Management of Cancer and Health After the Clinic Visit: A Call to Action for Self-Management in Cancer Care
Bibliographic record
Abstract
Individuals with cancer and their families assume responsibility for management of cancer as an acute and chronic disease. Yet, cancer lags other chronic diseases in its provision of proactive self-management support in routine, everyday care leaving this population vulnerable to worse health status, long-term disability, and poorer survival. Enabling cancer patients to manage the medical and emotional consequences and lifestyle and work changes due to cancer and treatment is essential to optimizing health and recovery across the continuum of cancer. In this paper, the Global Partners on Self-Management in Cancer puts forth six priority areas for action: Action 1: Prepare patients and survivors for active involvement in care; Action 2: Shift the care culture to support patients as partners in cocreating health and embed self-management support in everyday health-care provider practices and in care pathways; Action 3: Prepare the workforce in the knowledge and skills necessary to enable patients in effective self-management and reach consensus on core curricula; Action 4: Establish and reach consensus on a patient-reported outcome system for measuring the effects of self-management support and performance accountability; Action 5: Advance the evidence and stimulate research on self-management and self-management support in cancer populations; Action 6: Expand reach and access to self-management support programs across care sectors and tailored to diversity of need and stimulation of research to advance knowledge. It is time for a revolution to better integrate self-management support as part of high-quality, person-centered support and precision medicine in cancer care to optimize health outcomes, accelerate recovery, and possibly improve survival.
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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 | 0.113 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.019 | 0.036 |
| Scholarly communication | 0.024 | 0.049 |
| Open science | 0.010 | 0.037 |
| Research integrity | 0.047 | 0.116 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".