Progress toward integrating Distress as the Sixth Vital Sign: a global snapshot of triumphs and tribulations in precision supportive care
Bibliographic record
Abstract
Abstract Background: The International Psycho-Oncology Society (IPOS) recognizes psychosocial cancer care as a universal human right. IPOS emphasized that distress should be measured as the 6th Vital Sign alongside temperature, blood pressure, pulse, respiratory rate, and pain. To date, >75 cancer care organizations and accreditation bodies have endorsed screening, monitoring, and treating the multifactorial symptoms of distress as an essential component to high-quality care. The degree to which this international commitment has translated into the integration of precision supportive care within clinical settings is unknown. Methods: Building upon a 2018 IPOS World Congress Symposium, this commentary provides 4 snapshots into the progress made toward integrating precision supportive care in India, Australia, Europe, and the United States. The commentary demonstrates the different approaches taken to develop screening practices or overcome barriers to comprehensive precision supportive care. Results: Although psychosocial cancer care is a universal right, service and patient barriers to implementation remain, such as: inadequate workforce distribution and service investment in psychosocial care; siloed teams and limited communication skills; and cultural challenges. Recurrent themes emerged which can be used to invigorate commitment to IPOS standards: ongoing capacity building of the international psycho-oncology community; supporting communication skills training and encouraging programmatic thinking within services; and advocating for ongoing investment in precision supportive care through evaluation and strong clinical leadership. Conclusions: In examining 4 unique settings, the commentary recognizes the geographic variation in health care resources and social contexts of cancer care alongside cultural perspectives on psychosocial distress, screening methods, and the value of precision supportive care.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| 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".