HIV-Related Stigma Among Healthcare Providers in Different Healthcare Settings: A Cross-Sectional Study in Kerman, Iran
Bibliographic record
Abstract
BACKGROUND: Stigmatizing attitudes among healthcare providers are an important barrier to accessing services among people living with HIV (PLHIV). This cross-sectional study aimed to assess the status and correlates of HIV-related stigma among healthcare providers in Kerman, Iran. METHODS: Using a validated and pilot-tested stigma scale questionnaire, we measured HIV-related stigma among 400 healthcare providers recruited from three teaching hospitals (n=363), private sectors (n=28), and the only voluntary counseling and testing (VCT) center (n=9) in Kerman city. Data were gathered using self-administered questionnaires at participants' workplace during Fall 2016. To examine the correlates of stigmatizing attitudes, we constructed bivariable and multivariable linear regression models. RESULTS: The mean ± standard deviation (SD) of stigma score was 25.95 ± 7.20 out of the possible 50, with higher scores reflecting more stigmatizing attitudes. Paramedics, nurses' aides, and housekeeping staff had the highest, and VCT personnel had the lowest average stigma scores, respectively. Multivariable regression analyses showed that prior experience of working with PLHIV (β=-2.48; P=.03), exposure to HIV-related educational courses (β=-2.03; P=.02), and <10 years of work experience (β=-2.70; P<.001) were associated with lower stigma scores. CONCLUSION: Our findings highlight the need for health managers to provide training opportunities for healthcare providers, including programs that focus on improving HIV-related knowledge for healthcare providers. Enforcing policies that aim to reduce HIV-related stigma and discrimination among healthcare providers in Iran are urgently needed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".