Edmonton Symptom Assessment Scale Time Duration of Self-Completion Versus Assisted Completion in Patients with Advanced Cancer: A Randomized Comparison
Bibliographic record
Abstract
INTRODUCTION: To compare the time duration of self-completion (SC) of the Edmonton Symptom Assessment Scale (ESAS) by patients with advanced cancer (ACPs) versus assisted completion (AC) with a health care professional. MATERIALS AND METHODS: In this randomized comparison of ACPs seen in initial consultation at the outpatient Supportive Care Center at MD Anderson, ACPs who have never completed the ESAS at MD Anderson were allocated (1:1) to either SC of the ESAS form versus AC by a nurse. Time of completion was measured by the nurse using a stopwatch. Patients completed the Rapid Estimate of Adult Literacy in Medicine (REALM) test prior to administration of the ESAS. In the SC group, the nurse reviewed the responses to verify that the reported ESAS scores were correct. RESULTS: A total of 126 ACPs were enrolled (69 patients to AC and 57 to SC). Seventy-one patients were female, median age was 60 years, and median REALM score was 65. Median (interquartile range) time (in seconds) of SC was significantly less than AC (73 [42.9-89.1] vs. 109 [79.5-136.7], p < .0001). With nurse review time included, median time of SC increased to 117 seconds, which was not significantly different from AC (p = .28). Lower literacy (REALM) score and shortness of breath were significantly associated with increased completion time (p = .007). CONCLUSION: Regular use of ESAS will have minimal impact on clinical time, as it can be completed in about 1 minute and provides a concise yet comprehensive and multidimensional perspective of symptoms that affect quality of life of patients with cancer. IMPLICATIONS FOR PRACTICE: Because the Edmonton Symptom Assessment Scale can be completed in less than 2 minutes, hopefully the routine use of this simple yet comprehensive and multidimensional symptom assessment tool will be used at all medical visits in all patients with cancer so that the timely management of symptoms affecting patients' lives and treatment courses can occur, further enhancing personalized cancer care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".