Managing cancer and living meaningfully (CALM): A randomized controlled trial of a psychological intervention for patients with advanced cancer.
Bibliographic record
Abstract
LBA10001 Background: Patients with advanced cancer experience substantial distress in response to the burden of disease and the challenge of living meaningfully in the face of impending mortality. We developed a novel, brief, manualized psychotherapeutic intervention called CALM designed to alleviate distress and facilitate adjustment in this population. CALM consists of 3-6 individual sessions delivered over 3-6 months and supports exploration in 4 broad domains: 1) symptom management and communication with health care providers; 2) changes in self and relations with close others; 3) sense of meaning and purpose; and 4) the future and mortality. Methods: Patients with advanced cancer were recruited from outpatient clinics at a comprehensive cancer center and randomized to receive either CALM or usual care (UC). Assessments of depressive symptoms (primary outcome), death-related distress and other secondary outcomes were conducted at baseline, 3 (primary endpoint) and 6 months. ANCOVA was used to test for outcome differences between groups at follow-up, controlling for baseline scores. Results: Three hundred and five participants were recruited and randomized (n = 151 CALM; n = 154 UC). Compliance with the intervention was 77.5% and attrition was 28% (16% deceased, 8% lost to follow-up, 4% withdrew). The CALM group reported less severe depressive symptoms compared to UC at 3 (ΔM1-M2 = 1.09, p < 0.04; Cohen’s d = 0.23) and 6 months (ΔM1-M2 = 1.33, p < 0.01; Cohen’s d = 0.29). Other statistically significant findings in psychological well-being and preparation for the end of life at 3- and 6- months also favored CALM vs UC. Conclusions: CALM is an effective intervention for patients with advanced cancer that provides a systematic approach to alleviate distress and to address predictable challenges. Clinical trial information: NCT01506492.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".