NIHRDataInsights/HRCSData huggingface dataset:
Title: Kailo - A systemic approach to improving adolescent mental health
Funder: Medical Research Council

Abstract: Adolescent mental health is a non-communicable disease of great policy, practice and economic concern. Levels of unmet need have long been recognised. Inequalities in poor mental health for marginalised and disadvantaged young people have been highlighted and exacerbated by the current COVID-19 pandemic. There is increasing acknowledgement that existing mental health systems and services play an important but fundamentally limited and stretched role in responding to and treating difficulties. Adolescent mental health is a systemic issue, and to demonstrably turn the tide of deteriorating mental health in society we must address the wider and systemic determinants. Such efforts may be informed by the latest scientific advances in our understanding of the aetiology of poor mental health and the systemic moderators, mediators that exert an influence. Yet a 'one-size fits all' approach will have limited impact, as the wider determinants of mental health are expressed differently in varying contexts. It follows that evidence-informed preventative and health-promotive activities must be tailored to local context. To this end our partnership has developed and will test an evidence-informed preventative framework called Kailo across a number of communities in the UK. The design and implementation of the framework will be led by leading social design and research teams, supporting equitable and inclusive co-design methodologies, informed by the latest evidence and targeting the wider determinants of adolescent mental health. The framework will be iteratively tested and optimised through a range of innovative developmental and systemic evaluation methods, including realistic feasibility testing, system mapping and system dynamic simulation modelling and contributory impact evaluation. This will inform ongoing refinement of the approach into a sustainable, replicable model, disseminated through extensive policy, practice and research knowledge mobilisation channels.


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING;7.1 INDIVIDUAL CARE NEEDS;8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: MENTAL HEALTH
Title: ATTUNE : Understanding mechanisms and mental health impacts of Adverse Childhood Experiences to co-design preventive arts and digital interventions.
Funder: Medical Research Council

Abstract: Research Questions: What are the psychological and geo-socio-economic contextual mechanisms by which ACEs unfold to affect or safeguard the mental health and lives of young people (aged 10-24)? Are co-designed, youth-informed public mental health and serious games interventions acceptable, feasible, potentially cost effective, and beneficial for ACE exposed young people? Research Plan: Via participatory creative arts methods we will generate lived experience data and combine this with secondary analysis of large cohorts to address knowledge gaps about mental health risk and resiliency pathways. Using this information, a) we will undertake an experience based co-design process to produce public mental health resources relevant to schools, the third sector and social services; b) We will test if ACE-exposed adolescents engage with and benefit from a co-designed serious game version of Narrative Exposure Therapy (NET). We will test feasibility, acceptability, levels of personalization and guidance, potential cost-effectiveness, and scalability by place. There are four cross-cutting themes: ethics, PPI, interdisciplinary learning, and neurodivergence, throughout. Expected outputs: 1) Data showing how ACEs impact the developing mind, gaps in care, and youth perspectives on ACEs and appropriate care. 2) New knowledge about mechanisms of risk and resiliency. 3) Youth led evaluative films and arts outputs enhancing interdisciplinary learning and reporting research findings about interventions and mechanisms/logic models. 4) Interdisciplinary learning on ethical issues in arts/digital/mental health research, PPI, and neurodiversity. 5) Co-produced public mental health resources and serious game-based psychoeducational and therapeutic interventions, with data on acceptability, feasibility, potential cost-effectiveness, and mechanisms. Impacts: Transform practice, care pathways and systems. Provide trauma-informed resources. Learning for future research, policy and practice.


Research activity codes: 7.1 INDIVIDUAL CARE NEEDS;8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: MENTAL HEALTH
Title: Eating Disorders: Delineating illness and recovery trajectories to inform personalised prevention and early intervention in young people (EDIFY)
Funder: Medical Research Council

