Global unmet psychosocial needs in cancer care: health policy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Preventable psychosocial suffering is an unmet need in patients with cancer around the world, significantly compromising quality of life and impairing cancer health outcomes. This narrative review overviews the global prevalence of emotional distress and cancer-related needs and the access barriers to psychosocial care. The COVID-19 pandemic has served only to amplify the need for psychosocial care, exacerbating the inadequacy of available psychosocial resources, particularly in low- and middle-income countries. Proposed solutions include implementing routine screening for emotional distress, addressing stigma related to mental health needs, and increased attention to the psychosocial dimensions of cancer care in oncology training and interprofessional models of care. There is an urgent need to address health policy issues such as resource allocation in cancer control plans and to embrace technological innovation in order to fill the universal gaps to providing more equitable psychosocial cancer care. Funding: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it