Prevalence of depression in a cohort of 400 patients with pancreatic neoplasm attending day hospital for major surgery: Role on depression of psychosocial functioning and clinical factors
Bibliographic record
Abstract
OBJECTIVE: (1) To determine the prevalence and type of depressive symptoms at day-hospital clinical evaluation, before undergoing major surgery in patients diagnosed with pancreatic neoplasm. (2) To analyze the association between depression and sociodemographic, clinical, and psychosocial variables. (3) To understand how coping strategies, perceived social support, and self-efficacy might affect depressive symptoms in this cohort of patients. METHODS: Secondary data analysis collected during the baseline phase of a randomized controlled trial performed at the Pancreas Institute of the University Hospital of Verona, Italy, between June 2017 and June 2018. RESULTS: 18.5% of pancreatic patients had a PHQ-9 score ≥10 (cut-off). Depressed patients were basically more often female (p = 0.07), younger (p = 0.06), and married/with a partner (p = 0.02). Depression was associated to high trait anxiety (p < 0.01), the use of anxiolytics (p < 0.01), sleep-inducing drugs (p < 0.01), and painkillers (p < 0.01). Among psychosocial variables, depressed patients showed lower perceived self-efficacy (p < 0.01) and family and friends' social support (p < 0.01) and used significantly more often dysfunctional coping strategies (p < 0.01), compared to nondepressed. A logistic multivariate model using psychosocial variables as explanatory and depression as dependent was calculated and post hoc analyses were conducted to describe the contribution of each psychosocial variable on depression. CONCLUSIONS: Our study advocates the need for screening for distress and depression in cancer surgery units and recommends to strengthen patients' adaptive coping, social support, and sense of effectiveness in facing the challenges related to the medical condition and treatment process.
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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 | 0.001 |
| 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) | 0.001 | 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".