Effect of SMS Reminders, Telephone Calls, and Transport Incentives on Enhancing the Completion of Tuberculosis Diagnosis and Initiation of Treatment for Diagnosed Patients: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
Background: Globally, tuberculosis (TB) programs have enhanced efforts to improve case detection, treatment initiation, and monitoring of treatment outcomes. However, less attention has been given to reducing the number of persons with presumed TB who never get tested for TB or those with confirmed TB who never start treatment in endemic regions such as Uganda. Such losses hinder progress toward attaining the 2035 End TB goals. The World Health Organization recommends mobile health (mHealth) interventions such as SMS reminders, telephone calls, mobile apps, and digital monitoring devices to foster universal health coverage. To our knowledge, there is limited evidence on whether these mHealth interventions can increase linkage to care for persons with presumed TB, particularly in sub-Saharan Africa. Objective: We aim to conduct a randomized controlled trial (MILEAGE4TB) whose aim is to assess the effect of SMS reminders, telephone calls, and transport incentives on improving completion of TB diagnosis among persons with presumed TB and initiation of treatment for diagnosed patients in Uganda. Methods: This will be a 5-arm individual randomized controlled trial among persons with presumed TB aged 18 years or older who are referred for Xpert MTB/RIF testing. Participants will be randomly assigned (2:2:2:1:1) to (1) standard of care, (2) SMS reminders only, (3) telephone calls only, (4) SMS reminders and a transport incentive, and (5) telephone calls and a transport incentive. An estimated sample size of 2389 participants will be considered. The primary outcome will be completion of TB diagnosis, defined as submitting a sputum sample for Xpert MTB/RIF testing and receiving test results within 30 days of being identified as having presumptive TB. The secondary outcomes will include (1) TB treatment initiation, which will be defined as starting TB treatment within 30 days of being diagnosed; (2) median turnaround times for TB diagnosis and treatment initiation; and (3) acceptability and feasibility of the interventions. Participants will be followed for 30 days to check whether they have tested for TB and collected their results. Chi-square tests will be performed for categorical outcomes. Analysis will be by intention to treat. Modified Poisson regression models will be used to estimate the effects of the interventions on completion of TB diagnosis and treatment initiation. Results: The study was funded in June 2020 and data collection for the trial started in August 2023. Results from this trial are not yet available. As of August 28, 2025, a total of 2355 participants had been recruited. Data from the preliminary analysis will be ready by December 2025 after all trial activities. Conclusions: This randomized controlled trial will provide insights on the use of mHealth interventions to improve the completion of TB diagnosis among persons with presumed TB and initiation of treatment for diagnosed patients.
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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 | 0,041 | 0,036 |
| Méta-épidémiologie (sens strict) | 0,009 | 0,004 |
| Méta-épidémiologie (sens large) | 0,016 | 0,010 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,005 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,010 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,082 | 0,013 |
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 ».