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
<div> Depression and anxiety are common comorbid conditions associated with cancer, however the risk factors responsible for the onset of depression and anxiety in cancer patients are not fully understood. Also, there is little clarity on how these factors may vary across the cancer phases: diagnosis, treatment and depression. We aimed to systematically understand and synthesise the risk factors associated with depression and anxiety during cancer diagnosis, treatment and survivorship. We focused our review on primary and community settings as these are likely settings where longer term cancer care is provided. We conducted a systematic search on PubMed, PsychInfo, Scopus, and EThOS following the PRISMA guidelines. We included cross-sectional and longitudinal studies which assessed the risk factors for depression and anxiety in adult cancer patients. Quality assessment was undertaken using the Newcastle-Ottawa assessment checklists. The quality of each study was further rated using the Agency for Healthcare Research and Quality Standards. Our search yielded 2645 papers, 21 of these were eligible for inclusion. Studies were heterogenous in terms of their characteristics, risk factors and outcomes measured. A total of 32 risk factors were associated with depression and anxiety. We clustered these risk factors into four domains using an expanded biopsychosocial model of health: cancer-specific, biological, psychological and social risk factors. The cancer-specific risk factors domain was associated with the diagnosis, treatment and survivorship phases. Multifactorial risk factors are associated with the onset of depression and anxiety in cancer patients. These risk factors vary across cancer journey and depend on factors such as type of cancer and individual profile of the patients. Our findings have potential applications for risk stratification in primary care and highlight the need for a personalised approach to psychological care provision, as part of cancer care. </div>
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 | 0.000 | 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) | 0.354 | 0.010 |
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