Effects of Depression, Anxiety, Stigma, and Disclosure on Health-Related Quality of Life among Chronic Hepatitis B Patients in Dalian, China
Bibliographic record
Abstract
Chronic hepatitis B virus (HBV) infection is a major public health problem in China. We evaluated the impact of psychosocial factors (stigma, disclosure, depression, and anxiety) on health-related quality of life (HRQoL) among people living with chronic HBV infection (CHB) in the city of Dalian, Liaoning Province, China. In this hospital-based cross-sectional study, 401 patients living with chronic HBV infection were enrolled as study participants. Study measures included the Beck depression and anxiety inventory, the WHO Quality of Life (WHOQOL-BREF) assessment, the Toronto Chinese HBV Stigma Scale, and disclosure of HBV status to sexual partners. The primary outcome was HRQoL score as measured by the WHOQOL-BREF. A linear regression model was used to examine the association between HRQoL and the potential risk factors including stigma, disclosure, depression, anxiety, and sociodemographic variables. Stigma, disclosure, depression, and anxiety were the covariates of interest. A majority of the participants were females ( n = 251, 65.6%), married (81.6%), and had a college or higher degree (32.4%). Depression, anxiety, stigma, and disclosure of HBV infection were associated with low HRQoL in all four domains of the WHOQOL-BREF (physical, psychological, social, and environmental domains) ( P < 0.05), when all psychological factors were included in the model separately. Depression was found to be independently associated with low HRQoL in people living with HBV, when all psychological factors were included in the model simultaneously ( P < 0.0001). Our data indicate the urgent need for healthcare providers (HCPs) and policy-makers to implement psychological interventions to improve HRQoL among people living with CHB.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".