Barriers to HIV Testing Among Young Men Who Have Sex With Men (MSM): Experiences from Clark County, Nevada
Bibliographic record
Abstract
Clark County, Nevada had a 52% increase in newly diagnosed HIV infections in young people age 13-24 with 83% of the new diagnoses in this age group being men who have sex with men (MSM). HIV testing and counseling is critical for HIV prevention, care and treatment, yet young people are the least likely to seek HIV testing. The purpose of this study was to identify barriers and facilitators to HIV testing experienced by young MSM in Clark County, Nevada. We conducted a qualitative focus group discussion to identify barriers and facilitators to HIV testing among eleven young MSM in March, 2015. The primary barrier to HIV testing identified by the group was a lack of awareness or knowledge about testing for HIV. Other barriers within the person included: fear of results, fear of rejection, and fear of disclosure. Barriers identified within the environment included: access issues, stigma, and unfriendly test environments for young people. In addition to increasing awareness, intervention to increase HIV testing among MSM young people should incorporate access to testing in environments where the adolescents are comfortable and which reduces stigma. HIV testing sites should be convenient, accessible and young person/gay friendly.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 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".