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  • Children and young people's mental health in the English-speaking Caribbean: a scoping review and evidence map

    Evidence from low- and middle-income countries and developing nations on children and young people's mental health is generally missed in the international narrative. This scoping review aimed to add to the body of evidence by providing an overview of the available research from the English-speaking Caribbean region. Authors: Liverpool, S., Pereira, B., Pollard, M., Prescod, J., Trotman, C. (2021).

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  • Unprecedented challenges and innovative responses: schools’ and colleges’ experiences of supporting mental health and wellbeing during the coronavirus pandemic

    The primary challenges staff identified in supporting mental health and wellbeing varied across the timepoints. They include issues relating to logistics, the demand for support and the availability of support.

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  • Children’s mental health in the time of coronavirus: what we know about what hurts and what helps

    Why focus on children’s mental health at this time? What has the impact been on young people’s mental wellbeing? How can we best support children and young people’s mental health at this time?

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  • Measuring pupil mental health and wellbeing: examples of best practice from schools and colleges working with the Mercers’ Company

    This briefing draws on learning emerging from research led by the Evidence Based Practice Unit in collaboration with the Child Outcomes Research Consortium, The University of Manchester and Common Room. The Mercers’ Company funded the research. The Mercers’ Company is the Premier Livery Company of the City of London. Authors: Deighton, J., Stapley, E., Lereya, T., Burrell, K., Atkins, L. (2019).

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  • Analysis of protective factors in schoolchildren in England using the dual-factor model of mental health

    The dual-factor approach to mental health was employed to explore levels and interrelations of protective factors associated with resilience in a dataset of 30,841 schoolchildren aged 11–14 in England. Authors: Jefferies, P., Fritz, J., Deighton, J., Ungar, M. (2023).

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  • Apps targeting anorexia nervosa in young people: a systematic review of active ingredients

    The aim of this review was to systematically identify the behavioural change techniques (BCTs) underpinning anorexia nervosa apps for young people. BCTs refer to the “common language” used by researchers to determine the triggers of behaviour change. Authors: Chiang, CP., Hayes, D., Panagiotopoulou, E. (2023).

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  • The Importance of child-staff therapeutic relationships in the Children and Young People Secure Estate

    The aim of this research was to explore young people’s experiences of therapeutic relationships with staff in secure settings, which is a central component of the Framework for Integrated Care (SECURE STAIRS). Authors: Jacobs, J., D'souza, S., Lane, R., Cracknell, L., Singleton, R., Edbrooke-Childs, J. (2023).

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  • The impact of universal, school based, interventions on help seeking in children and young people: a systematic literature review

    Universal help-seeking interventions in schools to support young people’s mental health have been widely used, but we know little about their initial impact and longer term follow-up. This systematic literature review aims to explore the impact of these types of programmes across different help-seeking constructs. Authors: Hayes, D., Mansfield, R., Mason, C., Santos, J., Moore, A., Boehnke, J., Ashworth, E., Moltrecht, B., Humphrey, N., Stallard, P., Patalay, P., & Deighton, J. (2023).

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  • Using flawed, uncertain, proximate and sparse (FUPS) data in the context of complexity: learning from the case of child mental health

    This paper presents an example of the use of a FUPS dataset in the complex system of child mental healthcare. The paper explores the use of this FUPS dataset to support meaningful dialogue between key stakeholders, including service providers, funders and users, in relation to outcomes of services. The term ‘FUPS’ is proposed to describe these flawed, uncertain, proximate and sparse datasets. Authors: Wolpert, M., Rutter, H. (2018).

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