The Role of Financial Difficulties as a Mediator between Physical Symptoms and Depression in Advanced Cancer Patients
Bibliographic record
Abstract
Financial difficulties experienced by cancer patients negatively impact the mental health of the patients. The objective of this study was to examine the mediating role of financial difficulties between physical symptoms and depression in patients with advanced cancer. A prospective, cross-sectional design was adopted in the study. The data were collected from 861 participants with advanced cancer in 15 different tertiary hospitals in Spain. The participants' socio-demographic characteristics were collected using a standardized self-report form. Hierarchical linear regression models were used to explore the mediating role of financial difficulties. In the results, 24% of patients reported a high level of financial difficulties. Physical symptoms were positively associated with financial difficulties and depression (β = 0.46 and β = 0.43, respectively), and financial difficulties was positively associated with depression (β = 0.26). Additionally, financial difficulties played a role in explaining the relationship between physical symptoms and depression, showing a standardized regression coefficient of 0.43 which decreased to 0.39 after the financial difficulties were controlled. Healthcare professionals should consider the importance of providing financial resources and emotional support to help patients and their families cope with the financial burden associated with cancer treatment and its symptoms.
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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 | 0.002 | 0.010 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".