Bibliographic record
Abstract
Abstract This text outlines the empirical research, theoretical underpinnings, and clinical application of a novel supportive-expressive psychotherapy for patients with metastatic cancer and their caregivers. Managing Cancer and Living Meaningfully, known by its acronym of CALM, provides a framework for therapists with diverse backgrounds and training to help patients and their caregivers to address the practical and profound challenges of advanced cancer and to live their lives as meaningfully as possible. CALM provides reflective space for them to consider treatment decisions and communication with their health care providers, disruptions in identity, attachment security and the sense of meaning in their life, and to address fears, hopes, and concerns related to the end of life. Particular attention is paid in CALM to the regulation of affect, to the renegotiation of attachment relationships and to helping patients and their caregivers to sustain “double awareness” of the possibilities for living, while also managing their disease and planning for the end of life. Such an approach not only helps to prevent depression and death anxiety, but also helps to reclaim the loss of the imaginative possibilities for living in the context of all-consuming cancer care. The universal dimensions of advanced cancer and the semi-structured nature of CALM permit it to be delivered in the language and cultural idiom of cancer treatment settings in virtually all parts of the world. This text provides the most comprehensive and up-to-date description of the evidence base for CALM, its theoretical foundations and a manualized guide to its clinical application, filled with rich clinical illustrations.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".