Screening for Distress (The Sixth Vital Sign) in A Global Recession: Sustainable Approach to Maintain Patient-Centered Care
Bibliographic record
Abstract
A substantial volume of research on the psychosocial impact of cancer clearly indicates that patients are likely to experience emotional distress. There is also evidence that psychosocial interventions aimed at decreasing distress provide tangible cost offsets to cancer patients, caregivers and treating institutions. One seemingly major drawback in the setup and delivery of a fully fledged screening program for distress is the extensive pecuniary requirements. Given that the categorical need for distress screening may be confounded by financial limitations, especially in a time of global recession, a cost-effective alternative seems appropriate. The model proposed herein is not a substitute screening program, nor does it eliminate the need to allocate resources to address the identified risks. It does, however, offer a cost-effective alternative to implement a high-risk distress patient identifying process, quite similar to algorithms used in screening for prostate cancer.
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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".