Abstract: Background: Early intervention and models of illness stages have been the focus of intense research activity across multiple disorders. Nothing comparable exists in eating disorders (EDs). Together with young people (YP), we will co-create an interdisciplinary, evidence-based model of how people develop EDs, what characterises illness stages and drives transitions between them, trajectories of symptoms across development, and how YP recover. This will provide a map for generating personalised, developmentally-informed interventions, tailored to risk profiles and illness stages, thus transforming ED policy and practice. Research Plan: Our proposal consists of 6 integrated work streams (WSs). WSs 1 and 6 are crosscutting. WS1 will use qualitative and arts-based approaches to co-create narrative accounts with YP of their lived experiences of ED illness and recovery, with emphasis on capturing the perspectives of diverse, under-represented groups (e.g. BAME, LGBTQ+). WS2 will use a combination of six well-characterised cohorts to develop and test predictive models of risk and resilience for EDs and associated high-risk behaviours in YP. WS3 will assess the recovery trajectories of a clinical cohort of YP with 1st episode EDs, using remote measurement technology to gather real time data from activity monitors/smartphones. WS4 will use multi-modal assessments to compare the biopsychosocial profiles of YP with early- and later-illness stage and changes in these over time. WS5 will develop two intervention protocols appropriate for different illness/developmental stages based on our findings and test proof-of-concept for a brain-directed intervention for young people with later-stage EDs. Finally, WS6 will assess how to share and implement findings with the public in novel and accessible ways. Impact: Collectively, our findings will transform ED detection, treatment and services and will support development of inclusive, all-age evidence-based ED policy and practice.


Research activity codes: 7.1 INDIVIDUAL CARE NEEDS;8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: MENTAL HEALTH
Title: Developing and Evaluating a Stepped Change Whole-University approach for Student Wellbeing and Mental Health
Funder: Medical Research Council

Abstract: Our research involves a rigorous evaluation of whole-university and stepped care frameworks to promote good mental health in students using a multi-disciplinary approach drawing on the humanities, psychology, psychiatry, information technology and statistics, working collaboratively across 6 universities. To address objective 1, we will introduce different whole-university (embedding compassion in education; online mental health literacy course) and stepped care interventions (digital self-monitoring) in a phased way across collaborating universities. To address objectives 2,3,5, a repeated biannual online student wellbeing survey at the start and end of the academic year, with cross-sectional and longitudinal components, will collect self-report quantitative data (demographics, mental health outcomes, process measures, attitudes, knowledge of and behaviours related to stepped care) from students across multiple institutions. Students can use a digital self-monitoring tool and electronic personal health record prospectively, with brief measures of wellbeing, stress, symptoms and use of support to address objective 2. We will test whether this tool helps students to better use stepped care. Observational experiments will collect pre- and post-intervention quantitative and qualitative data using a core set of outcome measures and examine data from biannual surveys to assess the impact of introducing each intervention. To address objectives 6, 7, focus groups will explore students' experiences of these initiatives including positives, negatives, areas to improve and relevance to diverse groups. To address objectives 1,4,5, randomised trials will compare different variants of digital self-help including guided vs unguided self-help. To address objective 4, pre-randomisation measures will assess potential predictors of heterogeneity of treatment effect. Repeated weekly web surveys within the trials will assess change in putative mediators to support objective 5.


Research activity codes: 7.1 INDIVIDUAL CARE NEEDS
Health categories: MENTAL HEALTH
Title: Adolescent Mental Health and Development in the Digital World
Funder: Medical Research Council

Abstract: Objectives We will work with young people in our Young Person Advisory group to: - increase understanding of the relationship between digital risk, resilience and adolescent mental health - develop and evaluate preventative and personalized digital interventions. We aim to: - identify risk and resilience factors related to troublesome online experiences and activities, to prevent or reduce the emergence of depression, anxiety, and self-harm in young people. - understand how individual differences, affect digital engagement (e.g. with social media and games) and adolescent brain and psychosocial development. - build, adapt and pilot new a generation of personalized and adaptive digital interventions incorporating a mechanistic understanding of human support with a new digital platform for delivery and trials in adolescent mental health conditions. - develop and test a novel socially assistive robot to help regulate difficult emotions with a focus on adolescents who self-harm. - develop and test a new digital tool to help adolescents better manage impulsive and risky behaviour with a focus on reducing the risk of self-harm. Methods to be used across the programme include; longitudinal analyses, quantitative multivariate and machine learning approaches, ecological momentary assessment, qualitative analyses, feasibility trials, mixed-methods process evaluation, user-centred co-production and human computer interaction methods. Planned, reciprocal linkages between work packages will enable cross-cutting themes on responsible innovation, impulsivity and emotion regulation to be investigated across disciplines and themes. Involvement work with young people shaped the bid and will occur at every stage of the research process. Application and exploitation: Our Mental Health & Digital Technology Policy Liaison Group and Partners Board will ensure that our work is used in the real world to deliver a step-change in mental health outcomes for young people.


