Cancer Nutrition Rehabilitation Program: The Role of Social Work
Bibliographic record
Abstract
The Cancer Nutrition Rehabilitation (cnr) program at the McGill University Health Centre is an interdisciplinary 8-week treatment program offering patients information, education, treatment, and support in areas such as diet, exercise, and rehabilitation, plus resources to address their psychosocial needs. The program social worker helps the patient and the patient's family to cope with the illness, to problem-solve, and to obtain needed resources. Here, we present a description of these patients-demographics, medical diagnoses, and psychosocial needs as assessed by the Person-in-Environment standardized instrument-derived from the social-work files of the 75 patients referred to social work in the period February 2007-December 2008. The reason most frequently reported for referral to social work was assistance with psychosocial problems. For 41.3% of the sample, these problems were assessed as high severity, and almost half the patients in the sample (47.8%) were assessed as having inadequate coping ability. Patient age was the most important demographic variable. Although seniors (63-94 years of age) were the least likely to have high-severity psychosocial problems, they were the most likely to have inadequate coping ability. That finding suggests that the cnr social worker, in addition to dealing with the instrumental, practical needs of cancer patients, is in a unique position to respond to their emotional difficulties in coping with their illness, and that health care professionals need to pay particular attention to the coping ability of elderly patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".