Positive Cancer Experiences: Perspectives From Cancer Survivors
Bibliographic record
Abstract
The purpose was to review the perspectives of cancer survivors about what they perceive constitutes positive cancer experiences. A national survey was conducted in collaboration with 10 Canadian provinces to identify experiences and unmet needs for cancer survivors between 1 and 3 years of posttreatment. The survey included open-ended questions designed to allow the respondents to add topics and details of importance. This publication presents the analysis of quantitative data and open-ended questions regarding cancer survivors' perspectives about positive experiences and gaps in care during their cancer journey. Of the 13 534 unique adult survey respondents, 7794 (57.6%) responded to the positive experiences question and 6434 (47.5%) to the question about gaps in care. Elements of positive experiences included the compassionate health care workers, maintaining a positive outlook and the support of family and friends. Gaps in care included a lack of access to services, information, and support. Respondents were able to identify positive aspects of their cancer experiences and where improvements were needed. These findings assist in determining how health care professionals can address the needs of cancer patients based on what survivors have identified as helpful.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".