University of North Carolina/Emory Center for Innovative Technology (iTech) for Addressing the HIV Epidemic Among Adolescents and Young Adults in the United States: Protocol and Rationale for Center Development
Bibliographic record
Abstract
BACKGROUND: Over a fifth of all new HIV infections in the United States occur among persons aged 13 24 years, with most of these diagnoses occurring among gay and bisexual males (81%). While the epidemic of HIV in the United States has leveled off for many age groups, the annual number of new HIV diagnoses among young men who have sex with men (YMSM; 13-24 years old) remains high. Traditional approaches to continuum improvement for youth have been insufficient, and targeted interventions are urgently needed for young people at risk for or infected with HIV. Interventions delivered through mobile health technology represent a promising approach for improving outcomes in this population. Mobile phones have nearly reached saturation among youth, making mobile technology a particularly promising tool for reaching this population. OBJECTIVE: The University of North Carolina/Emory Center for Innovative Technology (iTech) is a National Institutes of Health cooperative agreement as part of the Adolescent Medicine Trials Network for HIV/AIDS Interventions. iTech aims to impact the HIV epidemic by conducting innovative, interdisciplinary research on technology-based interventions across the HIV prevention and care continuum for adolescents and young adults in the United States, particularly YMSM, by providing the following: (1) evaluation of novel approaches to identifying youth with undiagnosed HIV infections; (2) evaluation of multilevel, combination prevention approaches, particularly relevant to gender- and sexual-minority youth facing co-occurring health risks; (3) evaluation of uptake of and adherence to biomedical prevention modalities; and 4) evaluation of interventions designed to promote or optimize engagement in care and antiretroviral therapy adherence in HIV-positive youth, to optimize viral load suppression. METHODS: iTech brings together multidisciplinary experts in the fields of adolescent HIV treatment and prevention, development and evaluation of technology-based interventions, HIV surveillance and epidemiology, and intervention design and evaluation. This initiative will support 8 efficacy trials and 2 exploratory projects, each led by 2 principal investigators. Taken together, the studies address all of the key steps of the HIV prevention and care continuum for youth in the United States. Each proposal uses technology in a scientifically rigorous and innovative way to access, engage, and impact at-risk or infected youth. Nine iTech subject recruitment venues are spread across 8 US cities. Three cores (management, analytic, and technology) support all iTech activities and form the research network's infrastructure, facilitating all aspects of study implementation and evaluation. RESULTS: Formative work has already begun on many of the above-mentioned iTech trials. We expect the first randomized controlled trials to begin in mid-2018. Additional details can be found in the individual intervention protocol papers in this issue. CONCLUSIONS: Through its comprehensive research portfolio, iTech aims to effectively advance HIV prevention and care for youth through technology-based, youth-relevant interventions that maximize adaptability and sustainability. REGISTERED REPORT IDENTIFIER: RR1-10.2196/10365.
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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 | 0.067 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.088 | 0.020 |
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".