Validation of the Edmonton Symptom Assessment Scale
Bibliographic record
Abstract
BACKGROUND: The Edmonton Symptom Assessment Scale (ESAS) is a nine-item patient-rated symptom visual analogue scale developed for use in assessing the symptoms of patients receiving palliative care. The purpose of this study was to validate the ESAS in a different population of patients. METHODS: In this prospective study, 240 patients with a diagnosis of cancer completed the ESAS, the Memorial Symptom Assessment Scale (MSAS), and the Functional Assessment Cancer Therapy (FACT) survey, and also had their Karnofsky performance status (KPS) assessed. An additional 42 patients participated in a test-retest study. RESULTS: The ESAS "distress" score correlated most closely with physical symptom subscales in the FACT and the MSAS and with KPS. The ESAS individual item and summary scores showed good internal consistency and correlated appropriately with corresponding measures from the FACT and MSAS instruments. Individual items between the instruments correlated well. Pain ratings in the ESAS, MSAS, and FACT correlated best with the "worst-pain" item of the Brief Pain Inventory (BPI). Test-retest evaluation showed very good correlation at 2 days and a somewhat smaller but significant correlation at 1 week. A 30-mm visual analogue scale cutoff point did not uniformly distinguish severity of symptoms for different symptoms. CONCLUSIONS: For this population, the ESAS was a valid instrument; test-retest validity was better at 2 days than at 1 week. The ESAS "distress" score tends to reflect physical well-being. The use of a 30-mm cutoff point on visual analogue scales to identify severe symptoms may not always apply to symptoms other than pain.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".