Comparative Study of the Quality of Life and Coping Strategies in Oncology Patients
Bibliographic record
Abstract
BACKGROUND: Despite the current data on morbidity and mortality, a growing number of patients with a diagnosis of cancer survive due to an early diagnosis and advances in treatment modalities. This study aimed to compare the quality of life and coping strategies in three groups of patients with cancer and identify associated clinical and sociodemographic characteristics. METHODS: A comparative study was conducted with outpatients at a public hospital in the state of São Paulo, Brazil. The 300 participants were assigned to three groups: patients in palliative care (Group A), patients in post-treatment follow-up with no evidence of disease (Group B), and patients undergoing treatment for cancer (Group C). Data collection involved the use of the McGill Quality of Life Questionnaire and the Ways of Coping Questionnaire. No generic quality-of-life assessment tool was utilized, as it would not be able to appropriately evaluate the impact of the disease on the specific group of patients receiving palliative care. RESULTS: Coping strategies were underused. Participants in the palliative care group had poorer quality of life, particularly in the psychological well-being and physical symptom domains. Age, currently undergoing treatment, and level of education were significantly associated with coping scores. Age, gender, income, and the absence of pharmacological pain control were independently associated with quality-of-life scores. Moreover, a positive association was found between coping and quality of life. CONCLUSION: Cancer patients in palliative care generally report a lower quality of life. However, male patients, those who did not rely on pharmacological pain control, and those with higher coping scores reported a better perception of their quality of life. This perception tended to decrease with age and income level. Patients currently undergoing treatment for the disease were more likely to use coping strategies. Patients with higher education and quality-of-life scores also had better coping scores. However, the use of coping strategies decreased with age.
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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 | 0.003 |
| 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".