TITLE THE TEENAGE AND YOUNG ADULT (TYA) POPULATION (16-24YO) BENEfiT FROM HAVING SPECIALIST NURSE INPUT
Bibliographic record
Abstract
Abstract AIMS The aim of this review is to analyse the need for a specialist nurse role for the TYA patients. Having a new dedicated TYA developmental role implemented can help by identifying areas for improvement from the wider team to ensure optimal support for patient group. METHOD Clinic attendance over a 1-year period has been measured. Looking specifically at patients who did not attend (DNA) appointments in a monthly TYA joint surgical and oncology clinic. We have evidence engaging this age group with the creation of a nurse led weekly telephone clinic for TYA patients and have looked at the trajectory of attendees throughout the year. RESULTS To date, nurse led clinic has had 107 individual bookings between August 2022 and February 2023. This is a devoted telephone clinic to provide holistic care. CONCLUSIONS There were 107 nurse lead telephone clinic appointments that were booked and attended by this patient group over 6-month period. This was protected time for which the nurse specialist was able to explore patients individual care needs in a holistic way. Figures for holistic needs assessment (eHNA) are yet to be collated; but the TYA group are now routinely offered eHNA to ensure a holistic care approach and support to this vulnerable patient group.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".