‘What Really Goes on in My Cancer Bubble, They Cannot Understand’: Social Functioning Among Adolescent and Young Adult (AYA) Cancer Patients
Bibliographic record
Abstract
Cancer during adolescence and young adulthood (AYA; 18-39 years) can disrupt age-related milestones and impair social functioning. Many AYA patients report unmet social support needs and relationship changes, leading to isolation. This mixed-methods study explores social challenges among AYA patients actively seeking support through a communication tool, the 'AYA Match app', supporting communication with loved ones. Upon downloading the app, participants completed questionnaires on social support (MOS-SSS) and social functioning (EORTC CAT) and open-ended questions about social challenges. Eligibility included a first cancer diagnosis at AYA age and fluency in Dutch. The findings show that cancer negatively affected AYA patients' social functioning. Physical limitations and difficulty relating to peers caused isolation and feelings of loneliness. Some preferred solitude or withheld emotions to protect loved ones. Challenges included forming new relationships, feeling left behind as peers reach milestones, and struggling with a changed life perspective. Participants with children reported less social support. This study highlights the complex social challenges AYA cancer patients face. While support from loved ones is crucial, it may not always be effective. Personalized interventions like peer support, improved family communication, and tailored digital tools are needed to improve social well-being and quality of life in AYAs with cancer.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".