Psycho-oncology and optimal standards of cancer care: \ndevelopments, multidisciplinary team approach and international guidelines
Bibliographic record
Abstract
The development of psycho-oncology over the last thirty-forty years has had a main role in sensitizing the general population, oncology health professional and health care administrators about the need for psychosocial care in cancer. The increase of awareness on the importance of psychosocial issues in medical illness has brought to the development of psychosomatic medicine as a sub-specialty of psychiatry and psychosocial oncology as a special area within cancer disciplines. \nPsychosocial oncology standards and guidelines are now available in several countries, with Cancer National Plan or Acts indicating psychosocial care in oncology as a mandatory requirement for optimal clinical care. \nIn the chapter the authors review the state of the art of psychosocial care in different countries, underline the criteria to be met for the development of psychosocial oncology services, programs and departments, present the most important recommendations and conclusions of the countries with special experience in the field (e.g Canada, USA, Australia), and the position statement on psychosocial care as a human right for cancer patients and their families.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".