Correlates of Successful Enrollment of Same-Sex Male Couples Into a Web-Based HIV Prevention Research Study: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: The recognition of the role of primary partners in HIV transmission has led to a growth in dyadic-focused HIV prevention efforts. The increasing focus on male couples in HIV research has been paralleled by an increase in the development of interventions aimed at reducing HIV risk behaviors among male couples. The ability to accurately assess the efficacy of these interventions rests on the ability to successfully enroll couples into HIV prevention research. OBJECTIVE: This study aimed to explore factors associated with successful dyadic engagement in Web-based HIV prevention research using recruitment and enrollment data from a large sample of same-sex male couples recruited online from the United States. METHODS: Data came from a large convenience sample of same-sex male couples in the United States, who were recruited through social media venues for a Web-based, mixed method HIV prevention research study. The analysis examined the demographic factors associated with successful dyadic engagement in research, measured as both members of the dyad meeting eligibility criteria, consenting for the study, and completing all study processes. RESULTS: Advertisements generated 221,258 impressions, resulting in 4589 clicks. Of the 4589 clicks, 3826 individuals were assessed for eligibility, of which 1076 individuals (538/1913, 28.12% couples) met eligibility criteria and were included in the study. Of the remaining 2740 ineligible participants, 1293/3826 (33.80%) were unlinked because their partner did not screen for eligibility, 48/2740 (1.75%) had incomplete partner data because at least one partner did not finish the survey, 22/2740 (0.80%) were ineligible because of 1 partner not meeting the eligibility criteria. Furthermore, 492/3826 (12.86%) individuals were fraudulent. The likelihood of being in a matched couple varied significantly by race and ethnicity, region, and relationship type. Men from the Midwest were less likely to have a partner who did not complete the survey. Men with college education and those who labeled their relationships as husband or other (vs boyfriend) were more likely to have a partner who did not complete the survey. CONCLUSIONS: The processes used allowed couples to independently progress through the stages necessary to enroll in the research study, while limiting opportunities for coercion, and resulted in a large sample with relative diversity in demographic characteristics. The results underscore the need for additional considerations when recruiting and enrolling, relative to improving the methods associated with these research processes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".