which works to transform health and reduce inequalities through change at the population level. Our aim is to establish an interdisciplinary PMH Consortium, focussing on upstream determinants and the prevention of risks and onset of mental health conditions through interdisciplinary stakeholder engagement, to create new opportunities for population-based improvement of mental health in the UK.The PMH Consortium brings together leading interdisciplinary representation in population mental health, spanning from sciences to the arts, across the UK. Membership includes six academic institutions, third sector organisations, lived experience expertise, and strong links with national bodies to ensure integrated cross-national and regional policy impact. The PMH Consortium comprises four cross-cutting platforms (Partners in policy, implementation, and lived experience; Data, linkages, and causal inference; Narrowing inequalities; Training and capacity building) and three challenge areas (Children and young people's mental health; Prevention of suicide and self-harm; Multiple long-term conditions) which are highly integrated and interdependent. The work will be underpinned by a Theory of Change across an initial four-year life cycle. CONCLUSION:This paper describes the aim, objectives, and approach of the PMH Consortium, as well as anticipated challenges and strengths. The goal of the PMH Consortium is to develop a model for population mental health research and policy translation that is both scalable and sustainable. It is critical to ensure continued impact and viability beyond the initial four years, contributing to the prevention of mental health conditions in the UK, with personal, economic, social, and health benefits.

Documentation comprises a large proportion of Child and Adolescent Mental Health Service (CAMHS) clinicians/practitioners' work burden and is often completed outside contracted working hours, either requiring overtime pay and/or contributing to burnout. Ambient voice technology (AVT) combines AI-driven automated transcription and reporting and is a promising tool to mitigate these challenges. Multiple commercial products have been deployed in clinical settings internationally, including mental health services. Guidance on safe and effective use is yet to be established, and specific regulation of AI-based health technology is still in its infancy or does not exist in many countries. Further, to date, evidence on safety, acceptability, system-level efficiency gains, performance and economic value is sparse. As a cross-disciplinary group with direct implementation experience, we provide a broad overview of the clinical, technical, ethical, regulatory and economic aspects of introducing AVT to CAMHS and neurodevelopmental clinical settings to guide decision-makers and highlight evidence gaps.

Since 2015, South London and Maudsley NHS Foundation Trust (London, United Kingdom) has maintained a data linkage between its de-identified Child and Adolescent Mental Health Services records and the Department for Education’s National Pupil Database. Most recently refreshed up to the 2023/24 academic year, this linkage is used to conduct population and clinical research spanning mental health and education. In this presentation, we will outline the linkage’s evolution, including governance and data-sharing frameworks that we have navigated, changes encountered in the decade since its original formation, and key learnings. We will discuss public engagement activities we have undertaken around the linkage, including novel approaches to directly involve children and young people in complex analytical decisions. Finally, we will showcase the wide array of research that has arisen from this linkage, spanning depression, Attention-Deficit/Hyperactivity Disorder (ADHD), educational attainment, special educational needs support, and more. Many of our findings have informed policymakers. Our most recent study replicates a longitudinal analysis first conducted in Norway, showing diminishing associations between ADHD and end-of-school exam performance. This demonstrates how the growing availability of data linkages permits international research replication. By identifying overlapping trends, countries can work jointly on policy solutions in full confidence that many of us are grappling with the same challenges, despite having mental health and education systems that diverge operationally. In the decade since its inception, this linkage has exemplified how administrative data drives research and policy, and there is greater opportunity than ever before for global collaboration.