Talking with adolescent and young adult cancer survivors about health after cancer: A review and communication guide for clinicians
Bibliographic record
Abstract
Adolescent and young adult (AYA) cancer survivors represent a vulnerable population in cancer care and survivorship. AYA survivors are a heterogeneous group that includes people between the ages of 15 and 39 years who were treated for cancer during their childhood or AYA years, at which time they had variable agency and may have received cancer care in pediatric or adult settings. AYA survivors experience one or multiple health care transitions, moving from active oncology to posttreatment survivorship and/or from pediatric to adult care. Clinician communication that centers the needs and preferences of the AYA and their family (parent, partner, other support person) is a therapeutic tool that can support AYAs in these health care transitions and promote AYA engagement in their care. In this article, the authors review clinician communication practices through the lens of AYAs' and families' lived experiences with a focus on the initial diagnosis and treatment phase, completion of treatment, and throughout posttreatment survivorship care. Specific communication topics relevant to survivorship encompass managing uncertainty and fear of cancer recurrence, discussing treatment-related future health risks, and supporting self-management and engagement in care. Best practices for clinician communication include maintaining openness, compassion, and flexibility to re-assess and adapt communication styles as an AYA cancer survivors' needs, concerns, and preferences change over time.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".