A Nurse Case Management HIV Prevention Intervention (Come As You Are) for Youth Experiencing Homelessness: Protocol for a Randomized Wait-list Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Youth experiencing homelessness are more likely than housed youth to experience premature death, suicide, drug overdose, pregnancy, substance use, and mental illness. Yet while youth experiencing homelessness are 6 to 12 times more likely to become infected with HIV than housed youth, with HIV prevalence as high as 16%, many do not access the prevention services they need. Despite adversities, youth experiencing homelessness are interested in health promotion programs, can be recruited and retained in interventions and research studies, and demonstrate improved outcomes when programs are tailored and relevant to them. OBJECTIVE: The study aims to compare the efficacy of a nurse case management HIV prevention and care intervention, titled Come As You Are, with that of usual care among youth experiencing homelessness aged 16 to 25 years. METHODS: The study is designed as a 2-armed randomized wait-list controlled trial. Participants (n=450) will be recruited and followed up for 9 months after the intervention for a total study period of 12 months. Come As You Are combines nurse case management with a smartphone-based daily ecological momentary assessment to develop participant-driven HIV prevention behavioral goals that can be monitored in real-time. Youth in the city of Houston, Texas will be recruited from drop-in centers, shelters, street outreach programs, youth-serving organizations, and clinics. RESULTS: Institutional review board approval (Committee for the Protection of Human Subjects, University of Texas Health Science Center at Houston) was obtained in November 2018. The first participant was enrolled in November 2019. Data collection is ongoing. To date, 123 participants have consented to participate in the study, 89 have been enrolled, and 15 have completed their final follow-up. CONCLUSIONS: There is a paucity of HIV prevention research regarding youth experiencing homelessness. Novel and scalable interventions that address the full continuum of behavioral and biomedical HIV prevention are needed. This study will determine whether a personalized and mobile HIV prevention approach can reduce HIV risk among a hard-to-reach, transient population of youth at high risk. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26716.
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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 | 0.027 | 0.022 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.077 | 0.012 |
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".