Severity, interference, qualities, and correlates of severe pain: Descriptive cross-sectional study on pain experience of cancer patients in Sri Lanka
Bibliographic record
Abstract
OBJECTIVE: Pain is the most debilitating and subjective experience of cancer patients. This study examines the severity, interference, characteristics, and associations of severe pain in Sri Lankan cancer patients. METHODS: A descriptive study was conducted in Sri Lanka on 384 patients at age 18 or older who had cancer pain for 3 months or more due to the initial lesion, secondaries, radiation, or chemotherapy. Patients with non-cancerous pain or brain metastases were excluded. Data was collected using a validated Sinhala version of the Short-Form Brief Pain Inventory and the Short-Form McGill Pain Questionnaire-2. Logistic regression was used to identify severe pain correlations. RESULTS: The mean of the "worst pain" experience was 7.97, and 73.2% reported their "worst pain" as severe. The "normal works" (62.5%) and "sleep" (58.3%) were severely influenced by pain. "Aching pain," was the most reported pain quality. A statistically significant association was shown between severe pain and male gender (adjusted odds ratio (AOR) = 1.723), being in marriage (AOR = 1.947), absence of family commitments (AOR = 1.8), and pain of 3 months or more duration (AOR = 1.76). CONCLUSION: The experiences of cancer pain vary, with the majority suffering from severe 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".