Coping Strategies and Associated Symptom Burden Among Patients With Advanced Cancer
Bibliographic record
Abstract
BACKGROUND: Few studies examine how patients with advanced cancer cope with stress. The objective of our study was to evaluate coping strategies adopted by patients with cancer and their relationship with symptom burden. METHODS: A secondary data analysis of a prospective cross-sectional survey of patients with cancer and tobacco use was conducted, which examined demographics, symptom burden (Edmonton Symptom Assessment System), and coping strategies (the Brief COPE Questionnaire). Demographic characteristics were summarized by standard summary statistics; we also examined associations between patient characteristics and coping strategies using t-test, rank-sum test, chi-squared test, or Fisher's exact test depending on the distribution of data. RESULTS: Among 399 patients, the majority were female (60%), Caucasian (70%), the mean age was 56.5 (±12.0) years, and the most common malignancies were gastrointestinal (21%) and breast (19%). Patients with cancer adopted multiple adaptive coping strategies, most frequently acceptance (86.7%) and emotional support (79.9%), with humor (18.5%) being the least. Common maladaptive strategies included venting (14.5%) and self-distraction (36.6%), while substance use (1.0%) was infrequently reported. Of the adaptive strategies, female gender was significantly associated with higher engagement with emotional and instrumental support, positive reframing, religious coping, and acceptance (P < .05 for all). College educated patients reported significantly higher implementation of humor, planning, and acceptance. Maladaptive coping strategies such as denial were associated with increased pain and depression, while patients adopting emotional-focused strategies rated decreased emotional distress. CONCLUSIONS: The majority of patients with advanced cancer reported adopting multiple, adaptive coping strategies, and a minority utilized maladaptive or avoidant strategies, rarely substance use, and may need additional psychological support.
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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 | 0.002 |
| 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) | 0.002 | 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".