Self-Harm in Eating Disorders (SHINE): a mixed-methods exploratory study.

INTRODUCTION: Self-harm is highly prevalent among young people with eating disorders. However, why a young person may develop and continue to experience both an eating disorder and self-harm is unclear. This study will investigate the frequency, intensity, duration, function, context and processes of self-harm among people aged 16-25 diagnosed with an eating disorder. It will explore participants' perspectives on the genesis and functions of both their self-harm and eating disorder, as well as their support needs. The study was designed with the input of members of a Young Persons' Advisory Group, who will be key to study delivery and dissemination. METHODS AND ANALYSIS: This exploratory study has a sequential mixed-methods explanatory design. Between 70 and 100 young people aged 16-25 with both an eating disorder diagnosis and self-harm thoughts and/or behaviours will be recruited from three NHS Eating Disorder outpatient services in England. Phase 1: a 14-day (six prompts per day) ecological momentary assessment (EMA) of participants' feelings, thoughts, motivations, behaviours and experiences of self-harm. Phase 2: 20-30 participants from phase 1 will be reapproached to take part in an in-depth qualitative interview on the psychological, emotional and social factors that underlie their self-harm and eating disorder as well as their support needs. EMA data from phase 1 will be analysed using descriptive and multilevel statistics. Qualitative interview data from phase 2 will be analysed using inductive and deductive thematic analysis. Results from both phases will be integrated using a mixed-methods matrix, with each participant's data from both phases compared alongside comparative analysis of the datasets as a whole. ETHICS AND DISSEMINATION: The study gained ethical approval from the NHS HRA West Midlands-Black Country Research Ethics Committee (number: 296032). We anticipate disseminating findings to clinical, academic and lived experience audiences, at academic conferences, through peer-reviewed articles, and through various public engagement activities (eg, infographics, podcasts).

Development and external validation of predictive models for prevalent and recurrent atrial fibrillation: a protocol for the analysis of the CATCH ME combined dataset.

BACKGROUND: Atrial fibrillation (AF) is caused by different mechanisms but current treatment strategies do not target these mechanisms. Stratified therapy based on mechanistic drivers and biomarkers of AF have the potential to improve AF prevention and management outcomes. We will integrate mechanistic insights with known pathophysiological drivers of AF in models predicting recurrent AF and prevalent AF to test hypotheses related to AF mechanisms and response to rhythm control therapy. METHODS: We will harmonise and combine baseline and outcome data from 12 studies collected by six centres from the United Kingdom, Germany, France, Spain, and the Netherlands which assess prevalent AF or recurrent AF. A Delphi process and statistical selection will be used to identify candidate clinical predictors. Prediction models will be developed in patients with AF for AF recurrence and AF-related outcomes, and in patients with or without AF at baseline for prevalent AF. Models will be used to test mechanistic hypotheses and investigate the predictive value of plasma biomarkers. DISCUSSION: This retrospective, harmonised, individual patient data analysis will use information from 12 datasets collected in five European countries. It is envisioned that the outcome of this analysis would provide a greater understanding of the factors associated with recurrent and prevalent AF, potentially allowing development of stratified approaches to prevention and therapy management.