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;6.6 PSYCHOLOGICAL AND BEHAVIOURAL;7.1 INDIVIDUAL CARE NEEDS
Health categories: MENTAL HEALTH
Title: Regulating Emotions - Strengthening Adolescent Resilience (RE-STAR)
Funder: Medical Research Council

Abstract: RE-STAR's goal is to find ways to reduce the risk of depression in young people with neuroatypicalities (YPN) associated with ADHD and ASD traits: a group at especially high risk for this. It will integrate developmental science and co-intentional research to develop a multi-faceted understanding of the role of YPN's emotion regulation difficulties as drivers of depression. Then, working with YPN, it will adapt and integrate a number of existing generic approaches into a comprehensive school-based intervention strategy, tailored to the specific needs of those with ADHD and ASD traits; the aim being to pre-emptively strengthen emotion regulation in early adolescence to reduce depression later on. Through its Youth Researcher Panel, RE-STAR will embody a co-creation philosophy: YPN's understanding of emotion regulation will be at the heart of RE-STAR: YPN will shape study design and undertake data collection. This will begin with the co-development of a new youth-report emotion regulation scale in WP1. Using this scale, and working across the full spectrum of atypicality, WP2 will study the cognitive/neurophysiological underpinnings of emotional regulation in YPN, while WP3 will longitudinally characterise YPN's adolescent pathways to depression and if these are moderated by daily stressors and hassles. WP4 will use co-creative performance-based practices to delve deeper into YPN's understanding of their experiences and how this impacts, and is impacted by, emotion regulation and mental health. WP5 will focus on school as both a context for YPN's emotion regulation challenges and a potential platform for effective intervention. In all WPs, characteristics shared between ADHD and ASD traits will be distinguished from those unique to each. Finally, in WP6, the key findings from the prior WPs will be brought together to create and feasibility test a new school-based RE-STAR strategy which will be co-developed by YPN and other educational and mental health stakeholders.


Research activity codes: 7.1 INDIVIDUAL CARE NEEDS
Health categories: MENTAL HEALTH
Title: The automated coding of expressed emotion to enhance clinical and epidemiological mental health research in adolescence
Funder: Medical Research Council

Abstract: Our goal is to develop, validate and scale an automatic tool to measure caregiver expressed emotion (EE) for the adolescent age range. Caregiver EE acts a transdiagnostic risk factor for both adolescent-onset psychopathology and as potential mediator of both pharmacological and psycho-social treatment. EE can be accurately captured using five minutes of audio of a mother speaking about their offspring. The ease of collecting these five minute speech samples (FMSS) is countered by the time and skills needed to apply EE coding frameworks - significantly limiting their application in both adolescent development and clinical research. This project will integrate developmental science and computational linguistic approaches to develop an Artificial Intelligence (AI) system to automatically identify constructs linked to expressed emotions values from FMSS. This project's technical objectives are to use the audio data and corresponding FMSS coding from 2021 adolescents within the in E-Risk cohort to (i) test deep learning classification models for EE scores and compare with summary ratings produced by highly trained humans (ii) test the feasibility of these deep learning sequence labelling models models to annotate positive and negative comments, negativity and warmth (iii) examine the AI model performance across socio-economic strata and geographical locations (iv) explore whether the human ratings of EE and AI outputs are predictive of adolescent mental health outcomes. We will co-develop guidance with young people, caregivers, researchers and university governance, on the main ethical-social-technical challenges in using and sharing parental speech data and how they may be surmounted. We will then use the ethical-social-technical learning we have acquired, to develop a detailed product brief on what is required to provide an accessible, secure digital platform that enables external researchers to automatically code expression emotion from FMSS audio data.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: MENTAL HEALTH
Title: Healthy, resilient and flexible: Co-developing a mental health intervention for and with frontline gig workers: a systems approach
Funder: Medical Research Council

