H014 ‘You are not alone’ a three year project to develop our Huntington’s disease youth engagement service (HDYES)
Bibliographic record
Abstract
Background and Aim HDYES directly supports children and young people (CYP) affected by Huntington’s disease (HD) in England. Funding from the National Lottery Community Fund has strengthened our capacity and our aim is to support 300 CYP (8 – 25), 150 parents, guardians and carers (PGC) and 200 professionals over three years from June 2023. Methods Our expanded team supports CYP through 1:1 support/events; PGC through 1:1 support/courses and professionals through training. Key to the project is our HD Youth Voice group, who are changing the landscape, sharing their experiences and the powerful message that you are not alone. Results Reporting on 5 months of data, showing early change: We supported 190 CYP, 29 had enough ‘distance travelled’ data to report on, this showed early change with 30% gaining a better understanding of HD; 56% feeling less isolated and 17% feeling more resilient. We supported 45 PGC, 18 completed a survey, of those 100% had better understanding of HD, 87% could better support their child, 89% were less isolated, 67% more resilient and 89% more prepared for the future. We trained 127 professionals, 40 completed a survey, 100% said they had increased knowledge and were better able to support a CYP affected by HD. Conclusion When they join HDYES, CYP have lower knowledge about HD, connection to others, future preparedness and, particularly, resilience. This appears to increase as they receive more support from HYDES. The confidence of PGC, and professionals, in understanding HD and supporting CYP increased immediately after training or support from HDYES.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.007 |
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".