Exploring Facilitators and Barriers to STD/STI/HIV Self-Testing Among College Students in the United States: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: HIV affects 1.2 million Americans, with 20% of new diagnoses being 13 to 24-year-olds. Young adult college students are more likely than the general population of 18 to 24-year-olds in the U.S. to engage in sexual practices that increase their risk of STIs. OBJECTIVES: This scoping review explores factors that promote or hinder STD/STI/HIV self-testing among U.S. college students. SEARCH METHODS: A scoping review of original, experimental (randomized or nonrandomized), observational (longitudinal and cross-sectional), and qualitative or mixed-methods U.S. research was conducted using OVID Medline, OVID Embase, PubMed, CINAHL, Web of Science Core Collection, and Cochrane CENTRAL. English-language studies measured STD/STI/HIV self-test kits and college student testing. SELECTION CRITERIA: Inclusion and exclusion criteria were used to narrow down articles that addressed barriers and facilitators to STD/STI/HIV testing, and self-testing among college students in the U.S. RESULTS: Database searches yielded 8,373 articles. After removing duplicates, 6173 items remained. After independent dual-title/abstract screening, 100 papers were full-text reviewed. Seven retrieved articles were unavailable, and 93 were selected for full-text screening. After reviewing the whole text, 89 papers did not fulfill the inclusion requirements and were deleted, leaving 4 articles in the final analysis. CONCLUSION: Additional research on self-testing among college students in the U.S. is urgently required. The results should guide university health policies on the need to cater to the unique requirements of college students by increasing the availability of healthcare and embracing STD/STI/HIV self-testing. This can enhance testing rates, diminish stigmas, and ultimately contribute to wider endeavors to reduce the transmission of infections in the U.S.
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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 | 0.015 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".