Text Messaging to Improve Linkage, Retention, and Health Outcomes Among HIV-Positive Young Transgender Women: Protocol for a Randomized Controlled Trial (Text Me, Girl!)
Bibliographic record
Abstract
BACKGROUND: Transgender women in the United States experience numerous risk factors for HIV acquisition and transmission, including increased rates of homelessness, alcohol and drug use, sex work, and nonprescribed hormone and soft tissue-filler injections. In addition, transgender women face discrimination and social/economic marginalization more intense and deleterious than that experienced by lesbian, gay, or bisexual individuals, further worsening health outcomes. Although little research has been done specifically with young transgender women aged 35 years and younger, existing evidence suggests even further elevated rates of homelessness, substance use, and engagement in HIV transmission risk behaviors relative to their older transgender women and nontransgender young adult counterparts. Young transgender women living with HIV experience a range of barriers that challenge their ability to be successfully linked and retained in HIV care. OBJECTIVE: The aim of this randomized controlled trial, Text Me, Girl!, is to assess the impact of a 90-day, theory-based, transgender-specific, text-messaging intervention designed to improve HIV-related health outcomes along the HIV care continuum among young (aged 18-34 years) transgender women (N=130) living with HIV/AIDS. METHODS: Participants were randomized into either Group A (immediate text message intervention delivery; n=61) or Group B (delayed text message intervention delivery whereby participants were delivered the text-messaging intervention after a 90-day delay period; n=69). Over the course of the 90-day intervention, participants received 270 theory-based text messages that were targeted, tailored, and personalized specifically for young transgender women living with HIV. Participants received 3 messages per day in real time within a 10-hour gradual and automated delivery system. The text-message content was scripted along the HIV care continuum and based on social support theory, social cognitive theory, and health belief model. The desired outcome of Text Me, Girl! was virological suppression. RESULTS: Recruitment began on November 18, 2016, and the first participant was enrolled on December 16, 2016; enrollment closed on May 31, 2018. Intervention delivery ended on November 30, 2018, and follow-up evaluations will conclude on August 31, 2019. Primary outcome analyses will begin immediately following the conclusion of the follow-up evaluations. CONCLUSIONS: Text messaging is a communication platform well suited for engaging young transgender women in HIV care because it is easily accessible and widely used, as well as private, portable, and inexpensive. Text Me, Girl! aimed to improve HIV care continuum outcomes among young transgender women by providing culturally responsive text messages to promote linkage, retention, and adherence, with the ultimate goal of achieving viral suppression. The Text Me, Girl! text message library is readily scalable and can be adapted for other hard-to-reach populations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12837.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.084 | 0.009 |
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".