Psychometric assessment of HIV stigma in patients attending a tertiary facility: An initial validation of the Berger HIV stigma scale in a Ghanaian perspective
Bibliographic record
Abstract
BACKGROUND: HIV-related stigma and discrimination are major challenges to people living with HIV (PLWHIV) and are due to misconceptions. Due to socioeconomic variations, there is increased stigma experienced by PLWHIV in sub-Saharan Africa (SSA). Stigma affects adherence to antiretroviral medications by PLWHIV and defeats the goal of achieving viral suppression. This study evaluated the Bergers HIV stigma scale in PLWHIV in Ghana regarding construct validity and reliability and assessed which aspect of stigma is critical for immediate redress. METHODS: The Berger et al. HIV stigma scale (39 items) and some selected questions from HIV stigma and discrimination measurement tool of the International Centre for Research on Women, Washington, DC were administered to a cohort of PLWHIV in Ghana (n = 160). Clinico- demographic data was collected from their folders and verbally. The psychometric assessment included exploratory factor analysis whiles scale reliability was evaluated as internal consistency by calculating Cronbach's α. RESULTS: The exploratory factor analysis suggested a four-factor solution which is like the original Berger HIV scale with sub-scales personalised stigma, disclosure concerns, negative self- image, and concerns with public attitudes. Items in the sub-scales personalised stigma (15- items), disclosure concerns (6), negative self-image (7) and concerns with public attitudes (6) were reduced compared to the original scale. Cronbach's α for the overall HIV stigma scale (34-items) was 0.808 whiles the sub-scales α ranged from 0.77 to 0.89. Analysis suggested the prevalence of a fundamental one-dimensional factor solution which yielded a 34-item scale after removing items for low factor loadings. Disclosure concerns was the highest ranked subscale although our study also found that about 65% of PLWHIV among our study participants had disclosed their status. CONCLUSION: Our 34-item abridged Berger HIV stigma scale showed sufficient reliability with high Cronbach's α and construct validity. Disclosure concerns ranked high among the sub-scales on the scale. Exploring specific interventions and strategies to address stigma concerns in our population will aid in the reduction of HIV-related stigma and associated consequences.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".