Mobile Text Messaging to Improve Medication Adherence and Viral Load in a Vulnerable Canadian Population Living With Human Immunodeficiency Virus: A Repeated Measures Study
Notice bibliographique
Résumé
Background: Combination antiretroviral therapy (cART) as treatment for human immunodeficiency virus (HIV) infection is effective and available, but poor medication adherence limits benefits, particularly in vulnerable populations. In a Kenyan randomized controlled trial, a weekly text-messaging intervention (WelTel) improved cART adherence and HIV viral load (VL). Despite growing evidence for short message service (SMS) text-message interventions in HIV care, there is a paucity of data utilizing these interventions in marginalized or female cohorts. Objective: This study was undertaken to assess whether the standardized WelTel SMS text-message intervention applied to a vulnerable, predominantly female, population improved cART adherence and VL. Methods: We conducted a repeated measures study of the WelTel intervention in high-risk HIV-positive persons by measuring change in VL, CD4 count, and self-reported adherence 12 months before and 12 months after the WelTel intervention was introduced. Inclusion criteria included VL ≥200 copies/mL, indication for treatment, and meeting vulnerability criteria. Participants were given a mobile phone with unlimited texting (where required), and weekly check-in text messages were sent for one year from the WelTel computer platform. Clinical data were collected for control and intervention years. Participants were followed by a multidisciplinary team in a clinical setting. Outcomes were assessed using Wilcoxon signed ranks tests for change in CD4 and VL from control year to study end and mixed-effects logistic regressions for change in cART adherence and appointment attendance. A secondary analysis was conducted to assess the effect of response rate on the outcome by modeling final log10 VL by number of responses while controlling for mean log10 VL in the control year. Results: Eighty-five participants enrolled in the study, but 5 withdrew (final N=80). Participants were predominantly female (90%, 72/80) with a variety of vulnerabilities. Mean VL decreased from 1098 copies/mL in the control year to 439 copies/mL at study end (P=.004). Adherence to cART significantly improved (OR 1.14, IQR 1.10-1.18; P<.001), whereas appointment attendance decreased slightly with the intervention (OR 0.81, IQR 0.67-0.99; P=.03). A response was received for 46.57% (1753/3764) of messages sent and 9.62% (362/3764) of text messages sent were replied to with a problem. An outcome analysis examining relationship between reply rate and VL did not meet statistical significance (P=.07), but may be worthy of investigating further in a larger study. Conclusions: WelTel may be an effective tool for improving cART adherence and reducing VLs among high-risk, vulnerable HIV-positive persons. Trial Registration: Clinicaltrials.gov NCT02603536; https://clinicaltrials.gov/ct2/show/NCT02603536 (Archived by WebCite at http://www.webcitation.org/6qK57zCwv)
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,026 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».