How Dialysis Patients Live: A Study on Their Depression and Associated Factors in Southern Italy
Bibliographic record
Abstract
Depression is an independent risk factor of poor outcomes for Chronic Kidney Disease (CKD) patients. Perceived social support and alexithymia are psychosocial variables identified by previous studies as predictive of depression in normal controls and CKD patients. Repetitively thinking and socially sharing emotional experiences have been investigated in association with depression in normal populations. Our cross-sectional study aimed to assess the effects of perceived social support, alexithymia, mental rumination, and social sharing on depression in CKD patients and controls. 103 CKD patients (age = 61.9 ± 7.2, 54 men) and 101 controls (age = 64.51 ± 6.56; 47 men) completed a questionnaire of 5 sections: Pluridimensional Inventory for Haemodialysis Patients (IPPE), Multidimensional Scale of Perceived Social Support (MSPSS), Geriatric Depression Scale (GDS), Toronto Alexihymia Scale (TAS-20), Social Sharing and Mental Rumination. Multiple regression analysis models with dummy variables assessed the effects of IPPE, MSPSS, TAS-20, Social Sharing, and Mental Rumination on GDS across the subgroups of participants. SPSS software was used. Depression levels resulted higher for patients than controls, especially in patients dialyzed for less than 4 years. The effects of perceived social support and alexithymia differed with respect to the subsamples. Rumination was positively associated with depression in normal controls, but negatively related with depression in patients dialyzed for 4+ years. The study confirmed high levels of depression in CKD patients. Depression was influenced by perceive social support, alexithymia, and the cognitive elaboration of emotional troubles associated with the disease. Rumination appeared as a dysfunctional consequence of emotions for normal controls, but had an adaptive function for patients dialyzed for 4+ years
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".