The Needs and Experiences of Post-Treatment Adolescent and Young Adult Cancer Survivors
Bibliographic record
Abstract
(1) Background: Adolescents and young adults (AYAs) who have been diagnosed with and treated for cancer have unique healthcare needs, but more research is needed to inform developmentally targeted cancer care for this population. The purpose of the current analyses was to describe the physical and psychosocial concerns and experiences of AYA cancer survivors during the post-treatment phase. (2) Methods: A national survey was conducted by the Canadian Partnership Against Cancer to evaluate the experiences and unmet needs of cancer survivors (≥18 years) within the first 5 years following cancer treatment. The current analyses were conducted on the AYA survivor population (18-34 years). (3) Results: A total of 575 surveys were completed by AYAs. Of these, 61% were female, 51% were married/partnered, and 52% were 1-3 years post treatment. Approximately three-quarters report their physical or emotional health as good/very good. Overall, 88% reported at least one physical concern [mean of 3.98+2.11 physical concerns (range 0-9)], 90% reported at least one emotional concern [mean of 3.77+1.75 emotional concern (range 0-6)], and 79% reported at least one practical challenge [mean of 2.39+1.28 practical concerns (range 0-5)]. The most common concerns were anxiety/worry about cancer returning (83%), fatigue/tiredness (78%), and depression/loss of interest in daily activities (66%). On average, 43% of those reporting a concern sought help. Common reasons for not seeking help included not wanting to ask, being told that it was normal to feel the way they did, or embarrassment. Of those who did seek help, 37% encountered difficulty obtaining assistance. (4) Conclusions: These results suggest that post-treatment AYA cancer survivors have a high rate and number of physical, psychosocial, and practical concerns and are often not seeking or receiving help to address these. Proactive approaches to characterizing and eliminating barriers to obtaining appropriate care are needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".