Managing Cancer And Living Meaningfully: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: We have developed a novel and brief semi-structured psychotherapeutic intervention for patients with advanced or metastatic cancer, called Managing Cancer And Living Meaningfully. We describe here the methodology of a randomized controlled trial to test the efficacy of this treatment to alleviate distress and promote well-being in this population. METHODS/DESIGN: The study is an unblinded randomized controlled trial with 2 conditions (intervention plus usual care versus usual care alone) and assessments at baseline, 3 and 6 months. The site is the Princess Margaret Cancer Centre, part of the University Health Network, in Toronto, Canada. Eligibility criteria include: ≥ 18 years of age; English fluency; no cognitive impairment; and diagnosis of advanced cancer. The 3-6 session intervention is manualized and allows for flexibility to meet individual patients' needs. It is delivered over a 3-6 month period and provides reflective space for patients (and their primary caregivers) to address 4 main domains: symptom management and communication with health care providers; changes in self and relations with close others; sense of meaning and purpose; and the future and mortality. Usual care at the Princess Margaret Cancer Centre includes distress screening and referral as required to in-hospital psychosocial and palliative care services. The primary outcome is frequency of depressive symptoms and the primary endpoint is at 3 months. Secondary outcomes include diagnosis of major or minor depression, generalized anxiety, death anxiety, spiritual well-being, quality of life, demoralization, attachment security, posttraumatic growth, communication with partners, and satisfaction with clinical interactions. DISCUSSION: Managing Cancer And Living Meaningfully has the potential to relieve distress and promote psychological well-being in patients with advanced cancer and their primary caregivers. This trial is being conducted to determine its benefit and inform its dissemination. The intervention has cross-national relevance and training workshops have been held thus far with clinicians from North and South America, Europe, the Middle East, Asia and Africa. TRIAL REGISTRATION: ClinicalTrials.gov NCT01506492 4 January 2012.
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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 | 0.051 | 0.046 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.121 | 0.020 |
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".