A Multilingual, Culturally Competent Mobile Health Intervention to Improve Treatment Adherence Among Women Living With HIV: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Adherence to HIV care is complex, as barriers to care are multidimensional, particularly for ethnic minority women. Mobile health (mHealth) solutions are supportive in improving HIV health care outcomes. In the United States, however, mHealth interventions are not widely implemented in public HIV clinics and have not been customized for women. There is an unmet need for culturally and linguistically appropriate mHealth interventions that address the health care needs of minority women living with HIV. OBJECTIVE: This study aims to describe a protocol investigating the feasibility of an mHealth intervention for treatment adherence among women living with HIV. This is a two-phase, mixed methods, pilot randomized controlled trial that begins with qualitative patient interviews to inform the system design. Participants will be block randomized by language (English, Spanish, and Haitian Creole) to 1 of 2 study arms. METHODS: Women (age ≥18 years) who were followed up at the women's HIV clinic of an academic medical center, with a recent history of nonadherence to HIV care (missed appointments, unsuppressed viral load, or not taking medications as prescribed), will be enrolled. The experimental arm will receive the intervention, which includes health reminders and psychoeducational messaging, plus clinical standard of care reminders. The psychoeducational messaging will target patient-level barriers of HIV stigma and medical mistrust and resilience as a patient-level strength. The control arm will receive standard of care reminders only (ie, mailed appointments and automated telephone calls). All aspects of the study and intervention will be offered in the participants' preferred language. The primary outcome is the feasibility and acceptability of the study. The secondary outcomes are changes in self-reported medication adherence, depression symptoms, HIV stigma, medical mistrust, resilience, and clinic attendance and viral suppression extracted from the participants' medical records. Data will be assessed at baseline (T0) and 2 subsequent clinic visits-approximately 3 to 4 months from the baseline (time 1; T1) and 6 to 9 months from the baseline (time 2; T2). Qualitative data will be transcribed and analyzed iteratively. Bivariate analyses will compare data by the study group (chi-square, odds ratios, and t tests). Exploratory analyses will be conducted for each outcome variable-T1 and T2 values will be compared with values at T0 by the study group. RESULTS: As of March 2020, baseline quantitative data were collected on 54 participants (28 English speakers, 14 Spanish speakers, and 12 Haitian Creole speakers). The first 3 focus groups (1 in each of the 3 languages) were completed, with a total of 20 participants. The findings are currently being integrated into the beta version of the mHealth texting system. CONCLUSIONS: The findings of this novel HIV adherence intervention may shed light on the barriers and facilitators of HIV health care and the mechanisms of an mHealth intervention that is customized for ethnic minority women living with HIV. TRIAL REGISTRATION: ClinicalTrials.gov NCT03738410; https://clinicaltrials.gov/ct2/show/NCT03738410. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17656.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,038 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,008 | 0,004 |
| Méta-épidémiologie (sens large) | 0,014 | 0,007 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,009 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,094 | 0,014 |
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 ».