Psychosocial Care for Cancer: A Framework to Guide Practice, and Actionable Recommendations for Ontario
Bibliographic record
Abstract
OBJECTIVES: We set out to create a psychosocial oncology care framework and a set of relevant recommendations that can be used to improve the quality of comprehensive cancer care for Ontario patients and their families.meet the psychosocial health care needs of cancer patients and their families at both the provider and system levels. DATA SOURCES AND METHODS: The adapte process and the practice guideline development cycle were used to adapt the 10 recommendations from the 2008 U.S. Institute of Medicine standard Cancer Care for the Whole Patient: Meeting Psychosocial Health Needs into the psychosocial oncology care framework. In addition, the evidence contained in the original document was used, in combination with the expertise of the working group, to create a set of actionable recommendations. Refinement after formal external review was conducted. DATA EXTRACTION AND SYNTHESIS: The new framework consists of 8 defining domains. Of those 8 domains, 7 were adapted from recommendations in the source document; 1 new domain, to raise awareness about the need for psychosocial support of cancer patients and their families, was added. To ensure high-quality psychosocial care and services, 31 actionable recommendations were created. The document was submitted to an external review process. More than 70% of practitioners rated the quality of the advice document as high and reported that they would recommend its use. CONCLUSIONS: This advice document advocates for a multidisciplinary approach to cancer care in response to the distress experienced by cancer patients and their families. The recommendations will be useful in future to measure performance, quality of practice, and access to psychosocial services.
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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) | 0.000 | 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".