Symptom Burden, Medication Detriment, and Support for the Use of the 15D Health-Related Quality of Life Instrument in a Chronic Pain Clinic Population
Bibliographic record
Abstract
Chronic noncancer pain is a prevalent problem associated with poor quality of life. While symptom burden is frequently mentioned in the literature and clinical settings, this research highlights the considerable negative impact of chronic pain on the individual. The 15D, a measure of health-related quality of life (HRQOL), is a user-friendly tool with good psychometric properties. Using a modified edmonton symptom assessment scale (ESAS), we examined whether demographics, medical history, and symptom burden reports from the ESAS would be related statistically to HRQOL measured with the 15D. Symptom burden, medication detriment scores, and number of medical comorbidities were significant negative predictors of 15D scores with ESAS symptom burden being the strongest predictor. Our findings highlight the tremendous symptom burden experienced in our sample. Our data suggest that heavier prescription medication treatment for chronic pain has the potential to negatively impact HRQOL. Much remains unknown regarding how to assess and improve HRQOL in this relatively heterogeneous clinical population.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".