What is Symptom Burden: A Qualitative exploration of Patient Definitions
Bibliographic record
Abstract
Current definitions of "symptom burden" are largely derived from clinicians, and there are many variations in the way the term is used, defined, and operationalized. The aim of this study was to explore patient perceptions of symptom burden in the context of advanced and incurable disease. A group of 58 cancer patients followed by a palliative care team answered a single open-ended question: "Please define 'symptom burden'". Three authors independently coded and analyzed patient responses using a grounded theory approach. They identified six themes, the most frequently coded of which were: "can't do usual activities", "psychological suffering" and "specific severe symptoms". Our findings indicate that the concept of symptom burden is complex and extends beyond numerical symptom-scoring systems. In addition to inquiring about specific symptoms, it may be important to directly ask patients about their overall burden or experience of symptoms.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".