Abstract B009: Pain alleviating factors reported by cancer patients
Bibliographic record
Abstract
Abstract Introduction: Pain is one of the complications of cancer or cancer treatment and affects the quality of life of cancer patients. Unfortunately, factors that alleviate cancer pain have been understudied despite pain being one of the most common symptoms of cancer. The purpose of this secondary comparative analysis study was to identify factors that alleviate cancer pain and their relationship to specific cancer types. Methods: The study comprised 579 participants from inpatient and outpatient cancer care centers in Seattle, WA. The participants used paper or a tablet computer to complete the McGill Pain Questionnaire, which included an open-ended question: “What kinds of things relieve your pain?” Text responses were coded into six outcome categories: 1) Activity level, 2) Cognitive, 3) Environmental, 4) Medical, 5) Physical, and 6) Sedentary behavior. Race and ethnicity categories were collapsed into Black/Other and White based on frequency distribution. We conducted a multivariable regression analysis adjusting for sociodemographic characteristics using the number of activities/factors in each of the six outcome categories. Results: Patients were mostly White (86%), female (27%) and aged 58.7± 12.3 years on average. Nearly 13% of the sample were Black/Other patients. The current pain intensity was more intense for Black/Other patients than White patients (p <0.001). Activity (ρ=0.02), cognition (ρ<0.001), and medication (ρ<0.001) were more frequently used as pain-alleviating factors among lung cancer patients compared to head and neck cancer patients. Males (ρ=0.02) and lung cancer patients (ρ=0.02) engaged in significantly less physical activity alleviating factors than females and head and neck cancer patients. Differences between the race groups were not statistically significant for mean alleviating factors. Conclusion: Although pain intensity is more intense for minority patients than their White counterparts, their behaviors to alleviate their pain do not differ in this sample. Differences in pain alleviating factors by gender and type of cancer warrant additional research to understand the complexity of patients’ self-care behaviors with consideration of demographic and cancer variables as well as analgesics. Citation Format: Dottington Fullwood, Sydney Means, Diana J. Wilkie, Folakemi T. Odedina. Pain alleviating factors reported by cancer patients [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr B009.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".