Abstract: Profit-driven platforms analyse the data flow and add features on the platforms to motivate workers (i.e. set up quests or inert a points system) or increase customer satisfaction (i.e. driver tracking or customer rating) or improve operational efficiency (i.e. demand response in minutes). These features and their logic of design can contribute to a stressful work environment and cause safety and health concerns. Latest research has revealed traffic rules violations and high rates of road accidents among workers who drive in the gig economy. The ultimate goal of this research is to develop a system-level digital intervention (main study) to prevent excessive work stress and reduce job burnout among frontline gig workers. It is envisaged as a set of intervention approaches and supporting mechanisms embedded in software architecture solutions that can be developed and integrated into existing platforms. It will influence, interrupt or modify the workflow and operation system that are controlled by the algorithm and system engineering logic. Ideally, it should be able to detect excessive workload, stressful moments and risky behaviours and inform the workers. This way, workers could gain more control by, for example, adjusting rate of order dispatch or delivery time window, negotiating performance incentive design or disputing bad customer reviews. Additional support functions can be added to offer more work-related support, such as a virtual line-manager or workers forum. To progress to the main study, it is extremely important that we use this PHIND stage to develop a technology model, identify desired functions and working mechanisms, working collaboratively and closely with all the key stakeholders. Based on the learnings, we can then design and implement a comprehensive intervention program and evaluate the effectiveness in the main study. The co-development will be guided by a theoretical model: job demand-resource (JD-R) model.


Research activity codes: 3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING
Health categories: MENTAL HEALTH
Title: Investigating the Effect of the Menstrual Cycle on Social Stress in Early Psychosis Through Ecological Momentary Assessment
Funder: Medical Research Council

Abstract: The perimenstrual phase of the menstrual cycle carries a higher risk of relapse in women with psychosis. A plausible mechanism for this finding is through response to social stress, known to be abnormal both in psychosis and in those at high risk of developing psychosis. Response to stress varies across the menstrual cycle, likely as a consequence of allopreganolone, a metabolite of progesterone, which is a potent anxiolytic. We will ask women in the early phase of psychosis (those experiencing their first episode and those at increased risk due to sub-threshold symptoms) to record daily responses to social stress through Social Mind, an app developed with MRC funding, over a follow-up period of one to two years. They will also record when they are experiencing menstrual bleeding through the app. The app will passively measure social withdrawal through GPS data. We will analyse the effect of the menstrual cycle on response to social stress, social withdrawal and relapse of psychosis. We will model whether the effect of the menstrual cycle in psychosis is mediated through social stress. We will compare these effects between women experiencing their first episode, those at high risk and those without mental health problems. Elucidating the underlying mechanisms between the menstrual cycle and increased psychosis relapse risk could identify novel treatment targets.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: MENTAL HEALTH
Title: High Impact Chronic Pain and UK Biobank: presentation, transitions and targets for intervention
Funder: Medical Research Council

Abstract: BACKGROUND: Chronic pain (CP), lasting more than 3 months, represents a major global burden in terms of years lived with disability and economic impact due to healthcare use and work absenteeism. Approximately 25% of those with CP (10% of the adult UK population) experience far-reaching impact from CP, including widespread disability and distress, social exclusion, and high healthcare needs, recognised as High Impact Chronic Pain (HICP). AIMS AND OBJECTIVES: We propose an interdisciplinary programme of research to inform prevention, selfcare and treatment options for HICP. Specific objectives are to 1. Use clustering methods to identify and describe phenotypes of HICP, and validate these in other datasets 2. Use causal inference methods to investigate the role of (a) cognitive and affective factors, and (b) trauma or traumatic events in explaining transitions of HICP 3. Identify potential targets for prevention and treatment, and estimate expected benefit from individual or population level intervention DESIGN AND METHODS: Working with patient partners we will use data from UK Biobank to investigate changes in the impact of chronic musculoskeletal pain over time. The presence of CP was assessed in all UKB participants at inclusion in 2006-2010. A detailed CP survey was launched in 2019 (completed by >173,000 individuals) and will be repeated in 2023. Additional data on risk factors, mediating and moderating factors will be extracted from existing surveys (e.g. lifestyle, work cogntive function, mental health) and linked healthcare records (trauma, sudden illness, comorbidity). Social determinants (e.g. age, gender, ethnicity, deprivation), will be taken into account in all analyses. DISSEMINATION: Open access publications, conference presentations, lay summaries, and infographics will be co-created with patient partners and clinical advisors, and shared within the research community, public health/clinical networks, and the wider public.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;7.1 INDIVIDUAL CARE NEEDS
Health categories: MENTAL HEALTH