The CO-produced Psychosocial INtervention delivered by GPs to young people after self-harm (COPING): protocol for a feasibility study
Bibliographic record
Abstract
Background: Self-harm in young people is a growing concern and reducing rates a global priority. Rates of self-harm documented in general practice have been increasing for young people in the UK in the last two decades, especially in 13-16-year-olds. General practitioners (GPs) can intervene early after self-harm but there are no effective treatments presently available. We developed the GP-led COPING intervention, in partnership with young people with lived experience and GPs, to be delivered to young people 16-25 years across two consultations. This study aims to examine the feasibility and acceptability of conducting a fully powered effectiveness trial of the COPING intervention in NHS general practice. Methods: This will be a mixed-methods external non-randomised before-after single arm feasibility study in NHS general practices in the West Midlands, England. Patients aged 16-25 years who have self-harmed in the last 12 months will be eligible to receive COPING. Feasibility outcomes will be recruitment rates, intervention delivery, retention rates, and completion of follow-up outcome measures. All participants will receive COPING with a target sample of 31 with final follow-up data collection at six months from baseline. Clinical data such as self-harm repetition will be collected. A nested qualitative study and national survey of GPs will explore COPING acceptability, deliverability, implementation, and likelihood of contamination. Discussion: Brief GP-led interventions for young people after self-harm are needed to address national guideline and policy recommendations. This study of the COPING intervention will assess whether a main trial is feasible. Registration: ISRCTN (ISRCTN16572400; 28.11.2023).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.053 | 0.035 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.079 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".