The Cedar Project WelTel mHealth intervention for HIV prevention in young Indigenous people who use illicit drugs: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Despite successes in preventing and treating HIV, Indigenous people in Canada continue to face disproportionately high rates of HIV infection. Programs that support healing from lifetime trauma, support connection to culture, and reduce drug-related harms are critical to preventing HIV among young Indigenous people who use drugs. The Cedar Project WelTel mHealth intervention proposed here is a structured mobile-phone initiative to connect young Indigenous people who use drugs with Cedar Case Managers in a community-based setting. The intervention consists of a package of supports, including a mobile phone and cellular plan, weekly two-way text messaging, and support from Cedar Case Managers. METHODS: The Cedar Project WelTel mHealth study is a multi-site Zelen pre-randomized trial to measure the effect of a two-way supportive text-message intervention to reduce HIV vulnerability among young Indigenous people who use illicit drugs in two Canadian cities. The trial is nested within the Cedar Project, an ongoing cohort study addressing HIV and hepatitis C vulnerability among young Indigenous people who use drugs in Vancouver and Prince George, British Columbia. The Cedar Project Partnership, an independent body of Indigenous Elders, leaders, and health/social service experts, governs all aspects of the study. Two hundred participants will be followed over a 16-month period, with HIV propensity score at 6 months as the primary outcome. Secondary outcomes include HIV propensity at 1 year, HIV risk, resilience, psychological distress, access to drug-related services, and connection to culture measured at 6 months and 1 year. Primary analysis is by intention to treat. DISCUSSION: Culturally safe interventions that address barriers to HIV prevention while supporting the strength of young Indigenous people who use drugs are urgently needed. Despite presenting a tremendous opportunity to connect young, highly transient Indigenous people who use drugs to prevention services, supportive two-way mHealth programs have yet to be tested for HIV prevention in a community-based setting with this population. TRIAL REGISTRATION: ClinicalTrials.gov NCT02437123 https://clinicaltrials.gov/show/NCT02437123 (registered 4 May 2015). Protocol version: 24 July 2015.
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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 | 0.033 | 0.029 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.125 | 0.018 |
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".