TB Research

Use of a digital adherence technology to support TB treatment among adolescents

Schraufnagel AM, Crowder R, Wambi P, Nakasendwa S, Kityamuwesi A, Jaganath D, Musoke M, Nannozi J, et al. (22 authors)

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2025-08

Abstract

BACKGROUND Adolescents (ages 10-19) affected by TB face unique challenges to completing TB treatment. Digital adherence technologies (DATs) may be a useful tool for TB treatment monitoring. In this study, we assessed whether 99DOTS, a low-cost DAT, could improve treatment outcomes among adolescents with pulmonary TB (PTB). METHODS We conducted an interrupted time series (ITS) analysis of adolescents initiating treatment for drug-susceptible PTB at 30 health facilities in Uganda. ITS analysis was used to model the change in TB treatment outcomes and loss to follow-up in adolescents prior to and after the implementation of a 99DOTS-based intervention. RESULTS Of 630 adolescents, 78.4% of adolescents were enrolled on 99DOTS in the post-intervention period. In the adjusted analysis, the proportion treated successfully increased (level change, proportion ratio [PR] 1.18, 95% confidence interval [CI] 1.08-1.28) and the proportion lost to follow-up decreased (level change, PR 0.93, 95% CI 0.88-0.98) in the immediate post-intervention period. Both proportions remained similar throughout the post-intervention period ( P value for slope change >0.05). CONCLUSION There was a high uptake of 99DOTS among adolescents with TB, and use of 99DOTS was associated with improved treatment outcomes. DATs should be further explored as a promising adolescent-specific tool for improving TB treatment outcomes. .

MeSH terms

  • Humans
  • Mycobacterium tuberculosis
  • Tuberculosis, Pulmonary
  • Antitubercular Agents
  • Drug Monitoring
  • Treatment Outcome
  • Follow-Up Studies
  • Program Evaluation
  • Reminder Systems
  • Adolescent
  • Child
  • Uganda
  • Female
  • Male
  • Young Adult
  • Interrupted Time Series Analysis
  • Cell Phone
  • Digital Health
  • Adherence Interventions