Psychometric properties of a Spanish version of the 10-item Berger's stigma scale in Colombia: a validation study
Bibliographic record
Abstract
Introduction: HIV-related stigma is detrimental to people living with HIV (PLH), and reducing it is essential for achieving an HIV/AIDS-free generation. Abbreviated stigma scales can improve the feasibility of surveys that broadly explore factors affecting PLH. This study tested the psychometric properties of a Spanish translation of the abbreviated 10-item Berger's HIV stigma scale. Methods: We recruited a sample of 105 PLH regularly attending a specialized clinic in Cali, Colombia. English-to-Spanish and Spanish-to-English back translation was performed of the Berger's 10-item HIV stigma scale. Exploratory and confirmatory factor analyses were carried out to assess its validity. Pre- and post-test reliability (15 days) was estimated with the intra-class correlation coefficient (ICC). Results: The Confirmatory Factor Analysis (CFA) was used to confirm a two-factor solution with three poor items removed, resulting in a 7-item HIV Stigma Scale. The resulting 7-item HIV stigma scale had a Cronbach's alpha of 0.73 with an ICC of 0.83 (CI 95%: 0.75–0.89). One factor loaded three items related to negative self-image (internalised stigma), and the other four items were related to personalized (enacted) HIV stigma. Both factors were related to depression and adherence to antiretroviral therapy. Conclusion: The Spanish translation of the 10-item HIV stigma scale did not perform well due to problems in items 4, 5, and 6. Rather, a modified 7-item version had a good fit with a two-factor loading in which both HIV stigma factors correlated significantly with depression and HIV medication adherence.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.001 | 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 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".