Translation and validation in Brazilian Portuguese of the reactions to homosexuality scale
Bibliographic record
Abstract
Internalized homonegativity results from the acceptance of negative attitudes about one's same-sex orientation, which has negative consequences for the health of gay, bisexual and other men who have sex with men (GBM). We translated the 7-item Reactions to Homosexuality Scale (RHS) to Brazilian Portuguese and assessed its factor structure, validity and reliability. The first step included the translation, back-translation, evaluation, peer review, and pre-testing of the scale. Then, we piloted the scale in two convenience samples of adult Brazilians recruited online during October 2019 and February to March 2020 through advertisements on Grindr and Hornet, respectively. The largest sample was randomly split into two groups for exploratory factor analysis (EFA) then confirmatory factor analysis (CFA). Criterion and construct validity were assessed via correlations between scale scores and study variables. A total of 5573 GBM (sample 1: 218; sample 2: 5355) completed the RHS. EFA (N = 2652) yielded two eigenvalues greater than one (Factor 1: 3.5 and Factor 2: 1.1). A one-factor solution provided the most interpretable model based on examination of scree plot and item factor loadings (χ2(14) = 1373.1, p < 0.001; CFI = 0.89; TLI = 0.84; RMSEA = 0.19; SRMS = 0.09). Though one-factor CFA showed moderate fit, freeing errors terms to covary, based on item content and interpretation, significantly improved model fit (χ2(12) = 309.1, p < .001; CFI = 0.97; TLI = 0.96; RMSEA = 0.09; SRMR = 0.02). As hypothesized, men who did not self-identify as gay (mean score 17.9 compared to those self-identifying as gay: 11.8) and men who reported no sex with men in the past 6 months (mean score 12.6 compared to those who reported sex with men: 10.6) scored higher reflecting higher internalized homonegativity. The RHS was effectively translated and validated in Brazilian Portuguese and can be used to evaluate the role of internalized homonegativity on GBM's health, as well as its impact on the uptake of HIV prevention technologies.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".