Effectiveness of a brief manualized intervention, Managing Cancer and Living Meaningfully (CALM), adapted to the Italian cancer care setting: Study protocol for a single-blinded randomized controlled trial
Bibliographic record
Abstract
Patients with advanced cancer suffer from psychosocial distress that may impair quality of life and that may be ameliorated by psychotherapeutic treatment. We describe here the methodology of a randomized controlled trial (RCT) to assess the effectiveness of a novel, brief, semi-structured psychotherapeutic intervention to reduce distress and increase well-being in patients with advanced or metastatic cancer. The intervention, called Managing Cancer and Living Meaningfully (CALM), was originally developed in Canada and we are now testing its Italian adaptation (CALM-IT). The study is a single-blinded phase III RCT with assessment at baseline, 3 and 6 months with two conditions: CALM-IT versus a nonspecific supportive intervention (SPI). Eligibility criteria include: ≥ 18 years of age; fluency in the Italian language; no cognitive deficit, and diagnosis of advanced or metastatic cancer with an expected survival of 12-18 months. CALM-IT includes up to 12 sessions, delivered over 6 months and covers 4 domains: i) Symptom Management and Communication with Health Care Providers; ii) Changes in Self and Relations with Close Others; iii) Sense of Meaning and Purpose; and iv) the Future and Mortality. The primary outcome is difference in severity of depressive symptoms between treatment arm and the primary endpoint is 6 months. The secondary endpoint is 3 months and secondary outcomes are: generalized anxiety, distress about dying and death, demoralization, spiritual well-being, attachment security, posttraumatic growth, communication with partners, quality of life, and satisfaction with clinical care. If shown to be effective, CALM-IT can be implemented nationally to relieve distress and to promote psychological well-being in patients with advanced cancer.
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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 | 0.021 | 0.023 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.045 | 0.008 |
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".