Bibliographic record
Abstract
PURPOSE OF REVIEW: Cancer diagnosis and treatment can have long-lasting psychological and physical consequences that affect both patients and their intimate partners. Improved understanding of extant dyadic interventions in the context of cancer, and how access to these may be enhanced through web-based technologies, introduce new directions for how cancer-related psychological distress for couples may be ameliorated. RECENT FINDINGS: Couples are negatively impacted by cancer, both individually, and as a dyad. Bolstering techniques to support effective communication about common cancer-related concerns and support for adjusting to new roles and responsibilities may help to strengthen the couple's relationship so partners are better able to cope with cancer. Although there are various intervention options available for couples dealing with cancer, many pose barriers to participation because of constraints on time and/or distance. However, online interventions have been shown to be effective, both in easing psychological distress and reducing participant burden. SUMMARY: Couples dealing with cancer experience psychological distress and must learn to navigate changing roles and responsibilities in the face of the disease. Online interventions offer flexible and innovative platforms and programs that help to address couples' educational needs while strengthening dyadic coping.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".