Stakeholders’ Perceptions of Benefits of and Barriers to Using Video-Observed Treatment for Monitoring Patients With Tuberculosis in Uganda: Exploratory Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: Nonadherence to treatment remains a barrier to tuberculosis (TB) control. Directly observed therapy (DOT) is the standard for monitoring adherence to TB treatment worldwide, but its implementation is challenging, especially in resource-limited settings. DOT is labor-intensive and inconvenient to both patients and health care workers. Video DOT (VDOT) is a novel patient-centered alternative that uses mobile technology to observe patients taking medication remotely. However, the perceptions and acceptability of potential end users have not been evaluated in Africa. OBJECTIVE: This study explores stakeholders' acceptability of, as well as perceptions of potential benefits of and barriers to, using VDOT to inform a pilot study for monitoring patients with TB in urban Uganda. METHODS: An exploratory, qualitative, cross-sectional study with an exit survey was conducted in Kampala, Uganda, from April to May 2018. We conducted 5 focus group discussions, each comprising 6 participants. Groups included patients with TB (n=2 groups; male and female), health care providers (n=1), caregivers (n=1), and community DOT volunteer workers (n=1). The questions that captured perceived benefits and barriers were guided by domains adopted from the Technology Acceptance Model. These included perceived usefulness, ease of use, and intent to use technology. Eligible participants were aged ≥18 years and provided written informed consent. For patients with TB, we included only those who had completed at least 2 months of treatment to minimize the likelihood of infection. A purposive sample of patients, caregivers, health care providers, and community DOT workers was recruited at 4 TB clinics in Kampala. Trained interviewers conducted unstructured interviews that were audio-recorded, transcribed, and analyzed using inductive content analysis to generate emerging themes. RESULTS: The average age of participants was 34.5 (SD 10.7) years. VDOT was acceptable to most participants on a scale of 1 to 10. Of the participants, 70% (21/30) perceived it as highly acceptable, with scores ≥8, whereas 30% (9/30) scored between 5 and 7. Emergent themes on perceived benefits of VDOT were facilitation of easy adherence monitoring, timely follow-up on missed doses, patient-provider communication, and saving time and money because of minimal travel to meet in person. Perceived barriers included limited technology usability skills, inadequate cellular connectivity, internet access, availability of electricity, cost of the smartphone, and use of the internet. Some female patients raised concerns about the disruption of their domestic work routines to record videos. The impact of VDOT on privacy and confidentiality emerged as both a perceived benefit and barrier. CONCLUSIONS: VDOT was acceptable and perceived as beneficial by most study participants, despite potential technical and cost barriers. Mixed perceptions emerged about the impact of VDOT on privacy and confidentiality. Future efforts should focus on training users, ensuring adequate technical infrastructure, assuring privacy, and performing comparative cost analyses in the local context.
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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 | 0,010 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».