Exploring the Use of Customized Links to Improve Electronic Engagement With Sexual and Reproductive Health Care Among Young African American Male Individuals: Web-Based Survey Study
Bibliographic record
Abstract
BACKGROUND: Research has shown that heterosexual African American male individuals aged 18-24 years have a higher prevalence of sexually transmitted infections (STIs) and are more likely to engage in risky sexual behavior. There is a critical need to promote sexual reproductive health (SRH) services among this population, especially in urban settings. Young African American male individuals use social media platforms to access health information, showcasing the potential of social media and web-based links as tools to leverage electronic engagement with this population to promote SRH care. OBJECTIVE: This study aims to explore electronic engagement with young African American male individuals in discussions about SRH care. This paper focuses on the recruitment and social media marketing methods used to recruit young, heterosexual African American male individuals aged 18-24 years for the Stay Safe Project, a larger study that aims to promote SRH services among this population in Detroit, Michigan. We investigate the use of TinyURL, a URL shortener and customized tool, and culturally informed social media marketing strategies to promote electronic engagement within this population. METHODS: Participants were recruited between December 2021 and February 2022 through various modes, including email listserves, Mailchimp, the UMHealthResearch website, X (formerly Twitter), Facebook, and Instagram. Images and vector graphics of African American male individuals were used to create social media advertisements that directed participants to click on a TinyURL that led to a recruitment survey for the study. RESULTS: TinyURL metrics were used to monitor demographic and user data, analyzing the top countries, browsers, operating systems, and devices of individuals who engaged with the customized TinyURL links and the total human and unique clicks from various social media platforms. Mailchimp was the most successful platform for electronic engagement with human and unique clicks on the custom TinyURL link, followed by Instagram and Facebook. In contrast, X, traditional email, and research recruiting websites had the least engagement among our population. Success was determined based on the type of user and follower for each platform, whether gained in the community through sign-ups or promoted at peak user time and embedded and spotlighted on nontraditional media (eg, social media sites, blogs, and podcasts) for the user. Low engagement (eg, traditional email) from the target population, limited visibility, and fewer followers contributed to decreased engagement. CONCLUSIONS: This study provides insight into leveraging customized, shortened URLs, TinyURL metrics, and social media platforms to improve electronic engagement with young African American male individuals seeking information and resources about SRH care. The results of this study have been used to develop a pilot intervention for this population that will contribute to strategies for encouraging sexual well-being, clinic use, and appropriate linkage to SRH care services among young, heterosexual African American male individuals.
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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 | 0.008 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".