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Record W4413949401 · doi:10.3322/caac.70030

Talking with adolescent and young adult cancer survivors about health after cancer: A review and communication guide for clinicians

2025· review· en· W4413949401 on OpenAlexaff
Stephanie M. Smith, Lauren C. Heathcote, Jennifer N John, Catherine Benedict, Abby R. Rosenberg, Lidia Schapira

Bibliographic record

VenueCA A Cancer Journal for Clinicians · 2025
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsChild, Adolescent and Family Mental Health
FundersNational Cancer InstituteMacmillan Cancer SupportAmerican Society of Clinical OncologyConquer Cancer Foundation
KeywordsSurvivorship curveMedicineCancer survivorYoung adultCancerHealth carePopulationFamily medicineGerontology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.685
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.475
Teacher spread0.409 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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