Text Messaging to Improve Linkage, Retention, and Health Outcomes Among HIV-Positive Young Transgender Women: Protocol for a Randomized Controlled Trial (Text Me, Girl!)
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,008 | 0,004 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,084 | 0,009 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».