Transcultural Validation of the French Version of the Modified Edmonton Symptom Assessment Scale: The ESAS12-F
Bibliographic record
Abstract
Abstract Background: Cancer-related physical symptoms can decrease patients' overall quality of life and are often underdiagnosed. The Edmonton Symptom Assessment Scale (ESAS) is widely used in palliative care for cancer patients to easily assess cancer patients' symptoms. It has been often modified, adding symptoms and explanations, and translated into many languages. The European Association of Palliative Care research team developed a database, which included the modified 12-item ESAS-r as the symptom assessment tool. Objectives: The purpose of this study was to achieve the translation and cross-cultural validation in French of the 12-item ESAS-r, the ESAS12-F. Design: A French version of the ESAS-r was developed using a standardized forward and backward translation method. Patients completed the ESAS12-F and provided feedback on the translation. Setting/Subjects: Forty-five patients with advanced cancer, followed by the palliative care team from the Lyon Sud University Hospital in France, were recruited. Results: Eighty-nine percent of patients considered the ESAS easy to understand. They highlighted some concerns more about the tool itself than the translation: the time line “now,” the difficulty to quantify a symptom in a numerical evaluation. Some items (sleep and appetite) needed to be reread and for some others (digestive and psychological symptoms, and well-being) to be reordered in the questionnaire. Conclusion: The ESAS12-F is well accepted and easy to use for the cancer patients. The next step is to carry out a psychometric validation of the definitive version of the ESAS12-F.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".