Individual‐, household‐, and community‐level factors associated with pregnant married women's discriminatory attitude towards people living with<scp>HIV</scp>in<scp>sub‐Saharan</scp>Africa: A multicountry cross‐sectional study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Discriminatory attitude towards people living with human immunodeficiency virus (HIV) remains a major problem in the prevention and treatment of HIV in sub-Sahara Africa (SSA). Understanding the multiple factors linked to discriminatory attitude towards people living with HIV/AIDS (PLWHA) in SSA is necessary for developing appropriate interventions. This study aimed at investigating the individual, household, and community-level factors associated with pregnant married women's discriminatory attitude towards people living with HIV/AIDS. METHODS: We used data from the Demographic and Health Surveys of 12 sub-Saharan African countries conducted between 2015 and 2019. Data on 17 065 pregnant married women were analyzed. Bivariate (chi-squared test) and multivariable multilevel logistic regression analyses were applied to investigate the factors associated with discriminatory attitude towards PLWHA. The results were reported as adjusted odds ratio (aOR) at 95% confidence interval (CI). RESULTS: The mean age of participants was 31.2 ± 8.5. The prevalence of discriminatory attitude towards PLWHA was 36.2% (95% CI: 33.4%-39.1%). Individual/household-level factors associated with discriminatory attitude towards PLWHA were women's educational level (secondary school-aOR = 0.49, 95% CI: 0.26-0.93), husband's educational level (higher education-aOR = 0.35, 95% CI: 0.16-0.76), decision-making power (yes-aOR = 0.51, 95% CI: 0.38-0.69), wife-beating attitude (disagreement with wife beating-aOR = 0.58, 95% CI: 0.43-0.79), and religion (Muslim-aOR = 1.92, 95% CI: 1.22-3.04). Community socioeconomic status (medium-aOR = 0.61, 95% CI: 0.41-0.93) was the only community-level factor associated with discriminatory attitude towards PLWHA. CONCLUSION: More than one-third of pregnant married women in SSA had discriminatory attitude towards PLWHA. Women's educational level, husband's educational level, decision-making power, wife-beating attitude, religion, and community socio-economic status were associated with discriminatory attitude towards PLWHA. To lessen the prevalence of discriminatory attitude towards PLWHA, considering these significant factors is needed. Therefore, governments and other stakeholders in the respective countries need to increase education coverage. Moreover, empowering women through education and economy is crucial. Finally, working with religious leaders to increase awareness about HIV and discriminatory attitude towards PLWHA should also be a priority in SSA.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".