Adaptive and maladaptive coping strategies among patients with advanced cancer.
Bibliographic record
Abstract
e24129 Background: Few studies have examined the coping mechanisms among patients with advanced cancer seen by palliative care. The objective of the study was to evaluate coping strategies in advanced cancer patients and identity risk factors for maladaptive coping. Methods: The authors conducted a secondary analysis of a cross-sectional survey on chemical coping. We prospectively enrolled patients with advanced cancer from a Supportive Care Clinic and documented the patient demographics, symptom expression (Edmonton Symptom Assessment System), Zubrod performance status, substance use history including tobacco, and coping strategies (the Brief COPE Questionnaire). Univariate and multivariate analyses were performed to identify risk factors for the use of maladaptive coping strategies. Results: Among 399 patients, the most common malignancies were gastrointestinal (21%) and breast (19%). Cancer patients frequently incorporated adaptive coping strategies including acceptance (86.7%), emotional support (79.9%), religion (69.4%), active coping (62.4%), instrumental support (48.4%), positive reframing (48.6%), planning (49.6%), and infrequently, humor (18.5%). Common maladaptive strategies included self-distraction (36.6%) and venting (14.5%), while self-blame (6.3%), denial (4.5%), behavioral disengagement (1.8%), and substance use (1.0%) were infrequently reported. On univariate analysis, venting was significantly associated with anxiety and depression, female gender, and tobacco use; and self-distraction was significantly associated with younger age, gender, depression, dyspnea, and a post-secondary education (P<0.05 for all). On multivariate analysis, male gender (OR -1.22, p<0.0001) and smoking (non-smoker vs everyday OR -1.9, P=0.008 ) remained significant for maladaptive venting; and age (HR -0.026, p=0.005), male gender (OR -0.65, p=0.004), dyspnea (OR -0.12, p=0.01) and post-secondary education (OR 0.596, p=0.022) remained significant for self-distraction. Conclusions: The vast majority of patients with advanced cancer seen by palliative care reported using adaptive coping strategies. We identified subgroup of patients who may be more likely to use maladapative coping strategies and may benefit from further psychological support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.004 | 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".