Prevalence and associated factors of alexithymia among people living with HIV/AIDS in China: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Alexithymia is common and causes serious harm to people living with HIV/AIDS. Therefore, this study aimed to examine its prevalence and associated factors among people living with HIV/AIDS in China. METHODS: A cross-sectional study was conducted in two designated AIDS medical institutions in Harbin, China between January and December 2019. In total, 767 participants completed the 20-item Toronto Alexithymia Scale, the University of California Los Angeles Loneliness short-form, the Patient Health Questionnaire-9, the HIV Treatment Regimen Fatigue Scale, and the Alcohol Use Disorders Identification Test-Consumption. The participants responded to several questions regarding their demographic characteristics, life satisfaction, disease-related economic burden, and their antiretroviral therapy (ART) side effects. Multivariate logistic regression assessed the relationship between alexithymia and associated factors. Odds ratios (OR) and 95% confidence intervals (CI) for OR were calculated. RESULTS: Approximately 36.1% of the participants were classified as having alexithymia. After adjusted age and education, the logistic regression model indicated that disease-related economic burden (OR = 1.477, 95% CI = 1.155-1.888), ART side effects (OR = 1.249, 95% CI = 1.001-1.559), loneliness (OR = 1.166, 95% CI = 1.101-1.236), and HIV treatment regimen fatigue (OR = 1.028, 95% CI = 1.017-1.039) were positively associated with alexithymia. CONCLUSIONS: The mental health problems of people living with HIV/AIDS are essential to understand and deserve attention. Disease-related economic burdens are major associated factors. Multiple actors should provide better services and guarantees for patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".