Depression and Cigarette Smoking Independently Relate to Reduced Health-Related Quality of Life among Canadians Living with Hepatitis C
Bibliographic record
Abstract
BACKGROUND: Many people living with chronic viral hepatitis C (HCV) report reduced health-related quality of life. The relative contribution of behavioural, psychosocial and HCV disease factors to reduction in HCV health-related quality of life is not well understood. The objectives of the present study were to compare standardized health-related quality of life scores between Canadian HCV patients and age-matched Canadian and American norms, and to examine the relative contribution of biopsychosocial variables (ie, cigarette smoking, alcohol intake and depression) to health-related quality of life scores among Canadian HCV patients. METHODS: HCV RNA-positive patients were recruited during their first visit to the Ottawa Hospital Viral Hepatitis Clinic (Ottawa, Ontario). A questionnaire assessing health behaviours, health-related quality of life and depressed mood was completed. Data on liver studies, liver biopsy findings and HIV serostatus were also collected. RESULTS: A total of 123 participants (71% men) ranging from 20 to 67 years of age were evaluated. All had compensated liver function. Patients reported significantly lower health-related quality of life compared with age-matched Canadian and American normative samples. In a series of hierarchical multiple regression models, depression and smoking were independently related to compromised health-related quality of life scores, even after controlling for sociodemographic variables and health behaviours. DISCUSSION: These results highlight the value of adopting a biopsychosocial model of HCV care. Depressed mood and smoking behaviour should be evaluated in HCV patients. Empirically validated psychological and pharmacological treatments for depression and smoking cessation may improve health-related quality of life in HCV infected patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".