Randomized Controlled Trials of Technology-Based HIV/STI and Drug Abuse Preventive Interventions for African American and Hispanic Youth: Systematic Review
Bibliographic record
Abstract
BACKGROUND: HIV/sexually transmitted infections (STIs) and drug abuse remain significant public health concerns in the United States, and African American and Hispanic youth are disproportionately affected. Although technology-based interventions are efficacious in preventing and reducing HIV/STI and licit/illicit drug use behaviors, relatively little is known regarding the state of the science of these interventions among African American and Hispanic youth. OBJECTIVE: The aim of this review is to identify and examine randomized controlled trials (RCTs) of technology-based HIV/STI and/or drug abuse preventive interventions for African American and Hispanic youth. METHODS: We searched electronic databases (ie, PubMed, Proquest, PsycINFO, Ebscohost, Google Scholar) to identify studies between January 2006 and October 2016. RCTs of technology-based interventions targeting African American and Hispanic youth HIV/STI risk behaviors, including sexual risk, licit and illicit drug use, and HIV/STI testing were included. RESULTS: Our search revealed a total of three studies that used an RCT design and included samples comprised of >50% African American and/or Hispanic youth. The follow-up assessments ranged from two weeks to six months and the number of participants in each trial ranged from 72 to 141. The three interventions were theory-driven, interactive, and tailored. The long-term effects of the interventions were mixed, and outcomes included reductions in sex partners, licit drug use, and condomless anal sex acts. CONCLUSIONS: Although technology-based interventions seem promising in the prevention of HIV/STI and drug abuse among African American and Hispanic youth, more research is needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.032 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".