Nonuptake of HIV Testing Among Transgender Populations in the United States: Results from the 2015 U.S. Transgender Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: In this study, we examined the nonuptake of HIV testing and the main reasons for never testing among transgender populations. Methods: Data on 26,927 respondents from the 2015 U.S. Transgender Survey were analyzed in this study. The main reasons for never testing were categorized as low risk perception; access related; fear or HIV-related stigma; and others. We performed weighted descriptive statistics and multivariable logistic regression analyses, controlling for sociodemographic characteristics and sexual orientation. Results: Forty-five percent of the respondents had never tested for HIV. Trans women (adjusted odds ratio [aOR]=1.1, 95% confidence interval [CI]=1.07-1.25) and assigned female at birth genderqueer/nonbinary individuals (AFAB GQ/NB) (aOR=1.3, 95% CI=1.16-1.35) had significantly higher odds of reporting never testing for HIV compared with trans men. The most reported reason for never testing was low risk perception (87%). AFAB GQ/NB (aOR=1.4, 95% CI=1.22-1.66) had significantly higher odds of reporting low risk perception as the main reason for never testing for HIV relative to trans men. AFAB GQ/NB were less likely to report access related as the main reason for never testing (aOR=0.8, 95% CI=0.56-0.95). The odds of trans women and assigned male at birth GQ/NB individuals reporting fear or HIV-related stigma as the main reason for never testing were 1.7 (95% CI=1.13-2.55) and 2.8 (95% CI=1.69-4.70) times that of trans men. Both trans women (aOR=0.8, 95% CI=0.65-0.97) and AFAB GQ/NB (aOR=0.7, 95% CI=0.60-0.88) had lower odds of reporting others. The main reasons for never testing also varied by sociodemographic factors, including age, educational attainment, race/ethnicity, employment status, poverty, and sexual orientation. Conclusions: HIV testing is suboptimal among transgender populations. Our findings also suggest that barriers to HIV testing vary by transgender populations, thus interventions for improved uptake should be population specific.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it