The care and service partnership for cancer patients and their families to iimprove patients and professionals’ experience
Bibliographic record
Abstract
Context: The introduction of Accompanying Patients (APs) as full members of the clinical team is a social innovation. This program is the first to offer APs to complement the oncology service offering emotional, informational, educational and navigation support. Objective: To assess the effect of APs on patients and health professionals Study Design and Analysis: A multiple longitudinal case study using mixed methods. Setting: University of Montréal Health Centre (Montreal, Canada); University of Laval Health Centre (Québec, Canada); Integrated University health and social services Centre of the East of Montréal (Montreal, Canada);. Population studied: People with cancer undergoing treatment and health professionals working in the cancer wards Intervention/Instrument & Outcome Measures: People with cancer had at least one contact with an AP during their treatment. They were asked to complete questionnaires (the Communication and Attitudinal Self-efficacy scale; the The Kessler Psychological Distress Scale (K6). Additional interviews were conducted with a sample of these patients. in addition, health professionals were interviewed about their perception of the contribution or limitations of the AP’s interventions. Results; The 3 institutions provided support to 989 patients; 540 of whom agreed to participate in the research project. These accompaniments were mainly carried out in the breast cancer trajectory (96%). Interviews with patients show that the intervention reduces anxiety, helps them prepare for medical appointments, be more proactive in making decisions and have a better experience of care and quality of life. It allows APs to make sense of their care journey and give back to the next. The results of the Communication and Attitudinal Self-efficacy scale for cancer show that 100% of the accompanied patients understand and participate in their care and 90% maintain a positive attitude. The Kessler Psychological Distress Scale (K6) showed that supported patients had less psychological distress than cancer patients in general (10.7% versus 33.5%). For professionals, they have access to patients’ personal information that can be helpful in treating their patients, feedback on their practices and on organizational issues.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".