2014 President's plenary international psycho‐oncology society: moving toward cancer care for the whole patient
Bibliographic record
Abstract
The International Psycho-oncology Society (IPOS) has just celebrated its 30th anniversary. The growth of psychosocial oncology has been exponential, and this relatively new field is becoming a core service that focuses on prevention, reducing the burden of cancer, and enhancing the quality of life from time of diagnosis, through treatment, survivorship, and palliative care. Looking back over the past 30 years, we see that cancer care globally has evolved to a new and higher standard. Today, 'cancer care for the whole patient' is being accomplished with an evidence-based model that addresses psychosocial needs and integrates psycho-oncology into the treatment and care of patients. The President's Plenary Session in Lisbon, Portugal, highlighted the IPOS Mission of promoting global excellence in psychosocial care of people affected by cancer through our research, public policy, advocacy, and education. The internationally endorsed IPOS Standard of Quality Cancer Care, for example, clearly states the necessity of integrating the psychosocial domain into routine care, and that distress should be measured as the sixth vital sign after temperature, blood pressure, pulse, respiratory rate, and pain. The plenary paper also discussed the global progress being made in Europe, North America, and Australia in providing quality cancer care for the whole patient. Collaborative partnerships between IPOS and organizations such as the European Partnership Action Against Cancer and the World Health Organization are essential in building capacity for the delivery of high-quality psycho-oncology services in the future.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.018 | 0.022 |
| Insufficient payload (model declined to judge) | 0.041 | 0.019 |
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".