Experiences of adult cancer survivors in transitions
Bibliographic record
Abstract
PURPOSE: To understand the experiences of adult cancer survivors as they transition from the end of cancer treatment to follow-up care as a basis for developing actionable recommendations to integrate cancer care delivery and survivorship care. METHODS: A national survey was conducted in collaboration with ten Canadian provinces to identify unmet needs and experiences with follow-up for cancer survivors between 1 and 3 years post-treatment. Surveys were available in English and French and completed either on paper or on-line. Samples were drawn from provincial cancer registries and packages distributed by mail. RESULTS: A total of 40,790 survey packages were mailed out across the ten provinces and 12,929 surveys were completed by adults (age 30+ years), and 329 surveys were completed by adolescents and young adults (age 18 to 29 years) giving an overall response rate of 33.3%. For the purposes of this publication, the focus will be on the adult sample. In the adult cohort (age 30+ years), 51% of the sample were females, 60% were 65 years of age or older, and 77% had not experienced metastatic spread. Three-quarters reported their health as good/very good and 82% that their quality of life was good/very good. Overall, 87% experienced at least one physical concern, 78% experienced at least one emotional concern, and 44% experienced at least one practical concern. The average number of concerns reported for each domain ranged from 2.0 to 3.8. For those who sought help, a third experienced difficulty obtaining assistance or did not receive it. The most frequently cited reasons for not seeking help was that someone had told them what they were experiencing was normal. CONCLUSIONS: The results indicate that many adult survivors have concerns about physical, emotional, and practical issues but are not receiving help to reduce their suffering. It is imperative we take action to correct this current reality.
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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 | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 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".