Engaging patients as partners in cancer care: An innovative strategy to implement screening for distress?
Bibliographic record
Abstract
Patient distress is frequently missed in everyday cancer care, yet can be associated with decreased quality of life and satisfaction with care, as well as increased risk for comorbidity and morbidity. Considered as an aspect of a patient-centred approach, screening for distress is now an international standard of practice and constitutes an accreditation criterion for cancer centers in the USA and Canada. Inspired by existing health partnership models, the Centre Hospitalier de l'Université de Montréal's (CHUM) Integrative Cancer Care Center recruited patients to act as partners during the creation and implementation of its screening for distress program. Patient partner roles in the program included becoming a member of a specialized psychosocial oncology team, contributing to a healthcare professional training program and helping to select tools to detect distress. This paper describes why and how the CHUM cancer care centre developed an innovative screening for distress program, using a patient partnership approach, to better meet the needs of patients with 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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".