early intervention
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Common elements: An innovative methodology for identifying effective interventions in early childhood education
Evidence-based education programmes, like many clinical interventions, are multi-faceted and can be expensive to implement. In this talk I will describe an alternative: distilling the common elements across many evidence-based programmes. Published programme manuals are selected through systematic review, then extensively coded and cross-referenced. Finally, the common elements that emerge are shared with practitioners as part of a ‘library’ of practices (rather than a holistic programme manual). Although the common elements methodology has been used in the prevention and intervention sciences, this project reflects the first attempt at applying this approach to early childhood education. I will describe the common elements methods and preliminary findings from our Nuffield-funded project, in collaboration with the Early Intervention Foundation. I will discuss the challenges and opportunities we have encountered, alongside our strategies for sharing evidence with practitioners in a digestible way.
Improving the identification of cardiometabolic risk in early psychosis
People with chronic schizophrenia die on average 10-15 years sooner than the general population, mostly due to physical comorbidity. While sociodemographic, chronic lifestyle and iatrogenic factors are important contributors to this comorbidity, a growing body of research is beginning to suggest that early signs of cardiometabolic dysfunction may be present from the onset of psychosis in some young adults, and may even be detectable before the onset of psychosis. Given that primary prevention is the best means to prevent the onset of more chronic and severe cardiometabolic phenotypes such as CVD, there is clear need to be able to identify young adults with psychosis who are most at risk of future adverse cardiometabolic outcomes, such that the most intensive interventions can be directed in an informed way to attenuate the risk or even prevent those adverse outcomes from occurring.In this talk, Ben will first outline some recent advances in our understanding of the association between cardiometabolic and schizophrenia spectrum disorders. He will then introduce the field of cardiometabolic risk prediction, and highlight how existing tools developed for older general population adults are unlikely to be suitable for young people with psychosis. Finally, he will discuss the current state of play and the future of the Psychosis Metabolic Risk Calculator (PsyMetRiC), a novel clinically useful cardiometabolic risk prediction algorithm tailored for young people with psychosis, which has been developed and externally validated using data from three psychosis early intervention services in the UK.
Time window for early intervention in tauopathy mouse model
FENS Forum 2024
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