Methodological strategies to engage young black and Latino heterosexual couples in sexual and reproductive health research
Bibliographic record
Abstract
BACKGROUND: Approaches that move beyond individuals and target couples may be an effective strategy for reducing sexual and reproductive health (SRH) disparities among adolescents and young adults (AYA). However, few researchers have attempted to recruit couples due to feasibility and methodological issues. This study aims to enhance implementation and methodological approaches to successfully engage heterosexual Black and Latino adolescent and young adult (AYA) couples in sexual reproductive health (SRH) research. METHODS: We developed a four-step approach to systematically engage AYA couples in a qualitative study examining factors that influence uptake of combination HIV prevention methods: 1) understanding barriers and facilitators to engaging AYA couples, (2) identifying AYAs living in geographic areas of HIV vulnerability, (3) recruiting and screening AYA couples, and (4) scheduling and completion of the interview session. RESULTS: Black and Latino youth aged 16 to 24 and their opposite sex romantic were recruited in the South Bronx, New York from September 2017-May 2018. Three hundred and seventy-two men and women completed screening procedures to determine eligibility for the index participant; 125 were eligible and enrolled into the study. Forty-nine nominated partners (NPs) participated in screening procedures and enrolled into the study. A total of 49 couples enrolled into the study; 23 couples completed study activities. CONCLUSIONS: Developing a systematic recruitment plan aided in successfully engaging Black and Latino heterosexual youth. Nevertheless, barriers to study enrollment remained including locating eligible IPs and screening of the NP. Targeting both young men and women was an effective recruitment strategy. Moreover, dyadic strategies that allow for simultaneous interaction with both couple members may be a beneficial strategy to couples' study enrollment and completion of study activities.
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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 | 0.290 | 0.203 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".