Patient-Reported Barriers to Adherence to Antiretroviral Therapy: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
BACKGROUND: Maintaining high levels of adherence to antiretroviral therapy (ART) is a challenge across settings and populations. Understanding the relative importance of different barriers to adherence will help inform the targeting of different interventions and future research priorities. METHODS AND FINDINGS: We searched MEDLINE via PubMed, Embase, Web of Science, and PsychINFO from 01 January 1997 to 31 March 2016 for studies reporting barriers to adherence to ART. We calculated pooled proportions of reported barriers to adherence per age group (adults, adolescents, and children). We included data from 125 studies that provided information about adherence barriers for 17,061 adults, 1,099 children, and 856 adolescents. We assessed differences according to geographical location and level of economic development. The most frequently reported individual barriers included forgetting (adults 41.4%, 95% CI 37.3%-45.4%; adolescents 63.1%, 95% CI 46.3%-80.0%; children/caregivers 29.2%, 95% CI 20.1%-38.4%), being away from home (adults 30.4%, 95% CI 25.5%-35.2%; adolescents 40.7%, 95% CI 25.7%-55.6%; children/caregivers 18.5%, 95% CI 10.3%-26.8%), and a change to daily routine (adults 28.0%, 95% CI 20.9%-35.0%; adolescents 32.4%, 95% CI 0%-75.0%; children/caregivers 26.3%, 95% CI 15.3%-37.4%). Depression was reported as a barrier to adherence by more than 15% of patients across all age categories (adults 15.5%, 95% CI 12.8%-18.3%; adolescents 25.7%, 95% CI 17.7%-33.6%; children 15.1%, 95% CI 3.9%-26.3%), while alcohol/substance misuse was commonly reported by adults (12.9%, 95% CI 9.7%-16.1%) and adolescents (28.8%, 95% CI 11.8%-45.8%). Secrecy/stigma was a commonly cited barrier to adherence, reported by more than 10% of adults and children across all regions (adults 13.6%, 95% CI 11.9%-15.3%; children/caregivers 22.3%, 95% CI 10.2%-34.5%). Among adults, feeling sick (15.9%, 95% CI 13.0%-18.8%) was a more commonly cited barrier to adherence than feeling well (9.3%, 95% CI 7.2%-11.4%). Health service-related barriers, including distance to clinic (adults 17.5%, 95% CI 13.0%-21.9%) and stock outs (adults 16.1%, 95% CI 11.7%-20.4%), were also frequently reported. Limitations of this review relate to the fact that included studies differed in approaches to assessing adherence barriers and included variable durations of follow up. Studies that report self-reported adherence will likely underestimate the frequency of non-adherence. For children, barriers were mainly reported by caregivers, which may not correspond to the most important barriers faced by children. CONCLUSIONS: Patients on ART face multiple barriers to adherence, and no single intervention will be sufficient to ensure that high levels of adherence to treatment and virological suppression are sustained. For maximum efficacy, health providers should consider a more triaged approach that first identifies patients at risk of poor adherence and then seeks to establish the support that is needed to overcome the most important barriers to adherence.
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 | 0,017 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,020 | 0,037 |
| Bibliométrie | 0,007 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 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 ».