Meal context and food preferences in cancer patients: results from a French self-report survey
Bibliographic record
Abstract
PURPOSE: The present study examined patient self-reports of descriptions, experiences and consequences of meal disturbances and food preferences within a cultural context (i.e., French meal traditions) in various treated cancer patients along their disease trajectory. METHODS: Over 800 questionnaires were sent to 20 cancer treatment centres in France. During a 9-month period, 255 questionnaires were received from five centres. Inclusion criteria included those French patients over 18 years of age, could read and understand French, had an Eastern Cooperative Oncology Group score between 0 and 2, experienced treatment-induced nutrition changes and/or had decreased oral intake. Dietetic staff assessed clinical characteristics while patients completed a 17-item questionnaire. RESULTS: The majority of patients were diagnosed with breast, gastro-intestinal (GI) tract and head and neck cancers (62 %). Half of the patients (49 %) experienced weight loss >5 %. The main treatment-induced side effects were fatigue, nausea, dry mouth, hypersensitivity to odors and GI tract transit disorders. These discomforts affected eating and drinking in 83 % of patients, inducing appetite loss and selected food aversion. Food preference appeared heterogeneous. Food taste, odor and finally appearance stimulated appetite. Finally, dietary behaviors and satisfaction were driven by the extent to which food was enjoyed. CONCLUSIONS: During oncologic treatments, eating and drinking were affected in more than three-quarters of patients. As recommended by practice guidelines, nutritional assessment and follow-up are required. Personalized nutritional counseling should include the role of the family, patient's meal traditions, and food habits.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".